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17 Commits

Author SHA1 Message Date
linkong
bb9183b8a4 release: bump version to 0.48.0 2026-05-07 18:06:06 +08:00
linkong
421234301a release: bump version to 0.47.0 2026-04-30 16:56:37 +08:00
linkong
f22079d33a release: bump version to 0.46.3 2026-04-30 14:46:19 +08:00
linkong
9f737fdb89 release: bump version to 0.46.2 2026-04-30 14:30:12 +08:00
linkong
7418ce2fc1 release: bump version to 0.46.1 2026-04-30 09:41:08 +08:00
rayd1o
b1a5934b80 release: bump version to 0.46.0 2026-04-30 04:42:29 +08:00
rayd1o
ba54545ac7 release: bump version to 0.45.0 2026-04-29 23:43:54 +08:00
linkong
9dafbf4f6e release: bump version to 0.44.2 2026-04-29 18:11:37 +08:00
linkong
a87537e903 release: bump version to 0.44.1 2026-04-29 18:07:35 +08:00
linkong
87594a95ff release: bump version to 0.44.0 2026-04-29 17:27:44 +08:00
linkong
2da25376bd release: bump version to 0.43.1 2026-04-28 16:21:33 +08:00
linkong
ac69d5d354 release: bump version to 0.43.0 2026-04-28 16:10:17 +08:00
rayd1o
1cd2dab0ee release: bump version to 0.42.2 2026-04-28 04:35:13 +08:00
rayd1o
42d019af36 release: bump version to 0.42.1 2026-04-28 04:29:44 +08:00
rayd1o
b4e8afb272 release: bump version to 0.42.0 2026-04-28 04:27:18 +08:00
rayd1o
eeee788530 release: bump version to 0.41.2 2026-04-27 23:23:23 +08:00
linkong
655e2a7d2d release: bump version to 0.41.1
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-27 16:31:34 +08:00
181 changed files with 27698 additions and 3022 deletions

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@@ -12,6 +12,19 @@ allowed-tools: ["Read", "Edit", "Bash", "Grep", "Glob"]
`$ARGUMENTS` 非空,则只检查指定文件/目录;否则检查所有未提交修改(`git diff HEAD`)。
## 节省上下文规则
优先用确定性的 CLI 检查缩小范围,不要一上来把完整文件或大 diff 读入上下文:
```bash
git diff --name-only HEAD
git diff --unified=0 HEAD -- <path>
git diff --check
rg -n "TODO|FIXME|console\.log|debugger|print\(" <changed-paths>
```
只有 focused diff 不足以安全判断或修改时,才读取完整文件。
## 审查清单
按优先级检查以下问题(只报告在本次 diff 中**新增或修改**的代码里存在的问题):
@@ -59,8 +72,13 @@ git diff HEAD --name-only
### Step 2 — 逐文件阅读并分析
- 用 Read 工具读取完整文件(不只读 diff
- 对照审查清单,记录每个问题:文件名、行号、问题类型、建议修复方式
先从 focused diff 开始:
```bash
git diff --unified=0 HEAD -- <file>
```
`rg``git diff --check`、编译器或 linter 输出确认确定性问题。只有需要上下文时才用 Read 读取完整文件。对照审查清单,记录每个问题:文件名、行号、问题类型、建议修复方式。
### Step 3 — 报告问题清单
@@ -95,6 +113,7 @@ git diff HEAD --name-only
- 只改在审查清单中发现的问题,不做额外优化
- 每次 Edit 只修改确实有问题的行,保持 diff 最小
- 改完后用 `grep` 验证旧的坏代码已消失
- 优先做精确补丁;只有仓库已有对应格式化流程时,才运行格式化工具
### Step 5 — 输出总结

93
.claude/commands/docs.md Normal file
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@@ -0,0 +1,93 @@
---
description: Create or update repository documentation from current code changes
argument-hint: Optional: topic to document, or leave empty to infer from git diff
allowed-tools: ["Read", "Edit", "Write", "Bash", "Glob", "Grep"]
---
# /docs — Documentation Workflow
## Goal
Create or update documentation that explains why a change exists, how it behaves, and what maintainers need to know. Keep this command generic. Repository-specific coverage rules live in the repository and must be loaded separately.
## Repository Rules
Before deciding scope, check whether the repository has a documentation rules file:
```bash
test -f docs/documentation-coverage-rules.md && sed -n '1,240p' docs/documentation-coverage-rules.md
```
If it exists, apply it as the project-specific coverage checklist. If it does not exist, continue with the generic workflow below.
## Workflow
### Step 1 — Understand The Change
```bash
git diff HEAD --stat
git diff HEAD --name-only
git log --oneline -10
rg --files docs
```
If `$ARGUMENTS` specifies a topic, focus on that topic. Otherwise infer the documentation topic from the changed files. Do not read the full repository diff by default; inspect focused files only:
```bash
git diff HEAD -- <path>
rg -n "class |def |function |export |router|@router|interface |type " <path>
```
### Step 2 — Decide Scope
- Prefer updating an existing relevant document over creating a duplicate.
- Use one document for one coherent topic.
- Split documents only when the change crosses meaningful domains.
- Keep filenames lowercase and hyphenated.
- Apply the repository-specific rules file before writing.
For ambiguous or large documentation changes, briefly state the intended doc plan before editing. For clear small changes, proceed directly.
### Step 3 — Write
Explain:
- Background/problem: what was wrong or missing before.
- Core design decisions and rationale.
- Operational or user-facing impact.
- Relevant code paths, only when useful for future maintainers.
Style:
- Follow the repositorys existing language and heading conventions.
- Use fenced code blocks with language tags.
- Prefer tables for comparisons or parameter lists.
- Keep snippets concise and relevant.
### Step 4 — Verify
- Read the completed docs once for clarity and stale statements.
- Verify referenced paths exist with `test -e` or `rg --files`.
- Run applicable checks from `docs/documentation-coverage-rules.md`.
- Check Markdown links use readable user-facing titles unless repository rules allow otherwise.
### Step 5 — Report
Summarize changed docs and verification:
```md
Updated:
- path/to/doc.md — what changed
Verified:
- checks that passed
- checks that could not be run, if any
```
## Hard Constraints
- Do not leave placeholder docs.
- Do not duplicate bilingual files byte-for-byte.
- Do not reference PR numbers, issue numbers, or the current conversation unless explicitly requested.
- Do not write changelog-style lists without the reasoning and tradeoffs behind the change.
- Keep docs maintainable and concise.

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@@ -72,6 +72,8 @@ Verification
## 执行风格
- 重证据,轻口头判断
- 优先使用确定性工具证据:`rg``git diff --stat``git diff -- <path>`、测试、构建、lint、`curl`、数据库查询等能直接证明成功标准的方式
- 不把大段命令输出粘进回复;保留在工具调用里,回复只总结关键证据
- 重验收,轻自我感觉
- 优先用测试、日志、产物、对比结果来证明完成
- 对长期任务保持“未达标就继续”的节奏

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@@ -28,6 +28,19 @@ allowed-tools: ["Read", "Edit", "Bash", "Glob", "Grep"]
- `docs/CHANGELOG.md`
- `docs/version-history.md`
## 节省上下文规则
发版判断应以确定性 CLI 证据为主,优先使用紧凑命令和定点读取:
```bash
git status --short
git diff --stat HEAD
git diff --name-only HEAD
rg -n "version|^## |^Released:|当前开发版本|current" VERSION frontend/package.json pyproject.toml docs/CHANGELOG.md docs/version-history.md
```
除非需要判断某个代码变更是否属于本次发版,否则不要读取完整 diff。
## 执行步骤
### Step 1 — 环境检查
@@ -45,7 +58,7 @@ cat VERSION # 读取当前版本
### Step 2 — 确定发版类型与新版本号
-`$ARGUMENTS` 提供了明确类型(`feature` / `bugfix`),直接使用
- 否则根据当前 `git diff HEAD``git log` 推断
- 否则根据 `git diff --stat HEAD``git diff --name-only HEAD`、必要的 focused diff`git log` 推断
- 计算新版本号(例:`0.26.2` → bugfix → `0.26.3`
- **先输出发版计划供用户确认**
@@ -91,12 +104,13 @@ cat VERSION # 读取当前版本
针对本次变更范围做最小验证:
- Python 文件有修改:`python3 -m py_compile <changed_files>`
- Frontend 文件有修改:运行项目标准检查(若无则跳过并说明)
- Python 文件有修改:先用 `git diff --name-only HEAD -- '*.py'` 列出,再运行 `python3 -m py_compile <changed_files>`
- Frontend 文件有修改:先用 `git diff --name-only HEAD -- frontend` 判断范围,再运行项目标准检查(若无则跳过并说明)
- 版本号一致性检查:用 grep 确认 VERSION、package.json、pyproject.toml 中的版本号完全一致
```bash
grep -h "version" VERSION frontend/package.json pyproject.toml
cat VERSION
rg -n "\"version\":|^version =|version = " frontend/package.json pyproject.toml uv.lock
```
### Step 7 — 提交前预览

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@@ -21,6 +21,19 @@ If the user specifies a file or directory, check only that. Otherwise check all
Only report issues present in **newly added or modified** lines of this diff — do not audit unchanged code.
## Token-Saving Rule
Prefer deterministic CLI checks before reading files into model context:
```bash
git diff --name-only HEAD
git diff --unified=0 HEAD -- <path>
git diff --check
rg -n "TODO|FIXME|console\.log|debugger|print\(" <changed-paths>
```
Read full files only when the focused diff does not provide enough surrounding context to make a safe edit.
## Checklist
### 1. Duplicate Logic
@@ -64,7 +77,13 @@ Filter to the user-specified path if one was provided.
### Step 2 — Read and analyze each file
Read the full file (not just the diff) with the Read tool. For each file, record every issue found: filename, line number, category, and suggested fix.
Start with focused diffs:
```bash
git diff --unified=0 HEAD -- <file>
```
Use `rg`, `git diff --check`, and compiler/linter output for deterministic findings. Read the full file only for files that need surrounding context. For each issue found, record filename, line number, category, and suggested fix.
### Step 3 — Report findings before touching anything
@@ -99,6 +118,7 @@ Principles:
- Only fix issues identified in the checklist — no extra improvements
- Keep each Edit as small as possible
- After fixing, verify the old bad pattern is gone with grep
- Prefer `apply_patch` for targeted edits; use formatters only when the repository already uses them for the touched file type
### Step 5 — Summary

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@@ -0,0 +1,82 @@
---
name: docs
description: Create or update repository documentation from current code changes. Use when the user asks to write docs, update docs, summarize implementation changes into docs, or check documentation coverage. Load repository-specific coverage rules from docs/documentation-coverage-rules.md when present.
---
# Docs
Use this skill when the task is documentation work: creating, updating, checking, or summarizing docs for code or behavior changes.
## Goal
Write documentation that explains why a change exists, how it behaves, and what maintainers need to know. Keep the skill generic; repository-specific rules belong in the repository, not in this skill.
## Repository Rules
Before deciding scope, check whether the repository has a documentation rules file:
```bash
test -f docs/documentation-coverage-rules.md && sed -n '1,240p' docs/documentation-coverage-rules.md
```
If it exists, apply it as the project-specific coverage checklist. If it does not exist, continue with the generic workflow below.
## Workflow
1. Gather focused context:
```bash
git diff HEAD --stat
git diff HEAD --name-only
git log --oneline -10
rg --files docs
```
If the user gives a topic, focus on that topic. Otherwise infer the doc topic from changed files. Avoid reading large full diffs by default; inspect focused files and symbols:
```bash
git diff HEAD -- <path>
rg -n "class |def |function |export |router|@router|interface |type " <path>
```
2. Decide scope:
- Prefer updating an existing relevant doc over creating a duplicate.
- Use one document for one coherent topic.
- Split documents only when changes cross meaningful domains.
- Keep filenames lowercase and hyphenated.
3. Write the doc:
- Explain background/problem, design decisions, constraints, and operational impact.
- Keep code snippets short and directly relevant.
- List related files only when they help future maintainers navigate.
- Use the repositorys existing language, heading style, and naming conventions.
4. Verify:
- Read the completed doc once for clarity and stale statements.
- Verify important referenced paths exist with `test -e` or `rg --files`.
- Run repository-specific doc checks from `docs/documentation-coverage-rules.md` when present.
- For Markdown links, check that user-facing titles are readable and not raw filenames unless the repository rules allow it.
## Hard Constraints
- Do not leave placeholder docs or copied source text pretending to be documentation.
- Do not duplicate bilingual files byte-for-byte.
- Do not reference PR numbers, issue numbers, or the current conversation unless explicitly requested.
- Do not write changelog-style lists without the reasoning, constraints, and tradeoffs behind the change.
- Keep docs concise enough to maintain.
## Recommended Output
After editing, summarize:
```md
Updated:
- path/to/doc.md — what changed
Verified:
- checks that passed
- checks that could not be run, if any
```

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@@ -72,6 +72,8 @@ In Codex, only use actual subagents when the user explicitly asks for delegation
## Operating Rules
- Prefer objective checks over self-reported completion.
- Prefer deterministic tool evidence over long model summaries: use `rg`, `git diff --stat`, targeted `git diff -- <path>`, tests, builds, linters, `curl`, or database queries when they can prove a criterion.
- Do not paste large command output into the conversation; summarize the evidence and keep raw output in tool calls.
- Do not confuse progress with completion.
- If the worker says "done", verify it.
- If verification fails, continue from the gap instead of restarting blindly.

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@@ -18,7 +18,7 @@ Do not use this skill for ordinary commits that are not being released.
## Versioning Rules
- `feature` -> bump `+0.1.0`
- `feature` -> bump minor and reset patch to `0` (`x.y.z``x.(y+1).0`; for example `0.41.2``0.42.0`)
- `bugfix` -> bump `+0.0.1`
- `docs`, `maintenance`, and `refactor` do not bump by default unless the user explicitly wants a release
@@ -35,6 +35,19 @@ Use `git rev-parse --show-toplevel` to get the repo root. All paths are relative
- `docs/CHANGELOG.md`
- `docs/version-history.md`
## Token-Saving Rule
Release work should be driven by deterministic CLI evidence. Prefer compact commands and targeted file reads:
```bash
git status --short
git diff --stat HEAD
git diff --name-only HEAD
rg -n "version|^## |^Released:|current" VERSION frontend/package.json pyproject.toml docs/CHANGELOG.md docs/version-history.md
```
Do not inspect full diffs unless deciding whether changed code belongs in the release.
## Workflow
### Step 1 — Environment check
@@ -52,8 +65,10 @@ If unrelated uncommitted changes exist, list them and ask the user whether to in
### Step 2 — Determine release type and next version
- If the user provided an explicit type (`feature` / `bugfix`), use it
- Otherwise infer from `git diff HEAD` and recent `git log`
- Compute the next version (e.g. `0.26.2` → bugfix → `0.26.3`)
- Otherwise infer from `git diff --stat HEAD`, `git diff --name-only HEAD`, focused diffs for changed code, and recent `git log`
- Compute the next version:
- `feature`: increment minor and reset patch to `0` (e.g. `0.41.2``0.42.0`)
- `bugfix`: increment patch only (e.g. `0.26.2``0.26.3`)
- **Show the release plan before making any changes:**
```
@@ -104,12 +119,13 @@ Get today's date with `date +%Y-%m-%d`.
Run the smallest relevant validation for the changes in scope:
- Python files changed: `python3 -m py_compile <changed_files>`
- Frontend files changed: run the project-standard check if available; otherwise skip and say so
- Python files changed: list changed Python files with `git diff --name-only HEAD -- '*.py'`, then run `python3 -m py_compile <changed_files>`
- Frontend files changed: list changed frontend files with `git diff --name-only HEAD -- frontend`, then run the project-standard check if available; otherwise skip and say so
- Version consistency: confirm VERSION, package.json, pyproject.toml, and uv.lock all show the same version
```bash
grep -h "version" VERSION frontend/package.json pyproject.toml
cat VERSION
rg -n "\"version\":|^version =|version = " frontend/package.json pyproject.toml uv.lock
```
### Step 7 — Pre-commit preview

13
.dockerignore Normal file
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@@ -0,0 +1,13 @@
**
!pyproject.toml
!uv.lock
!aiprovider/
!aiprovider/**
aiprovider/.env
aiprovider/.env.*
!aiprovider/.env.example
**/__pycache__/
**/*.pyc
**/*.pyo

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@@ -23,8 +23,16 @@
- [ ] 保持 Earth 当前这批纯个人偏好设置继续走本地持久化:`旋转模式`、HUD 面板显示/隐藏、`地形透明度` 暂不升级到后端系统设置,避免把设备级偏好过早做成全局配置
- [ ] 如果后续明确需要“账号级同步 Earth 偏好”,再单独设计 `Earth user preferences`:优先按用户维度而不是全局系统设置保存,并规划 `localStorage -> backend` 的平滑迁移策略
- [ ] 为 Planet / Earth 补一个可用的日志查看系统:先明确前后端/AI Provider/采集任务的日志入口、最近日志聚合、筛选与 tail 能力,再决定是先做脚本级统一入口还是控制台内置日志面板
- [ ] 重写控制台 UI逐步抛弃 Ant Design建立自有组件体系并统一采用 `tabler.io` / Tabler Icons 作为控制台主图标库
- [ ] 把 Earth 态势新闻源从 [earth_news.py](/home/ray/dev/linkong/planet/backend/app/services/earth_news.py) 的硬编码列表抽成可配置目录,优先保持当前“实时聚合”链路不变,只先解决新闻源不可配置的问题
- [ ] 为 Earth 态势新闻设计后续采集器化方案:明确新闻数据模型、去重策略、区域映射、过期清理和 Earth/AI 复用方式,再决定何时把新闻从实时抓取升级成正式 collector
- [ ] AIS v3.1:修复船只聚合完整性,`/geo/vessels` 合并 raw observation 聚合结果与 legacy `vessel_position + vessel_static` 最新结果,确保 BarentsWatch-only 船只不会因为 AISStream 子集存在而消失,并增加 raw/legacy/final unique MMSI 诊断统计
- [ ] AIS v3.2:把 AISStream 从收满 `max_messages` 后结束的批采集改成长连接 streaming service持续写入 raw observations通过内部 `/ws``vessels` channel 推送新船、位置和航向增量Earth 前端按 MMSI upsert marker
- [ ] AIS v3.3:修正 AISStream 采集页面状态语义,使用 connecting/streaming/reconnecting/stopped 与 indeterminate 状态展示运行时长、消息数、unique MMSI、message rate、最近消息和错误不再用一次性 REST 进度条表示长连接
- [ ] AIS v3.4修复船只身份字段和名称聚合MMSI/IMO/callsign 按字符串显示且不带千分位符;查询并列出所有仍以 MMSI 号码或 `MMSI <number>` 作为船名的记录标注来源、最近观测、message types 和缺失原因,并把这批 fallback-name 船只纳入名称聚合修复集合
- [ ] Earth Live Sync建立统一态势实时同步链路新增 `earth_summary` WS channel任意采集器成功后广播轻量 summary invalidation前端收到后重新拉 `/api/v1/visualization/geo/summary` 并更新 HUD同时为 BGP 增加 `bgp` WS channel使 BGP incidents/anomalies/collectors 在不刷新页面时也能 upsert 图层;卫星采集完成后触发 summary 刷新,必要时按 TLE 版本重新 hydrate 卫星数据
- [ ] AIS v4开放船只多源聚合策略配置支持 source priority、字段级规则、freshness 窗口和高级保护开关;保存时校验未知字段、非法模式和危险动态字段锁定,并在聚合接口返回命中的配置版本
- [ ] AIS v5实现船舶资料 enrichment 与冲突治理,按 `mmsi + imo + name + callsign` 异步补充船型细分、AIS 大类、旗国、尺寸、建造年份、运营方和图片缓存;详情面板展示缓存资料和字段来源,不在实时 AIS 请求链路现场抓第三方页面
- [ ] 为 Earth 地球表面增加一层与基础纹理对齐的材质/纹理 overlay并在同层叠加国界轮廓参考线要求国界线与底图稳定对齐且 hover 到国家轮廓时能高亮当前国家,便于校准地表和增强交互
- [ ] 把 Earth 新闻接入通用巡航队列:按新闻发生地和时间排序生成巡航目标,巡航聚焦到新闻事件时显示对应新闻卡片,并保持实现边界为“通用巡航层 + 新闻业务适配层”,不要再把新闻逻辑直接耦合回 `main.js` 状态机
- [ ] 为未知位置的算力中心建立分层坐标补全链路:优先 `精确坐标 > 站点/园区命中 > 城市 > 州/省 > 国家内主要算力城市 > 国家质心`,并把每次回退的 `confidence / reason / precision` 明确写进统一 GeoJSON

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@@ -1 +1 @@
0.41.0
0.48.0

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@@ -1,6 +1,12 @@
FROM python:3.14-slim
# syntax=docker/dockerfile:1.7
COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
ARG PYTHON_IMAGE=python:3.14-slim
ARG UV_IMAGE=ghcr.io/astral-sh/uv:latest
FROM ${UV_IMAGE} AS uv
FROM ${PYTHON_IMAGE}
COPY --from=uv /uv /uvx /bin/
WORKDIR /app
@@ -14,9 +20,10 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
&& rm -rf /var/lib/apt/lists/*
COPY pyproject.toml uv.lock /app/
RUN uv sync --frozen --no-dev
RUN --mount=type=cache,target=/root/.cache/uv \
uv sync --frozen --no-dev
COPY . /app
COPY aiprovider /app/aiprovider
EXPOSE 8010

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@@ -37,8 +37,26 @@ def verify_service_token(x_provider_token: str | None = Header(default=None)) ->
)
def get_provider_service() -> ProviderService:
return ProviderService()
def get_provider_service(
x_ai_provider: str | None = Header(default=None),
x_ai_provider_api: str | None = Header(default=None),
x_ai_base_url: str | None = Header(default=None),
x_ai_api_key: str | None = Header(default=None),
x_ai_model: str | None = Header(default=None),
x_ai_max_tokens: str | None = Header(default=None),
x_ai_anthropic_version: str | None = Header(default=None),
) -> ProviderService:
overrides = {
"provider": x_ai_provider,
"provider_api": x_ai_provider_api,
"base_url": x_ai_base_url,
"api_key": x_ai_api_key,
"model": x_ai_model,
"anthropic_version": x_ai_anthropic_version,
}
if x_ai_max_tokens:
overrides["max_tokens"] = x_ai_max_tokens
return ProviderService({key: value for key, value in overrides.items() if value not in (None, "")})
@app.get("/health")

View File

@@ -46,19 +46,22 @@ def _resolve_provider_api(provider: str, configured_api: str) -> str:
class ProviderService:
def __init__(self) -> None:
self.provider = _normalize_provider(settings.AI_PROVIDER)
def __init__(self, overrides: dict[str, Any] | None = None) -> None:
overrides = overrides or {}
self.provider = _normalize_provider(overrides.get("provider") or settings.AI_PROVIDER)
self.provider_api = _resolve_provider_api(
self.provider,
_normalize_provider_api(settings.AI_PROVIDER_API),
_normalize_provider_api(overrides.get("provider_api") or settings.AI_PROVIDER_API),
)
self.base_url = settings.AI_BASE_URL.rstrip("/")
self.api_key = settings.AI_API_KEY
self.default_model = settings.AI_MODEL
self.base_url = str(overrides.get("base_url") or settings.AI_BASE_URL).rstrip("/")
self.api_key = str(overrides.get("api_key") or settings.AI_API_KEY)
self.default_model = str(overrides.get("model") or settings.AI_MODEL)
self.timeout = settings.AI_TIMEOUT_SECONDS
self.http_retry_attempts = max(settings.AI_HTTP_RETRY_ATTEMPTS, 1)
self.max_tokens = settings.AI_MAX_TOKENS
self.anthropic_version = settings.AI_ANTHROPIC_VERSION
self.max_tokens = int(overrides.get("max_tokens") or settings.AI_MAX_TOKENS)
self.anthropic_version = str(
overrides.get("anthropic_version") or settings.AI_ANTHROPIC_VERSION
)
self.system_prompt = settings.AI_ANALYSIS_SYSTEM_PROMPT
def get_status(self) -> AIProviderStatusResponse:

View File

@@ -1,6 +1,10 @@
FROM python:3.14-slim
ARG PYTHON_IMAGE=python:3.14-slim
ARG UV_IMAGE=ghcr.io/astral-sh/uv:latest
COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
FROM ${UV_IMAGE} AS uv
FROM ${PYTHON_IMAGE}
COPY --from=uv /uv /uvx /bin/
WORKDIR /app

View File

@@ -12,6 +12,7 @@ from app.api.v1 import (
settings,
collected_data,
visualization,
vessel_aggregation,
bgp,
news,
system_control,
@@ -34,6 +35,11 @@ api_router.include_router(alerts.router, prefix="/alerts", tags=["alerts"])
api_router.include_router(settings.router, prefix="/settings", tags=["settings"])
api_router.include_router(system_control.router, prefix="/system", tags=["system"])
api_router.include_router(visualization.router, prefix="/visualization", tags=["visualization"])
api_router.include_router(
vessel_aggregation.router,
prefix="/vessel-aggregation",
tags=["vessel-aggregation"],
)
api_router.include_router(bgp.router, prefix="/bgp", tags=["bgp"])
api_router.include_router(tv.router, prefix="/tv", tags=["tv"])
api_router.include_router(news.router, prefix="/news", tags=["news"])

View File

@@ -1,20 +1,52 @@
"""DataSourceConfig API for user-defined data sources"""
from typing import Optional
from typing import Any, Optional
from datetime import datetime
import base64
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy import select, func
import json
import re
from fastapi import APIRouter, Depends, HTTPException, Query
from sqlalchemy import delete, select, func
from sqlalchemy.ext.asyncio import AsyncSession
from pydantic import BaseModel, Field
import httpx
from app.core.target_schema_registry import get_target_schema, list_target_schemas
from app.core.datasource_defaults import DEFAULT_DATASOURCES
from app.db.session import get_db
from app.models.user import User
from app.models.datasource_config import DataSourceConfig
from app.models.datasource_mapping import DataSourceMappingTemplate
from app.models.collected_data import CollectedData
from app.models.vessel import AISRawObservation, AISSourceHealth
from app.core.security import get_current_user
from app.core.cache import cache
from app.core.time import to_iso8601_utc
from app.schemas.ai import SituationalAnalysisRequest
from app.services.ai_client import AIProviderClient, get_ai_provider_client
from app.services.datasource_mapping import (
MappingError,
build_heuristic_mapping,
execute_mapping,
redact_for_llm,
stable_payload_hash,
)
from app.services.custom_datasource_runtime import (
CustomDatasourceRuntimeError,
fetch_rest_payload,
get_custom_stream_status,
run_mapped_rest_config,
run_mapped_websocket_config,
start_custom_stream,
stop_custom_stream,
test_websocket_config,
)
from app.services.datasource_connectivity import (
get_builtin_connection_status,
save_connectivity_success,
strip_connectivity_validation,
test_builtin_connectivity,
)
router = APIRouter()
@@ -22,7 +54,7 @@ router = APIRouter()
class DataSourceConfigCreate(BaseModel):
name: str = Field(..., min_length=1, max_length=100)
description: Optional[str] = None
source_type: str = Field(..., description="http, api, database")
source_type: str = Field(..., description="rest, websocket, http, api, database")
endpoint: str = Field(..., max_length=500)
auth_type: str = Field(default="none", description="none, bearer, api_key, basic")
auth_config: dict = Field(default={})
@@ -59,6 +91,70 @@ class DataSourceConfigResponse(BaseModel):
from_attributes = True
def _is_builtin_config_name(name: str | None) -> bool:
return bool(name and name in DEFAULT_DATASOURCES)
async def _ensure_builtin_connection_verified(
db: AsyncSession,
config_data: DataSourceConfigCreate,
) -> None:
if not _is_builtin_config_name(config_data.name):
return
status_result = await get_builtin_connection_status(
db,
config_data.name,
config_data.endpoint,
config_data.auth_type,
config_data.headers,
config_data.config,
)
if not status_result.get("connected"):
raise HTTPException(
status_code=400,
detail=status_result.get("message") or "请先完成连接验证,再保存内置采集器配置。",
)
class CustomSampleRequest(BaseModel):
datasource_config_id: Optional[int] = None
config: Optional[DataSourceConfigCreate] = None
limit_bytes: int = Field(default=200000, ge=1000, le=1000000)
class MappingProposeRequest(BaseModel):
sample_payload: Any
target_schema: str
use_ai: bool = True
class MappingPreviewRequest(BaseModel):
sample_payload: Any
target_schema: str
mapping_json: dict
limit: int = Field(default=20, ge=1, le=100)
class MappingTemplateCreate(BaseModel):
datasource_config_id: int
target_schema: str
mapping_json: dict
sample_payload: Any | None = None
sample_payload_hash: Optional[str] = None
validation_status: str = Field(default="draft", pattern="^(draft|valid|invalid)$")
is_active: bool = False
class MappingTemplateUpdate(BaseModel):
target_schema: Optional[str] = None
mapping_json: Optional[dict] = None
sample_payload: Any | None = None
sample_payload_hash: Optional[str] = None
validation_status: Optional[str] = Field(default=None, pattern="^(draft|valid|invalid)$")
is_active: Optional[bool] = None
async def test_endpoint(
endpoint: str,
auth_type: str,
@@ -96,6 +192,136 @@ async def test_endpoint(
}
def _build_request_headers(auth_type: str, auth_config: dict, headers: dict) -> dict[str, str]:
request_headers = {str(key): str(value) for key, value in (headers or {}).items()}
auth_type = str(auth_type or "none").lower()
auth_config = auth_config or {}
if auth_type == "bearer" and auth_config.get("token"):
request_headers["Authorization"] = f"Bearer {auth_config['token']}"
elif auth_type == "api_key" and auth_config.get("api_key"):
location = str(auth_config.get("in") or auth_config.get("location") or "header").lower()
if location != "query":
key_name = auth_config.get("key_name", "X-API-Key")
request_headers[str(key_name)] = str(auth_config["api_key"])
elif auth_type == "basic":
username = auth_config.get("username", "")
password = auth_config.get("password", "")
credentials = f"{username}:{password}"
encoded = base64.b64encode(credentials.encode()).decode()
request_headers["Authorization"] = f"Basic {encoded}"
return request_headers
def _build_query_params(auth_type: str, auth_config: dict, config: dict) -> dict[str, Any]:
params = {}
candidate = (config or {}).get("params") or (config or {}).get("query_params")
if isinstance(candidate, dict):
params.update(candidate)
auth_type = str(auth_type or "none").lower()
auth_config = auth_config or {}
if auth_type == "api_key" and auth_config.get("api_key"):
location = str(auth_config.get("in") or auth_config.get("location") or "header").lower()
if location == "query":
key_name = auth_config.get("key_name") or auth_config.get("param_name") or "api_key"
params[str(key_name)] = auth_config["api_key"]
return params
async def fetch_custom_sample_from_config(config: DataSourceConfig, limit_bytes: int) -> Any:
if str(config.source_type or "").lower() in {"websocket", "ws"}:
raise HTTPException(status_code=400, detail="WebSocket sources must use connection test or run-mapped stream.")
request_config = config.config or {}
method = str(request_config.get("method") or request_config.get("request_method") or "GET").upper()
if method not in {"GET", "POST"}:
raise HTTPException(status_code=400, detail="Only GET and POST sample requests are supported.")
headers = _build_request_headers(config.auth_type, config.auth_config or {}, config.headers or {})
params = _build_query_params(config.auth_type, config.auth_config or {}, request_config)
timeout = float(request_config.get("timeout", 30))
json_body = request_config.get("json_body")
if json_body is None and str(request_config.get("body_type") or "").lower() in {"json", ""}:
candidate = request_config.get("body")
if isinstance(candidate, (dict, list)):
json_body = candidate
async with httpx.AsyncClient(timeout=timeout, follow_redirects=True) as client:
response = await client.request(
method,
config.endpoint,
headers=headers,
params=params or None,
json=json_body,
)
response.raise_for_status()
content = response.content[:limit_bytes]
if "application/json" in response.headers.get("content-type", ""):
return json.loads(content.decode(response.encoding or "utf-8"))
return {"text": content.decode(response.encoding or "utf-8", errors="replace")}
def _parse_mapping_from_ai_text(content: str) -> dict[str, Any] | None:
if not content:
return None
candidates = [content]
fenced = re.findall(r"```(?:json)?\s*(\{.*?\})\s*```", content, flags=re.DOTALL)
candidates = fenced + candidates
for candidate in candidates:
try:
parsed = json.loads(candidate)
except json.JSONDecodeError:
continue
if isinstance(parsed, dict) and isinstance(parsed.get("fields"), dict):
return parsed
return None
async def _get_config_for_sample(
payload: CustomSampleRequest,
db: AsyncSession,
) -> DataSourceConfig:
if payload.datasource_config_id is not None:
result = await db.execute(
select(DataSourceConfig).where(DataSourceConfig.id == payload.datasource_config_id)
)
config = result.scalar_one_or_none()
if not config:
raise HTTPException(status_code=404, detail="Configuration not found")
return config
if payload.config is None:
raise HTTPException(status_code=400, detail="datasource_config_id or config is required")
config_data = payload.config
return DataSourceConfig(
name=config_data.name,
description=config_data.description,
source_type=config_data.source_type,
endpoint=config_data.endpoint,
auth_type=config_data.auth_type,
auth_config=config_data.auth_config,
headers=config_data.headers,
config=config_data.config,
)
def serialize_mapping_template(template: DataSourceMappingTemplate) -> dict[str, Any]:
return {
"id": template.id,
"datasource_config_id": template.datasource_config_id,
"target_schema": template.target_schema,
"mapping_json": template.mapping_json,
"sample_payload_hash": template.sample_payload_hash,
"validation_status": template.validation_status,
"version": template.version,
"is_active": template.is_active,
"created_at": to_iso8601_utc(template.created_at),
"updated_at": to_iso8601_utc(template.updated_at),
}
@router.get("/configs")
async def list_configs(
active_only: bool = False,
@@ -105,7 +331,7 @@ async def list_configs(
"""List all user-defined data source configurations"""
query = select(DataSourceConfig)
if active_only:
query = query.where(DataSourceConfig.is_active == True)
query = query.where(DataSourceConfig.is_active)
query = query.order_by(DataSourceConfig.created_at.desc())
result = await db.execute(query)
@@ -132,6 +358,52 @@ async def list_configs(
}
@router.get("/configs/all")
async def list_all_datasources(
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
"""List all data sources: YAML defaults + DB overrides"""
from app.core.data_sources import COLLECTOR_URL_KEYS, get_data_sources_config
config = get_data_sources_config()
db_query = await db.execute(select(DataSourceConfig))
db_configs = {c.name: c for c in db_query.scalars().all()}
result = []
for name, yaml_key in COLLECTOR_URL_KEYS.items():
yaml_url = config.get_yaml_url(name)
db_config = db_configs.get(name)
result.append(
{
"name": name,
"default_url": yaml_url,
"endpoint": db_config.endpoint if db_config else yaml_url,
"is_overridden": db_config is not None and db_config.endpoint != yaml_url
if yaml_url
else db_config is not None,
"is_active": db_config.is_active if db_config else True,
"source_type": db_config.source_type if db_config else "http",
"auth_type": db_config.auth_type if db_config else "none",
"auth_configured": {
"api_key": bool((db_config.auth_config or {}).get("api_key"))
if db_config
else False,
},
"headers": db_config.headers if db_config else {},
"config": strip_connectivity_validation(db_config.config if db_config else {}),
"config_id": db_config.id if db_config else None,
"description": db_config.description
if db_config
else f"Data source from YAML: {yaml_key}",
}
)
return {"total": len(result), "data": result}
@router.get("/configs/{config_id}")
async def get_config(
config_id: int,
@@ -176,7 +448,7 @@ async def create_config(
auth_type=config_data.auth_type,
auth_config=config_data.auth_config,
headers=config_data.headers,
config=config_data.config,
config=strip_connectivity_validation(config_data.config),
)
db.add(config)
@@ -208,6 +480,10 @@ async def update_config(
update_data = config_data.model_dump(exclude_unset=True)
for field, value in update_data.items():
if field == "config":
value = strip_connectivity_validation(value)
if field == "auth_config" and value == {} and (config.auth_config or {}):
continue
setattr(config, field, value)
await db.commit()
@@ -225,6 +501,8 @@ async def update_config(
@router.delete("/configs/{config_id}")
async def delete_config(
config_id: int,
delete_mappings: bool = Query(False),
delete_source_data: bool = Query(False),
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
@@ -235,12 +513,59 @@ async def delete_config(
if not config:
raise HTTPException(status_code=404, detail="Configuration not found")
deleted_mappings = 0
deleted_records = {
"collected_data": 0,
"ais_raw_observations": 0,
"ais_source_health": 0,
}
if delete_source_data:
collected_result = await db.execute(
delete(CollectedData).where(CollectedData.source == config.name)
)
raw_result = await db.execute(
delete(AISRawObservation).where(AISRawObservation.source == config.name)
)
health_result = await db.execute(
delete(AISSourceHealth).where(AISSourceHealth.source == config.name)
)
deleted_records = {
"collected_data": collected_result.rowcount or 0,
"ais_raw_observations": raw_result.rowcount or 0,
"ais_source_health": health_result.rowcount or 0,
}
if delete_mappings or delete_source_data:
mapping_result = await db.execute(
delete(DataSourceMappingTemplate).where(
DataSourceMappingTemplate.datasource_config_id == config_id
)
)
deleted_mappings = mapping_result.rowcount or 0
await db.delete(config)
await db.commit()
cache.delete_pattern("datasource_configs:*")
return {"message": "Configuration deleted successfully"}
if delete_source_data and (config.config or {}).get("target_schema") == "vessel_ais":
from app.core.websocket.broadcaster import broadcaster
await broadcaster.broadcast_custom(
"vessels",
{
"action": "reload",
"source": config.name,
"reason": "custom_source_deleted",
},
)
return {
"message": "Configuration deleted successfully",
"deleted_mappings": deleted_mappings,
"deleted_records": deleted_records,
}
@router.post("/configs/{config_id}/test")
@@ -257,6 +582,8 @@ async def test_config(
raise HTTPException(status_code=404, detail="Configuration not found")
try:
if str(config.source_type or "").lower() in {"websocket", "ws"}:
return await test_websocket_config(config)
result = await test_endpoint(
endpoint=config.endpoint,
auth_type=config.auth_type,
@@ -287,6 +614,18 @@ async def test_new_config(
):
"""Test a new data source configuration without saving"""
try:
if str(config_data.source_type or "").lower() in {"websocket", "ws"}:
config = DataSourceConfig(
name=config_data.name,
description=config_data.description,
source_type=config_data.source_type,
endpoint=config_data.endpoint,
auth_type=config_data.auth_type,
auth_config=config_data.auth_config,
headers=config_data.headers,
config=config_data.config,
)
return await test_websocket_config(config)
result = await test_endpoint(
endpoint=config_data.endpoint,
auth_type=config_data.auth_type,
@@ -310,38 +649,363 @@ async def test_new_config(
}
@router.get("/configs/all")
async def list_all_datasources(
@router.post("/configs/builtin/connection-status")
async def get_builtin_config_connection_status(
config_data: DataSourceConfigCreate,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
"""List all data sources: YAML defaults + DB overrides"""
from app.core.data_sources import COLLECTOR_URL_KEYS, get_data_sources_config
if not _is_builtin_config_name(config_data.name):
raise HTTPException(status_code=400, detail="Only built-in datasource configs are supported.")
config = get_data_sources_config()
return await get_builtin_connection_status(
db,
config_data.name,
config_data.endpoint,
config_data.auth_type,
config_data.headers,
config_data.config,
)
db_query = await db.execute(select(DataSourceConfig))
db_configs = {c.name: c for c in db_query.scalars().all()}
result = []
for name, yaml_key in COLLECTOR_URL_KEYS.items():
yaml_url = config.get_yaml_url(name)
db_config = db_configs.get(name)
@router.post("/configs/builtin/connect")
async def connect_builtin_config(
config_data: DataSourceConfigCreate,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
if not _is_builtin_config_name(config_data.name):
raise HTTPException(status_code=400, detail="Only built-in datasource configs are supported.")
result.append(
result = await test_builtin_connectivity(
config_data.name,
config_data.endpoint,
config_data.auth_type,
config_data.headers,
config_data.config,
db,
config_data.auth_config,
)
if result.get("success") and result.get("checksum"):
validation = await save_connectivity_success(
db,
config_data.name,
result["checksum"],
result,
connected_by="connection_button",
)
await db.commit()
return {
**result,
"connected": True,
"validation": validation,
}
return {
**result,
"connected": False,
}
@router.post("/custom/sample")
async def fetch_custom_sample(
payload: CustomSampleRequest,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
"""Fetch a sample payload for a saved or draft custom data source."""
config = await _get_config_for_sample(payload, db)
try:
sample = await fetch_custom_sample_from_config(config, payload.limit_bytes)
except httpx.HTTPStatusError as exc:
raise HTTPException(
status_code=exc.response.status_code,
detail=f"Sample request failed: HTTP {exc.response.status_code}",
) from exc
except httpx.HTTPError as exc:
raise HTTPException(status_code=502, detail=f"Sample request failed: {exc}") from exc
return {
"success": True,
"sample_payload": sample,
"sample_payload_hash": stable_payload_hash(sample),
"redacted_preview": redact_for_llm(sample),
}
@router.get("/target-schemas")
async def get_datasource_target_schemas(
current_user: User = Depends(get_current_user),
):
"""List target schemas available for custom datasource mapping."""
return {"data": list_target_schemas()}
@router.post("/mappings/propose")
async def propose_datasource_mapping(
payload: MappingProposeRequest,
current_user: User = Depends(get_current_user),
ai_client: AIProviderClient = Depends(get_ai_provider_client),
):
"""Generate a mapping draft for a sample payload and target schema."""
schema = get_target_schema(payload.target_schema)
redacted_sample = redact_for_llm(payload.sample_payload)
fallback_mapping = build_heuristic_mapping(redacted_sample, payload.target_schema)
ai_error: str | None = None
mapping = fallback_mapping
generated_by = "heuristic"
if payload.use_ai:
try:
response = await ai_client.analyze(
SituationalAnalysisRequest(
title=f"Generate datasource mapping for {schema.key}",
objective=(
"Return only JSON for a deterministic mapping DSL. "
"The JSON must contain source.items_path and fields. "
"Do not include prose or code."
),
context={
"target_schema": schema.to_dict(),
"sample_payload": redacted_sample,
"mapping_dsl_example": fallback_mapping,
},
observations=[
"Use JSONPath-like paths beginning with $.",
"Never generate executable code.",
"Use field types from the target schema.",
],
constraints=[
"Return a single JSON object.",
"Do not include credentials or secrets.",
"Mark uncertain optional fields with default null.",
],
)
)
parsed = _parse_mapping_from_ai_text(response.content)
if parsed:
mapping = parsed
generated_by = "ai_provider"
else:
ai_error = "AI provider did not return a valid mapping JSON object."
except HTTPException as exc:
ai_error = str(exc.detail)
mapping.setdefault("meta", {})
if isinstance(mapping["meta"], dict):
mapping["meta"].update(
{
"name": name,
"default_url": yaml_url,
"endpoint": db_config.endpoint if db_config else yaml_url,
"is_overridden": db_config is not None and db_config.endpoint != yaml_url
if yaml_url
else db_config is not None,
"is_active": db_config.is_active if db_config else True,
"source_type": db_config.source_type if db_config else "http",
"description": db_config.description
if db_config
else f"Data source from YAML: {yaml_key}",
"generated_by": generated_by,
"requires_review": True,
"ai_error": ai_error,
}
)
return {"total": len(result), "data": result}
return {
"target_schema": schema.to_dict(),
"mapping_json": mapping,
"sample_payload_hash": stable_payload_hash(payload.sample_payload),
"redacted_sample_payload": redacted_sample,
}
@router.post("/mappings/preview")
async def preview_datasource_mapping(
payload: MappingPreviewRequest,
current_user: User = Depends(get_current_user),
):
"""Preview deterministic mapping output for a sample payload."""
try:
preview = execute_mapping(
payload.sample_payload,
payload.mapping_json,
payload.target_schema,
limit=payload.limit,
)
except (MappingError, ValueError) as exc:
raise HTTPException(status_code=400, detail=str(exc)) from exc
return {
"success": preview["failed_count"] == 0,
"preview": preview,
"sample_payload_hash": stable_payload_hash(payload.sample_payload),
}
@router.get("/mappings")
async def list_datasource_mappings(
datasource_config_id: Optional[int] = None,
active_only: bool = False,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
"""List saved mapping templates."""
query = select(DataSourceMappingTemplate).order_by(
DataSourceMappingTemplate.datasource_config_id,
DataSourceMappingTemplate.version.desc(),
)
if datasource_config_id is not None:
query = query.where(DataSourceMappingTemplate.datasource_config_id == datasource_config_id)
if active_only:
query = query.where(DataSourceMappingTemplate.is_active.is_(True))
result = await db.execute(query)
mappings = result.scalars().all()
return {"total": len(mappings), "data": [serialize_mapping_template(item) for item in mappings]}
@router.post("/mappings")
async def create_datasource_mapping(
payload: MappingTemplateCreate,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
"""Save a mapping template for a datasource config."""
get_target_schema(payload.target_schema)
datasource = await db.get(DataSourceConfig, payload.datasource_config_id)
if not datasource:
raise HTTPException(status_code=404, detail="Configuration not found")
if payload.sample_payload is not None:
try:
execute_mapping(payload.sample_payload, payload.mapping_json, payload.target_schema, limit=100)
except (MappingError, ValueError) as exc:
raise HTTPException(status_code=400, detail=f"Mapping validation failed: {exc}") from exc
result = await db.execute(
select(func.max(DataSourceMappingTemplate.version)).where(
DataSourceMappingTemplate.datasource_config_id == payload.datasource_config_id,
DataSourceMappingTemplate.target_schema == payload.target_schema,
)
)
next_version = int(result.scalar() or 0) + 1
if payload.is_active:
await db.execute(
DataSourceMappingTemplate.__table__.update()
.where(DataSourceMappingTemplate.datasource_config_id == payload.datasource_config_id)
.values(is_active=False)
)
template = DataSourceMappingTemplate(
datasource_config_id=payload.datasource_config_id,
target_schema=payload.target_schema,
mapping_json=payload.mapping_json,
sample_payload_hash=payload.sample_payload_hash
or (stable_payload_hash(payload.sample_payload) if payload.sample_payload is not None else None),
validation_status=payload.validation_status,
version=next_version,
is_active=payload.is_active,
)
db.add(template)
await db.commit()
await db.refresh(template)
return {"message": "Mapping template saved successfully", "data": serialize_mapping_template(template)}
@router.put("/mappings/{mapping_id}")
async def update_datasource_mapping(
mapping_id: int,
payload: MappingTemplateUpdate,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
"""Update a mapping template in place."""
template = await db.get(DataSourceMappingTemplate, mapping_id)
if not template:
raise HTTPException(status_code=404, detail="Mapping template not found")
target_schema = payload.target_schema or template.target_schema
mapping_json = payload.mapping_json or template.mapping_json
get_target_schema(target_schema)
if payload.sample_payload is not None:
try:
execute_mapping(payload.sample_payload, mapping_json, target_schema, limit=100)
except (MappingError, ValueError) as exc:
raise HTTPException(status_code=400, detail=f"Mapping validation failed: {exc}") from exc
if payload.is_active is True:
await db.execute(
DataSourceMappingTemplate.__table__.update()
.where(DataSourceMappingTemplate.datasource_config_id == template.datasource_config_id)
.where(DataSourceMappingTemplate.id != template.id)
.values(is_active=False)
)
template.target_schema = target_schema
template.mapping_json = mapping_json
if payload.sample_payload_hash is not None:
template.sample_payload_hash = payload.sample_payload_hash
elif payload.sample_payload is not None:
template.sample_payload_hash = stable_payload_hash(payload.sample_payload)
if payload.validation_status is not None:
template.validation_status = payload.validation_status
if payload.is_active is not None:
template.is_active = payload.is_active
await db.commit()
await db.refresh(template)
return {"message": "Mapping template updated successfully", "data": serialize_mapping_template(template)}
@router.post("/{config_id}/run-mapped")
async def run_mapped_datasource(
config_id: int,
background: bool = Query(False, description="For WebSocket sources, start a background stream task."),
debug_max_messages: int | None = Query(None, ge=1),
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
"""Run a saved custom datasource through its active deterministic mapping."""
datasource = await db.get(DataSourceConfig, config_id)
if not datasource:
raise HTTPException(status_code=404, detail="Configuration not found")
try:
if str(datasource.source_type or "").lower() in {"websocket", "ws"}:
if background and debug_max_messages is None:
started = start_custom_stream(config_id)
if not started:
raise HTTPException(status_code=409, detail="Custom WebSocket source is already running")
return {
"status": "started",
"datasource_config_id": config_id,
"stream": get_custom_stream_status(config_id),
}
return await run_mapped_websocket_config(
db,
datasource,
debug_max_messages=debug_max_messages,
)
return await run_mapped_rest_config(db, datasource)
except httpx.HTTPStatusError as exc:
raise HTTPException(
status_code=exc.response.status_code,
detail=f"Datasource request failed: HTTP {exc.response.status_code}",
) from exc
except httpx.HTTPError as exc:
raise HTTPException(status_code=502, detail=f"Datasource request failed: {exc}") from exc
except (CustomDatasourceRuntimeError, MappingError, ValueError) as exc:
raise HTTPException(status_code=400, detail=f"Mapping failed: {exc}") from exc
@router.post("/{config_id}/stop-mapped")
async def stop_mapped_datasource(
config_id: int,
current_user: User = Depends(get_current_user),
):
stopped = await stop_custom_stream(config_id)
return {
"status": "stopped" if stopped else "not_running",
"datasource_config_id": config_id,
"stream": get_custom_stream_status(config_id),
}
@router.get("/{config_id}/stream-status")
async def get_mapped_stream_status(
config_id: int,
current_user: User = Depends(get_current_user),
):
return get_custom_stream_status(config_id)

View File

@@ -9,6 +9,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
from app.core.time import to_iso8601_utc
from app.core.security import get_current_user
from app.core.data_sources import get_data_sources_config
from app.core.datasource_defaults import DEFAULT_DATASOURCES
from app.db.session import get_db
from app.models.collected_data import CollectedData
from app.models.data_snapshot import DataSnapshot
@@ -35,6 +36,17 @@ def format_frequency_label(minutes: int) -> str:
return f"{minutes}m"
def datasource_metadata(source: str) -> dict:
info = DEFAULT_DATASOURCES.get(source, {})
return {
"display_name": info.get("display_name") or info.get("name") or source,
"is_free": bool(info.get("is_free", True)),
"requires_credentials": bool(info.get("requires_credentials", False)),
"credential_provider": info.get("credential_provider"),
"credential_status": info.get("credential_status", "none"),
}
def is_due_for_collection(datasource: DataSource, now: datetime) -> bool:
if datasource.last_run_at is None:
return True
@@ -72,31 +84,6 @@ async def _load_latest_running_tasks(
return {task.datasource_id: task for task in result.scalars().all()}
async def _load_latest_completed_tasks(
db: AsyncSession,
datasource_ids: list[int],
) -> dict[int, CollectionTask]:
if not datasource_ids:
return {}
ranked_tasks = (
select(
CollectionTask.id.label("task_id"),
_task_rank_column(CollectionTask.completed_at),
)
.where(CollectionTask.datasource_id.in_(datasource_ids))
.where(CollectionTask.completed_at.isnot(None))
.where(CollectionTask.status.in_(("success", "failed", "cancelled")))
.subquery()
)
result = await db.execute(
select(CollectionTask)
.join(ranked_tasks, CollectionTask.id == ranked_tasks.c.task_id)
.where(ranked_tasks.c.row_num == 1)
)
return {task.datasource_id: task for task in result.scalars().all()}
async def _load_latest_task_ids(
db: AsyncSession,
datasource_ids: list[int],
@@ -123,21 +110,6 @@ async def _load_latest_task_ids(
return {datasource_id: task_id for datasource_id, task_id in result.all()}
async def _load_datasource_data_counts(
db: AsyncSession,
sources: list[str],
) -> dict[str, int]:
if not sources:
return {}
result = await db.execute(
select(CollectedData.source, func.count(CollectedData.id))
.where(CollectedData.source.in_(sources))
.group_by(CollectedData.source)
)
return {source: count for source, count in result.all()}
async def _load_datasource_endpoint_overrides(
db: AsyncSession,
sources: list[str],
@@ -161,7 +133,7 @@ async def _load_datasource_endpoint_overrides(
async def _load_datasource_list_context(
db: AsyncSession,
datasources: list[DataSource],
) -> tuple[dict[int, CollectionTask], dict[int, CollectionTask], dict[str, int], dict[str, str]]:
) -> tuple[dict[int, CollectionTask], dict[str, str]]:
datasource_ids = [datasource.id for datasource in datasources]
sources = [datasource.source for datasource in datasources]
@@ -185,10 +157,8 @@ async def _load_datasource_list_context(
if stale_datasource_ids:
running_tasks = await _load_latest_running_tasks(db, datasource_ids)
completed_tasks = await _load_latest_completed_tasks(db, datasource_ids)
data_counts = await _load_datasource_data_counts(db, sources)
endpoint_overrides = await _load_datasource_endpoint_overrides(db, sources)
return running_tasks, completed_tasks, data_counts, endpoint_overrides
return running_tasks, endpoint_overrides
async def get_datasource_record(db: AsyncSession, source_id: str) -> Optional[DataSource]:
@@ -401,27 +371,19 @@ async def list_datasources(
collector_list = []
config = get_data_sources_config()
running_tasks, completed_tasks, data_counts, endpoint_overrides = await _load_datasource_list_context(
db,
datasources,
)
running_tasks, endpoint_overrides = await _load_datasource_list_context(db, datasources)
for datasource in datasources:
running_task = running_tasks.get(datasource.id)
last_task = completed_tasks.get(datasource.id)
endpoint = endpoint_overrides.get(datasource.source) or config.get_yaml_url(
datasource.source,
)
data_count = data_counts.get(datasource.source, 0)
last_run_at = datasource.last_run_at or (last_task.completed_at if last_task else None)
last_run = to_iso8601_utc(last_run_at)
last_status = datasource.last_status or (last_task.status if last_task else None)
endpoint = endpoint_overrides.get(datasource.source) or config.get_yaml_url(datasource.source)
last_run_at = datasource.last_run_at
last_status = datasource.last_status
collector_list.append(
{
"id": datasource.id,
"source": datasource.source,
"name": datasource.name,
**datasource_metadata(datasource.source),
"module": datasource.module,
"priority": datasource.priority,
"frequency": format_frequency_label(datasource.frequency_minutes),
@@ -429,15 +391,18 @@ async def list_datasources(
"is_active": datasource.is_active,
"collector_class": datasource.collector_class,
"endpoint": endpoint,
"last_run": last_run,
"last_run": to_iso8601_utc(last_run_at),
"last_run_at": to_iso8601_utc(last_run_at),
"last_status": last_status,
"last_records_processed": last_task.records_processed if last_task else None,
"data_count": data_count,
"is_running": running_task is not None,
"task_id": running_task.id if running_task else None,
"progress": running_task.progress if running_task else None,
"phase": running_task.phase if running_task else None,
"phase_progress": running_task.phase_progress if running_task else None,
"phase_message": running_task.phase_message if running_task else None,
"phase_current": running_task.phase_current if running_task else None,
"phase_total": running_task.phase_total if running_task else None,
"phase_unit": running_task.phase_unit if running_task else None,
"records_processed": running_task.records_processed if running_task else None,
"total_records": running_task.total_records if running_task else None,
}
@@ -576,6 +541,7 @@ async def get_datasource(
return {
"id": datasource.id,
"name": datasource.name,
**datasource_metadata(datasource.source),
"module": datasource.module,
"priority": datasource.priority,
"frequency": format_frequency_label(datasource.frequency_minutes),
@@ -665,6 +631,11 @@ async def trigger_datasource(
"message": "当前采集任务尚未完成,重新触发会丢失本次未完成进度。是否强制重新采集?",
"task_id": running_task.id,
"phase": running_task.phase,
"phase_progress": running_task.phase_progress,
"phase_message": running_task.phase_message,
"phase_current": running_task.phase_current,
"phase_total": running_task.phase_total,
"phase_unit": running_task.phase_unit,
"progress": running_task.progress,
"records_processed": running_task.records_processed,
"total_records": running_task.total_records,
@@ -748,13 +719,29 @@ async def get_task_status(
task = await get_running_task(db, datasource.id)
if not task:
return {"is_running": False, "task_id": None, "progress": None, "phase": None, "status": "idle"}
return {
"is_running": False,
"task_id": None,
"progress": None,
"phase": None,
"phase_progress": None,
"phase_message": None,
"phase_current": None,
"phase_total": None,
"phase_unit": None,
"status": "idle",
}
return {
"is_running": task.status == "running",
"task_id": task.id,
"progress": task.progress,
"phase": task.phase,
"phase_progress": task.phase_progress,
"phase_message": task.phase_message,
"phase_current": task.phase_current,
"phase_total": task.phase_total,
"phase_unit": task.phase_unit,
"records_processed": task.records_processed,
"total_records": task.total_records,
"status": task.status,

View File

@@ -9,10 +9,37 @@ from sqlalchemy.ext.asyncio import AsyncSession
from app.core.security import get_current_user
from app.core.time import to_iso8601_utc
from app.core.config import settings as app_settings
from app.core.data_sources import get_data_sources_config
from app.core.datasource_defaults import DEFAULT_DATASOURCES
from app.db.session import get_db
from app.models.datasource import DataSource
from app.models.datasource_config import DataSourceConfig
from app.models.system_setting import SystemSetting
from app.models.user import User
from app.models.vessel import AISSourceHealth
from app.services.barentswatch import (
BarentsWatchConfig,
check_barentswatch_config,
check_barentswatch_connectivity,
get_barentswatch_datasource_record,
resolve_barentswatch_config,
)
from app.services.credential_guides import (
generate_credential_guide,
get_credential_guide,
reset_credential_guide,
)
from app.services.datasource_connectivity import (
build_builtin_connectivity_checksum,
save_connectivity_success,
)
from app.services.ai_client import AIProviderClient, get_ai_provider_client
from app.services.llm_provider_catalog import (
get_fallback_llm_provider_preset,
list_fallback_llm_provider_presets,
refresh_llm_provider_preset,
)
from app.services.scheduler import sync_datasource_job
from app.services.tv_streams import DEFAULT_TV_SETTINGS, get_tv_settings_payload, normalize_tv_settings
@@ -39,6 +66,21 @@ DEFAULT_SETTINGS = {
"password_policy": "medium",
},
"tv": DEFAULT_TV_SETTINGS,
"external_integrations": {
"ai_provider": {
"service_url": "",
"service_token": "",
"provider": "minimax",
"provider_api": "anthropic-messages",
"base_url": "https://api.minimaxi.com/anthropic",
"model": "MiniMax-M2.7",
"api_key": "",
"max_tokens": 1200,
"anthropic_version": "2023-06-01",
"timeout_seconds": 60,
"retry_attempts": 2,
}
},
}
@@ -96,6 +138,34 @@ class TVSettingsUpdate(BaseModel):
sources: list[TVStreamSourceUpdate] = Field(default_factory=list)
class AIProviderIntegrationUpdate(BaseModel):
service_url: str = ""
service_token: Optional[str] = None
provider: str = Field(default="minimax", max_length=80)
provider_api: str = Field(default="anthropic-messages", max_length=80)
base_url: str = Field(default="", max_length=500)
model: str = Field(default="", max_length=200)
api_key: Optional[str] = None
max_tokens: int = Field(default=1200, ge=1, le=200000)
anthropic_version: str = Field(default="2023-06-01", max_length=40)
timeout_seconds: int = Field(default=60, ge=5, le=600)
retry_attempts: int = Field(default=2, ge=1, le=10)
clear_service_token: bool = False
clear_api_key: bool = False
class BarentsWatchIntegrationUpdate(BaseModel):
endpoint: str = ""
client_id: str = ""
client_secret: Optional[str] = None
clear_client_secret: bool = False
class ExternalIntegrationsUpdate(BaseModel):
ai_provider: AIProviderIntegrationUpdate
barentswatch: BarentsWatchIntegrationUpdate
def merge_with_defaults(category: str, payload: Optional[dict]) -> dict:
merged = deepcopy(DEFAULT_SETTINGS[category])
if payload:
@@ -146,6 +216,151 @@ async def save_setting_payload(db: AsyncSession, category: str, payload: dict) -
return merge_with_defaults(category, record.payload)
def _mask_secret(value: Optional[str]) -> dict:
if not value:
return {"configured": False, "preview": ""}
text = str(value)
if "-" in text:
prefix = text.split("-", 1)[0] + "-"
preview = prefix + ("*" * max(len(text) - len(prefix), 1))
else:
prefix_len = min(4, len(text))
preview = text[:prefix_len] + ("*" * max(len(text) - prefix_len, 1))
return {"configured": True, "preview": preview}
async def get_runtime_ai_provider_config(db: AsyncSession) -> dict:
runtime_record = await get_setting_record(db, "external_integrations")
payload = merge_with_defaults(
"external_integrations",
runtime_record.payload if runtime_record else None,
)
ai_payload = payload.get("ai_provider") or {}
has_runtime_llm_config = bool(
runtime_record
and isinstance(runtime_record.payload, dict)
and isinstance(runtime_record.payload.get("ai_provider"), dict)
)
return {
"service_url": ai_payload.get("service_url") or app_settings.AI_PROVIDER_SERVICE_URL,
"service_token": ai_payload.get("service_token") or app_settings.AI_PROVIDER_SERVICE_TOKEN,
"timeout_seconds": int(
ai_payload.get("timeout_seconds") or app_settings.AI_PROVIDER_TIMEOUT_SECONDS
),
"retry_attempts": int(
ai_payload.get("retry_attempts") or app_settings.AI_PROVIDER_RETRY_ATTEMPTS
),
"llm_config": {
"provider": ai_payload.get("provider") or "minimax",
"provider_api": ai_payload.get("provider_api") or "anthropic-messages",
"base_url": ai_payload.get("base_url") or "https://api.minimaxi.com/anthropic",
"model": ai_payload.get("model") or "MiniMax-M2.7",
"api_key": ai_payload.get("api_key") or "",
"max_tokens": int(ai_payload.get("max_tokens") or 1200),
"anthropic_version": ai_payload.get("anthropic_version") or "2023-06-01",
} if has_runtime_llm_config else {},
}
async def get_barentswatch_config_record(db: AsyncSession) -> Optional[DataSourceConfig]:
return await get_barentswatch_datasource_record(db)
async def serialize_external_integrations(db: AsyncSession) -> dict:
ai_config = await get_runtime_ai_provider_config(db)
runtime_setting = await get_setting_record(db, "external_integrations")
display_llm_config = ai_config["llm_config"] or DEFAULT_SETTINGS["external_integrations"]["ai_provider"]
barentswatch_record = await get_barentswatch_config_record(db)
barentswatch_auth = barentswatch_record.auth_config if barentswatch_record else {}
barentswatch_auth = barentswatch_auth or {}
resolved_barentswatch = await resolve_barentswatch_config(db)
return {
"ai_provider": {
"service_url": ai_config["service_url"],
"service_token": _mask_secret(ai_config["service_token"]),
"provider": display_llm_config.get("provider") or "minimax",
"provider_api": display_llm_config.get("provider_api") or "anthropic-messages",
"base_url": display_llm_config.get("base_url") or "https://api.minimaxi.com/anthropic",
"model": display_llm_config.get("model") or "MiniMax-M2.7",
"api_key": _mask_secret(display_llm_config.get("api_key")),
"max_tokens": int(display_llm_config.get("max_tokens") or 1200),
"anthropic_version": display_llm_config.get("anthropic_version") or "2023-06-01",
"timeout_seconds": ai_config["timeout_seconds"],
"retry_attempts": ai_config["retry_attempts"],
"source": "runtime" if runtime_setting else "env",
},
"barentswatch": {
"endpoint": resolved_barentswatch.endpoint,
"client_id": barentswatch_auth.get("client_id") or resolved_barentswatch.client_id,
"client_secret": _mask_secret(
barentswatch_auth.get("client_secret") or resolved_barentswatch.client_secret
),
"source": resolved_barentswatch.credential_source,
},
}
async def save_external_integrations_payload(
db: AsyncSession,
update: ExternalIntegrationsUpdate,
) -> dict:
current_payload = await get_setting_payload(db, "external_integrations")
current_ai = current_payload.get("ai_provider") or {}
ai_payload = {
"service_url": update.ai_provider.service_url.strip()
or app_settings.AI_PROVIDER_SERVICE_URL,
"service_token": current_ai.get("service_token") or "",
"provider": update.ai_provider.provider.strip() or "minimax",
"provider_api": update.ai_provider.provider_api.strip() or "anthropic-messages",
"base_url": update.ai_provider.base_url.strip(),
"model": update.ai_provider.model.strip(),
"api_key": current_ai.get("api_key") or "",
"max_tokens": update.ai_provider.max_tokens,
"anthropic_version": update.ai_provider.anthropic_version.strip() or "2023-06-01",
"timeout_seconds": update.ai_provider.timeout_seconds,
"retry_attempts": update.ai_provider.retry_attempts,
}
if update.ai_provider.clear_service_token:
ai_payload["service_token"] = ""
elif update.ai_provider.service_token not in (None, ""):
ai_payload["service_token"] = update.ai_provider.service_token
if update.ai_provider.clear_api_key:
ai_payload["api_key"] = ""
elif update.ai_provider.api_key not in (None, ""):
ai_payload["api_key"] = update.ai_provider.api_key
await save_setting_payload(db, "external_integrations", {"ai_provider": ai_payload})
default_endpoint = get_data_sources_config().get_yaml_url("barentswatch_vessels")
barentswatch_record = await get_barentswatch_config_record(db)
if barentswatch_record is None:
barentswatch_record = DataSourceConfig(
name="barentswatch_vessels",
description="BarentsWatch Live AIS credentials",
source_type="api",
endpoint=update.barentswatch.endpoint.strip() or default_endpoint,
auth_type="oauth_client",
auth_config={},
headers={},
config={},
is_active=True,
)
db.add(barentswatch_record)
current_auth = dict(barentswatch_record.auth_config or {})
if update.barentswatch.clear_client_secret:
current_auth.pop("client_secret", None)
elif update.barentswatch.client_secret not in (None, ""):
current_auth["client_secret"] = update.barentswatch.client_secret
current_auth["client_id"] = update.barentswatch.client_id.strip()
barentswatch_record.endpoint = update.barentswatch.endpoint.strip() or default_endpoint
barentswatch_record.auth_type = "oauth_client"
barentswatch_record.auth_config = current_auth
await db.commit()
return await serialize_external_integrations(db)
def format_frequency_label(minutes: int) -> str:
if minutes % 1440 == 0:
return f"{minutes // 1440}d"
@@ -154,10 +369,17 @@ def format_frequency_label(minutes: int) -> str:
return f"{minutes}m"
def serialize_collector(datasource: DataSource) -> dict:
async def get_ais_source_health_by_source(db: AsyncSession) -> dict[str, dict]:
result = await db.execute(select(AISSourceHealth))
return {item.source: item.to_dict() for item in result.scalars().all()}
def serialize_collector(datasource: DataSource, ais_health_by_source: dict[str, dict] | None = None) -> dict:
defaults = DEFAULT_DATASOURCES.get(datasource.source, {})
return {
"id": datasource.id,
"name": datasource.name,
"display_name": defaults.get("display_name") or datasource.name,
"source": datasource.source,
"module": datasource.module,
"priority": datasource.priority,
@@ -167,6 +389,11 @@ def serialize_collector(datasource: DataSource) -> dict:
"last_run_at": to_iso8601_utc(datasource.last_run_at),
"last_status": datasource.last_status,
"next_run_at": to_iso8601_utc(datasource.next_run_at),
"is_free": bool(defaults.get("is_free", True)),
"requires_credentials": bool(defaults.get("requires_credentials", False)),
"credential_provider": defaults.get("credential_provider"),
"credential_status": defaults.get("credential_status", "none"),
"ais_health": (ais_health_by_source or {}).get(datasource.source),
}
@@ -243,6 +470,135 @@ async def update_tv_settings(
return {"status": "updated", "tv": normalize_tv_settings(saved)}
@router.get("/integrations")
async def get_external_integrations(
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
return {"integrations": await serialize_external_integrations(db)}
@router.get("/integrations/barentswatch/connectivity")
async def get_barentswatch_connectivity(
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
return await check_barentswatch_connectivity(db)
@router.post("/integrations/barentswatch/connect")
async def connect_barentswatch_integration(
payload: BarentsWatchIntegrationUpdate,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
current = await resolve_barentswatch_config(db)
config = BarentsWatchConfig(
endpoint=payload.endpoint.strip() or current.endpoint,
client_id=payload.client_id.strip() or current.client_id,
client_secret=(
""
if payload.clear_client_secret
else payload.client_secret or current.client_secret
),
credential_source="draft",
endpoint_source="draft",
)
result = await check_barentswatch_config(config)
if result.get("success"):
checksum, _context = await build_builtin_connectivity_checksum(
"barentswatch_vessels",
config.endpoint,
"none",
{},
{},
db,
credential_override={
"client_id": config.client_id,
"client_secret": config.client_secret,
},
)
validation = await save_connectivity_success(
db,
"barentswatch_vessels",
checksum,
result,
connected_by="connection_button",
)
await db.commit()
return {**result, "connected": True, "validation": validation}
return {**result, "connected": False}
@router.get("/credential-guides/{provider}")
async def read_credential_guide(
provider: str,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
try:
return {"guide": await get_credential_guide(db, provider)}
except ValueError as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
@router.post("/credential-guides/{provider}/generate")
async def generate_provider_credential_guide(
provider: str,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
ai_client: AIProviderClient = Depends(get_ai_provider_client),
):
try:
return {"guide": await generate_credential_guide(db, provider, ai_client)}
except ValueError as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
@router.post("/credential-guides/{provider}/reset")
async def reset_provider_credential_guide(
provider: str,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
try:
return {"guide": await reset_credential_guide(db, provider)}
except ValueError as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
@router.get("/integrations/ai-provider/presets")
async def get_ai_provider_presets(
current_user: User = Depends(get_current_user),
):
return {"data": list_fallback_llm_provider_presets()}
@router.post("/integrations/ai-provider/presets/{provider}/refresh")
async def refresh_ai_provider_preset(
provider: str,
current_user: User = Depends(get_current_user),
):
try:
return {"data": await refresh_llm_provider_preset(provider)}
except ValueError as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
except Exception as exc:
fallback = get_fallback_llm_provider_preset(provider)
fallback["refresh_error"] = str(exc)
return {"data": fallback}
@router.put("/integrations")
async def update_external_integrations(
payload: ExternalIntegrationsUpdate,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
saved = await save_external_integrations_payload(db, payload)
return {"status": "updated", "integrations": saved}
@router.get("/collectors")
async def get_collector_settings(
current_user: User = Depends(get_current_user),
@@ -250,7 +606,8 @@ async def get_collector_settings(
):
result = await db.execute(select(DataSource).order_by(DataSource.module, DataSource.id))
datasources = result.scalars().all()
return {"collectors": [serialize_collector(datasource) for datasource in datasources]}
ais_health_by_source = await get_ais_source_health_by_source(db)
return {"collectors": [serialize_collector(datasource, ais_health_by_source) for datasource in datasources]}
@router.put("/collectors/{datasource_id}")
@@ -270,7 +627,8 @@ async def update_collector_settings(
await db.commit()
await db.refresh(datasource)
await sync_datasource_job(datasource.id)
return {"status": "updated", "collector": serialize_collector(datasource)}
ais_health_by_source = await get_ais_source_health_by_source(db)
return {"status": "updated", "collector": serialize_collector(datasource, ais_health_by_source)}
@router.get("")
@@ -284,11 +642,13 @@ async def get_all_settings(
db,
["system", "notifications", "security"],
)
ais_health_by_source = await get_ais_source_health_by_source(db)
return {
"system": setting_payloads["system"],
"notifications": setting_payloads["notifications"],
"security": setting_payloads["security"],
"tv": await get_tv_settings_payload(db),
"collectors": [serialize_collector(datasource) for datasource in datasources],
"integrations": await serialize_external_integrations(db),
"collectors": [serialize_collector(datasource, ais_health_by_source) for datasource in datasources],
"generated_at": to_iso8601_utc(datetime.now(UTC)),
}

View File

@@ -27,7 +27,9 @@ async def list_tasks(
offset = (page - 1) * page_size
query = """
SELECT ct.id, ct.datasource_id, ds.name as datasource_name, ct.status,
ct.started_at, ct.completed_at, ct.records_processed, ct.error_message
ct.started_at, ct.completed_at, ct.records_processed, ct.error_message,
ct.phase, ct.phase_progress, ct.phase_message, ct.phase_current,
ct.phase_total, ct.phase_unit, ct.total_records, ct.progress
FROM collection_tasks ct
JOIN data_sources ds ON ct.datasource_id = ds.id
WHERE 1=1
@@ -66,6 +68,14 @@ async def list_tasks(
"completed_at": to_iso8601_utc(t[5]),
"records_processed": t[6],
"error_message": t[7],
"phase": t[8],
"phase_progress": t[9],
"phase_message": t[10],
"phase_current": t[11],
"phase_total": t[12],
"phase_unit": t[13],
"total_records": t[14],
"progress": t[15],
}
for t in tasks
],
@@ -81,7 +91,9 @@ async def get_task(
result = await db.execute(
text("""
SELECT ct.id, ct.datasource_id, ds.name as datasource_name, ct.status,
ct.started_at, ct.completed_at, ct.records_processed, ct.error_message
ct.started_at, ct.completed_at, ct.records_processed, ct.error_message,
ct.phase, ct.phase_progress, ct.phase_message, ct.phase_current,
ct.phase_total, ct.phase_unit, ct.total_records, ct.progress
FROM collection_tasks ct
JOIN data_sources ds ON ct.datasource_id = ds.id
WHERE ct.id = :id
@@ -105,6 +117,14 @@ async def get_task(
"completed_at": to_iso8601_utc(task[5]),
"records_processed": task[6],
"error_message": task[7],
"phase": task[8],
"phase_progress": task[9],
"phase_message": task[10],
"phase_current": task[11],
"phase_total": task[12],
"phase_unit": task[13],
"total_records": task[14],
"progress": task[15],
}

View File

@@ -0,0 +1,132 @@
"""v4 strategy + v5 conflict-promotion + enrichment APIs for vessel_ais."""
from __future__ import annotations
from typing import Any
from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.security import get_current_user
from app.db.session import get_db
from app.models.user import User
from app.models.vessel import AISConflictRecord
from app.services.vessel_aggregation_strategy import (
StrategyValidationError,
load_strategy,
reset_strategy,
save_strategy,
)
from app.services.vessel_enrichment import (
get_vessel_enrichment_bundle,
upsert_vessel_media_enrichment,
upsert_vessel_profile_enrichment,
)
router = APIRouter()
@router.get("/strategy")
async def get_aggregation_strategy(db: AsyncSession = Depends(get_db)):
return await load_strategy(db)
@router.put("/strategy")
async def put_aggregation_strategy(
payload: dict[str, Any],
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
try:
return await save_strategy(db, payload)
except StrategyValidationError as exc:
raise HTTPException(status_code=400, detail=str(exc)) from exc
@router.delete("/strategy")
async def reset_aggregation_strategy(
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
return await reset_strategy(db)
@router.post("/conflicts/{mmsi}/{field}/promote-to-rule")
async def promote_conflict_to_rule(
mmsi: int,
field: str,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
"""Lift the current conflict resolution into a persistent strategy rule."""
result = await db.execute(
select(AISConflictRecord)
.where(AISConflictRecord.target_schema == "vessel_ais")
.where(AISConflictRecord.entity_key == str(mmsi))
.where(AISConflictRecord.field == field)
.order_by(AISConflictRecord.updated_at.desc(), AISConflictRecord.id.desc())
.limit(1)
)
record = result.scalar_one_or_none()
if record is None or not record.selected_source:
raise HTTPException(status_code=404, detail="Conflict record with selected_source not found")
strategy = await load_strategy(db)
vessel_ais = dict(strategy.get("vessel_ais") or {})
field_rules = dict(vessel_ais.get("field_rules") or {})
field_rules[field] = {"mode": "source_priority", "source_priority": [record.selected_source]}
vessel_ais["field_rules"] = field_rules
incoming = {"version": int(strategy.get("version") or 0), "vessel_ais": vessel_ais}
try:
return await save_strategy(db, incoming)
except StrategyValidationError as exc:
raise HTTPException(status_code=400, detail=str(exc)) from exc
@router.delete("/conflicts/{mmsi}/{field}/promote-to-rule")
async def revert_conflict_rule(
mmsi: int,
field: str,
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
strategy = await load_strategy(db)
vessel_ais = dict(strategy.get("vessel_ais") or {})
field_rules = dict(vessel_ais.get("field_rules") or {})
if field in field_rules:
del field_rules[field]
vessel_ais["field_rules"] = field_rules
incoming = {"version": int(strategy.get("version") or 0), "vessel_ais": vessel_ais}
try:
return await save_strategy(db, incoming)
except StrategyValidationError as exc:
raise HTTPException(status_code=400, detail=str(exc)) from exc
@router.get("/enrichment/{mmsi}")
async def get_vessel_enrichment(mmsi: int, db: AsyncSession = Depends(get_db)):
return await get_vessel_enrichment_bundle(db, mmsi)
@router.put("/enrichment/{mmsi}/profile")
async def put_vessel_profile_enrichment(
mmsi: int,
payload: dict[str, Any],
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
return await upsert_vessel_profile_enrichment(db, mmsi=mmsi, payload=payload)
@router.put("/enrichment/{mmsi}/media")
async def put_vessel_media_enrichment(
mmsi: int,
payload: dict[str, Any],
current_user: User = Depends(get_current_user),
db: AsyncSession = Depends(get_db),
):
return await upsert_vessel_media_enrichment(db, mmsi=mmsi, payload=payload)

View File

@@ -4,8 +4,9 @@ Unified API for all visualization data sources.
Returns GeoJSON format compatible with Three.js, CesiumJS, and Unreal Cesium.
"""
from datetime import UTC, datetime
from datetime import UTC, datetime, timedelta
import math
import re
import httpx
from fastapi import APIRouter, HTTPException, Depends, Query, Response
from sqlalchemy.ext.asyncio import AsyncSession
@@ -19,11 +20,22 @@ from app.core.time import to_iso8601_utc
from app.db.session import get_db
from app.models.bgp_anomaly import BGPAnomaly
from app.models.bgp_incident import BGPIncident
from app.models.bgp_observation import BGPObservation
from app.models.collected_data import CollectedData
from app.models.vessel import AISSourceHealth, VesselPosition, VesselStatic
from app.services.bgp_collectors import build_bgp_collector_coverage
from app.services.cable_graph import build_graph_from_data, CableGraph, haversine_distance
from app.services.collectors.bgp_common import RIPE_RIS_COLLECTOR_COORDS
from app.services.persistent_logs import record_system_log
from app.services.vessel_ais_aggregation import (
build_field_conflict_candidates,
count_unique_raw_vessel_mmsi,
get_aggregated_vessel,
get_aggregated_vessel_track,
get_aggregated_vessels,
get_vessel_conflict_records,
get_vessel_raw_observations,
)
from app.core.logging import get_logger
router = APIRouter()
@@ -31,6 +43,7 @@ logger = get_logger(__name__, service="api")
TERRAIN_TILE_URL_TEMPLATE = (
"https://s3.amazonaws.com/elevation-tiles-prod/terrarium/{z}/{x}/{y}.png"
)
VESSEL_NAME_FALLBACK_PATTERN = re.compile(r"^mmsi\s*\d+$", re.IGNORECASE)
# ============== Converter Functions ==============
@@ -272,6 +285,120 @@ async def _load_current_collected_data(
return list(result.scalars().all())
async def _latest_task_id_for_source(
db: AsyncSession,
source: str,
*,
exclude_unknown_name: bool = False,
) -> int | None:
stmt = (
select(
CollectedData.task_id,
func.max(CollectedData.collected_at).label("latest_collected_at"),
func.max(CollectedData.id).label("latest_id"),
)
.where(CollectedData.source == source)
.where(CollectedData.task_id.isnot(None))
.group_by(CollectedData.task_id)
.order_by(func.max(CollectedData.collected_at).desc(), func.max(CollectedData.id).desc())
.limit(1)
)
if exclude_unknown_name:
stmt = stmt.where(CollectedData.name != "Unknown")
result = await db.execute(stmt)
row = result.first()
return int(row.task_id) if row and row.task_id is not None else None
async def _load_current_or_latest_task_data(
db: AsyncSession,
source: str,
*,
exclude_unknown_name: bool = False,
limit: Optional[int] = None,
) -> List[CollectedData]:
records = await _load_current_collected_data(
db,
source,
exclude_unknown_name=exclude_unknown_name,
limit=limit,
)
if records:
return records
latest_task_id = await _latest_task_id_for_source(
db,
source,
exclude_unknown_name=exclude_unknown_name,
)
if latest_task_id is None:
return []
stmt = (
select(CollectedData)
.where(CollectedData.source == source)
.where(CollectedData.task_id == latest_task_id)
.order_by(CollectedData.id.desc())
)
if exclude_unknown_name:
stmt = stmt.where(CollectedData.name != "Unknown")
if limit is not None:
stmt = stmt.limit(limit)
result = await db.execute(stmt)
return list(result.scalars().all())
async def _count_current_or_latest_task_data(
db: AsyncSession,
source: str,
*,
exclude_unknown_name: bool = False,
) -> int:
current_stmt = (
select(func.count(CollectedData.id))
.where(CollectedData.source == source)
.where(CollectedData.is_current.is_(True))
)
if exclude_unknown_name:
current_stmt = current_stmt.where(CollectedData.name != "Unknown")
current_result = await db.execute(current_stmt)
current_scalar = current_result.scalar()
if current_scalar is None and hasattr(current_result, "scalars"):
current_rows = current_result.scalars().all()
current_count = sum(
1
for row in current_rows
if getattr(row, "source", None) == source
and (not exclude_unknown_name or getattr(row, "name", None) != "Unknown")
)
else:
current_count = int(current_scalar or 0)
if current_count > 0:
return current_count
latest_task_id = await _latest_task_id_for_source(
db,
source,
exclude_unknown_name=exclude_unknown_name,
)
if latest_task_id is None:
return 0
latest_stmt = (
select(func.count(CollectedData.id))
.where(CollectedData.source == source)
.where(CollectedData.task_id == latest_task_id)
)
if exclude_unknown_name:
latest_stmt = latest_stmt.where(CollectedData.name != "Unknown")
latest_result = await db.execute(latest_stmt)
return int(latest_result.scalar() or 0)
async def _load_current_collected_data_by_sources(
db: AsyncSession,
sources: List[str],
@@ -511,7 +638,7 @@ def _normalize_capacity_band(capacity_value: Optional[float], capacity_unit: str
if unit in {"pflop/s", "pflops", "pflop"}:
normalized_tflops = capacity_value * 1000
elif unit in {"gflop/s", "gflops", "gflop"}:
normalized_tflops = capacity_value / 1000
normalized_tflops = capacity_value
else:
normalized_tflops = capacity_value
@@ -609,6 +736,267 @@ def convert_compute_centers_to_geojson(records: List[CollectedData]) -> Dict[str
return {"type": "FeatureCollection", "features": features}
VESSEL_TYPE_FILTERS = {
"cargo": lambda props: str(props.get("vessel_type_name", "")).lower() == "cargo"
or 70 <= int(props.get("vessel_type") or -1) <= 79,
"tanker": lambda props: str(props.get("vessel_type_name", "")).lower() == "tanker"
or 80 <= int(props.get("vessel_type") or -1) <= 89,
"passenger": lambda props: str(props.get("vessel_type_name", "")).lower() == "passenger"
or 60 <= int(props.get("vessel_type") or -1) <= 69,
"fishing": lambda props: str(props.get("vessel_type_name", "")).lower() == "fishing"
or int(props.get("vessel_type") or -1) == 30,
"military": lambda props: str(props.get("vessel_type_name", "")).lower() == "military"
or int(props.get("vessel_type") or -1) == 35,
"other": lambda props: str(props.get("vessel_type_name", "")).lower()
not in {"cargo", "tanker", "passenger", "fishing", "military"},
}
def convert_vessels_to_geojson(rows: List[Any]) -> Dict[str, Any]:
features = []
seen_mmsi: set[int] = set()
for position, static in rows:
if position.lat is None or position.lon is None:
continue
if position.mmsi in seen_mmsi:
continue
seen_mmsi.add(position.mmsi)
props = {
"mmsi": position.mmsi,
"mmsi_display": str(position.mmsi),
"name": getattr(static, "name", None) or f"MMSI {position.mmsi}",
"name_is_fallback": _is_vessel_name_fallback(getattr(static, "name", None), position.mmsi),
"callsign": getattr(static, "callsign", None),
"imo": getattr(static, "imo", None),
"imo_display": str(getattr(static, "imo")) if getattr(static, "imo", None) else None,
"vessel_type": getattr(static, "vessel_type", None),
"vessel_type_name": getattr(static, "vessel_type_name", None) or "Other",
"flag": getattr(static, "flag", None),
"length": getattr(static, "length", None),
"width": getattr(static, "width", None),
"draught": getattr(static, "draught", None),
"sog": position.sog,
"cog": position.cog,
"heading": position.heading,
"nav_status": position.nav_status,
"received_at": to_iso8601_utc(position.received_at),
"data_type": "vessel",
}
features.append(
{
"type": "Feature",
"id": position.mmsi,
"geometry": {
"type": "Point",
"coordinates": [position.lon, position.lat],
},
"properties": props,
}
)
return {"type": "FeatureCollection", "features": features}
def convert_aggregated_vessels_to_geojson(vessels: List[dict[str, Any]]) -> Dict[str, Any]:
features = []
for vessel in vessels:
if vessel.get("lat") is None or vessel.get("lon") is None:
continue
source_summary = {}
for source, summary in (vessel.get("source_summary") or {}).items():
source_summary[source] = {
**summary,
"latest_observed_at": to_iso8601_utc(summary.get("latest_observed_at")),
}
props = {
"mmsi": vessel["mmsi"],
"mmsi_display": str(vessel["mmsi"]),
"name": vessel.get("name") or f"MMSI {vessel['mmsi']}",
"name_is_fallback": _is_vessel_name_fallback(vessel.get("name"), vessel["mmsi"]),
"callsign": vessel.get("callsign"),
"imo": vessel.get("imo"),
"imo_display": str(vessel.get("imo")) if vessel.get("imo") else None,
"vessel_type": vessel.get("vessel_type"),
"vessel_type_name": vessel.get("vessel_type_name") or "Other",
"flag": vessel.get("flag"),
"length": vessel.get("length"),
"width": vessel.get("width"),
"draught": vessel.get("draught"),
"sog": vessel.get("sog"),
"cog": vessel.get("cog"),
"heading": vessel.get("heading"),
"nav_status": vessel.get("nav_status"),
"received_at": to_iso8601_utc(vessel.get("received_at")),
"field_sources": vessel.get("field_sources") or {},
"selected_reasons": vessel.get("selected_reasons") or {},
"source_summary": source_summary,
"quality_flags": vessel.get("quality_flags") or [],
"conflict_count": vessel.get("conflict_count", 0),
"aggregation_strategy_version": vessel.get("aggregation_strategy_version", 0),
"data_type": "vessel",
}
features.append(
{
"type": "Feature",
"id": vessel["mmsi"],
"geometry": {
"type": "Point",
"coordinates": [vessel["lon"], vessel["lat"]],
},
"properties": props,
}
)
return {"type": "FeatureCollection", "features": features}
def _parse_bbox(value: Optional[str]) -> tuple[float, float, float, float] | None:
if not value:
return None
parts = [part.strip() for part in value.split(",")]
if len(parts) != 4:
raise HTTPException(status_code=400, detail="bbox must be lon_min,lat_min,lon_max,lat_max")
try:
lon_min, lat_min, lon_max, lat_max = [float(part) for part in parts]
except ValueError as exc:
raise HTTPException(status_code=400, detail="bbox values must be numbers") from exc
if lat_min > lat_max:
lat_min, lat_max = lat_max, lat_min
if lon_min > lon_max:
lon_min, lon_max = lon_max, lon_min
return lon_min, lat_min, lon_max, lat_max
def _is_vessel_name_fallback(name: Any, mmsi: Any) -> bool:
text = str(name or "").strip()
mmsi_text = str(mmsi or "").strip()
if not text:
return True
if mmsi_text and text == mmsi_text:
return True
return bool(VESSEL_NAME_FALLBACK_PATTERN.match(text))
def _requested_vessel_types(value: Optional[str]) -> set[str]:
return {
item.strip().lower()
for item in (value or "").split(",")
if item.strip()
}
def _matches_vessel_type(props: dict[str, Any], requested_types: set[str]) -> bool:
if not requested_types:
return True
for requested_type in requested_types:
predicate = VESSEL_TYPE_FILTERS.get(requested_type)
if predicate and predicate(props):
return True
return False
def _feature_mmsi_key(feature: dict[str, Any]) -> str | None:
props = feature.get("properties", {})
mmsi = props.get("mmsi") or feature.get("id")
if mmsi in (None, ""):
return None
return str(mmsi)
def _feature_in_bbox(feature: dict[str, Any], bbox: tuple[float, float, float, float] | None) -> bool:
if bbox is None:
return True
coordinates = feature.get("geometry", {}).get("coordinates") or []
if len(coordinates) < 2:
return False
try:
lon = float(coordinates[0])
lat = float(coordinates[1])
except (TypeError, ValueError):
return False
lon_min, lat_min, lon_max, lat_max = bbox
return lon_min <= lon <= lon_max and lat_min <= lat <= lat_max
def _filter_vessel_features(
features: list[dict[str, Any]],
*,
bbox: tuple[float, float, float, float] | None,
requested_types: set[str],
) -> list[dict[str, Any]]:
return [
feature
for feature in features
if _feature_in_bbox(feature, bbox)
and _matches_vessel_type(feature.get("properties", {}), requested_types)
]
def _merge_vessel_features(
raw_features: list[dict[str, Any]],
legacy_features: list[dict[str, Any]],
) -> tuple[list[dict[str, Any]], dict[str, Any]]:
"""Prefer aggregated raw observations as the canonical source of truth.
Legacy `vessel_position` rows only fill MMSIs that the unified pipeline does
not yet know about, so a vessel never appears twice when both BarentsWatch
and AISStream observe it. Once the legacy table drains, this branch becomes
a no-op.
"""
merged: list[dict[str, Any]] = []
seen: set[str] = set()
raw_keys: set[str] = set()
legacy_keys: set[str] = set()
for feature in raw_features:
key = _feature_mmsi_key(feature)
if key is None or key in seen:
continue
seen.add(key)
raw_keys.add(key)
merged.append(feature)
legacy_added = 0
for feature in legacy_features:
key = _feature_mmsi_key(feature)
if key is None:
continue
legacy_keys.add(key)
if key in seen:
continue
seen.add(key)
legacy_added += 1
merged.append(feature)
return merged, {
"raw_unique_mmsi": len(raw_keys),
"legacy_unique_mmsi": len(legacy_keys),
"legacy_backfilled_mmsi": legacy_added,
"final_unique_mmsi": len(seen),
}
def _build_vessel_stats(features: List[dict[str, Any]]) -> dict[str, Any]:
by_type: dict[str, int] = {}
underway = 0
anchored_or_moored = 0
for feature in features:
props = feature.get("properties", {})
vessel_type = str(props.get("vessel_type_name") or "Other")
by_type[vessel_type] = by_type.get(vessel_type, 0) + 1
nav_status = props.get("nav_status")
if nav_status in (1, 5):
anchored_or_moored += 1
else:
underway += 1
return {
"total": len(features),
"by_type": by_type,
"underway": underway,
"anchored_or_moored": anchored_or_moored,
}
def convert_bgp_anomalies_to_geojson(
records: List[BGPAnomaly],
geography_hints: Optional[Dict[str, Dict[str, Any]]] = None,
@@ -1188,7 +1576,7 @@ async def get_satellites_geojson(
db: AsyncSession = Depends(get_db),
):
"""获取卫星 TLE GeoJSON 数据"""
records = await _load_current_collected_data(
records = await _load_current_or_latest_task_data(
db,
"celestrak_tle",
exclude_unknown_name=True,
@@ -1298,6 +1686,304 @@ async def get_compute_centers_geojson(
}
@router.get("/geo/vessels")
async def get_vessels_geojson(
bbox: Optional[str] = Query(
None,
description="Viewport bbox as lon_min,lat_min,lon_max,lat_max",
),
type: Optional[str] = Query(
None,
description="Comma-separated vessel types: cargo,tanker,passenger,fishing,military,other",
),
limit: Optional[int] = Query(
None,
ge=0,
description="Maximum vessel features to return. Omit or pass 0 for no limit.",
),
db: AsyncSession = Depends(get_db),
):
"""Return latest vessel positions as GeoJSON points."""
parsed_bbox = _parse_bbox(bbox)
requested_types = _requested_vessel_types(type)
merged_features, diagnostics = await _load_merged_vessel_features(db)
features = _filter_vessel_features(
merged_features,
bbox=parsed_bbox,
requested_types=requested_types,
)
if limit and limit > 0:
features = features[:limit]
return {
"type": "FeatureCollection",
"features": features,
"count": len(features),
"stats": _build_vessel_stats(features),
"diagnostics": {
**diagnostics,
"filtered_count": len(features),
},
}
async def _load_merged_vessel_features(db: AsyncSession) -> tuple[list[dict[str, Any]], dict[str, Any]]:
aggregated_vessels = await get_aggregated_vessels(db)
raw_geojson = convert_aggregated_vessels_to_geojson(aggregated_vessels)
latest_times = (
select(
VesselPosition.mmsi.label("mmsi"),
func.max(VesselPosition.received_at).label("received_at"),
)
.group_by(VesselPosition.mmsi)
.subquery()
)
stmt = (
select(VesselPosition, VesselStatic)
.join(
latest_times,
(VesselPosition.mmsi == latest_times.c.mmsi)
& (VesselPosition.received_at == latest_times.c.received_at),
)
.outerjoin(VesselStatic, VesselStatic.mmsi == VesselPosition.mmsi)
.order_by(VesselPosition.received_at.desc())
)
result = await db.execute(stmt)
rows = list(result.all())
legacy_geojson = convert_vessels_to_geojson(rows)
merged_features, diagnostics = _merge_vessel_features(
raw_geojson.get("features", []),
legacy_geojson.get("features", []),
)
return merged_features, {
**diagnostics,
"raw_feature_count": len(raw_geojson.get("features", [])),
"legacy_feature_count": len(legacy_geojson.get("features", [])),
}
@router.get("/vessels/custom-supplements")
async def get_vessel_custom_supplements(db: AsyncSession = Depends(get_db)):
"""Group custom vessel_ais sources by their declared merge target for diagnostics."""
from app.models.datasource_config import DataSourceConfig
result = await db.execute(
select(DataSourceConfig.name, DataSourceConfig.config, DataSourceConfig.is_active)
.where(DataSourceConfig.config["target_schema"].as_string() == "vessel_ais")
)
grouped: dict[str, dict[str, Any]] = {}
for name, config, is_active in result.all():
config = config or {}
merge_target = str(config.get("merge_target_source") or "barentswatch_vessels")
bucket = grouped.setdefault(merge_target, {"merge_target": merge_target, "sources": []})
bucket["sources"].append({"name": name, "is_active": bool(is_active)})
return {"groups": list(grouped.values())}
@router.get("/vessels/name-fallbacks")
async def get_vessel_name_fallbacks(
limit: int = Query(500, ge=0, description="Maximum fallback-name vessels to return. 0 means no limit."),
db: AsyncSession = Depends(get_db),
):
"""Return vessels whose display name still falls back to MMSI."""
aggregated_vessels = await get_aggregated_vessels(db)
raw_geojson = convert_aggregated_vessels_to_geojson(aggregated_vessels)
latest_times = (
select(
VesselPosition.mmsi.label("mmsi"),
func.max(VesselPosition.received_at).label("received_at"),
)
.group_by(VesselPosition.mmsi)
.subquery()
)
result = await db.execute(
select(VesselPosition, VesselStatic)
.join(
latest_times,
(VesselPosition.mmsi == latest_times.c.mmsi)
& (VesselPosition.received_at == latest_times.c.received_at),
)
.outerjoin(VesselStatic, VesselStatic.mmsi == VesselPosition.mmsi)
.order_by(VesselPosition.received_at.desc())
)
legacy_geojson = convert_vessels_to_geojson(list(result.all()))
features, diagnostics = _merge_vessel_features(
raw_geojson.get("features", []),
legacy_geojson.get("features", []),
)
fallback_items = []
for feature in features:
props = feature.get("properties", {})
mmsi = props.get("mmsi")
name = props.get("name")
if not _is_vessel_name_fallback(name, mmsi):
continue
source_summary = props.get("source_summary") or {}
fallback_items.append(
{
"mmsi": str(mmsi),
"display_name": name or f"MMSI {mmsi}",
"reason": "missing_real_name",
"received_at": props.get("received_at"),
"sources": sorted(source_summary.keys()),
"source_summary": source_summary,
"message_types": sorted(
{
message_type
for summary in source_summary.values()
for message_type in (summary.get("message_types") or [])
}
),
"field_sources": props.get("field_sources") or {},
}
)
if limit and limit > 0:
fallback_items = fallback_items[:limit]
return {
"count": len(fallback_items),
"items": fallback_items,
"diagnostics": diagnostics,
}
@router.get("/vessels/{mmsi}")
async def get_vessel_detail(mmsi: int, db: AsyncSession = Depends(get_db)):
from app.services.vessel_enrichment import get_vessel_enrichment_bundle
aggregated = await get_aggregated_vessel(db, mmsi)
enrichment = await get_vessel_enrichment_bundle(db, mmsi)
if aggregated is not None:
return {
**aggregated,
"received_at": to_iso8601_utc(aggregated.get("received_at")),
"latitude": aggregated["lat"],
"longitude": aggregated["lon"],
"enrichment": enrichment,
}
latest_position_stmt = (
select(VesselPosition)
.where(VesselPosition.mmsi == mmsi)
.order_by(VesselPosition.received_at.desc())
.limit(1)
)
static = await db.get(VesselStatic, mmsi)
result = await db.execute(latest_position_stmt)
position = result.scalar_one_or_none()
if position is None:
raise HTTPException(status_code=404, detail="Vessel not found")
geojson = convert_vessels_to_geojson([(position, static)])
return {
**(geojson["features"][0]["properties"]),
"latitude": position.lat,
"longitude": position.lon,
"enrichment": enrichment,
}
@router.get("/vessels/{mmsi}/track")
async def get_vessel_track(
mmsi: int,
hours: int = Query(6, ge=1, le=24),
db: AsyncSession = Depends(get_db),
):
cutoff = datetime.now(UTC) - timedelta(hours=hours)
aggregated_points = await get_aggregated_vessel_track(db, mmsi, cutoff=cutoff)
if aggregated_points:
return {
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"geometry": {
"type": "LineString",
"coordinates": [[point["lon"], point["lat"]] for point in aggregated_points],
},
"properties": {
"mmsi": mmsi,
"hours": hours,
"point_count": len(aggregated_points),
"start_at": to_iso8601_utc(aggregated_points[0]["observed_at"]),
"end_at": to_iso8601_utc(aggregated_points[-1]["observed_at"]),
"point_sources": [point["source"] for point in aggregated_points],
},
}
],
"count": 1,
}
result = await db.execute(
select(VesselPosition)
.where(VesselPosition.mmsi == mmsi)
.where(VesselPosition.received_at >= cutoff)
.order_by(VesselPosition.received_at.asc())
)
positions = list(result.scalars().all())
if not positions:
return {
"type": "FeatureCollection",
"features": [],
"count": 0,
}
return {
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"geometry": {
"type": "LineString",
"coordinates": [[position.lon, position.lat] for position in positions],
},
"properties": {
"mmsi": mmsi,
"hours": hours,
"point_count": len(positions),
"start_at": to_iso8601_utc(positions[0].received_at),
"end_at": to_iso8601_utc(positions[-1].received_at),
},
}
],
"count": 1,
}
@router.get("/vessels/{mmsi}/observations")
async def get_vessel_observations(
mmsi: int,
limit: int = Query(100, ge=1, le=500),
db: AsyncSession = Depends(get_db),
):
"""Return raw AIS observations for debugging source-level collector facts."""
observations = await get_vessel_raw_observations(db, mmsi, limit=limit)
return {
"mmsi": mmsi,
"count": len(observations),
"observations": [item.to_dict() for item in observations],
"conflict_candidates": build_field_conflict_candidates(observations),
}
@router.get("/vessels/{mmsi}/conflicts")
async def get_vessel_conflicts(mmsi: int, db: AsyncSession = Depends(get_db)):
"""Return recorded AIS conflicts plus current raw-observation candidates."""
records = await get_vessel_conflict_records(db, mmsi)
observations = await get_vessel_raw_observations(db, mmsi, limit=500)
return {
"mmsi": mmsi,
"count": len(records),
"conflicts": [item.to_dict() for item in records],
"candidates": build_field_conflict_candidates(observations),
}
@router.get("/geo/bgp-anomalies")
async def get_bgp_anomalies_geojson(
severity: Optional[str] = Query(None),
@@ -1353,6 +2039,82 @@ async def get_bgp_collectors_geojson(db: AsyncSession = Depends(get_db)):
return {**geojson, "count": len(geojson.get("features", []))}
@router.get("/geo/summary")
async def get_visualization_geo_summary(db: AsyncSession = Depends(get_db)):
"""Return lightweight Earth HUD counts without loading layer GeoJSON payloads."""
cable_count = await _count_current_or_latest_task_data(db, "arcgis_cables")
landing_point_count = await _count_current_or_latest_task_data(db, "arcgis_landing_points")
satellite_count = await _count_current_or_latest_task_data(
db,
"celestrak_tle",
exclude_unknown_name=True,
)
supercomputer_count = await _count_current_or_latest_task_data(db, "top500")
gpu_cluster_count = await _count_current_or_latest_task_data(db, "epoch_ai_gpu")
compute_center_count = supercomputer_count + gpu_cluster_count
active_incident_result = await db.execute(
select(func.count(BGPIncident.id)).where(BGPIncident.status == "active"),
)
active_anomaly_result = await db.execute(
select(func.count(BGPAnomaly.id)).where(BGPAnomaly.status == "active"),
)
active_incident_count = int(active_incident_result.scalar() or 0)
active_anomaly_count = int(active_anomaly_result.scalar() or 0)
bgp_collector_result = await db.execute(
select(func.count(func.distinct(BGPObservation.collector)))
.where(BGPObservation.collector.isnot(None))
.where(func.length(func.btrim(BGPObservation.collector)) > 0)
.where(BGPObservation.source.in_(("ris_live_bgp", "bgpstream_bgp")))
)
bgp_collector_scalar = bgp_collector_result.scalar()
if bgp_collector_scalar is None:
bgp_collectors = await build_bgp_collector_coverage(
db,
source_filter=("ris_live_bgp", "bgpstream_bgp"),
)
bgp_collector_count = len(
[item for item in bgp_collectors if item.get("collector")]
)
else:
bgp_collector_count = int(bgp_collector_scalar or 0)
raw_unique_window_hours = 24
raw_unique_mmsi = await count_unique_raw_vessel_mmsi(
db,
observed_since=datetime.now(UTC) - timedelta(hours=raw_unique_window_hours),
)
legacy_unique_result = await db.execute(
select(func.count(func.distinct(VesselPosition.mmsi)))
)
legacy_unique_mmsi = int(legacy_unique_result.scalar() or 0)
vessel_count = max(raw_unique_mmsi, legacy_unique_mmsi)
aisstream_health = await db.get(AISSourceHealth, "aisstream_vessels")
return {
"generated_at": to_iso8601_utc(datetime.now(UTC)),
"stats": {
"cable_count": cable_count,
"landing_point_count": landing_point_count,
"satellite_count": satellite_count,
"compute_center_count": compute_center_count,
"vessel_count": vessel_count,
"vessel_raw_unique_mmsi": raw_unique_mmsi,
"vessel_raw_unique_window_hours": raw_unique_window_hours,
"vessel_legacy_unique_mmsi": legacy_unique_mmsi,
"aisstream_connection_state": aisstream_health.connection_state if aisstream_health else None,
"aisstream_last_seen_at": to_iso8601_utc(aisstream_health.last_seen_at) if aisstream_health else None,
"aisstream_message_rate": aisstream_health.message_rate if aisstream_health else None,
"aisstream_lag_seconds": aisstream_health.lag_seconds if aisstream_health else None,
"supercomputer_count": supercomputer_count,
"gpu_cluster_count": gpu_cluster_count,
"bgp_event_count": active_incident_count or active_anomaly_count,
"bgp_incident_count": active_incident_count,
"bgp_anomaly_count": active_anomaly_count,
"bgp_collector_count": bgp_collector_count,
},
}
@router.get("/all")
async def get_all_visualization_data(db: AsyncSession = Depends(get_db)):
"""获取所有可视化数据的统一端点

View File

@@ -40,16 +40,16 @@ async def authenticate_token(token: str) -> Optional[dict]:
@router.websocket("/ws")
async def websocket_endpoint(
websocket: WebSocket,
token: str = Query(...),
token: str | None = Query(None),
):
"""WebSocket endpoint for real-time data"""
logger.info_event(
"WebSocket connection attempt",
event="auth.websocket.connection_attempt",
context={"token_preview": f"{token[:8]}..."},
context={"token_preview": f"{token[:8]}..." if token else "anonymous"},
)
payload = await authenticate_token(token)
if payload is None:
payload = await authenticate_token(token) if token else None
if token and payload is None:
logger.warning_event(
"WebSocket authentication failed, closing connection",
event="auth.websocket.connection_rejected",
@@ -57,7 +57,17 @@ async def websocket_endpoint(
await websocket.close(code=4001)
return
user_id = str(payload.get("sub"))
is_anonymous = payload is None
user_id = str(payload.get("sub")) if payload else f"anonymous:{id(websocket)}"
supported_channels = ["vessels"] if is_anonymous else [
"gpu_clusters",
"submarine_cables",
"ixp_nodes",
"alerts",
"dashboard",
"datasource_tasks",
"vessels",
]
await manager.connect(websocket, user_id)
try:
@@ -68,14 +78,7 @@ async def websocket_endpoint(
"connection_id": f"conn_{user_id}",
"server_version": settings.VERSION,
"heartbeat_interval": 30,
"supported_channels": [
"gpu_clusters",
"submarine_cables",
"ixp_nodes",
"alerts",
"dashboard",
"datasource_tasks",
],
"supported_channels": supported_channels,
},
}
)
@@ -93,12 +96,24 @@ async def websocket_endpoint(
)
elif data.get("type") == "subscribe":
channels = data.get("data", {}).get("channels", [])
if is_anonymous:
channels = [channel for channel in channels if channel in supported_channels]
manager.subscribe(websocket, channels)
await websocket.send_json(
{
"type": "subscription_confirmed",
"data": {"action": "subscribe", "channels": channels},
}
)
elif data.get("type") == "unsubscribe":
channels = data.get("data", {}).get("channels", [])
manager.unsubscribe(websocket, channels)
await websocket.send_json(
{
"type": "subscription_confirmed",
"data": {"action": "unsubscribe", "channels": channels},
}
)
elif data.get("type") == "control_frame":
await websocket.send_json(
{"type": "control_acknowledged", "data": {"received": True}}

View File

@@ -1,7 +1,6 @@
import os
import yaml
from functools import lru_cache
from typing import Optional
COLLECTOR_URL_KEYS = {
@@ -31,6 +30,8 @@ COLLECTOR_URL_KEYS = {
"opengeofeed_prefix_geo": "opengeofeed.public_csv_url",
"nro_delegated_prefix_geo": "nro.delegated_stats_url",
"news_live_streams": "news_live_streams.channels_url",
"barentswatch_vessels": "barentswatch_vessels.url",
"aisstream_vessels": "aisstream_vessels.url",
}
@@ -73,7 +74,7 @@ class DataSourcesConfig:
from app.models.datasource_config import DataSourceConfig
query = select(DataSourceConfig).where(
DataSourceConfig.name == collector_name, DataSourceConfig.is_active == True
DataSourceConfig.name == collector_name, DataSourceConfig.is_active
)
result = await db.execute(query)
db_config = result.scalar_one_or_none()

View File

@@ -94,3 +94,11 @@ news_live_streams:
streams_url: "https://iptv-org.github.io/api/streams.json"
# IPTV-org 台标 JSON
logos_url: "https://iptv-org.github.io/api/logos.json"
barentswatch_vessels:
# BarentsWatch Live AIS latest combined endpoint. Requires an AIS bearer token.
url: "https://live.ais.barentswatch.no/v1/latest/combined"
aisstream_vessels:
# AISStream realtime WebSocket endpoint. Requires an AISStream API key.
url: "wss://stream.aisstream.io/v0/stream"

View File

@@ -4,163 +4,258 @@ DEFAULT_DATASOURCES = {
"top500": {
"id": 1,
"name": "TOP500 Supercomputers",
"display_name": "TOP500 超算榜单",
"module": "L1",
"priority": "P0",
"frequency_minutes": 240,
"is_free": True,
"requires_credentials": False,
},
"epoch_ai_gpu": {
"id": 2,
"name": "Epoch AI GPU Clusters",
"display_name": "Epoch AI GPU 集群",
"module": "L1",
"priority": "P0",
"frequency_minutes": 360,
"is_free": True,
"requires_credentials": False,
},
"huggingface_models": {
"id": 3,
"name": "HuggingFace Models",
"display_name": "Hugging Face 模型",
"module": "L2",
"priority": "P1",
"frequency_minutes": 720,
"is_free": True,
"requires_credentials": False,
},
"huggingface_datasets": {
"id": 4,
"name": "HuggingFace Datasets",
"display_name": "Hugging Face 数据集",
"module": "L2",
"priority": "P1",
"frequency_minutes": 720,
"is_free": True,
"requires_credentials": False,
},
"huggingface_spaces": {
"id": 5,
"name": "HuggingFace Spaces",
"display_name": "Hugging Face Spaces",
"module": "L2",
"priority": "P2",
"frequency_minutes": 1440,
"is_free": True,
"requires_credentials": False,
},
"peeringdb_ixp": {
"id": 6,
"name": "PeeringDB IXP",
"display_name": "PeeringDB 交换中心",
"module": "L2",
"priority": "P1",
"frequency_minutes": 1440,
"is_free": True,
"requires_credentials": False,
},
"peeringdb_network": {
"id": 7,
"name": "PeeringDB Networks",
"display_name": "PeeringDB 网络",
"module": "L2",
"priority": "P2",
"frequency_minutes": 2880,
"is_free": True,
"requires_credentials": False,
},
"peeringdb_facility": {
"id": 8,
"name": "PeeringDB Facilities",
"display_name": "PeeringDB 设施",
"module": "L2",
"priority": "P2",
"frequency_minutes": 2880,
"is_free": True,
"requires_credentials": False,
},
"telegeography_cables": {
"id": 9,
"name": "Submarine Cables",
"display_name": "海底光缆",
"module": "L2",
"priority": "P1",
"frequency_minutes": 10080,
"is_free": True,
"requires_credentials": False,
},
"telegeography_landing": {
"id": 10,
"name": "Cable Landing Points",
"display_name": "光缆登陆点",
"module": "L2",
"priority": "P2",
"frequency_minutes": 10080,
"is_free": True,
"requires_credentials": False,
},
"telegeography_systems": {
"id": 11,
"name": "Cable Systems",
"display_name": "光缆系统",
"module": "L2",
"priority": "P2",
"frequency_minutes": 10080,
"is_free": True,
"requires_credentials": False,
},
"arcgis_cables": {
"id": 15,
"name": "ArcGIS Submarine Cables",
"display_name": "ArcGIS 海底光缆",
"module": "L2",
"priority": "P1",
"frequency_minutes": 10080,
"is_free": True,
"requires_credentials": False,
},
"arcgis_landing_points": {
"id": 16,
"name": "ArcGIS Landing Points",
"display_name": "ArcGIS 登陆点",
"module": "L2",
"priority": "P1",
"frequency_minutes": 10080,
"is_free": True,
"requires_credentials": False,
},
"arcgis_cable_landing_relation": {
"id": 17,
"name": "ArcGIS Cable-Landing Relations",
"display_name": "ArcGIS 光缆登陆关系",
"module": "L2",
"priority": "P1",
"frequency_minutes": 10080,
"is_free": True,
"requires_credentials": False,
},
"fao_landing_points": {
"id": 18,
"name": "FAO Landing Points",
"display_name": "FAO 登陆点",
"module": "L2",
"priority": "P1",
"frequency_minutes": 10080,
"is_free": True,
"requires_credentials": False,
},
"spacetrack_tle": {
"id": 19,
"name": "Space-Track TLE",
"display_name": "Space-Track 轨道根数",
"module": "L3",
"priority": "P2",
"frequency_minutes": 1440,
"is_free": True,
"requires_credentials": True,
"credential_provider": "spacetrack",
"credential_status": "planned",
},
"celestrak_tle": {
"id": 20,
"name": "CelesTrak TLE",
"display_name": "CelesTrak 轨道根数",
"module": "L3",
"priority": "P2",
"frequency_minutes": 1440,
"is_free": True,
"requires_credentials": False,
},
"ris_live_bgp": {
"id": 21,
"name": "RIPE RIS Live BGP",
"display_name": "RIPE RIS 实时 BGP",
"module": "L3",
"priority": "P1",
"frequency_minutes": 15,
"is_free": True,
"requires_credentials": False,
},
"bgpstream_bgp": {
"id": 22,
"name": "CAIDA BGPStream Backfill",
"display_name": "CAIDA BGPStream 回填",
"module": "L3",
"priority": "P1",
"frequency_minutes": 360,
"is_free": True,
"requires_credentials": False,
},
"iptoasn_prefix_geo": {
"id": 23,
"name": "IPtoASN Prefix Geography",
"display_name": "IPtoASN 前缀地理",
"module": "L3",
"priority": "P1",
"frequency_minutes": 1440,
"is_free": True,
"requires_credentials": False,
},
"opengeofeed_prefix_geo": {
"id": 24,
"name": "OpenGeoFeed Prefix Geography",
"display_name": "OpenGeoFeed 前缀地理",
"module": "L3",
"priority": "P1",
"frequency_minutes": 1440,
"is_free": True,
"requires_credentials": False,
},
"nro_delegated_prefix_geo": {
"id": 25,
"name": "NRO Delegated Prefix Geography",
"display_name": "NRO 分配前缀地理",
"module": "L3",
"priority": "P1",
"frequency_minutes": 1440,
"is_free": True,
"requires_credentials": False,
},
"news_live_streams": {
"id": 26,
"name": "News Live Streams",
"display_name": "新闻直播源",
"module": "L4",
"priority": "P2",
"frequency_minutes": 720,
"is_free": True,
"requires_credentials": False,
},
"barentswatch_vessels": {
"id": 27,
"name": "BarentsWatch AIS Vessels",
"display_name": "BarentsWatch AIS 船舶",
"module": "L4",
"priority": "P1",
"frequency_minutes": 1,
"is_free": True,
"requires_credentials": True,
"credential_provider": "barentswatch",
"credential_status": "supported",
},
"aisstream_vessels": {
"id": 28,
"name": "AISStream Vessels",
"display_name": "AISStream 实时船舶",
"module": "L4",
"priority": "P1",
"frequency_minutes": 1,
"is_free": True,
"requires_credentials": True,
"credential_provider": "aisstream",
"credential_status": "supported",
},
}

View File

@@ -0,0 +1,157 @@
"""Registry of target schemas supported by mapped custom data sources."""
from __future__ import annotations
from dataclasses import dataclass
from datetime import datetime
from typing import Any
from pydantic import BaseModel, Field, ValidationError, field_validator
class VesselAISRecord(BaseModel):
mmsi: int = Field(ge=100000000, le=999999999)
lat: float = Field(ge=-90, le=90)
lon: float = Field(ge=-180, le=180)
sog: float | None = None
cog: float | None = Field(default=None, ge=0, le=360)
heading: int | None = Field(default=None, ge=0, le=511)
nav_status: int | None = None
name: str | None = None
callsign: str | None = None
vessel_type: str | int | None = None
vessel_type_name: str | None = None
received_at: datetime | None = None
class GeoPointRecord(BaseModel):
lat: float = Field(ge=-90, le=90)
lon: float = Field(ge=-180, le=180)
name: str | None = None
type: str | None = None
source_id: str | None = None
observed_at: datetime | None = None
metadata: dict[str, Any] = Field(default_factory=dict)
class GenericRecord(BaseModel):
data: dict[str, Any] = Field(default_factory=dict)
source_id: str | None = None
observed_at: datetime | None = None
@field_validator("data")
@classmethod
def require_payload(cls, value: dict[str, Any]) -> dict[str, Any]:
if not value:
raise ValueError("generic_records requires a non-empty data object")
return value
@dataclass(frozen=True)
class TargetField:
name: str
type: str
required: bool = False
description: str = ""
example: Any = None
def to_dict(self) -> dict[str, Any]:
return {
"name": self.name,
"type": self.type,
"required": self.required,
"description": self.description,
"example": self.example,
}
@dataclass(frozen=True)
class TargetSchema:
key: str
label: str
description: str
fields: tuple[TargetField, ...]
model: type[BaseModel]
destination: str
def to_dict(self) -> dict[str, Any]:
return {
"key": self.key,
"label": self.label,
"description": self.description,
"destination": self.destination,
"fields": [field.to_dict() for field in self.fields],
}
def validate_record(self, record: dict[str, Any]) -> tuple[dict[str, Any] | None, list[str]]:
try:
return self.model.model_validate(record).model_dump(mode="json"), []
except ValidationError as exc:
return None, [
".".join(str(part) for part in error["loc"]) + f": {error['msg']}"
for error in exc.errors()
]
TARGET_SCHEMAS: dict[str, TargetSchema] = {
"vessel_ais": TargetSchema(
key="vessel_ais",
label="船舶 AIS",
description="船只位置、航速、航向、MMSI 等 AIS 数据。",
destination="vessel_position",
model=VesselAISRecord,
fields=(
TargetField("mmsi", "integer", True, "MMSI 九位船舶标识", 257123000),
TargetField("lat", "float", True, "纬度", 59.91),
TargetField("lon", "float", True, "经度", 10.75),
TargetField("sog", "float", False, "对地航速,单位节", 12.4),
TargetField("cog", "float", False, "对地航向0-360 度", 184.5),
TargetField("heading", "integer", False, "船首向0-511", 186),
TargetField("nav_status", "integer", False, "导航状态码", 0),
TargetField("name", "string", False, "船名", "OSLO EXPRESS"),
TargetField("callsign", "string", False, "呼号", "LAAB"),
TargetField("vessel_type", "string", False, "船型代码", 70),
TargetField("vessel_type_name", "string", False, "船型名称", "Cargo"),
TargetField("received_at", "datetime", False, "数据接收时间", "2026-04-28T00:00:00Z"),
),
),
"geo_points": TargetSchema(
key="geo_points",
label="通用地理点",
description="带经纬度的通用实体或事件点位。",
destination="generic_geo_points",
model=GeoPointRecord,
fields=(
TargetField("lat", "float", True, "纬度", 1.3),
TargetField("lon", "float", True, "经度", 103.8),
TargetField("name", "string", False, "点位名称", "Singapore"),
TargetField("type", "string", False, "点位类型", "datacenter"),
TargetField("source_id", "string", False, "来源侧 ID", "sg-1"),
TargetField("observed_at", "datetime", False, "观测时间", "2026-04-28T00:00:00Z"),
TargetField("metadata", "object", False, "扩展字段", {"provider": "example"}),
),
),
"generic_records": TargetSchema(
key="generic_records",
label="通用结构化记录",
description="未知结构数据沉淀,不直接进入 Earth 图层。",
destination="collected_data",
model=GenericRecord,
fields=(
TargetField("data", "object", True, "结构化记录主体", {"raw": "value"}),
TargetField("source_id", "string", False, "来源侧 ID", "record-1"),
TargetField("observed_at", "datetime", False, "观测时间", "2026-04-28T00:00:00Z"),
),
),
}
def list_target_schemas() -> list[dict[str, Any]]:
return [schema.to_dict() for schema in TARGET_SCHEMAS.values()]
def get_target_schema(key: str) -> TargetSchema:
try:
return TARGET_SCHEMAS[key]
except KeyError as exc:
raise ValueError(f"Unsupported target schema: {key}") from exc

View File

@@ -75,7 +75,7 @@ class DataBroadcaster:
"timestamp": to_iso8601_utc(datetime.now(UTC)),
"payload": data,
},
channel=channel if channel in manager.active_connections else "all",
channel=channel,
)
async def broadcast_datasource_task_update(self, data: Dict[str, Any]):

View File

@@ -1,9 +1,6 @@
"""WebSocket Connection Manager"""
import json
import asyncio
from typing import Dict, Set, Optional
from datetime import datetime
from fastapi import WebSocket
import redis.asyncio as redis
@@ -15,6 +12,8 @@ class ConnectionManager:
def __init__(self):
self.active_connections: Dict[str, Set[WebSocket]] = {} # user_id -> connections
self.channel_subscriptions: Dict[str, Set[WebSocket]] = {}
self.websocket_channels: Dict[WebSocket, Set[str]] = {}
self.redis_client: Optional[redis.Redis] = None
async def connect(self, websocket: WebSocket, user_id: str):
@@ -40,6 +39,39 @@ class ConnectionManager:
self.active_connections[user_id].discard(websocket)
if not self.active_connections[user_id]:
del self.active_connections[user_id]
self.unsubscribe_all(websocket)
def subscribe(self, websocket: WebSocket, channels: list[str]):
normalized_channels = {
str(channel).strip()
for channel in channels
if str(channel).strip()
}
if not normalized_channels:
return
socket_channels = self.websocket_channels.setdefault(websocket, set())
for channel in normalized_channels:
self.channel_subscriptions.setdefault(channel, set()).add(websocket)
socket_channels.add(channel)
def unsubscribe(self, websocket: WebSocket, channels: list[str]):
for channel in {str(channel).strip() for channel in channels if str(channel).strip()}:
subscribers = self.channel_subscriptions.get(channel)
if subscribers is not None:
subscribers.discard(websocket)
if not subscribers:
del self.channel_subscriptions[channel]
socket_channels = self.websocket_channels.get(websocket)
if socket_channels is not None:
socket_channels.discard(channel)
if not socket_channels:
del self.websocket_channels[websocket]
def unsubscribe_all(self, websocket: WebSocket):
channels = list(self.websocket_channels.get(websocket, set()))
if channels:
self.unsubscribe(websocket, channels)
async def send_personal_message(self, message: dict, user_id: str):
if user_id in self.active_connections:
@@ -54,13 +86,19 @@ class ConnectionManager:
for user_id in self.active_connections:
await self.send_personal_message(message, user_id)
else:
await self.send_personal_message(message, channel)
for connection in list(self.channel_subscriptions.get(channel, set())):
try:
await connection.send_json(message)
except Exception:
self.unsubscribe_all(connection)
async def close_all(self):
for user_id in self.active_connections:
for connection in self.active_connections[user_id]:
await connection.close()
self.active_connections.clear()
self.channel_subscriptions.clear()
self.websocket_channels.clear()
manager = ConnectionManager()

View File

@@ -110,6 +110,9 @@ async def init_db():
import app.models.playground_session # noqa: F401
import app.models.playground_message # noqa: F401
import app.models.system_log # noqa: F401
import app.models.vessel # noqa: F401
import app.models.vessel_enrichment # noqa: F401
import app.models.datasource_mapping # noqa: F401
logger.warning_event(
"Database pool settings active",
@@ -144,7 +147,12 @@ async def init_db():
text(
"""
ALTER TABLE collection_tasks
ADD COLUMN IF NOT EXISTS phase VARCHAR(30) DEFAULT 'queued'
ADD COLUMN IF NOT EXISTS phase VARCHAR(30) DEFAULT 'queued',
ADD COLUMN IF NOT EXISTS phase_progress DOUBLE PRECISION,
ADD COLUMN IF NOT EXISTS phase_message VARCHAR(255),
ADD COLUMN IF NOT EXISTS phase_current BIGINT,
ADD COLUMN IF NOT EXISTS phase_total BIGINT,
ADD COLUMN IF NOT EXISTS phase_unit VARCHAR(30)
"""
)
)
@@ -156,6 +164,30 @@ async def init_db():
"""
)
)
await conn.execute(
text(
"""
CREATE INDEX IF NOT EXISTS idx_collected_data_source_current_id
ON collected_data (source, is_current, id)
"""
)
)
await conn.execute(
text(
"""
CREATE INDEX IF NOT EXISTS idx_collected_data_source_task_id
ON collected_data (source, task_id, id)
"""
)
)
await conn.execute(
text(
"""
CREATE INDEX IF NOT EXISTS idx_ais_raw_schema_observed_entity
ON ais_raw_observations (target_schema, observed_at, entity_key)
"""
)
)
await conn.execute(
text(
"""

View File

@@ -12,6 +12,8 @@ from app.models.system_setting import SystemSetting
from app.models.playground_session import PlaygroundSession
from app.models.playground_message import PlaygroundMessage
from app.models.system_log import SystemLog, AuditLog
from app.models.vessel import AISConflictRecord, AISRawObservation, AISSourceHealth, VesselPosition, VesselStatic
from app.models.datasource_mapping import DataSourceMappingTemplate
__all__ = [
"User",
@@ -29,4 +31,12 @@ __all__ = [
"BGPObservation",
"SystemLog",
"AuditLog",
"PlaygroundSession",
"PlaygroundMessage",
"VesselPosition",
"VesselStatic",
"AISRawObservation",
"AISConflictRecord",
"AISSourceHealth",
"DataSourceMappingTemplate",
]

View File

@@ -48,6 +48,8 @@ class CollectedData(Base):
# Indexes for common queries
__table_args__ = (
Index("idx_collected_data_source_collected", "source", "collected_at"),
Index("idx_collected_data_source_current_id", "source", "is_current", "id"),
Index("idx_collected_data_source_task_id", "source", "task_id", "id"),
Index("idx_collected_data_source_type", "source", "data_type"),
Index("idx_collected_data_source_source_id", "source", "source_id"),
)

View File

@@ -0,0 +1,32 @@
"""Mapping templates for user-defined data source payloads."""
from sqlalchemy import Boolean, Column, DateTime, ForeignKey, Integer, JSON, String
from sqlalchemy.sql import func
from app.db.session import Base
class DataSourceMappingTemplate(Base):
__tablename__ = "datasource_mapping_templates"
id = Column(Integer, primary_key=True, autoincrement=True)
datasource_config_id = Column(
Integer,
ForeignKey("datasource_configs.id"),
nullable=False,
index=True,
)
target_schema = Column(String(80), nullable=False, index=True)
mapping_json = Column(JSON, nullable=False, default={})
sample_payload_hash = Column(String(64), nullable=True)
validation_status = Column(String(30), nullable=False, default="draft")
version = Column(Integer, nullable=False, default=1)
is_active = Column(Boolean, nullable=False, default=False, index=True)
created_at = Column(DateTime(timezone=True), server_default=func.now())
updated_at = Column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())
def __repr__(self):
return (
f"<DataSourceMappingTemplate {self.id}: "
f"{self.datasource_config_id}/{self.target_schema}/v{self.version}>"
)

View File

@@ -1,6 +1,6 @@
"""Collection Task model"""
from sqlalchemy import Column, DateTime, Integer, String, Text, Float
from sqlalchemy import BigInteger, Column, DateTime, Integer, String, Text, Float
from sqlalchemy.sql import func
from app.db.session import Base
@@ -13,6 +13,11 @@ class CollectionTask(Base):
datasource_id = Column(Integer, nullable=False, index=True)
status = Column(String(20), nullable=False) # pending, running, success, failed, cancelled
phase = Column(String(30), default="queued")
phase_progress = Column(Float)
phase_message = Column(String(255))
phase_current = Column(BigInteger)
phase_total = Column(BigInteger)
phase_unit = Column(String(30))
started_at = Column(DateTime(timezone=True))
completed_at = Column(DateTime(timezone=True))
records_processed = Column(Integer, default=0)

View File

@@ -0,0 +1,186 @@
"""Vessel AIS models for live maritime tracking."""
from sqlalchemy import BigInteger, Column, DateTime, Float, Index, Integer, JSON, SmallInteger, String
from sqlalchemy.sql import func
from app.core.time import to_iso8601_utc
from app.db.session import Base
class VesselStatic(Base):
"""Slow-changing vessel identity and dimensions."""
__tablename__ = "vessel_static"
mmsi = Column(BigInteger, primary_key=True)
name = Column(String(128), nullable=True)
callsign = Column(String(16), nullable=True)
vessel_type = Column(SmallInteger, nullable=True, index=True)
vessel_type_name = Column(String(64), nullable=True, index=True)
flag = Column(String(4), nullable=True, index=True)
length = Column(Float, nullable=True)
width = Column(Float, nullable=True)
draught = Column(Float, nullable=True)
imo = Column(BigInteger, nullable=True)
updated_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now())
def to_dict(self) -> dict:
return {
"mmsi": self.mmsi,
"name": self.name,
"callsign": self.callsign,
"vessel_type": self.vessel_type,
"vessel_type_name": self.vessel_type_name,
"flag": self.flag,
"length": self.length,
"width": self.width,
"draught": self.draught,
"imo": self.imo,
"updated_at": to_iso8601_utc(self.updated_at),
}
class VesselPosition(Base):
"""Append-only AIS positions retained for short history windows."""
__tablename__ = "vessel_position"
id = Column(Integer, primary_key=True, autoincrement=True)
mmsi = Column(BigInteger, nullable=False, index=True)
lat = Column(Float, nullable=False)
lon = Column(Float, nullable=False)
sog = Column(Float, nullable=True)
cog = Column(Float, nullable=True)
heading = Column(SmallInteger, nullable=True)
nav_status = Column(SmallInteger, nullable=True, index=True)
received_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now(), index=True)
__table_args__ = (
Index("idx_vessel_pos_mmsi_time", "mmsi", "received_at"),
Index("idx_vessel_pos_time", "received_at"),
Index("idx_vessel_pos_lat_lon", "lat", "lon"),
)
def to_dict(self) -> dict:
return {
"id": self.id,
"mmsi": self.mmsi,
"lat": self.lat,
"lon": self.lon,
"sog": self.sog,
"cog": self.cog,
"heading": self.heading,
"nav_status": self.nav_status,
"received_at": to_iso8601_utc(self.received_at),
}
class AISRawObservation(Base):
"""Source-level AIS fact before aggregation and conflict resolution."""
__tablename__ = "ais_raw_observations"
id = Column(Integer, primary_key=True, autoincrement=True)
target_schema = Column(String(64), nullable=False, default="vessel_ais", index=True)
source = Column(String(100), nullable=False, index=True)
entity_key = Column(String(64), nullable=False, index=True)
delivery_mode = Column(String(32), nullable=False, index=True)
transport = Column(String(32), nullable=False, index=True)
message_type = Column(String(64), nullable=True, index=True)
source_message_id = Column(String(128), nullable=True, index=True)
observation_hash = Column(String(64), nullable=False, unique=True, index=True)
observed_at = Column(DateTime(timezone=True), nullable=False, index=True)
collected_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now(), index=True)
normalized_payload = Column(JSON, default=dict)
raw_payload = Column(JSON, default=dict)
quality_flags = Column(JSON, default=list)
__table_args__ = (
Index("idx_ais_raw_entity_observed", "target_schema", "entity_key", "observed_at"),
Index("idx_ais_raw_schema_observed_entity", "target_schema", "observed_at", "entity_key"),
Index("idx_ais_raw_source_entity", "source", "entity_key"),
)
def to_dict(self) -> dict:
return {
"id": self.id,
"target_schema": self.target_schema,
"source": self.source,
"entity_key": self.entity_key,
"delivery_mode": self.delivery_mode,
"transport": self.transport,
"message_type": self.message_type,
"source_message_id": self.source_message_id,
"observation_hash": self.observation_hash,
"observed_at": to_iso8601_utc(self.observed_at),
"collected_at": to_iso8601_utc(self.collected_at),
"normalized_payload": self.normalized_payload or {},
"raw_payload": self.raw_payload or {},
"quality_flags": self.quality_flags or [],
}
class AISConflictRecord(Base):
"""Recorded field-level disagreement between AIS sources."""
__tablename__ = "ais_conflict_records"
id = Column(Integer, primary_key=True, autoincrement=True)
target_schema = Column(String(64), nullable=False, default="vessel_ais", index=True)
entity_key = Column(String(64), nullable=False, index=True)
field = Column(String(64), nullable=False, index=True)
candidates = Column(JSON, default=dict)
selected_source = Column(String(100), nullable=True, index=True)
selected_value = Column(JSON, nullable=True)
selected_reason = Column(String(64), nullable=True, index=True)
resolved_by = Column(String(32), nullable=False, default="system", index=True)
status = Column(String(32), nullable=False, default="open", index=True)
created_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now(), index=True)
updated_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now())
__table_args__ = (
Index("idx_ais_conflict_entity_field", "target_schema", "entity_key", "field"),
)
def to_dict(self) -> dict:
return {
"id": self.id,
"target_schema": self.target_schema,
"entity_key": self.entity_key,
"field": self.field,
"candidates": self.candidates or {},
"selected_source": self.selected_source,
"selected_value": self.selected_value,
"selected_reason": self.selected_reason,
"resolved_by": self.resolved_by,
"status": self.status,
"created_at": to_iso8601_utc(self.created_at),
"updated_at": to_iso8601_utc(self.updated_at),
}
class AISSourceHealth(Base):
"""Runtime health signal for an AIS collector source."""
__tablename__ = "ais_source_health"
source = Column(String(100), primary_key=True)
connection_state = Column(String(32), nullable=False, default="disconnected", index=True)
last_seen_at = Column(DateTime(timezone=True), nullable=True, index=True)
last_success_at = Column(DateTime(timezone=True), nullable=True, index=True)
last_error = Column(String(500), nullable=True)
message_rate = Column(Float, nullable=True)
lag_seconds = Column(Float, nullable=True)
updated_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now(), index=True)
def to_dict(self) -> dict:
return {
"source": self.source,
"connection_state": self.connection_state,
"last_seen_at": to_iso8601_utc(self.last_seen_at),
"last_success_at": to_iso8601_utc(self.last_success_at),
"last_error": self.last_error,
"message_rate": self.message_rate,
"lag_seconds": self.lag_seconds,
"updated_at": to_iso8601_utc(self.updated_at),
}

View File

@@ -0,0 +1,63 @@
"""Vessel enrichment cache tables (v5).
Profile and media enrichment are stored separately so cache TTLs can differ
and so the conflict-resolution + display layers can read either independently.
"""
from sqlalchemy import BigInteger, Column, DateTime, Float, JSON, String
from sqlalchemy.sql import func
from app.core.time import to_iso8601_utc
from app.db.session import Base
class VesselProfileEnrichment(Base):
"""Cached static vessel profile (type, flag, dimensions, operator, etc.)."""
__tablename__ = "vessel_profile_enrichment"
mmsi = Column(BigInteger, primary_key=True)
source = Column(String(100), nullable=False, default="system")
payload = Column(JSON, nullable=False, default=dict)
fetched_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now())
expires_at = Column(DateTime(timezone=True), nullable=True)
confidence = Column(Float, nullable=True)
reference_url = Column(String(500), nullable=True)
updated_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now(), onupdate=func.now())
def to_dict(self) -> dict:
return {
"mmsi": self.mmsi,
"source": self.source,
"payload": self.payload or {},
"fetched_at": to_iso8601_utc(self.fetched_at),
"expires_at": to_iso8601_utc(self.expires_at),
"confidence": self.confidence,
"reference_url": self.reference_url,
}
class VesselMediaEnrichment(Base):
"""Cached vessel imagery / external detail references."""
__tablename__ = "vessel_media_enrichment"
mmsi = Column(BigInteger, primary_key=True)
source = Column(String(100), nullable=False, default="system")
payload = Column(JSON, nullable=False, default=dict)
fetched_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now())
expires_at = Column(DateTime(timezone=True), nullable=True)
confidence = Column(Float, nullable=True)
reference_url = Column(String(500), nullable=True)
updated_at = Column(DateTime(timezone=True), nullable=False, server_default=func.now(), onupdate=func.now())
def to_dict(self) -> dict:
return {
"mmsi": self.mmsi,
"source": self.source,
"payload": self.payload or {},
"fetched_at": to_iso8601_utc(self.fetched_at),
"expires_at": to_iso8601_utc(self.expires_at),
"confidence": self.confidence,
"reference_url": self.reference_url,
}

View File

@@ -3,9 +3,11 @@ from __future__ import annotations
import asyncio
import httpx
from fastapi import HTTPException, status
from fastapi import Depends, HTTPException, status
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.config import settings
from app.db.session import get_db
from app.schemas.ai import (
AIProviderStatusResponse,
SituationalAnalysisRequest,
@@ -14,11 +16,27 @@ from app.schemas.ai import (
class AIProviderClient:
def __init__(self) -> None:
self.service_url = settings.AI_PROVIDER_SERVICE_URL.rstrip("/")
self.service_token = settings.AI_PROVIDER_SERVICE_TOKEN
self.timeout = settings.AI_PROVIDER_TIMEOUT_SECONDS
self.retry_attempts = max(settings.AI_PROVIDER_RETRY_ATTEMPTS, 1)
def __init__(
self,
*,
service_url: str | None = None,
service_token: str | None = None,
timeout: int | None = None,
retry_attempts: int | None = None,
llm_config: dict | None = None,
) -> None:
self.service_url = (
service_url if service_url is not None else settings.AI_PROVIDER_SERVICE_URL
).rstrip("/")
self.service_token = (
service_token if service_token is not None else settings.AI_PROVIDER_SERVICE_TOKEN
)
self.timeout = timeout if timeout is not None else settings.AI_PROVIDER_TIMEOUT_SECONDS
self.retry_attempts = max(
retry_attempts if retry_attempts is not None else settings.AI_PROVIDER_RETRY_ATTEMPTS,
1,
)
self.llm_config = llm_config or {}
def _headers(self, request_id: str | None = None) -> dict[str, str]:
headers = {"Content-Type": "application/json"}
@@ -26,6 +44,19 @@ class AIProviderClient:
headers["X-Provider-Token"] = self.service_token
if request_id:
headers["X-Request-ID"] = request_id
llm_header_map = {
"provider": "X-AI-Provider",
"provider_api": "X-AI-Provider-API",
"base_url": "X-AI-Base-URL",
"api_key": "X-AI-API-Key",
"model": "X-AI-Model",
"max_tokens": "X-AI-Max-Tokens",
"anthropic_version": "X-AI-Anthropic-Version",
}
for key, header_name in llm_header_map.items():
value = self.llm_config.get(key)
if value not in (None, ""):
headers[header_name] = str(value)
return headers
async def get_status(self, request_id: str | None = None) -> AIProviderStatusResponse:
@@ -105,5 +136,14 @@ class AIProviderClient:
)
def get_ai_provider_client() -> AIProviderClient:
return AIProviderClient()
async def get_ai_provider_client(db: AsyncSession = Depends(get_db)) -> AIProviderClient:
from app.api.v1.settings import get_runtime_ai_provider_config
runtime_config = await get_runtime_ai_provider_config(db)
return AIProviderClient(
service_url=runtime_config["service_url"],
service_token=runtime_config["service_token"],
timeout=runtime_config["timeout_seconds"],
retry_attempts=runtime_config["retry_attempts"],
llm_config=runtime_config.get("llm_config") or {},
)

View File

@@ -0,0 +1,209 @@
"""BarentsWatch AIS credential resolution and connectivity checks."""
from __future__ import annotations
import os
import shlex
from dataclasses import dataclass
from pathlib import Path
from typing import Any
import httpx
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.data_sources import get_data_sources_config
from app.models.datasource_config import DataSourceConfig
BARENTSWATCH_LATEST_URL = "https://live.ais.barentswatch.no/v1/latest/combined"
BARENTSWATCH_TOKEN_URL = "https://id.barentswatch.no/connect/token"
BARENTSWATCH_DATASOURCE_NAME = "barentswatch_vessels"
@dataclass(frozen=True)
class BarentsWatchConfig:
endpoint: str
client_id: str
client_secret: str
credential_source: str
endpoint_source: str
def _read_zshrc_env(path: Path | None = None) -> dict[str, str]:
zshrc_path = path or Path.home() / ".zshrc"
if not zshrc_path.exists():
return {}
values: dict[str, str] = {}
for raw_line in zshrc_path.read_text(encoding="utf-8", errors="ignore").splitlines():
line = raw_line.strip()
if not line or line.startswith("#"):
continue
if line.startswith("export "):
line = line[len("export ") :].strip()
if "=" not in line:
continue
key, value = line.split("=", 1)
key = key.strip()
if not key or not key.replace("_", "").isalnum() or not key[0].isalpha():
continue
try:
parsed = shlex.split(value, comments=True, posix=True)
except ValueError:
parsed = [value.strip().strip("'\"")]
if parsed:
values[key] = parsed[0]
return values
def _first_env_value(zshrc_env: dict[str, str], *keys: str) -> tuple[str, str]:
for key in keys:
value = os.getenv(key)
if value:
return value, "environment"
for key in keys:
value = zshrc_env.get(key)
if value:
return value, "~/.zshrc"
return "", ""
async def get_barentswatch_datasource_record(db: AsyncSession) -> DataSourceConfig | None:
result = await db.execute(
select(DataSourceConfig)
.where(DataSourceConfig.name == BARENTSWATCH_DATASOURCE_NAME)
.where(DataSourceConfig.is_active.is_(True))
)
return result.scalar_one_or_none()
async def resolve_barentswatch_config(db: AsyncSession | None = None) -> BarentsWatchConfig:
record = await get_barentswatch_datasource_record(db) if db else None
auth_config = dict(record.auth_config or {}) if record else {}
config = dict(record.config or {}) if record else {}
zshrc_env = _read_zshrc_env()
env_client_id, env_source = _first_env_value(
zshrc_env,
"BARENTSWATCH_CLIENT_ID",
"BARRENTSWATCH_CLIENT_ID",
)
env_client_secret, secret_env_source = _first_env_value(
zshrc_env,
"BARENTSWATCH_CLIENT_SECRET",
"BARRENTSWATCH_CLIENT_SECRET",
)
client_id = auth_config.get("client_id") or config.get("client_id") or env_client_id
client_secret = (
auth_config.get("client_secret") or config.get("client_secret") or env_client_secret
)
credential_source = ""
if auth_config.get("client_id") or auth_config.get("client_secret"):
credential_source = "datasource_config"
elif config.get("client_id") or config.get("client_secret"):
credential_source = "datasource_runtime_config"
elif env_source or secret_env_source:
credential_source = env_source or secret_env_source
yaml_endpoint = get_data_sources_config().get_yaml_url(BARENTSWATCH_DATASOURCE_NAME)
endpoint = record.endpoint if record and record.endpoint else yaml_endpoint
return BarentsWatchConfig(
endpoint=endpoint or BARENTSWATCH_LATEST_URL,
client_id=str(client_id or ""),
client_secret=str(client_secret or ""),
credential_source=credential_source or "missing",
endpoint_source="datasource_config" if record and record.endpoint else "default",
)
async def fetch_barentswatch_access_token(
client: httpx.AsyncClient,
config: BarentsWatchConfig,
) -> str | None:
if not config.client_id or not config.client_secret:
return None
response = await client.post(
BARENTSWATCH_TOKEN_URL,
data={
"client_id": config.client_id,
"client_secret": config.client_secret,
"scope": "ais",
"grant_type": "client_credentials",
},
headers={"Content-Type": "application/x-www-form-urlencoded"},
)
response.raise_for_status()
payload = response.json()
token = payload.get("access_token")
return str(token) if token else None
async def check_barentswatch_connectivity(db: AsyncSession) -> dict[str, Any]:
config = await resolve_barentswatch_config(db)
return await check_barentswatch_config(config)
async def check_barentswatch_config(config: BarentsWatchConfig) -> dict[str, Any]:
if not config.client_id or not config.client_secret:
return {
"success": False,
"stage": "credentials",
"message": "未找到 BarentsWatch client id/client secret请先配置采集器凭证。",
"endpoint": config.endpoint,
"credential_source": config.credential_source,
"settings_tab": "collector_credentials",
}
try:
async with httpx.AsyncClient(timeout=20.0) as client:
token = await fetch_barentswatch_access_token(client, config)
if not token:
return {
"success": False,
"stage": "token",
"message": "BarentsWatch token 响应中没有 access_token请检查凭证。",
"endpoint": config.endpoint,
"credential_source": config.credential_source,
"settings_tab": "collector_credentials",
}
async with client.stream(
"GET",
config.endpoint,
headers={"Authorization": f"Bearer {token}"},
) as response:
response.raise_for_status()
return {
"success": True,
"stage": "endpoint",
"message": "BarentsWatch AIS token 和数据接口均可连通。",
"endpoint": config.endpoint,
"credential_source": config.credential_source,
"endpoint_source": config.endpoint_source,
}
except httpx.HTTPStatusError as exc:
status_code = exc.response.status_code
stage = "token" if str(exc.request.url) == BARENTSWATCH_TOKEN_URL else "endpoint"
return {
"success": False,
"stage": stage,
"message": f"BarentsWatch {stage} 请求返回 HTTP {status_code},请检查凭证或接口地址。",
"endpoint": config.endpoint,
"credential_source": config.credential_source,
"settings_tab": "collector_credentials",
}
except httpx.HTTPError as exc:
return {
"success": False,
"stage": "network",
"message": f"BarentsWatch 链路检查失败:{exc.__class__.__name__}",
"endpoint": config.endpoint,
"credential_source": config.credential_source,
"settings_tab": "collector_credentials",
}

View File

@@ -36,6 +36,8 @@ from app.services.collectors.iptoasn import IPtoASNPrefixGeoCollector
from app.services.collectors.opengeofeed import OpenGeoFeedPrefixGeoCollector
from app.services.collectors.nro_delegated import NRODelegatedPrefixGeoCollector
from app.services.collectors.news_live_streams import NewsLiveStreamsCollector
from app.services.collectors.aisstream import AISStreamCollector
from app.services.collectors.vessel_ais import VesselAISCollector
collector_registry.register(TOP500Collector())
collector_registry.register(EpochAIGPUCollector())
@@ -63,3 +65,41 @@ collector_registry.register(IPtoASNPrefixGeoCollector())
collector_registry.register(OpenGeoFeedPrefixGeoCollector())
collector_registry.register(NRODelegatedPrefixGeoCollector())
collector_registry.register(NewsLiveStreamsCollector())
collector_registry.register(VesselAISCollector())
collector_registry.register(AISStreamCollector())
__all__ = [
"BaseCollector",
"HTTPCollector",
"IntervalCollector",
"collector_registry",
"CollectorRegistry",
"TOP500Collector",
"EpochAIGPUCollector",
"HuggingFaceModelCollector",
"HuggingFaceDatasetCollector",
"HuggingFaceSpacesCollector",
"PeeringDBIXPCollector",
"PeeringDBNetworkCollector",
"PeeringDBFacilityCollector",
"TeleGeographyCableCollector",
"TeleGeographyLandingPointCollector",
"TeleGeographyCableSystemCollector",
"CloudflareRadarDeviceCollector",
"CloudflareRadarTrafficCollector",
"CloudflareRadarTopASCollector",
"ArcGISCableCollector",
"FAOLandingPointCollector",
"ArcGISLandingPointCollector",
"ArcGISCableLandingRelationCollector",
"SpaceTrackTLECollector",
"CelesTrakTLECollector",
"RISLiveCollector",
"BGPStreamBackfillCollector",
"IPtoASNPrefixGeoCollector",
"OpenGeoFeedPrefixGeoCollector",
"NRODelegatedPrefixGeoCollector",
"NewsLiveStreamsCollector",
"VesselAISCollector",
"AISStreamCollector",
]

View File

@@ -0,0 +1,491 @@
"""AISStream WebSocket collector for realtime vessel AIS observations."""
from datetime import UTC, datetime
import asyncio
import json
import os
from typing import Any
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.data_sources import get_data_sources_config
from app.core.time import to_iso8601_utc
from app.core.websocket.broadcaster import broadcaster
from app.models.datasource_config import DataSourceConfig
from app.models.task import CollectionTask
from app.services.collectors.base import BaseCollector
from app.services.vessel_ais_aggregation import (
AISSTREAM_DELIVERY_MODE,
AISSTREAM_TRANSPORT,
record_vessel_ais_observation,
update_ais_source_health,
)
from app.services.vessel_types import normalize_vessel_type_name
DEFAULT_AISSTREAM_URL = "wss://stream.aisstream.io/v0/stream"
DEFAULT_BOUNDING_BOXES = [[[-90, -180], [90, 180]]]
DEFAULT_MESSAGE_TYPES = ["PositionReport", "ShipStaticData"]
class AISStreamCollector(BaseCollector):
"""Collect AISStream WebSocket messages into the raw AIS observation layer."""
name = "aisstream_vessels"
priority = "P1"
module = "L4"
frequency_hours = 1
data_type = "vessel_ais"
fail_on_empty = False
async def _load_datasource_config(self) -> DataSourceConfig | None:
if self._db_session is None:
return None
result = await self._db_session.execute(
select(DataSourceConfig)
.where(DataSourceConfig.name == self.name)
.where(DataSourceConfig.is_active.is_(True))
)
return result.scalar_one_or_none()
async def _get_effective_config(self) -> dict[str, Any]:
datasource_config = await self._load_datasource_config()
config = dict(datasource_config.config or {}) if datasource_config else {}
auth_config = dict(datasource_config.auth_config or {}) if datasource_config else {}
endpoint = (
(datasource_config.endpoint if datasource_config else None)
or self._resolved_url
or get_data_sources_config().get_yaml_url(self.name)
or DEFAULT_AISSTREAM_URL
)
api_key = (
auth_config.get("api_key")
or config.get("api_key")
or os.getenv("AISSTREAM_API_KEY")
)
return {
"endpoint": endpoint,
"api_key": api_key,
"bounding_boxes": config.get("bounding_boxes") or DEFAULT_BOUNDING_BOXES,
"message_types": config.get("message_types") or DEFAULT_MESSAGE_TYPES,
"max_messages": int(config.get("max_messages") or 500),
"streaming_enabled": config.get("streaming_enabled", True) is not False,
"streaming_commit_interval": int(config.get("streaming_commit_interval") or 1),
"streaming_max_messages": int(config.get("streaming_max_messages") or 0),
"reconnect_delay_seconds": float(config.get("reconnect_delay_seconds") or 5),
"receive_timeout_seconds": float(config.get("receive_timeout_seconds") or 30),
}
def _build_subscription(self, config: dict[str, Any]) -> dict[str, Any]:
return {
"APIKey": config["api_key"],
"BoundingBoxes": config["bounding_boxes"],
"FilterMessageTypes": config["message_types"],
}
async def fetch(self) -> list[dict[str, Any]]:
config = await self._get_effective_config()
if not config["api_key"]:
raise RuntimeError("AISStream API key is not configured")
try:
import websockets
except ImportError as exc:
raise RuntimeError("Python package 'websockets' is required for AISStream") from exc
subscription = self._build_subscription(config)
messages: list[dict[str, Any]] = []
try:
async with websockets.connect(config["endpoint"]) as websocket:
await websocket.send(json.dumps(subscription))
while len(messages) < config["max_messages"]:
try:
raw_message = await asyncio.wait_for(
websocket.recv(),
timeout=config["receive_timeout_seconds"],
)
except TimeoutError:
break
payload = json.loads(raw_message)
if isinstance(payload, dict):
messages.append(payload)
except Exception as exc:
if self._db_session is not None:
await update_ais_source_health(
self._db_session,
source=self.name,
connection_state="disconnected",
last_error=f"{exc.__class__.__name__}: {exc}",
)
await self._db_session.commit()
raise
return messages
async def run(self, db: AsyncSession) -> dict[str, Any]:
"""Run AISStream as a long-lived streaming collector by default."""
config = await self._get_effective_config()
if not config.get("streaming_enabled", True):
return await super().run(db)
if not config["api_key"]:
return {"status": "failed", "error": "AISStream API key is not configured"}
from app.services.collectors.registry import collector_registry
if not collector_registry.is_active(self.name):
return {"status": "skipped", "reason": "Collector is disabled"}
try:
import websockets
except ImportError as exc:
return {"status": "failed", "error": "Python package 'websockets' is required for AISStream"}
start_time = datetime.now(UTC)
task = CollectionTask(
datasource_id=getattr(self, "_datasource_id", 1),
status="running",
phase="connecting",
phase_message="正在连接 AISStream 实时流",
phase_unit="messages",
started_at=start_time,
)
db.add(task)
await db.commit()
self._current_task = task
self._db_session = db
self._last_broadcast_progress = None
await self.resolve_url(db)
await self._publish_task_update(force=True)
records_added = 0
messages_seen = 0
unique_mmsi: set[str] = set()
reconnect_delay = config["reconnect_delay_seconds"]
try:
while True:
config = await self._get_effective_config()
subscription = self._build_subscription(config)
try:
await update_ais_source_health(
db,
source=self.name,
connection_state="connecting",
)
await self.set_phase("connecting", message="正在连接 AISStream 实时流")
await db.commit()
async with websockets.connect(config["endpoint"]) as websocket:
await websocket.send(json.dumps(subscription))
await update_ais_source_health(
db,
source=self.name,
connection_state="connected",
last_success_at=datetime.now(UTC),
)
await self.set_phase(
"streaming",
message="正在接收 AISStream 实时消息",
reset_progress=False,
)
await db.commit()
while True:
try:
raw_message = await asyncio.wait_for(
websocket.recv(),
timeout=config["receive_timeout_seconds"],
)
except TimeoutError:
await update_ais_source_health(
db,
source=self.name,
connection_state="connected",
last_success_at=datetime.now(UTC),
)
await db.commit()
continue
payload = json.loads(raw_message)
if not isinstance(payload, dict):
continue
messages_seen += 1
record = self._normalize_message(payload)
if not record:
continue
unique_mmsi.add(str(record["mmsi"]))
created = await self._save_stream_record(db, record)
if created:
records_added += 1
task.records_processed = messages_seen
task.total_records = None
task.progress = None
task.phase = "streaming"
task.phase_message = "正在接收 AISStream 实时消息"
task.phase_current = messages_seen
task.phase_total = None
task.phase_unit = "messages"
await self._publish_task_update(force=True)
if config["streaming_max_messages"] and messages_seen >= config["streaming_max_messages"]:
task.status = "success"
task.phase = "stopped"
task.phase_message = "AISStream 测试流已停止"
task.completed_at = datetime.now(UTC)
await db.commit()
await self._publish_task_update(force=True)
return {
"status": "success",
"task_id": task.id,
"records_processed": records_added,
"messages_seen": messages_seen,
"unique_mmsi": len(unique_mmsi),
"execution_time_seconds": (datetime.now(UTC) - start_time).total_seconds(),
}
except asyncio.CancelledError:
raise
except Exception as exc:
await update_ais_source_health(
db,
source=self.name,
connection_state="reconnecting",
last_error=f"{exc.__class__.__name__}: {exc}",
)
task.phase = "reconnecting"
task.phase_message = "AISStream 连接中断,正在重连"
task.error_message = f"{exc.__class__.__name__}: {exc}"
await db.commit()
await self._publish_task_update(force=True)
await asyncio.sleep(reconnect_delay)
except asyncio.CancelledError:
task.status = "cancelled"
task.phase = "stopped"
task.phase_message = "AISStream 实时流已停止"
task.completed_at = datetime.now(UTC)
await update_ais_source_health(
db,
source=self.name,
connection_state="disconnected",
last_error=None,
)
await db.commit()
await self._publish_task_update(force=True)
raise
def transform(self, raw_data: list[dict[str, Any]]) -> list[dict[str, Any]]:
records = []
for item in raw_data:
record = self._normalize_message(item)
if record:
records.append(record)
return records
async def _save_data(
self,
db: AsyncSession,
data: list[dict[str, Any]],
task_id: int | None = None,
snapshot_id: int | None = None,
) -> int:
now = datetime.now(UTC)
records_added = 0
latest_observed_at = now
for index, item in enumerate(data):
observed_at = item.get("received_at") or now
observation = await record_vessel_ais_observation(
db,
source=self.name,
normalized_payload=item,
raw_payload=item.get("_raw_payload") or item,
delivery_mode=AISSTREAM_DELIVERY_MODE,
transport=AISSTREAM_TRANSPORT,
message_type=item.get("_message_type") or "PositionReport",
source_message_id=item.get("_source_message_id"),
observed_at=observed_at,
collected_at=now,
)
if observation is not None:
records_added += 1
if isinstance(observed_at, datetime) and observed_at > latest_observed_at:
latest_observed_at = observed_at
if (index + 1) % 1000 == 0:
await self.update_progress(index + 1, commit=True)
await update_ais_source_health(
db,
source=self.name,
connection_state="connected",
observed_count=len(data),
last_seen_at=latest_observed_at,
last_success_at=now if data else None,
lag_seconds=max((now - latest_observed_at).total_seconds(), 0),
)
await db.commit()
await self.update_progress(records_added, force=True)
return records_added
async def _save_stream_record(self, db: AsyncSession, item: dict[str, Any]) -> bool:
now = datetime.now(UTC)
observed_at = item.get("received_at") or now
observation = await record_vessel_ais_observation(
db,
source=self.name,
normalized_payload=item,
raw_payload=item.get("_raw_payload") or item,
delivery_mode=AISSTREAM_DELIVERY_MODE,
transport=AISSTREAM_TRANSPORT,
message_type=item.get("_message_type") or "PositionReport",
source_message_id=item.get("_source_message_id"),
observed_at=observed_at,
collected_at=now,
)
await update_ais_source_health(
db,
source=self.name,
connection_state="connected",
observed_count=1,
last_seen_at=observed_at if isinstance(observed_at, datetime) else now,
last_success_at=now,
lag_seconds=max((now - observed_at).total_seconds(), 0) if isinstance(observed_at, datetime) else None,
)
await db.commit()
await self._broadcast_vessel_delta(item, created=observation is not None)
return observation is not None
async def _broadcast_vessel_delta(self, item: dict[str, Any], *, created: bool) -> None:
await broadcaster.broadcast_custom(
"vessels",
{
"action": "upsert",
"source": self.name,
"created": created,
"vessels": [
{
"mmsi": item.get("mmsi"),
"mmsi_display": str(item.get("mmsi")) if item.get("mmsi") is not None else None,
"name": item.get("name"),
"lat": item.get("lat"),
"lon": item.get("lon"),
"sog": item.get("sog"),
"cog": item.get("cog"),
"heading": item.get("heading"),
"nav_status": item.get("nav_status"),
"vessel_type": item.get("vessel_type"),
"vessel_type_name": item.get("vessel_type_name"),
"received_at": to_iso8601_utc(item.get("received_at")),
}
],
},
)
def _normalize_message(self, item: dict[str, Any]) -> dict[str, Any] | None:
message_type = str(item.get("MessageType") or item.get("message_type") or "")
metadata = item.get("MetaData") if isinstance(item.get("MetaData"), dict) else {}
message = item.get("Message") if isinstance(item.get("Message"), dict) else {}
body = message.get(message_type) if isinstance(message.get(message_type), dict) else message
if not isinstance(body, dict):
body = {}
mmsi = _as_int(_pick(metadata, "MMSI", "mmsi") or _pick(body, "MMSI", "mmsi"))
if mmsi is None:
return None
received_at = _parse_datetime(
_pick(metadata, "time_utc", "Time_UTC", "timestamp")
or _pick(body, "Timestamp", "timestamp", "time")
)
ship_name = _clean_text(
_pick(body, "Name", "ShipName", "name")
or _pick(metadata, "ShipName", "ship_name", "name")
)
record: dict[str, Any] = {
"mmsi": mmsi,
"received_at": received_at,
"_message_type": message_type or None,
"_source_message_id": item.get("MessageID") or item.get("message_id"),
"_raw_payload": item,
}
lat = _as_float(_pick(body, "Latitude", "lat", "latitude"))
lon = _as_float(_pick(body, "Longitude", "lon", "lng", "longitude"))
if lat is not None and lon is not None:
if not (-90 <= lat <= 90 and -180 <= lon <= 180):
return None
record.update(
{
"lat": lat,
"lon": lon,
"sog": _as_float(_pick(body, "Sog", "SOG", "speedOverGround")),
"cog": _as_float(_pick(body, "Cog", "COG", "courseOverGround")),
"heading": _as_int(_pick(body, "TrueHeading", "Heading", "heading")),
"nav_status": _as_int(_pick(body, "NavigationalStatus", "nav_status")),
}
)
vessel_type = _as_int(_pick(body, "Type", "ShipType", "vessel_type"))
record.update(
{
"name": ship_name,
"callsign": _pick(body, "CallSign", "callsign"),
"imo": _as_int(_pick(body, "ImoNumber", "IMO", "imo")),
"vessel_type": vessel_type,
"vessel_type_name": _pick(body, "TypeName", "ShipTypeName", "vessel_type_name")
or normalize_vessel_type_name(vessel_type),
"length": _as_float(_pick(body, "DimensionToBow", "Length", "length")),
"width": _as_float(_pick(body, "DimensionToPort", "Width", "width")),
}
)
return record
def _pick(item: dict[str, Any], *keys: str) -> Any:
for key in keys:
if key in item and item[key] not in (None, ""):
return item[key]
return None
def _clean_text(value: Any) -> str | None:
if value in (None, ""):
return None
text = str(value).strip()
return text or None
def _as_float(value: Any) -> float | None:
try:
if value in (None, ""):
return None
return float(value)
except (TypeError, ValueError):
return None
def _as_int(value: Any) -> int | None:
try:
if value in (None, ""):
return None
return int(float(value))
except (TypeError, ValueError):
return None
def _parse_datetime(value: Any) -> datetime | None:
if isinstance(value, datetime):
return value if value.tzinfo else value.replace(tzinfo=UTC)
if not value:
return None
if isinstance(value, (int, float)):
timestamp = float(value)
if timestamp > 10_000_000_000:
timestamp /= 1000
return datetime.fromtimestamp(timestamp, UTC)
if isinstance(value, str):
try:
parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
return parsed if parsed.tzinfo else parsed.replace(tzinfo=UTC)
except ValueError:
return None
return None

View File

@@ -54,6 +54,11 @@ class BaseCollector(ABC):
"task_id": self._current_task.id,
"status": self._current_task.status,
"phase": self._current_task.phase,
"phase_progress": self._current_task.phase_progress,
"phase_message": self._current_task.phase_message,
"phase_current": self._current_task.phase_current,
"phase_total": self._current_task.phase_total,
"phase_unit": self._current_task.phase_unit,
"progress": progress,
"records_processed": self._current_task.records_processed,
"total_records": self._current_task.total_records,
@@ -80,12 +85,52 @@ class BaseCollector(ABC):
await self._publish_task_update(force=force)
async def set_phase(self, phase: str):
async def set_phase(self, phase: str, *, message: str | None = None, reset_progress: bool = True):
if self._current_task and self._db_session:
self._current_task.phase = phase
self._current_task.phase_message = message
if reset_progress:
self._current_task.phase_progress = None
self._current_task.phase_current = None
self._current_task.phase_total = None
self._current_task.phase_unit = None
await self._db_session.commit()
await self._publish_task_update(force=True)
async def update_phase_progress(
self,
*,
current: int | None = None,
total: int | None = None,
unit: str | None = None,
message: str | None = None,
progress: float | None = None,
commit: bool = False,
force: bool = False,
):
"""Update progress for the current phase without changing task totals."""
if not self._current_task or not self._db_session:
return
if progress is None and current is not None and total and total > 0:
progress = (current / total) * 100
if progress is not None:
self._current_task.phase_progress = max(0.0, min(float(progress), 100.0))
if current is not None:
self._current_task.phase_current = max(0, int(current))
if total is not None:
self._current_task.phase_total = max(0, int(total))
if unit is not None:
self._current_task.phase_unit = unit
if message is not None:
self._current_task.phase_message = message
if commit:
await self._db_session.commit()
await self._publish_task_update(force=force)
@abstractmethod
async def fetch(self) -> List[Dict[str, Any]]:
"""Fetch raw data from source"""
@@ -251,7 +296,7 @@ class BaseCollector(ABC):
await self._publish_task_update(force=True)
try:
await self.set_phase("fetching")
await self.set_phase("fetching", message="正在拉取原始数据")
raw_data = await self.fetch()
task.total_records = len(raw_data)
await db.commit()
@@ -260,15 +305,20 @@ class BaseCollector(ABC):
if self.fail_on_empty and not raw_data:
raise RuntimeError(f"Collector {self.name} returned no data")
await self.set_phase("transforming")
await self.set_phase("transforming", message="正在转换采集数据")
data = self.transform(raw_data)
snapshot_id = await self._create_snapshot(db, task_id, data, start_time)
await self.set_phase("saving")
await self.set_phase("saving", message="正在保存采集数据")
records_count = await self._save_data(db, data, task_id=task_id, snapshot_id=snapshot_id)
task.status = "success"
task.phase = "completed"
task.phase_progress = 100.0
task.phase_message = "采集完成"
task.phase_current = records_count
task.phase_total = records_count
task.phase_unit = "records"
task.records_processed = records_count
task.progress = 100.0
task.completed_at = datetime.now(UTC)
@@ -285,6 +335,7 @@ class BaseCollector(ABC):
await db.rollback()
task.status = "cancelled"
task.phase = "cancelled"
task.phase_message = "采集已取消"
task.error_message = "Collection cancelled by operator and rolled back"
task.completed_at = datetime.now(UTC)
if snapshot_id is not None:
@@ -301,6 +352,7 @@ class BaseCollector(ABC):
await db.rollback()
task.status = "failed"
task.phase = "failed"
task.phase_message = str(e)
task.error_message = str(e)
task.completed_at = datetime.now(UTC)
if snapshot_id is not None:

View File

@@ -108,6 +108,11 @@ class IPtoASNPrefixGeoCollector(BaseCollector):
self._current_task.total_records = total_expected
self._current_task.records_processed = 0
self._current_task.progress = 0.0
self._current_task.phase_progress = 0.0
self._current_task.phase_message = "正在下载 IPtoASN 数据"
self._current_task.phase_current = 0
self._current_task.phase_total = total_expected
self._current_task.phase_unit = "bytes"
await self._db_session.commit()
await self._publish_task_update(force=True)
@@ -135,7 +140,14 @@ class IPtoASNPrefixGeoCollector(BaseCollector):
return
last_emit["value"] = aggregated
last_emit["t"] = now
await self.update_progress(min(aggregated, total_expected), commit=True)
current = min(aggregated, total_expected)
await self.update_phase_progress(
current=current,
total=total_expected,
unit="bytes",
message="正在下载 IPtoASN 数据",
)
await self.update_progress(current, commit=True)
batches = await asyncio.gather(
*(
@@ -148,6 +160,12 @@ class IPtoASNPrefixGeoCollector(BaseCollector):
)
)
if total_expected > 0:
await self.update_phase_progress(
current=total_expected,
total=total_expected,
unit="bytes",
message="IPtoASN 数据下载完成",
)
await self.update_progress(total_expected, commit=True, force=True)
rows: list[dict[str, Any]] = []

View File

@@ -39,12 +39,23 @@ class NRODelegatedPrefixGeoCollector(BaseCollector):
self._current_task.total_records = total_expected
self._current_task.records_processed = 0
self._current_task.progress = 0.0
self._current_task.phase_progress = 0.0
self._current_task.phase_message = "正在下载 NRO delegated 数据"
self._current_task.phase_current = 0
self._current_task.phase_total = total_expected
self._current_task.phase_unit = "bytes"
await self._db_session.commit()
await self._publish_task_update(force=True)
async def on_progress(downloaded: int, total: int | None) -> None:
if not total or total <= 0:
return
await self.update_phase_progress(
current=min(downloaded, total),
total=total,
unit="bytes",
message="正在下载 NRO delegated 数据",
)
await self.update_progress(min(downloaded, total), commit=True)
body_path = await self._downloader.download_file(

View File

@@ -40,12 +40,23 @@ class OpenGeoFeedPrefixGeoCollector(BaseCollector):
self._current_task.total_records = total_expected
self._current_task.records_processed = 0
self._current_task.progress = 0.0
self._current_task.phase_progress = 0.0
self._current_task.phase_message = "正在下载 OpenGeoFeed 数据"
self._current_task.phase_current = 0
self._current_task.phase_total = total_expected
self._current_task.phase_unit = "bytes"
await self._db_session.commit()
await self._publish_task_update(force=True)
async def on_progress(downloaded: int, total: int | None) -> None:
if not total or total <= 0:
return
await self.update_phase_progress(
current=min(downloaded, total),
total=total,
unit="bytes",
message="正在下载 OpenGeoFeed 数据",
)
await self.update_progress(min(downloaded, total), commit=True)
body_path = await self._downloader.download_file(

View File

@@ -0,0 +1,279 @@
"""BarentsWatch AIS collector for vessel tracking."""
from datetime import UTC, datetime
from typing import Any
import httpx
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.time import to_iso8601_utc
from app.core.websocket.broadcaster import broadcaster
from app.services.barentswatch import (
BARENTSWATCH_LATEST_URL,
fetch_barentswatch_access_token,
resolve_barentswatch_config,
)
from app.services.collectors.base import BaseCollector
from app.services.vessel_ais_aggregation import (
BARENTSWATCH_DELIVERY_MODE,
BARENTSWATCH_TRANSPORT,
record_vessel_ais_observation,
update_ais_source_health,
)
from app.services.vessel_types import normalize_vessel_type_name
class VesselAISCollector(BaseCollector):
"""Collect latest AIS positions and append them to vessel tables."""
name = "barentswatch_vessels"
priority = "P1"
module = "L4"
frequency_hours = 1
data_type = "vessel_ais"
@property
def base_url(self) -> str:
return self._resolved_url or BARENTSWATCH_LATEST_URL
async def _get_access_token(self, client: httpx.AsyncClient) -> str | None:
config = await resolve_barentswatch_config(self._db_session)
return await fetch_barentswatch_access_token(client, config)
async def fetch(self) -> list[dict[str, Any]]:
async with httpx.AsyncClient(timeout=60.0) as client:
headers: dict[str, str] = {}
token = await self._get_access_token(client)
if token:
headers["Authorization"] = f"Bearer {token}"
response = await client.get(self.base_url, headers=headers)
if response.status_code == 401 and not token:
return self._get_sample_data()
response.raise_for_status()
payload = response.json()
if isinstance(payload, list):
return [item for item in payload if isinstance(item, dict)]
if isinstance(payload, dict):
for key in ("features", "data", "items", "vessels"):
value = payload.get(key)
if isinstance(value, list):
if key == "features":
return [
{
**(item.get("properties") or {}),
"geometry": item.get("geometry"),
}
for item in value
if isinstance(item, dict)
]
return [item for item in value if isinstance(item, dict)]
return self._get_sample_data()
def transform(self, raw_data: list[dict[str, Any]]) -> list[dict[str, Any]]:
transformed = []
for item in raw_data:
record = self._normalize_record(item)
if record:
transformed.append(record)
return transformed
async def _save_data(
self,
db: AsyncSession,
data: list[dict[str, Any]],
task_id: int | None = None,
snapshot_id: int | None = None,
) -> int:
now = datetime.now(UTC)
records_added = 0
for index, item in enumerate(data):
observed_at = item.get("received_at") or now
await record_vessel_ais_observation(
db,
source=self.name,
normalized_payload=item,
raw_payload=item,
delivery_mode=BARENTSWATCH_DELIVERY_MODE,
transport=BARENTSWATCH_TRANSPORT,
observed_at=observed_at,
collected_at=now,
)
records_added += 1
if (index + 1) % 1000 == 0:
await self.update_progress(index + 1, commit=True)
latest_observed_at = max(
(item.get("received_at") for item in data if item.get("received_at")),
default=now,
)
await update_ais_source_health(
db,
source=self.name,
connection_state="connected",
observed_count=len(data),
last_seen_at=latest_observed_at,
last_success_at=now if data else None,
lag_seconds=max((now - latest_observed_at).total_seconds(), 0),
)
await db.commit()
await self._broadcast_vessel_snapshot(data)
await self.update_progress(records_added, force=True)
return records_added
async def _broadcast_vessel_snapshot(self, data: list[dict[str, Any]]) -> None:
"""Push REST collector updates through the same realtime vessel channel."""
if not data:
return
batch_size = 500
for offset in range(0, len(data), batch_size):
batch = data[offset : offset + batch_size]
await broadcaster.broadcast_custom(
"vessels",
{
"action": "upsert",
"source": self.name,
"created": True,
"vessels": [
{
"mmsi": item.get("mmsi"),
"mmsi_display": str(item.get("mmsi")) if item.get("mmsi") is not None else None,
"name": item.get("name"),
"callsign": item.get("callsign"),
"lat": item.get("lat"),
"lon": item.get("lon"),
"sog": item.get("sog"),
"cog": item.get("cog"),
"heading": item.get("heading"),
"nav_status": item.get("nav_status"),
"vessel_type": item.get("vessel_type"),
"vessel_type_name": item.get("vessel_type_name"),
"received_at": to_iso8601_utc(item.get("received_at")),
}
for item in batch
],
},
)
def _normalize_record(self, item: dict[str, Any]) -> dict[str, Any] | None:
mmsi = _as_int(_pick(item, "mmsi", "MMSI", "Mmsi"))
lat = _as_float(_pick(item, "lat", "latitude", "Latitude"))
lon = _as_float(_pick(item, "lon", "lng", "longitude", "Longitude"))
geometry = item.get("geometry")
coordinates = geometry.get("coordinates") if isinstance(geometry, dict) else None
if (lat is None or lon is None) and isinstance(coordinates, list) and len(coordinates) >= 2:
lon = _as_float(coordinates[0])
lat = _as_float(coordinates[1])
if mmsi is None or lat is None or lon is None:
return None
if not (-90 <= lat <= 90 and -180 <= lon <= 180):
return None
vessel_type = _as_int(_pick(item, "vessel_type", "shipType", "ship_type", "ShipType"))
vessel_type_name = (
_pick(item, "vessel_type_name", "shipTypeName", "ship_type_name", "VesselTypeName")
or normalize_vessel_type_name(vessel_type)
)
received_at = _parse_datetime(_pick(item, "received_at", "timestamp", "time", "msgtime"))
return {
"mmsi": mmsi,
"name": _pick(item, "name", "shipName", "ship_name", "Name"),
"callsign": _pick(item, "callsign", "callSign", "CallSign"),
"vessel_type": vessel_type,
"vessel_type_name": vessel_type_name,
"flag": _pick(item, "flag", "country", "Flag"),
"length": _as_float(_pick(item, "length", "shipLength", "Length")),
"width": _as_float(_pick(item, "width", "shipWidth", "Width")),
"draught": _as_float(_pick(item, "draught", "draft", "Draught")),
"imo": _as_int(_pick(item, "imo", "IMO", "imoNumber")),
"lat": lat,
"lon": lon,
"sog": _as_float(_pick(item, "sog", "speedOverGround", "SOG")),
"cog": _as_float(_pick(item, "cog", "courseOverGround", "COG")),
"heading": _as_int(_pick(item, "heading", "trueHeading", "Heading")),
"nav_status": _as_int(_pick(item, "nav_status", "navStatus", "NavigationalStatus")),
"received_at": received_at,
}
def _get_sample_data(self) -> list[dict[str, Any]]:
return [
{
"mmsi": 257123000,
"name": "OSLO TRADER",
"lat": 59.91,
"lon": 10.73,
"sog": 12.4,
"cog": 214,
"heading": 215,
"nav_status": 0,
"vessel_type": 70,
"vessel_type_name": "Cargo",
"flag": "NO",
"length": 185,
},
{
"mmsi": 257456000,
"name": "NORDIC FJORD",
"lat": 60.39,
"lon": 5.32,
"sog": 0.2,
"cog": 82,
"heading": 80,
"nav_status": 1,
"vessel_type": 60,
"vessel_type_name": "Passenger",
"flag": "NO",
"length": 126,
},
]
def _pick(item: dict[str, Any], *keys: str) -> Any:
for key in keys:
if key in item and item[key] not in (None, ""):
return item[key]
return None
def _as_float(value: Any) -> float | None:
try:
if value in (None, ""):
return None
return float(value)
except (TypeError, ValueError):
return None
def _as_int(value: Any) -> int | None:
try:
if value in (None, ""):
return None
return int(float(value))
except (TypeError, ValueError):
return None
def _parse_datetime(value: Any) -> datetime | None:
if isinstance(value, datetime):
return value if value.tzinfo else value.replace(tzinfo=UTC)
if not value:
return None
if isinstance(value, (int, float)):
timestamp = float(value)
if timestamp > 10_000_000_000:
timestamp /= 1000
return datetime.fromtimestamp(timestamp, UTC)
if isinstance(value, str):
try:
parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
return parsed if parsed.tzinfo else parsed.replace(tzinfo=UTC)
except ValueError:
return None
return None

View File

@@ -0,0 +1,224 @@
"""Credential setup guides for collector integrations."""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any
from sqlalchemy import select
from app.models.system_setting import SystemSetting
from app.schemas.ai import SituationalAnalysisRequest
from app.services.ai_client import AIProviderClient
CREDENTIAL_GUIDES_CATEGORY = "collector_credential_guides"
@dataclass(frozen=True)
class CredentialGuideDefault:
provider: str
title: str
prompt: str
markdown: str
BARENTSWATCH_DEFAULT_GUIDE = CredentialGuideDefault(
provider="barentswatch",
title="BarentsWatch AIS 凭证获取教程",
prompt=(
"请生成一份中文教程,指导开发者获取 BarentsWatch Live AIS API 的 "
"OAuth client credentials。教程要面向已经有本地开发环境的人包含注册/登录、"
"创建 client、申请或确认 ais scope、复制 client id 和 client secret、"
"在系统设置中填写并验证连接、常见失败排查。不要编造具体页面按钮文案,"
"必须参考官方 tutorialhttps://developer.barentswatch.no/docs/tutorial 。"
"必须强调 Live AIS 要选择 AIS-client / AIS - API而不是普通 API-client。"
"如果步骤可能变化,要提醒以 BarentsWatch developer portal 当前页面为准。"
),
markdown="""## BarentsWatch AIS 凭证获取
官方教程https://developer.barentswatch.no/docs/tutorial
1. 先打开上面的 BarentsWatch 官方 tutorial按官方流程登录或注册开发者账号。
2. 在 Developer access 页面选择 `AIS - API`,不要选择普通的 `BarentsWatch - API`。
3. 在 `AIS - API` 下创建用于 Planet 的 AIS client。
4. 创建时记下你设置的 password / client secret。
5. 回到 My Page 复制完整 `Client ID`。它通常长得像 `your.email@example.com:client-name`。
6. 回到 Planet 的 `设置 -> 采集器设置 -> BarentsWatch AIS`,填入 `Client ID` 和 `Client Secret`。
7. 点击 `连接` 验证 token 和 AIS endpoint 是否可访问。
8. 连接成功后保存凭证。
### 请求规则
- Token 地址:`https://id.barentswatch.no/connect/token`
- 请求方式:`POST`
- Content-Type`application/x-www-form-urlencoded`
- Body 必须包含:`grant_type=client_credentials`、`client_id`、`client_secret`、`scope=ais`
- `client_id`、`client_secret`、`scope`、`grant_type` 都要放在 body不要放在 header。
- AIS 数据请求使用 header`Authorization: Bearer <access_token>`
### 常见排查
- `未找到凭证`:确认 `Client ID` 和 `Client Secret` 已填写,或已经写入 `~/.zshrc`。
- `HTTP 401/403`:通常是选成了普通 `BarentsWatch - API` client、client secret 错误,或 token 请求没有使用 `scope=ais`。
- `network` 错误:检查本机是否能访问 `id.barentswatch.no` 和 `live.ais.barentswatch.no`。
- Endpoint 建议保持默认:`https://live.ais.barentswatch.no/v1/latest/combined`。
""",
)
AISSTREAM_DEFAULT_GUIDE = CredentialGuideDefault(
provider="aisstream",
title="AISStream API Key 获取教程",
prompt=(
"请生成一份中文教程,指导开发者获取 AISStream 的 API Key 并配置到 Planet。"
"教程要面向已经有本地开发环境的人,包含注册/登录 AISStream、获取 API Key、"
"理解免费额度和订阅范围、在 Planet 设置中心填写 API Key、配置 bounding boxes "
"和 message types、验证连接、常见失败排查。必须提醒用户以 AISStream 当前官网和"
"服务条款为准,不要编造具体页面按钮文案。"
),
markdown="""## AISStream API Key 获取
官方入口https://aisstream.io/
1. 打开 AISStream 官网,按当前页面指引注册或登录账号。
2. 在账号/API 管理页面创建或复制你的 API Key。
3. 先确认当前账号额度、使用条款和可订阅区域。实时 AIS 流量可能很大,不建议一开始订阅全球范围。
4. 回到 Planet 的 `设置 -> 采集器设置 -> AISStream 实时船舶`。
5. 在 `AISStream 凭证` 中填入 API Key。
6. Endpoint 通常保持默认:`wss://stream.aisstream.io/v0/stream`。
7. 按需配置 `Bounding Boxes JSON` 和 `消息类型`。
8. 点击连接测试,确认系统能读取凭证且 WebSocket endpoint 格式有效。
9. 保存采集器设置后再运行 `aisstream_vessels` collector。
### 推荐配置
默认消息类型:
```json
["PositionReport", "ShipStaticData"]
```
默认 Bounding Boxes 示例:
```json
[[[-90, -180], [90, 180]]]
```
这个示例表示全球范围。实际使用时建议先改成较小区域,降低消息量和处理压力。
### 请求规则
- Endpoint`wss://stream.aisstream.io/v0/stream`
- 传输方式WebSocket
- API Key 放在订阅 payload 中,不放在 HTTP header。
- Planet 会把 AISStream 标记为 `delivery_mode = realtime_stream`、`transport = websocket`。
- AISStream collector 只写入 AIS raw observations不直接覆盖最终船只展示表。
### 常见排查
- `未找到凭证`:确认 API Key 已保存到采集器设置,或设置了 `AISSTREAM_API_KEY` 环境变量 / `~/.zshrc`。
- `endpoint 必须是 ws:// 或 wss://`AISStream 是 WebSocket 流接口,不要填普通 `https://` API 地址。
- 采集量过大:缩小 `Bounding Boxes JSON`,减少 `message_types`,或降低单次最大消息数。
- 没有船只数据:确认订阅区域内确实有 AIS 活动,并检查 API Key 当前额度和权限。
- 连接中断实时流可能受网络和上游限流影响collector 会记录源健康状态供聚合服务回退。
""",
)
DEFAULT_CREDENTIAL_GUIDES = {
BARENTSWATCH_DEFAULT_GUIDE.provider: BARENTSWATCH_DEFAULT_GUIDE,
AISSTREAM_DEFAULT_GUIDE.provider: AISSTREAM_DEFAULT_GUIDE,
}
async def _get_guide_store(db) -> tuple[SystemSetting | None, dict[str, Any]]:
result = await db.execute(
select(SystemSetting).where(SystemSetting.category == CREDENTIAL_GUIDES_CATEGORY)
)
record = result.scalar_one_or_none()
payload = dict(record.payload or {}) if record and isinstance(record.payload, dict) else {}
return record, payload
async def get_credential_guide(db, provider: str) -> dict[str, Any]:
default = DEFAULT_CREDENTIAL_GUIDES.get(provider)
if default is None:
raise ValueError(f"Unsupported credential guide provider: {provider}")
_record, store = await _get_guide_store(db)
custom = store.get(provider) if isinstance(store.get(provider), dict) else None
return {
"provider": provider,
"title": custom.get("title") if custom else default.title,
"markdown": custom.get("markdown") if custom else default.markdown,
"prompt": default.prompt,
"source": "ai" if custom else "default",
}
async def save_credential_guide(db, provider: str, title: str, markdown: str) -> dict[str, Any]:
default = DEFAULT_CREDENTIAL_GUIDES.get(provider)
if default is None:
raise ValueError(f"Unsupported credential guide provider: {provider}")
record, store = await _get_guide_store(db)
store[provider] = {
"title": title or default.title,
"markdown": markdown,
}
if record is None:
db.add(SystemSetting(category=CREDENTIAL_GUIDES_CATEGORY, payload=store))
else:
record.payload = store
await db.commit()
return await get_credential_guide(db, provider)
async def reset_credential_guide(db, provider: str) -> dict[str, Any]:
default = DEFAULT_CREDENTIAL_GUIDES.get(provider)
if default is None:
raise ValueError(f"Unsupported credential guide provider: {provider}")
record, store = await _get_guide_store(db)
if provider in store:
store.pop(provider, None)
if record is not None:
record.payload = store
await db.commit()
return await get_credential_guide(db, provider)
async def generate_credential_guide(
db,
provider: str,
ai_client: AIProviderClient,
) -> dict[str, Any]:
default = DEFAULT_CREDENTIAL_GUIDES.get(provider)
if default is None:
raise ValueError(f"Unsupported credential guide provider: {provider}")
response = await ai_client.analyze(
SituationalAnalysisRequest(
title=f"Generate credential guide for {provider}",
objective=default.prompt,
context={
"provider": provider,
"current_default_guide": default.markdown,
"product_context": "Planet collector credential settings",
},
observations=[
"Use concise Chinese markdown.",
"Prefer stable concepts over brittle UI labels.",
"Include verification and troubleshooting steps.",
],
constraints=[
"Do not ask the user for secrets.",
"Do not include fabricated screenshots.",
"Return markdown only.",
],
)
)
markdown = response.content.strip()
if not markdown:
markdown = default.markdown
return await save_credential_guide(db, provider, default.title, markdown)

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"""Runtime helpers for mapped custom data sources."""
from __future__ import annotations
import asyncio
import base64
import json
from datetime import UTC, datetime
from typing import Any
import httpx
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.target_schema_registry import TARGET_SCHEMAS
from app.db.session import async_session_factory
from app.models.datasource_config import DataSourceConfig
from app.models.datasource_mapping import DataSourceMappingTemplate
from app.services.datasource_mapping import (
MappingError,
execute_mapping,
extract_path,
persist_mapped_records,
)
DEFAULT_MAPPING_TEMPLATES: dict[str, dict[str, Any]] = {
"vessel_ais": {
"source": {"items_path": "$"},
"fields": {
"mmsi": {"path": "$.mmsi", "type": "integer"},
"name": {"path": "$.name", "type": "string", "default": None},
"lat": {"path": "$.lat", "type": "float"},
"lon": {"path": "$.lon", "type": "float"},
"sog": {"path": "$.sog", "type": "float", "default": None},
"cog": {"path": "$.cog", "type": "float", "default": None},
"heading": {"path": "$.heading", "type": "integer", "default": None},
"nav_status": {"path": "$.nav_status", "type": "integer", "default": None},
"callsign": {"path": "$.callsign", "type": "string", "default": None},
"vessel_type": {"path": "$.vessel_type", "type": "string", "default": None},
"vessel_type_name": {"path": "$.vessel_type_name", "type": "string", "default": None},
"received_at": {"path": "$.received_at", "type": "datetime", "default": None},
},
"meta": {"generated_by": "default_template", "requires_review": False},
},
}
RUNNING_CUSTOM_STREAM_TASKS: dict[int, asyncio.Task[Any]] = {}
class CustomDatasourceRuntimeError(RuntimeError):
"""Raised when a custom datasource cannot run."""
def build_request_headers(auth_type: str, auth_config: dict, headers: dict) -> dict[str, str]:
request_headers = {str(key): str(value) for key, value in (headers or {}).items()}
auth_type = str(auth_type or "none").lower()
auth_config = auth_config or {}
if auth_type == "bearer" and auth_config.get("token"):
request_headers["Authorization"] = f"Bearer {auth_config['token']}"
elif auth_type == "api_key" and auth_config.get("api_key"):
location = str(auth_config.get("in") or auth_config.get("location") or "header").lower()
if location != "query":
key_name = auth_config.get("key_name", "X-API-Key")
request_headers[str(key_name)] = str(auth_config["api_key"])
elif auth_type == "basic":
username = auth_config.get("username", "")
password = auth_config.get("password", "")
credentials = f"{username}:{password}"
encoded = base64.b64encode(credentials.encode()).decode()
request_headers["Authorization"] = f"Basic {encoded}"
return request_headers
def build_query_params(auth_type: str, auth_config: dict, config: dict) -> dict[str, Any]:
params: dict[str, Any] = {}
candidate = (config or {}).get("params") or (config or {}).get("query_params")
if isinstance(candidate, dict):
params.update(candidate)
auth_type = str(auth_type or "none").lower()
auth_config = auth_config or {}
if auth_type == "api_key" and auth_config.get("api_key"):
location = str(auth_config.get("in") or auth_config.get("location") or "header").lower()
if location == "query":
key_name = auth_config.get("key_name") or auth_config.get("param_name") or "api_key"
params[str(key_name)] = auth_config["api_key"]
return params
async def load_active_mapping(
db: AsyncSession,
datasource_config_id: int,
) -> DataSourceMappingTemplate:
result = await db.execute(
select(DataSourceMappingTemplate)
.where(DataSourceMappingTemplate.datasource_config_id == datasource_config_id)
.where(DataSourceMappingTemplate.is_active.is_(True))
.order_by(DataSourceMappingTemplate.version.desc())
.limit(1)
)
mapping = result.scalar_one_or_none()
if mapping is not None:
return mapping
datasource = await db.get(DataSourceConfig, datasource_config_id)
if datasource is None:
raise CustomDatasourceRuntimeError("Configuration not found")
target_schema = (datasource.config or {}).get("target_schema")
template_body = DEFAULT_MAPPING_TEMPLATES.get(str(target_schema or "")) if target_schema else None
if not template_body or target_schema not in TARGET_SCHEMAS:
raise CustomDatasourceRuntimeError(
"No active mapping template found and no default template available for this target schema"
)
mapping = DataSourceMappingTemplate(
datasource_config_id=datasource_config_id,
target_schema=str(target_schema),
mapping_json=template_body,
sample_payload_hash=None,
validation_status="valid",
version=1,
is_active=True,
)
db.add(mapping)
await db.commit()
await db.refresh(mapping)
return mapping
async def fetch_rest_payload(config: DataSourceConfig, limit_bytes: int) -> Any:
request_config = config.config or {}
method = str(request_config.get("method") or request_config.get("request_method") or "GET").upper()
if method not in {"GET", "POST"}:
raise CustomDatasourceRuntimeError("Only GET and POST sample requests are supported.")
headers = build_request_headers(config.auth_type, config.auth_config or {}, config.headers or {})
params = build_query_params(config.auth_type, config.auth_config or {}, request_config)
timeout = float(request_config.get("timeout", 30))
json_body = request_config.get("json_body")
if json_body is None and str(request_config.get("body_type") or "").lower() in {"json", ""}:
candidate = request_config.get("body")
if isinstance(candidate, (dict, list)):
json_body = candidate
async with httpx.AsyncClient(timeout=timeout, follow_redirects=True) as client:
response = await client.request(
method,
config.endpoint,
headers=headers,
params=params or None,
json=json_body,
)
response.raise_for_status()
content = response.content[:limit_bytes]
if "application/json" in response.headers.get("content-type", ""):
return json.loads(content.decode(response.encoding or "utf-8"))
return {"text": content.decode(response.encoding or "utf-8", errors="replace")}
async def run_mapped_rest_config(
db: AsyncSession,
datasource: DataSourceConfig,
) -> dict[str, Any]:
mapping = await load_active_mapping(db, datasource.id)
sample = await fetch_rest_payload(datasource, 5_000_000)
mapped = execute_mapping(sample, mapping.mapping_json, mapping.target_schema)
if mapped["failed_count"] > 0:
return {
"status": "failed",
"datasource_config_id": datasource.id,
"mapping_id": mapping.id,
"mapping_version": mapping.version,
"target_schema": mapping.target_schema,
"mapped_count": mapped["mapped_count"],
"failed_count": mapped["failed_count"],
"errors": mapped["errors"][:20],
}
request_config = datasource.config or {}
written_count = await persist_mapped_records(
db,
datasource_name=datasource.name,
datasource_config_id=datasource.id,
target_schema=mapping.target_schema,
records=mapped["records"],
mapping_version=mapping.version,
delivery_mode=request_config.get("delivery_mode") or "polling",
transport="http",
)
return {
"status": "success",
"datasource_config_id": datasource.id,
"mapping_id": mapping.id,
"mapping_version": mapping.version,
"target_schema": mapping.target_schema,
"fetched_count": mapped["total_items"],
"mapped_count": mapped["mapped_count"],
"written_count": written_count,
}
def _items_from_ws_message(payload: Any, config: dict) -> Any:
message_path = config.get("ws_message_path")
items_path = config.get("ws_items_path")
value = extract_path(payload, message_path) if message_path else payload
return extract_path(value, items_path) if items_path else value
async def _connect_websocket(endpoint: str, headers: dict[str, str]):
import websockets
try:
return await websockets.connect(endpoint, additional_headers=headers or None)
except TypeError:
return await websockets.connect(endpoint, extra_headers=headers or None)
async def test_websocket_config(config: DataSourceConfig) -> dict[str, Any]:
if not str(config.endpoint or "").startswith(("ws://", "wss://")):
raise CustomDatasourceRuntimeError("WebSocket datasource endpoint must start with ws:// or wss://")
runtime_config = config.config or {}
headers = build_request_headers(config.auth_type, config.auth_config or {}, config.headers or {})
receive_timeout = float(runtime_config.get("receive_timeout_seconds") or runtime_config.get("timeout") or 10)
async with await _connect_websocket(config.endpoint, headers) as websocket:
subscribe_message = runtime_config.get("ws_subscribe_message")
if isinstance(subscribe_message, (dict, list)):
await websocket.send(json.dumps(subscribe_message))
elif isinstance(subscribe_message, str) and subscribe_message.strip():
await websocket.send(subscribe_message)
raw_message = await asyncio.wait_for(websocket.recv(), timeout=receive_timeout)
return {
"success": True,
"message_preview": raw_message[:1000] if isinstance(raw_message, str) else str(raw_message)[:1000],
}
async def run_mapped_websocket_config(
db: AsyncSession,
datasource: DataSourceConfig,
*,
debug_max_messages: int | None = None,
use_config_debug_max_messages: bool = True,
) -> dict[str, Any]:
if not str(datasource.endpoint or "").startswith(("ws://", "wss://")):
raise CustomDatasourceRuntimeError("WebSocket datasource endpoint must start with ws:// or wss://")
mapping = await load_active_mapping(db, datasource.id)
runtime_config = datasource.config or {}
max_messages = debug_max_messages
if max_messages is None and use_config_debug_max_messages:
max_messages = runtime_config.get("debug_max_messages")
max_messages = int(max_messages) if max_messages else None
receive_timeout = float(runtime_config.get("receive_timeout_seconds") or runtime_config.get("timeout") or 30)
reconnect = bool(runtime_config.get("ws_reconnect", True))
reconnect_delay = float(runtime_config.get("reconnect_delay_seconds") or 3)
headers = build_request_headers(datasource.auth_type, datasource.auth_config or {}, datasource.headers or {})
messages_seen = 0
mapped_count = 0
failed_count = 0
written_count = 0
errors: list[dict[str, Any]] = []
started_at = datetime.now(UTC)
while True:
try:
async with await _connect_websocket(datasource.endpoint, headers) as websocket:
subscribe_message = runtime_config.get("ws_subscribe_message")
if isinstance(subscribe_message, (dict, list)):
await websocket.send(json.dumps(subscribe_message))
elif isinstance(subscribe_message, str) and subscribe_message.strip():
await websocket.send(subscribe_message)
while True:
raw_message = await asyncio.wait_for(websocket.recv(), timeout=receive_timeout)
messages_seen += 1
try:
payload = json.loads(raw_message)
except json.JSONDecodeError as exc:
failed_count += 1
errors.append({"message": "invalid_json", "error": str(exc)})
continue
extracted = _items_from_ws_message(payload, runtime_config)
try:
mapped = execute_mapping(extracted, mapping.mapping_json, mapping.target_schema)
except (MappingError, ValueError) as exc:
failed_count += 1
errors.append({"message": "mapping_failed", "error": str(exc)})
continue
mapped_count += mapped["mapped_count"]
failed_count += mapped["failed_count"]
if mapped["errors"]:
errors.extend(mapped["errors"][:5])
if mapped["records"]:
written_count += await persist_mapped_records(
db,
datasource_name=datasource.name,
datasource_config_id=datasource.id,
target_schema=mapping.target_schema,
records=mapped["records"],
mapping_version=mapping.version,
delivery_mode=runtime_config.get("delivery_mode") or "realtime_stream",
transport="websocket",
)
if max_messages and messages_seen >= max_messages:
return {
"status": "success",
"datasource_config_id": datasource.id,
"mapping_id": mapping.id,
"mapping_version": mapping.version,
"target_schema": mapping.target_schema,
"messages_seen": messages_seen,
"mapped_count": mapped_count,
"failed_count": failed_count,
"written_count": written_count,
"errors": errors[:20],
"execution_time_seconds": (datetime.now(UTC) - started_at).total_seconds(),
}
except asyncio.CancelledError:
raise
except Exception as exc:
failed_count += 1
errors.append({"message": "websocket_error", "error": f"{exc.__class__.__name__}: {exc}"})
if not reconnect or max_messages:
return {
"status": "failed" if written_count == 0 else "partial",
"datasource_config_id": datasource.id,
"mapping_id": mapping.id,
"mapping_version": mapping.version,
"target_schema": mapping.target_schema,
"messages_seen": messages_seen,
"mapped_count": mapped_count,
"failed_count": failed_count,
"written_count": written_count,
"errors": errors[:20],
}
await asyncio.sleep(reconnect_delay)
async def run_custom_stream_by_id(config_id: int) -> dict[str, Any]:
async with async_session_factory() as db:
datasource = await db.get(DataSourceConfig, config_id)
if not datasource:
raise CustomDatasourceRuntimeError("Configuration not found")
return await run_mapped_websocket_config(
db,
datasource,
use_config_debug_max_messages=False,
)
def start_custom_stream(config_id: int) -> bool:
existing = RUNNING_CUSTOM_STREAM_TASKS.get(config_id)
if existing is not None and not existing.done():
return False
task = asyncio.create_task(run_custom_stream_by_id(config_id), name=f"custom-stream:{config_id}")
RUNNING_CUSTOM_STREAM_TASKS[config_id] = task
def _cleanup(done_task: asyncio.Task[Any]) -> None:
if RUNNING_CUSTOM_STREAM_TASKS.get(config_id) is done_task:
RUNNING_CUSTOM_STREAM_TASKS.pop(config_id, None)
task.add_done_callback(_cleanup)
return True
async def stop_custom_stream(config_id: int) -> bool:
task = RUNNING_CUSTOM_STREAM_TASKS.get(config_id)
if task is None or task.done():
RUNNING_CUSTOM_STREAM_TASKS.pop(config_id, None)
return False
task.cancel()
try:
await task
except asyncio.CancelledError:
return True
return task.cancelled()
def get_custom_stream_status(config_id: int) -> dict[str, Any]:
task = RUNNING_CUSTOM_STREAM_TASKS.get(config_id)
return {
"config_id": config_id,
"running": bool(task and not task.done()),
"done": bool(task and task.done()),
}

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"""Connectivity validation helpers for built-in datasource overrides."""
from __future__ import annotations
from datetime import UTC, datetime
import hashlib
import json
import os
from typing import Any
import httpx
from sqlalchemy import func, select
from app.core.data_sources import get_data_sources_config
from app.core.datasource_defaults import DEFAULT_DATASOURCES
from app.models.collected_data import CollectedData
from app.models.datasource import DataSource
from app.models.datasource_config import DataSourceConfig
from app.models.system_setting import SystemSetting
from app.services.barentswatch import (
_read_zshrc_env,
fetch_barentswatch_access_token,
resolve_barentswatch_config,
)
CONNECTIVITY_VALIDATION_KEY = "connectivity_validation"
CONNECTIVITY_STORE_CATEGORY = "datasource_connectivity_validations"
SUPPORTED_CREDENTIAL_PROVIDERS = {"barentswatch", "spacetrack", "aisstream"}
def _sha256_json(payload: Any) -> str:
encoded = json.dumps(payload, ensure_ascii=False, sort_keys=True, default=str).encode("utf-8")
return hashlib.sha256(encoded).hexdigest()
def _resolve_spacetrack_credentials() -> tuple[str, str, str]:
zshrc_env = _read_zshrc_env()
username = os.getenv("SPACETRACK_USERNAME") or zshrc_env.get("SPACETRACK_USERNAME") or ""
password = os.getenv("SPACETRACK_PASSWORD") or zshrc_env.get("SPACETRACK_PASSWORD") or ""
source = "environment" if os.getenv("SPACETRACK_USERNAME") or os.getenv("SPACETRACK_PASSWORD") else ""
if not source and (username or password):
source = "~/.zshrc"
return username, password, source or "missing"
async def _resolve_aisstream_api_key(
db=None,
credential_override: dict[str, str] | None = None,
) -> tuple[str, str]:
if credential_override and credential_override.get("api_key"):
return str(credential_override["api_key"]), "draft"
env_key = os.getenv("AISSTREAM_API_KEY")
zshrc_key = _read_zshrc_env().get("AISSTREAM_API_KEY")
if db is not None:
result = await db.execute(
select(DataSourceConfig)
.where(DataSourceConfig.name == "aisstream_vessels")
.where(DataSourceConfig.is_active.is_(True))
)
record = result.scalar_one_or_none()
if record:
auth_config = record.auth_config or {}
runtime_config = record.config or {}
api_key = auth_config.get("api_key") or runtime_config.get("api_key")
if api_key:
return str(api_key), "datasource_config"
if env_key:
return env_key, "environment"
if zshrc_key:
return zshrc_key, "~/.zshrc"
return "", "missing"
def strip_connectivity_validation(config: dict | None) -> dict:
cleaned = dict(config or {})
cleaned.pop(CONNECTIVITY_VALIDATION_KEY, None)
return cleaned
def merge_connectivity_validation(existing_config: dict | None, next_config: dict | None) -> dict:
merged = strip_connectivity_validation(next_config)
validation = (existing_config or {}).get(CONNECTIVITY_VALIDATION_KEY)
if validation:
merged[CONNECTIVITY_VALIDATION_KEY] = validation
return merged
def get_connectivity_validation(config: DataSourceConfig | None) -> dict | None:
validation = (config.config or {}).get(CONNECTIVITY_VALIDATION_KEY) if config else None
return validation if isinstance(validation, dict) else None
async def build_builtin_connectivity_checksum(
source: str,
endpoint: str,
auth_type: str,
headers: dict | None,
config: dict | None,
db=None,
credential_override: dict[str, str] | None = None,
) -> tuple[str, dict[str, Any]]:
defaults = DEFAULT_DATASOURCES.get(source, {})
credential_provider = defaults.get("credential_provider")
credential_fingerprint = ""
credential_source = "none"
has_credentials = not defaults.get("requires_credentials", False)
if credential_provider == "barentswatch":
if credential_override:
client_id = credential_override.get("client_id", "")
client_secret = credential_override.get("client_secret", "")
credential_source = "draft"
else:
barentswatch_config = await resolve_barentswatch_config(db)
client_id = barentswatch_config.client_id
client_secret = barentswatch_config.client_secret
credential_source = barentswatch_config.credential_source
has_credentials = bool(client_id and client_secret)
credential_fingerprint = _sha256_json(
{
"client_id": client_id,
"client_secret": client_secret,
}
)
elif credential_provider == "spacetrack":
username, password, credential_source = _resolve_spacetrack_credentials()
has_credentials = bool(username and password)
credential_fingerprint = _sha256_json(
{
"username": username,
"password": password,
}
)
elif credential_provider == "aisstream":
api_key, credential_source = await _resolve_aisstream_api_key(db, credential_override)
has_credentials = bool(api_key)
credential_fingerprint = _sha256_json({"api_key": api_key})
elif defaults.get("requires_credentials"):
credential_source = str(credential_provider or "unsupported")
checksum_payload = {
"source": source,
"endpoint": endpoint,
"auth_type": "none",
"headers": headers or {},
"config": strip_connectivity_validation(config),
"credential_provider": credential_provider or "none",
"credential_fingerprint": credential_fingerprint,
}
return _sha256_json(checksum_payload), {
"requires_credentials": bool(defaults.get("requires_credentials", False)),
"credential_provider": credential_provider,
"credential_source": credential_source,
"has_credentials": has_credentials,
}
async def test_builtin_connectivity(
source: str,
endpoint: str,
auth_type: str,
headers: dict | None,
config: dict | None,
db=None,
credential_override: dict[str, str] | None = None,
) -> dict[str, Any]:
defaults = DEFAULT_DATASOURCES.get(source)
if not defaults:
return {
"success": False,
"message": "未知内置采集器,无法执行连接校验。",
}
checksum, credential_context = await build_builtin_connectivity_checksum(
source,
endpoint,
auth_type,
headers,
config,
db,
credential_override,
)
if credential_context["requires_credentials"] and not credential_context["has_credentials"]:
return {
"success": False,
"checksum": checksum,
"stage": "credentials",
"message": "该采集器需要凭证,请先到采集器凭证设置中配置。",
"settings_tab": "collector_credentials",
**credential_context,
}
if (
credential_context["requires_credentials"]
and credential_context["credential_provider"] not in SUPPORTED_CREDENTIAL_PROVIDERS
):
return {
"success": False,
"checksum": checksum,
"stage": "credentials",
"message": "该采集器的凭证链路尚未接入,暂时无法完成连接校验。",
"settings_tab": "collector_credentials",
**credential_context,
}
request_headers = {str(key): str(value) for key, value in (headers or {}).items()}
request_config = strip_connectivity_validation(config)
timeout = float(request_config.get("timeout") or 30)
request_endpoint = endpoint
if credential_context["credential_provider"] == "aisstream":
if not str(request_endpoint).startswith(("ws://", "wss://")):
return {
"success": False,
"checksum": checksum,
"stage": "endpoint",
"message": "AISStream endpoint 必须是 ws:// 或 wss:// WebSocket 地址。",
**credential_context,
}
return {
"success": True,
"checksum": checksum,
"stage": "credentials",
"message": "AISStream 凭证已配置WebSocket endpoint 格式有效。",
**credential_context,
}
try:
async with httpx.AsyncClient(timeout=timeout, follow_redirects=True) as client:
if credential_context["credential_provider"] == "barentswatch":
barentswatch_config = await resolve_barentswatch_config(db)
token = await fetch_barentswatch_access_token(client, barentswatch_config)
if not token:
return {
"success": False,
"checksum": checksum,
"stage": "token",
"message": "凭证可读取,但 token 响应中没有 access_token。",
"settings_tab": "collector_credentials",
**credential_context,
}
request_headers["Authorization"] = f"Bearer {token}"
elif credential_context["credential_provider"] == "spacetrack":
username, password, _source = _resolve_spacetrack_credentials()
login_url = "https://www.space-track.org/ajaxauth/login"
login_response = await client.post(
login_url,
data={
"identity": username,
"password": password,
},
)
login_response.raise_for_status()
started = datetime.now(UTC)
async with client.stream("GET", request_endpoint, headers=request_headers) as response:
response.raise_for_status()
status_code = response.status_code
elapsed_ms = (datetime.now(UTC) - started).total_seconds() * 1000
return {
"success": True,
"checksum": checksum,
"stage": "endpoint",
"message": "连接验证成功。",
"status_code": status_code,
"response_time_ms": elapsed_ms,
**credential_context,
}
except httpx.HTTPStatusError as exc:
return {
"success": False,
"checksum": checksum,
"stage": "endpoint",
"message": f"连接验证失败HTTP {exc.response.status_code}",
"error": f"HTTP Error: {exc.response.status_code}",
**credential_context,
}
except httpx.HTTPError as exc:
return {
"success": False,
"checksum": checksum,
"stage": "network",
"message": f"连接验证失败:{exc.__class__.__name__}",
"error": str(exc),
**credential_context,
}
def make_success_validation(checksum: str, result: dict[str, Any]) -> dict[str, Any]:
return {
"checksum": checksum,
"status": "success",
"validated_at": datetime.now(UTC).isoformat(),
"status_code": result.get("status_code"),
"credential_source": result.get("credential_source"),
}
def is_builtin_validation_current(config: DataSourceConfig | None, checksum: str) -> bool:
validation = get_connectivity_validation(config)
return bool(
validation
and validation.get("status") == "success"
and validation.get("checksum") == checksum
)
async def get_connectivity_store(db) -> dict[str, Any]:
result = await db.execute(
select(SystemSetting).where(SystemSetting.category == CONNECTIVITY_STORE_CATEGORY)
)
record = result.scalar_one_or_none()
return dict(record.payload or {}) if record and isinstance(record.payload, dict) else {}
async def save_connectivity_success(
db,
source: str,
checksum: str,
result: dict[str, Any],
*,
connected_by: str,
) -> dict[str, Any]:
store = await get_connectivity_store(db)
validation = {
**make_success_validation(checksum, result),
"connected_by": connected_by,
}
store[source] = validation
existing = await db.execute(
select(SystemSetting).where(SystemSetting.category == CONNECTIVITY_STORE_CATEGORY)
)
record = existing.scalar_one_or_none()
if record is None:
db.add(SystemSetting(category=CONNECTIVITY_STORE_CATEGORY, payload=store))
else:
record.payload = store
return validation
async def load_builtin_override_config(db, source: str) -> DataSourceConfig | None:
result = await db.execute(
select(DataSourceConfig)
.where(DataSourceConfig.name == source)
.where(DataSourceConfig.is_active.is_(True))
)
return result.scalar_one_or_none()
async def get_builtin_effective_candidate(db, source: str) -> dict[str, Any]:
override = await load_builtin_override_config(db, source)
default_endpoint = get_data_sources_config().get_yaml_url(source)
return {
"name": source,
"endpoint": (override.endpoint if override and override.endpoint else default_endpoint) or "",
"auth_type": override.auth_type if override else "none",
"headers": override.headers if override else {},
"config": strip_connectivity_validation(override.config if override else {}),
}
async def has_collected_data(db, source: str) -> bool:
result = await db.execute(select(func.count(CollectedData.id)).where(CollectedData.source == source))
if (result.scalar() or 0) > 0:
return True
datasource_result = await db.execute(select(DataSource).where(DataSource.source == source))
datasource = datasource_result.scalar_one_or_none()
return bool(datasource and datasource.last_status == "success")
async def get_builtin_connection_status(
db,
source: str,
endpoint: str,
auth_type: str,
headers: dict | None,
config: dict | None,
) -> dict[str, Any]:
checksum, credential_context = await build_builtin_connectivity_checksum(
source,
endpoint,
auth_type,
headers,
config,
db,
)
store = await get_connectivity_store(db)
validation = store.get(source)
if isinstance(validation, dict) and validation.get("status") == "success":
if validation.get("checksum") == checksum:
return {
"connected": True,
"checksum": checksum,
"connected_by": validation.get("connected_by") or "connection_button",
"message": "当前配置已完成连接验证。",
**credential_context,
}
effective = await get_builtin_effective_candidate(db, source)
effective_checksum, _ = await build_builtin_connectivity_checksum(
source,
effective["endpoint"],
effective["auth_type"],
effective["headers"],
effective["config"],
db,
)
if checksum == effective_checksum and await has_collected_data(db, source):
return {
"connected": True,
"checksum": checksum,
"connected_by": "collection",
"message": "当前配置已有成功采集数据,视为已连接。",
**credential_context,
}
if isinstance(validation, dict) and validation.get("status") == "success":
return {
"connected": False,
"checksum": checksum,
"connected_by": None,
"message": "接口地址或凭证指纹已变化,请重新点击连接验证。",
**credential_context,
}
return {
"connected": False,
"checksum": checksum,
"connected_by": None,
"message": "当前配置尚未连接,请点击连接验证。",
**credential_context,
}

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"""Deterministic mapping support for custom data sources."""
from __future__ import annotations
import hashlib
import json
import re
from datetime import UTC, datetime
from typing import Any
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.target_schema_registry import TargetSchema, get_target_schema
SECRET_KEY_PATTERN = re.compile(
r"(token|secret|password|passwd|authorization|api[_-]?key|client[_-]?secret)",
re.IGNORECASE,
)
class MappingError(ValueError):
"""Raised when a mapping definition cannot be executed."""
def stable_payload_hash(payload: Any) -> str:
encoded = json.dumps(payload, ensure_ascii=False, sort_keys=True, default=str).encode()
return hashlib.sha256(encoded).hexdigest()
def redact_for_llm(value: Any) -> Any:
if isinstance(value, dict):
redacted = {}
for key, item in value.items():
if SECRET_KEY_PATTERN.search(str(key)):
redacted[key] = "[REDACTED]"
else:
redacted[key] = redact_for_llm(item)
return redacted
if isinstance(value, list):
return [redact_for_llm(item) for item in value[:20]]
return value
def extract_path(payload: Any, path: str | None) -> Any:
if not path or path == "$":
return payload
normalized = path.strip()
if normalized.startswith("$."):
normalized = normalized[2:]
elif normalized.startswith("$"):
normalized = normalized[1:]
normalized = normalized.strip(".")
if not normalized:
return payload
current = payload
for raw_segment in normalized.split("."):
segment = raw_segment.strip()
if not segment:
continue
list_all = segment.endswith("[*]")
if list_all:
segment = segment[:-3]
index = None
match = re.fullmatch(r"(.+)\[(\d+)\]", segment)
if match:
segment = match.group(1)
index = int(match.group(2))
if segment:
if isinstance(current, dict):
current = current.get(segment)
else:
return None
if list_all:
return current if isinstance(current, list) else []
if index is not None:
if not isinstance(current, list) or index >= len(current):
return None
current = current[index]
return current
def _convert_value(value: Any, target_type: str | None) -> Any:
if value is None or target_type in (None, "", "any"):
return value
if target_type == "string":
return str(value)
if target_type == "integer":
return int(value)
if target_type == "float":
return float(value)
if target_type == "boolean":
if isinstance(value, bool):
return value
if isinstance(value, str):
return value.strip().lower() in {"1", "true", "yes", "y", "on"}
return bool(value)
if target_type == "datetime":
if isinstance(value, datetime):
return value
if isinstance(value, (int, float)):
return datetime.fromtimestamp(value)
if isinstance(value, str):
return datetime.fromisoformat(value.replace("Z", "+00:00"))
return value
if target_type == "object":
if isinstance(value, dict):
return value
raise ValueError("expected object")
if target_type == "array":
if isinstance(value, list):
return value
raise ValueError("expected array")
return value
def _apply_enum(value: Any, enum_map: Any) -> Any:
if not isinstance(enum_map, dict):
return value
key = str(value)
return enum_map.get(key, enum_map.get(value, value))
def _map_one(item: Any, field_mapping: dict[str, Any]) -> tuple[dict[str, Any], list[str]]:
output: dict[str, Any] = {}
errors: list[str] = []
for field_name, rule in field_mapping.items():
if isinstance(rule, str):
rule = {"path": rule}
if not isinstance(rule, dict):
errors.append(f"{field_name}: mapping rule must be an object or path string")
continue
value = extract_path(item, rule.get("path"))
if value is None and "default" in rule:
value = rule.get("default")
value = _apply_enum(value, rule.get("enum"))
try:
value = _convert_value(value, rule.get("type"))
except (TypeError, ValueError) as exc:
errors.append(f"{field_name}: failed to convert value {value!r}: {exc}")
continue
if value is not None or rule.get("include_null", False):
output[field_name] = value
return output, errors
def execute_mapping(
payload: Any,
mapping_json: dict[str, Any],
target_schema: str | TargetSchema,
*,
limit: int | None = None,
) -> dict[str, Any]:
schema = get_target_schema(target_schema) if isinstance(target_schema, str) else target_schema
source = mapping_json.get("source") or {}
fields = mapping_json.get("fields")
if not isinstance(fields, dict) or not fields:
raise MappingError("mapping_json.fields must be a non-empty object")
items_path = source.get("items_path") or mapping_json.get("items_path") or "$"
items = extract_path(payload, items_path)
if isinstance(items, dict):
items = [items]
elif not isinstance(items, list):
items = []
if limit is not None:
items = items[:limit]
mapped_records: list[dict[str, Any]] = []
errors: list[dict[str, Any]] = []
for index, item in enumerate(items):
mapped, mapping_errors = _map_one(item, fields)
validated, validation_errors = schema.validate_record(mapped)
all_errors = mapping_errors + validation_errors
if all_errors:
errors.append({"index": index, "errors": all_errors, "record": mapped})
continue
if validated is not None:
mapped_records.append(validated)
return {
"target_schema": schema.key,
"total_items": len(items),
"mapped_count": len(mapped_records),
"failed_count": len(errors),
"records": mapped_records,
"errors": errors,
}
def build_heuristic_mapping(sample_payload: Any, target_schema_key: str) -> dict[str, Any]:
schema = get_target_schema(target_schema_key)
items_path = "$"
sample_item = sample_payload
if isinstance(sample_payload, dict):
for key in ("data", "items", "results", "features", "vessels"):
candidate = sample_payload.get(key)
if isinstance(candidate, list) and candidate:
items_path = f"$.{key}[*]"
sample_item = candidate[0]
break
elif isinstance(sample_payload, list) and sample_payload:
items_path = "$"
sample_item = sample_payload[0]
available = _flatten_keys(sample_item if isinstance(sample_item, dict) else {})
fields: dict[str, Any] = {}
for field in schema.fields:
candidate = _best_field_match(field.name, available)
if candidate:
fields[field.name] = {"path": f"$.{candidate}", "type": field.type}
elif field.name == "data" and target_schema_key == "generic_records":
fields[field.name] = {"path": "$", "type": "object"}
elif not field.required:
fields[field.name] = {"path": f"$.{field.name}", "type": field.type, "default": None}
return {
"source": {"items_path": items_path},
"fields": fields,
"meta": {
"generated_by": "heuristic",
"requires_review": True,
},
}
def _flatten_keys(payload: dict[str, Any], prefix: str = "") -> list[str]:
keys: list[str] = []
for key, value in payload.items():
dotted = f"{prefix}.{key}" if prefix else str(key)
keys.append(dotted)
if isinstance(value, dict):
keys.extend(_flatten_keys(value, dotted))
return keys
def _best_field_match(field_name: str, candidates: list[str]) -> str | None:
aliases = {
"lat": ("lat", "latitude", "y"),
"lon": ("lon", "lng", "longitude", "x"),
"mmsi": ("mmsi",),
"sog": ("sog", "speed", "speedOverGround"),
"cog": ("cog", "course", "courseOverGround"),
"received_at": ("received_at", "timestamp", "time", "updated_at"),
"observed_at": ("observed_at", "timestamp", "time", "updated_at"),
"source_id": ("id", "source_id", "uuid"),
}.get(field_name, (field_name,))
lowered = {candidate.lower(): candidate for candidate in candidates}
for alias in aliases:
if alias.lower() in lowered:
return lowered[alias.lower()]
for candidate in candidates:
tail = candidate.split(".")[-1].lower()
if tail in {alias.lower() for alias in aliases}:
return candidate
return None
def _parse_datetime(value: Any) -> datetime | None:
if value is None:
return None
if isinstance(value, datetime):
return value
if isinstance(value, str):
return datetime.fromisoformat(value.replace("Z", "+00:00"))
return None
async def persist_mapped_records(
db: AsyncSession,
*,
datasource_name: str,
datasource_config_id: int,
target_schema: str,
records: list[dict[str, Any]],
mapping_version: int,
delivery_mode: str | None = None,
transport: str | None = None,
) -> int:
"""Persist validated mapped records to the destination for a target schema."""
if target_schema == "vessel_ais":
from app.core.time import to_iso8601_utc
from app.core.websocket.broadcaster import broadcaster
from app.services.vessel_ais_aggregation import (
record_vessel_ais_observation,
update_ais_source_health,
)
now = datetime.now(UTC)
latest_observed_at = now
written_count = 0
for record in records:
observed_at = _parse_datetime(record.get("received_at")) or now
observation = await record_vessel_ais_observation(
db,
source=datasource_name,
normalized_payload=record,
raw_payload=record,
delivery_mode=delivery_mode or "polling",
transport=transport or "http",
message_type="PositionReport",
observed_at=observed_at,
collected_at=now,
)
if observation is not None:
written_count += 1
if observed_at > latest_observed_at:
latest_observed_at = observed_at
await update_ais_source_health(
db,
source=datasource_name,
connection_state="connected",
observed_count=len(records),
last_seen_at=latest_observed_at,
last_success_at=now if records else None,
lag_seconds=max((now - latest_observed_at).total_seconds(), 0),
)
await db.commit()
if records:
await broadcaster.broadcast_custom(
"vessels",
{
"action": "upsert",
"source": datasource_name,
"created": True,
"vessels": [
{
"mmsi": record.get("mmsi"),
"mmsi_display": str(record.get("mmsi")) if record.get("mmsi") is not None else None,
"name": record.get("name"),
"callsign": record.get("callsign"),
"lat": record.get("lat"),
"lon": record.get("lon"),
"sog": record.get("sog"),
"cog": record.get("cog"),
"heading": record.get("heading"),
"nav_status": record.get("nav_status"),
"vessel_type": record.get("vessel_type"),
"vessel_type_name": record.get("vessel_type_name"),
"received_at": to_iso8601_utc(_parse_datetime(record.get("received_at"))),
}
for record in records
],
},
)
return written_count
from app.models.collected_data import CollectedData
collected_at = datetime.now(UTC)
for index, record in enumerate(records):
if target_schema == "geo_points":
source_id = record.get("source_id") or f"{datasource_config_id}:{index}"
name = record.get("name")
metadata = {
"latitude": record.get("lat"),
"longitude": record.get("lon"),
"type": record.get("type"),
"mapping_version": mapping_version,
"target_schema": target_schema,
**(record.get("metadata") or {}),
}
reference_date = _parse_datetime(record.get("observed_at"))
else:
source_id = record.get("source_id") or f"{datasource_config_id}:{index}"
name = None
metadata = {
"data": record.get("data") or {},
"mapping_version": mapping_version,
"target_schema": target_schema,
}
reference_date = _parse_datetime(record.get("observed_at"))
db.add(
CollectedData(
source=datasource_name,
source_id=str(source_id),
entity_key=f"{datasource_name}:{source_id}",
data_type=target_schema,
name=name,
title=name,
extra_data=metadata,
collected_at=collected_at,
reference_date=reference_date,
is_valid=1,
is_current=True,
change_type="created",
change_summary={},
)
)
await db.commit()
return len(records)

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"""LLM provider presets used by Settings and the runtime AI provider bridge."""
from __future__ import annotations
from typing import Any
import httpx
MODELS_DEV_URL = "https://models.dev/api.json"
FALLBACK_LLM_PROVIDER_PRESETS: dict[str, dict[str, Any]] = {
"minimax": {
"provider": "minimax",
"label": "MiniMax",
"provider_api": "anthropic-messages",
"base_url": "https://api.minimaxi.com/anthropic",
"model": "MiniMax-M2.7",
"models": ["MiniMax-M2.7", "MiniMax-M2.7-highspeed", "MiniMax-M2.5", "MiniMax-M2"],
"api_key_env": "MINIMAX_API_KEY",
"source": "fallback",
},
"openai": {
"provider": "openai",
"label": "OpenAI",
"provider_api": "openai-completions",
"base_url": "https://api.openai.com/v1",
"model": "gpt-5.1",
"models": ["gpt-5.1", "gpt-5.1-codex", "gpt-4.1", "gpt-4o"],
"api_key_env": "OPENAI_API_KEY",
"source": "fallback",
},
"anthropic": {
"provider": "anthropic",
"label": "Anthropic",
"provider_api": "anthropic-messages",
"base_url": "https://api.anthropic.com/v1",
"model": "claude-sonnet-4-6",
"models": ["claude-sonnet-4-6", "claude-opus-4-5", "claude-3-5-haiku-20241022"],
"api_key_env": "ANTHROPIC_API_KEY",
"source": "fallback",
},
"deepseek": {
"provider": "deepseek",
"label": "DeepSeek",
"provider_api": "openai-completions",
"base_url": "https://api.deepseek.com/v1",
"model": "deepseek-chat",
"models": ["deepseek-chat", "deepseek-reasoner"],
"api_key_env": "DEEPSEEK_API_KEY",
"source": "fallback",
},
"alibaba": {
"provider": "alibaba",
"label": "Alibaba Qwen / DashScope",
"provider_api": "openai-completions",
"base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
"model": "qwen3-max",
"models": ["qwen3-max", "qwen3.5-plus", "qwen-max", "qwen-plus"],
"api_key_env": "DASHSCOPE_API_KEY",
"source": "fallback",
},
"moonshotai": {
"provider": "moonshotai",
"label": "Moonshot AI / Kimi",
"provider_api": "openai-completions",
"base_url": "https://api.moonshot.ai/v1",
"model": "kimi-k2.5",
"models": ["kimi-k2.5", "kimi-k2-thinking", "kimi-k2-turbo-preview"],
"api_key_env": "MOONSHOT_API_KEY",
"source": "fallback",
},
"openrouter": {
"provider": "openrouter",
"label": "OpenRouter",
"provider_api": "openai-completions",
"base_url": "https://openrouter.ai/api/v1",
"model": "openai/gpt-5.1",
"models": ["openai/gpt-5.1", "anthropic/claude-sonnet-4.5", "qwen/qwen3-max"],
"api_key_env": "OPENROUTER_API_KEY",
"source": "fallback",
},
"ollama": {
"provider": "ollama",
"label": "Ollama Local",
"provider_api": "ollama-generate",
"base_url": "http://127.0.0.1:11434",
"model": "qwen2.5:7b",
"models": ["qwen2.5:7b", "llama3.1:8b", "mistral:7b"],
"api_key_env": "",
"source": "fallback",
},
}
MODELS_DEV_PROVIDER_KEYS = {
"minimax": "minimax",
"openai": "openai",
"anthropic": "anthropic",
"deepseek": "deepseek",
"alibaba": "alibaba",
"moonshotai": "moonshotai",
"openrouter": "openrouter",
}
def list_fallback_llm_provider_presets() -> list[dict[str, Any]]:
return [dict(value) for value in FALLBACK_LLM_PROVIDER_PRESETS.values()]
def get_fallback_llm_provider_preset(provider: str) -> dict[str, Any]:
key = provider.strip().lower()
if key not in FALLBACK_LLM_PROVIDER_PRESETS:
raise ValueError(f"Unsupported LLM provider preset: {provider}")
return dict(FALLBACK_LLM_PROVIDER_PRESETS[key])
async def refresh_llm_provider_preset(provider: str) -> dict[str, Any]:
fallback = get_fallback_llm_provider_preset(provider)
models_dev_key = MODELS_DEV_PROVIDER_KEYS.get(fallback["provider"])
if not models_dev_key:
return fallback
async with httpx.AsyncClient(timeout=15.0, follow_redirects=True) as client:
response = await client.get(
MODELS_DEV_URL,
headers={"User-Agent": "Planet/1.0"},
)
response.raise_for_status()
catalog = response.json()
upstream = catalog.get(models_dev_key)
if not isinstance(upstream, dict):
return fallback
upstream_models = upstream.get("models") if isinstance(upstream.get("models"), dict) else {}
model_ids = list(upstream_models.keys())[:80]
base_url = upstream.get("api") or fallback["base_url"]
if fallback["provider"] == "deepseek" and base_url == "https://api.deepseek.com":
base_url = "https://api.deepseek.com/v1"
refreshed = {
**fallback,
"label": upstream.get("name") or fallback["label"],
"base_url": base_url,
"model": model_ids[0] if model_ids else fallback["model"],
"models": model_ids or fallback["models"],
"api_key_env": (upstream.get("env") or [fallback["api_key_env"]])[0],
"source": MODELS_DEV_URL,
}
return refreshed

View File

@@ -14,6 +14,11 @@ from app.core.time import to_iso8601_utc
from app.models.datasource import DataSource
from app.models.task import CollectionTask
from app.services.collectors.registry import collector_registry
from app.services.datasource_connectivity import (
build_builtin_connectivity_checksum,
get_builtin_effective_candidate,
save_connectivity_success,
)
logger = get_logger(__name__)
@@ -179,6 +184,23 @@ async def run_collector_task(collector_name: str):
task_result = await collector.run(db)
datasource.last_run_at = datetime.now(UTC)
datasource.last_status = task_result.get("status")
if datasource.last_status == "success":
effective_candidate = await get_builtin_effective_candidate(db, datasource.source)
checksum, _credential_context = await build_builtin_connectivity_checksum(
datasource.source,
effective_candidate["endpoint"],
effective_candidate["auth_type"],
effective_candidate["headers"],
effective_candidate["config"],
db,
)
await save_connectivity_success(
db,
datasource.source,
checksum,
{"status_code": None},
connected_by="collection",
)
await _update_next_run_at(datasource, db)
logger.info_event(
"Collector completed",

View File

@@ -19,6 +19,10 @@ ALLOWED_ACTIONS: dict[str, dict[str, Any]] = {
"command": ["./planet.sh", "restart", "-b"],
"recovery_mode": "backend",
},
"restart-frontend": {
"command": ["./planet.sh", "restart", "-f"],
"recovery_mode": "frontend",
},
"restart-ai-provider": {
"command": ["./planet.sh", "restart", "-a"],
"recovery_mode": "ai-provider",

View File

@@ -0,0 +1,198 @@
"""Persistence + validation for the v4 vessel_ais aggregation strategy."""
from __future__ import annotations
from typing import Any
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.models.system_setting import SystemSetting
VESSEL_AGGREGATION_STRATEGY_CATEGORY = "vessel_aggregation_strategy"
DYNAMIC_FIELDS: tuple[str, ...] = ("lat", "lon", "sog", "cog", "heading", "nav_status")
STATIC_FIELDS: tuple[str, ...] = (
"name",
"callsign",
"imo",
"flag",
"vessel_type",
"vessel_type_name",
"length",
"width",
"draught",
)
ALLOWED_FIELDS: frozenset[str] = frozenset(DYNAMIC_FIELDS + STATIC_FIELDS)
ALLOWED_DYNAMIC_MODES: frozenset[str] = frozenset({"newest"})
ALLOWED_STATIC_MODES: frozenset[str] = frozenset({"source_priority", "non_empty", "newest", "locked"})
ALLOWED_LOCKED_DYNAMIC_MODES: frozenset[str] = frozenset({"newest", "source_priority", "locked"})
DEFAULT_STRATEGY: dict[str, Any] = {
"version": 1,
"vessel_ais": {
"source_priority": ["aisstream_vessels", "barentswatch_vessels"],
"field_rules": {},
"freshness": {
"realtime_stream_seconds": 900,
"polling_seconds": 3600,
},
"allow_dynamic_lock": False,
},
}
class StrategyValidationError(ValueError):
"""Raised when a saved strategy payload is malformed."""
def _coerce_str_list(value: Any, *, label: str) -> list[str]:
if value is None:
return []
if not isinstance(value, list):
raise StrategyValidationError(f"{label} must be a list of source names")
out: list[str] = []
for item in value:
if not isinstance(item, str) or not item.strip():
raise StrategyValidationError(f"{label} entries must be non-empty strings")
out.append(item.strip())
return out
def validate_strategy(payload: dict[str, Any]) -> dict[str, Any]:
"""Validate and normalize a strategy payload. Raise StrategyValidationError on issues."""
if not isinstance(payload, dict):
raise StrategyValidationError("strategy payload must be an object")
vessel_ais = payload.get("vessel_ais")
if not isinstance(vessel_ais, dict):
raise StrategyValidationError("strategy.vessel_ais is required and must be an object")
allow_dynamic_lock = bool(vessel_ais.get("allow_dynamic_lock", False))
source_priority = _coerce_str_list(
vessel_ais.get("source_priority"),
label="vessel_ais.source_priority",
)
raw_rules = vessel_ais.get("field_rules") or {}
if not isinstance(raw_rules, dict):
raise StrategyValidationError("vessel_ais.field_rules must be an object")
field_rules: dict[str, dict[str, Any]] = {}
for field, rule in raw_rules.items():
if field not in ALLOWED_FIELDS:
raise StrategyValidationError(f"unknown vessel_ais field: {field}")
if not isinstance(rule, dict):
raise StrategyValidationError(f"field_rules.{field} must be an object")
mode = str(rule.get("mode") or "").strip()
if not mode:
raise StrategyValidationError(f"field_rules.{field}.mode is required")
is_dynamic = field in DYNAMIC_FIELDS
if is_dynamic:
allowed_modes = ALLOWED_LOCKED_DYNAMIC_MODES if allow_dynamic_lock else ALLOWED_DYNAMIC_MODES
if mode not in allowed_modes:
if not allow_dynamic_lock:
raise StrategyValidationError(
f"field_rules.{field}.mode='{mode}' requires allow_dynamic_lock=true"
)
raise StrategyValidationError(
f"field_rules.{field}.mode must be one of {sorted(allowed_modes)}"
)
else:
if mode not in ALLOWED_STATIC_MODES:
raise StrategyValidationError(
f"field_rules.{field}.mode must be one of {sorted(ALLOWED_STATIC_MODES)}"
)
normalized_rule: dict[str, Any] = {"mode": mode}
rule_priority = rule.get("source_priority")
if rule_priority is not None:
normalized_rule["source_priority"] = _coerce_str_list(
rule_priority,
label=f"field_rules.{field}.source_priority",
)
if mode == "locked":
locked_source = rule.get("locked_source")
if not isinstance(locked_source, str) or not locked_source.strip():
raise StrategyValidationError(
f"field_rules.{field}.locked_source must be a non-empty string when mode=locked"
)
normalized_rule["locked_source"] = locked_source.strip()
field_rules[field] = normalized_rule
raw_freshness = vessel_ais.get("freshness") or {}
if not isinstance(raw_freshness, dict):
raise StrategyValidationError("vessel_ais.freshness must be an object")
freshness: dict[str, int] = {}
for key in ("realtime_stream_seconds", "polling_seconds"):
value = raw_freshness.get(key, DEFAULT_STRATEGY["vessel_ais"]["freshness"][key])
try:
seconds = int(value)
except (TypeError, ValueError) as exc:
raise StrategyValidationError(f"freshness.{key} must be an integer") from exc
if seconds < 0:
raise StrategyValidationError(f"freshness.{key} must be non-negative")
freshness[key] = seconds
return {
"version": int(payload.get("version") or 0) + 1,
"vessel_ais": {
"source_priority": source_priority,
"field_rules": field_rules,
"freshness": freshness,
"allow_dynamic_lock": allow_dynamic_lock,
},
}
async def _select_setting(db: AsyncSession) -> SystemSetting | None:
result = await db.execute(
select(SystemSetting).where(SystemSetting.category == VESSEL_AGGREGATION_STRATEGY_CATEGORY)
)
return result.scalar_one_or_none()
def _current_version(setting: SystemSetting | None) -> int:
if setting is None:
return 0
payload = setting.payload or {}
return int(payload.get("version") or 0)
async def load_strategy(db: AsyncSession) -> dict[str, Any]:
setting = await _select_setting(db)
if setting is None or not isinstance(setting.payload, dict):
return DEFAULT_STRATEGY
payload = setting.payload
if "vessel_ais" not in payload:
return DEFAULT_STRATEGY
return payload
async def save_strategy(db: AsyncSession, payload: dict[str, Any]) -> dict[str, Any]:
"""Validate + persist; bumps version automatically."""
existing = await _select_setting(db)
incoming = dict(payload)
incoming.setdefault("version", _current_version(existing))
validated = validate_strategy(incoming)
if existing is None:
existing = SystemSetting(category=VESSEL_AGGREGATION_STRATEGY_CATEGORY, payload=validated)
db.add(existing)
else:
existing.payload = validated
await db.commit()
return validated
async def reset_strategy(db: AsyncSession) -> dict[str, Any]:
existing = await _select_setting(db)
payload = {**DEFAULT_STRATEGY, "version": _current_version(existing) + 1}
if existing is None:
existing = SystemSetting(category=VESSEL_AGGREGATION_STRATEGY_CATEGORY, payload=payload)
db.add(existing)
else:
existing.payload = payload
await db.commit()
return payload

View File

@@ -0,0 +1,698 @@
"""AIS raw observation and aggregation support for vessel collectors."""
from datetime import UTC, datetime, timedelta
from hashlib import sha256
import json
from typing import Any, Iterable
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.models.vessel import AISConflictRecord, AISRawObservation, AISSourceHealth
from app.services.vessel_aggregation_strategy import (
DEFAULT_STRATEGY,
load_strategy,
)
from app.services.vessel_types import normalize_vessel_type_name
VESSEL_AIS_SCHEMA = "vessel_ais"
DEFAULT_AGGREGATION_WINDOW_HOURS = 24
BARENTSWATCH_DELIVERY_MODE = "polling"
BARENTSWATCH_TRANSPORT = "http"
AISSTREAM_DELIVERY_MODE = "realtime_stream"
AISSTREAM_TRANSPORT = "websocket"
DELIVERY_MODE_PRIORITY = {
"realtime_stream": 40,
"batch_stream": 30,
"polling": 20,
"snapshot": 10,
}
DYNAMIC_FIELDS = ("lat", "lon", "sog", "cog", "heading", "nav_status")
CONFLICT_FIELDS = (
"name",
"callsign",
"imo",
"flag",
"vessel_type",
"vessel_type_name",
"length",
"width",
"draught",
)
def _json_default(value: Any) -> Any:
if isinstance(value, datetime):
return value.astimezone(UTC).isoformat()
return str(value)
def _stable_payload(value: Any) -> str:
return json.dumps(value, sort_keys=True, separators=(",", ":"), default=_json_default)
def _jsonable(value: Any) -> Any:
if isinstance(value, datetime):
return value.astimezone(UTC).isoformat()
if isinstance(value, dict):
return {str(key): _jsonable(item) for key, item in value.items()}
if isinstance(value, list):
return [_jsonable(item) for item in value]
return value
def _coerce_datetime(value: Any) -> datetime | None:
if isinstance(value, datetime):
return value if value.tzinfo else value.replace(tzinfo=UTC)
if isinstance(value, (int, float)):
timestamp = float(value)
if timestamp > 10_000_000_000:
timestamp /= 1000
return datetime.fromtimestamp(timestamp, UTC)
if isinstance(value, str) and value:
try:
parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
return parsed if parsed.tzinfo else parsed.replace(tzinfo=UTC)
except ValueError:
return None
return None
def build_observation_hash(
*,
source: str,
entity_key: str,
message_type: str | None,
observed_at: datetime,
normalized_payload: dict[str, Any],
source_message_id: str | None = None,
) -> str:
"""Build a deterministic idempotency key for one source-level AIS observation."""
if source_message_id:
basis = {
"source": source,
"entity_key": entity_key,
"source_message_id": source_message_id,
}
else:
basis = {
"source": source,
"entity_key": entity_key,
"message_type": message_type,
"observed_at": observed_at.astimezone(UTC).isoformat(),
"payload": normalized_payload,
}
return sha256(_stable_payload(basis).encode("utf-8")).hexdigest()
def build_field_conflict_candidates(
observations: Iterable[AISRawObservation],
fields: Iterable[str] = CONFLICT_FIELDS,
) -> list[dict[str, Any]]:
"""Return current field disagreements from raw observations without mutating state."""
candidates_by_field: dict[str, dict[str, Any]] = {}
for observation in observations:
payload = observation.normalized_payload or {}
for field in fields:
value = payload.get(field)
if value in (None, ""):
continue
field_candidates = candidates_by_field.setdefault(field, {})
field_candidates[observation.source] = value
conflicts = []
for field, candidates in sorted(candidates_by_field.items()):
unique_values = {_stable_payload(value) for value in candidates.values()}
if len(unique_values) <= 1:
continue
conflicts.append(
{
"field": field,
"candidates": candidates,
"status": "candidate",
}
)
return conflicts
def _payload_value(payload: dict[str, Any], field: str) -> Any:
value = payload.get(field)
return None if value in (None, "") else value
def _clean_text(value: Any) -> str | None:
if value in (None, ""):
return None
text = str(value).strip()
return text or None
def _raw_metadata_value(observation: AISRawObservation, field: str) -> Any:
raw_payload = observation.raw_payload or {}
metadata = raw_payload.get("MetaData") if isinstance(raw_payload, dict) else None
if not isinstance(metadata, dict):
return None
if field == "name":
return _clean_text(metadata.get("ShipName") or metadata.get("ship_name") or metadata.get("name"))
return None
def _delivery_priority(observation: AISRawObservation) -> int:
return DELIVERY_MODE_PRIORITY.get(str(observation.delivery_mode or ""), 0)
def _has_valid_position(payload: dict[str, Any]) -> bool:
try:
lat = float(payload.get("lat"))
lon = float(payload.get("lon"))
except (TypeError, ValueError):
return False
return -90 <= lat <= 90 and -180 <= lon <= 180
def _is_future_observation(observation: AISRawObservation, now: datetime) -> bool:
return observation.observed_at > now
def _strategy_source_rank(
source: str,
strategy: dict[str, Any],
) -> int:
priority = (strategy.get("vessel_ais") or {}).get("source_priority") or []
if source in priority:
return len(priority) - priority.index(source)
return 0
def _is_stream_stale(
observation: AISRawObservation,
*,
now: datetime,
strategy: dict[str, Any],
) -> bool:
delivery_mode = str(observation.delivery_mode or "")
freshness = (strategy.get("vessel_ais") or {}).get("freshness") or {}
if delivery_mode == "realtime_stream":
window = int(freshness.get("realtime_stream_seconds", 0) or 0)
else:
window = int(freshness.get("polling_seconds", 0) or 0)
if window <= 0:
return False
return (now - observation.observed_at).total_seconds() > window
def _select_position_observation(
observations: list[AISRawObservation],
*,
now: datetime,
strategy: dict[str, Any] | None = None,
) -> tuple[AISRawObservation | None, list[str]]:
strategy = strategy or DEFAULT_STRATEGY
rejected_flags: list[str] = []
fresh_candidates: list[AISRawObservation] = []
stale_candidates: list[AISRawObservation] = []
for observation in observations:
payload = observation.normalized_payload or {}
if not _has_valid_position(payload):
rejected_flags.append("invalid_position")
continue
if _is_future_observation(observation, now):
rejected_flags.append("future_timestamp")
continue
if _is_stream_stale(observation, now=now, strategy=strategy):
stale_candidates.append(observation)
rejected_flags.append("freshness_fallback")
continue
fresh_candidates.append(observation)
candidates = fresh_candidates or stale_candidates
if not candidates:
return None, sorted(set(rejected_flags))
candidates.sort(
key=lambda item: (
item.observed_at,
_delivery_priority(item),
_strategy_source_rank(item.source, strategy),
item.collected_at,
item.id or 0,
),
reverse=True,
)
return candidates[0], sorted(set(rejected_flags))
def _select_static_field(
observations: list[AISRawObservation],
field: str,
strategy: dict[str, Any] | None = None,
) -> tuple[Any, str | None, str | None]:
strategy = strategy or DEFAULT_STRATEGY
candidates = []
for observation in observations:
value = _payload_value(observation.normalized_payload or {}, field)
if value is None:
value = _raw_metadata_value(observation, field)
if value is None:
continue
candidates.append((observation, value))
if not candidates:
return None, None, None
field_rules = (strategy.get("vessel_ais") or {}).get("field_rules") or {}
rule = field_rules.get(field) or {"mode": "source_priority"}
mode = rule.get("mode")
if mode == "locked":
locked_source = rule.get("locked_source")
for observation, value in candidates:
if observation.source == locked_source:
return value, observation.source, "locked"
if mode in ("source_priority", "locked"):
priority = rule.get("source_priority") or (strategy.get("vessel_ais") or {}).get("source_priority") or []
ranked = sorted(
candidates,
key=lambda item: (
priority.index(item[0].source) if item[0].source in priority else len(priority) + 1,
-_delivery_priority(item[0]),
-(item[0].observed_at.timestamp() if item[0].observed_at else 0),
),
)
observation, value = ranked[0]
return value, observation.source, "source_priority"
if mode == "newest":
ranked = sorted(
candidates,
key=lambda item: (item[0].observed_at, _delivery_priority(item[0]), item[0].id or 0),
reverse=True,
)
observation, value = ranked[0]
return value, observation.source, "newest_observation"
# default / non_empty: prefer delivery mode priority, then newest
candidates.sort(
key=lambda item: (
_delivery_priority(item[0]),
item[0].observed_at,
item[0].collected_at,
item[0].id or 0,
),
reverse=True,
)
selected_observation, selected_value = candidates[0]
unique_values = {_stable_payload(value) for _, value in candidates}
reason = "delivery_mode_priority" if len(unique_values) > 1 else "non_empty_priority"
return selected_value, selected_observation.source, reason
def _build_source_summary(observations: list[AISRawObservation]) -> dict[str, dict[str, Any]]:
summary: dict[str, dict[str, Any]] = {}
for observation in observations:
source_summary = summary.setdefault(
observation.source,
{
"observation_count": 0,
"latest_observed_at": None,
"delivery_mode": observation.delivery_mode,
"transport": observation.transport,
"message_types": [],
},
)
source_summary["observation_count"] += 1
latest_observed_at = source_summary["latest_observed_at"]
if latest_observed_at is None or observation.observed_at > latest_observed_at:
source_summary["latest_observed_at"] = observation.observed_at
if observation.message_type and observation.message_type not in source_summary["message_types"]:
source_summary["message_types"].append(observation.message_type)
return summary
def _build_aggregated_vessel(
entity_key: str,
observations: list[AISRawObservation],
*,
now: datetime,
strategy: dict[str, Any] | None = None,
) -> dict[str, Any] | None:
strategy = strategy or DEFAULT_STRATEGY
position_observation, rejected_flags = _select_position_observation(
observations, now=now, strategy=strategy
)
if position_observation is None:
return None
payload = position_observation.normalized_payload or {}
mmsi = int(entity_key)
result: dict[str, Any] = {
"mmsi": mmsi,
"lat": float(payload["lat"]),
"lon": float(payload["lon"]),
"received_at": position_observation.observed_at,
"field_sources": {},
"selected_reasons": {},
"source_summary": _build_source_summary(observations),
"quality_flags": sorted(
set((position_observation.quality_flags or []) + rejected_flags)
),
"aggregation_strategy_version": int(strategy.get("version") or 0),
}
for field in DYNAMIC_FIELDS:
value = _payload_value(payload, field)
if field in ("lat", "lon") or value is not None:
result[field] = value
result["field_sources"][field] = position_observation.source
result["selected_reasons"][field] = "newest_observation"
for field in CONFLICT_FIELDS:
selected_value, selected_source, reason = _select_static_field(
observations, field, strategy=strategy
)
if selected_value is None:
continue
result[field] = selected_value
result["field_sources"][field] = selected_source
result["selected_reasons"][field] = reason
result["name"] = result.get("name") or f"MMSI {mmsi}"
result["vessel_type_name"] = result.get("vessel_type_name") or normalize_vessel_type_name(
result.get("vessel_type")
)
return result
async def _upsert_conflict_records(
db: AsyncSession,
entity_key: str,
observations: list[AISRawObservation],
aggregated: dict[str, Any],
) -> int:
conflicts = build_field_conflict_candidates(observations)
now = datetime.now(UTC)
for conflict in conflicts:
field = conflict["field"]
result = await db.execute(
select(AISConflictRecord)
.where(AISConflictRecord.target_schema == VESSEL_AIS_SCHEMA)
.where(AISConflictRecord.entity_key == entity_key)
.where(AISConflictRecord.field == field)
.limit(1)
)
record = result.scalar_one_or_none()
if record is None:
record = AISConflictRecord(
target_schema=VESSEL_AIS_SCHEMA,
entity_key=entity_key,
field=field,
)
db.add(record)
record.candidates = conflict["candidates"]
record.selected_source = (aggregated.get("field_sources") or {}).get(field)
record.selected_value = aggregated.get(field)
record.selected_reason = (aggregated.get("selected_reasons") or {}).get(field)
record.resolved_by = "system"
record.status = "open"
record.updated_at = now
return len(conflicts)
def _group_observations(observations: Iterable[AISRawObservation]) -> dict[str, list[AISRawObservation]]:
grouped: dict[str, list[AISRawObservation]] = {}
for observation in observations:
grouped.setdefault(str(observation.entity_key), []).append(observation)
return grouped
async def record_vessel_ais_observation(
db: AsyncSession,
*,
source: str,
normalized_payload: dict[str, Any],
raw_payload: dict[str, Any] | None = None,
delivery_mode: str,
transport: str,
message_type: str | None = "PositionReport",
source_message_id: str | None = None,
observed_at: datetime | None = None,
collected_at: datetime | None = None,
quality_flags: list[str] | None = None,
) -> AISRawObservation | None:
"""Insert one raw observation if the source-level fact has not already been stored."""
entity_key = str(normalized_payload["mmsi"])
collected_at = collected_at or datetime.now(UTC)
observed_at = (
_coerce_datetime(observed_at)
or _coerce_datetime(normalized_payload.get("received_at"))
or collected_at
)
normalized_json = _jsonable(normalized_payload)
raw_json = _jsonable(raw_payload or {})
observation_hash = build_observation_hash(
source=source,
entity_key=entity_key,
message_type=message_type,
observed_at=observed_at,
normalized_payload=normalized_json,
source_message_id=source_message_id,
)
existing_result = await db.execute(
select(AISRawObservation.id).where(AISRawObservation.observation_hash == observation_hash)
)
if existing_result.scalar_one_or_none() is not None:
return None
observation = AISRawObservation(
target_schema=VESSEL_AIS_SCHEMA,
source=source,
entity_key=entity_key,
delivery_mode=delivery_mode,
transport=transport,
message_type=message_type,
source_message_id=source_message_id,
observation_hash=observation_hash,
observed_at=observed_at,
collected_at=collected_at,
normalized_payload=normalized_json,
raw_payload=raw_json,
quality_flags=quality_flags or [],
)
db.add(observation)
return observation
async def aggregate_vessel_observations(
db: AsyncSession,
observations: Iterable[AISRawObservation],
*,
write_conflicts: bool = False,
strategy: dict[str, Any] | None = None,
) -> list[dict[str, Any]]:
strategy = strategy if strategy is not None else await _safe_load_strategy(db)
now = datetime.now(UTC)
vessels = []
for entity_key, entity_observations in _group_observations(observations).items():
aggregated = _build_aggregated_vessel(
entity_key, entity_observations, now=now, strategy=strategy
)
if aggregated is None:
continue
if write_conflicts:
aggregated["conflict_count"] = await _upsert_conflict_records(
db,
entity_key,
entity_observations,
aggregated,
)
else:
aggregated["conflict_count"] = len(build_field_conflict_candidates(entity_observations))
vessels.append(aggregated)
vessels.sort(key=lambda item: item.get("received_at") or datetime.min.replace(tzinfo=UTC), reverse=True)
return vessels
async def _safe_load_strategy(db: AsyncSession) -> dict[str, Any]:
"""Tolerate fake test sessions where load_strategy may misbehave."""
try:
return await load_strategy(db)
except Exception:
return DEFAULT_STRATEGY
async def get_aggregated_vessels(
db: AsyncSession,
*,
bbox: tuple[float, float, float, float] | None = None,
limit: int | None = None,
observed_since: datetime | None = None,
) -> list[dict[str, Any]]:
observed_since = observed_since or (
datetime.now(UTC) - timedelta(hours=DEFAULT_AGGREGATION_WINDOW_HOURS)
)
stmt = (
select(AISRawObservation)
.where(AISRawObservation.target_schema == VESSEL_AIS_SCHEMA)
.where(AISRawObservation.observed_at >= observed_since)
.order_by(AISRawObservation.observed_at.desc(), AISRawObservation.id.desc())
)
if limit and limit > 0:
stmt = stmt.limit(max(limit * 20, limit))
result = await db.execute(stmt)
if not hasattr(result, "scalars"):
return []
vessels = await aggregate_vessel_observations(db, result.scalars().all())
if bbox is not None:
lon_min, lat_min, lon_max, lat_max = bbox
vessels = [
vessel
for vessel in vessels
if lon_min <= float(vessel["lon"]) <= lon_max
and lat_min <= float(vessel["lat"]) <= lat_max
]
if limit and limit > 0:
return vessels[:limit]
return vessels
async def get_aggregated_vessel(db: AsyncSession, mmsi: int) -> dict[str, Any] | None:
observations = await get_vessel_raw_observations(db, mmsi, limit=1000)
vessels = await aggregate_vessel_observations(db, observations)
return vessels[0] if vessels else None
async def get_aggregated_vessel_track(
db: AsyncSession,
mmsi: int,
*,
cutoff: datetime,
) -> list[dict[str, Any]]:
result = await db.execute(
select(AISRawObservation)
.where(AISRawObservation.target_schema == VESSEL_AIS_SCHEMA)
.where(AISRawObservation.entity_key == str(mmsi))
.where(AISRawObservation.observed_at >= cutoff)
.order_by(AISRawObservation.observed_at.asc(), AISRawObservation.id.asc())
)
if not hasattr(result, "scalars"):
return []
points: list[dict[str, Any]] = []
seen: set[tuple[str, float, float, str]] = set()
for observation in result.scalars().all():
payload = observation.normalized_payload or {}
if not _has_valid_position(payload):
continue
lat = float(payload["lat"])
lon = float(payload["lon"])
key = (
observation.observed_at.isoformat(),
round(lat, 5),
round(lon, 5),
observation.source,
)
if key in seen:
continue
seen.add(key)
points.append(
{
"lat": lat,
"lon": lon,
"observed_at": observation.observed_at,
"source": observation.source,
"selected_reason": "track_timeline",
"quality_flags": observation.quality_flags or [],
}
)
return points
async def update_ais_source_health(
db: AsyncSession,
*,
source: str,
connection_state: str,
observed_count: int = 0,
last_seen_at: datetime | None = None,
last_success_at: datetime | None = None,
last_error: str | None = None,
lag_seconds: float | None = None,
) -> AISSourceHealth:
"""Upsert the health row for an AIS source."""
now = datetime.now(UTC)
health = await db.get(AISSourceHealth, source)
if health is None:
health = AISSourceHealth(source=source)
db.add(health)
health.connection_state = connection_state
health.last_seen_at = last_seen_at or health.last_seen_at
health.last_success_at = last_success_at or health.last_success_at
health.last_error = last_error
health.message_rate = float(observed_count)
health.lag_seconds = lag_seconds
health.updated_at = now
return health
async def count_unique_raw_vessel_mmsi(
db: AsyncSession,
*,
observed_since: datetime | None = None,
) -> int:
"""Count unique raw vessel MMSI values for HUD counts; never aggregates."""
from sqlalchemy import func as sa_func
unique_mmsi_stmt = (
select(AISRawObservation.entity_key)
.where(AISRawObservation.target_schema == VESSEL_AIS_SCHEMA)
.distinct()
)
if observed_since is not None:
unique_mmsi_stmt = unique_mmsi_stmt.where(
AISRawObservation.observed_at >= observed_since,
)
result = await db.execute(
select(sa_func.count()).select_from(unique_mmsi_stmt.subquery()),
)
return int(result.scalar() or 0)
async def get_vessel_raw_observations(
db: AsyncSession,
mmsi: int,
*,
limit: int = 100,
) -> list[AISRawObservation]:
result = await db.execute(
select(AISRawObservation)
.where(AISRawObservation.target_schema == VESSEL_AIS_SCHEMA)
.where(AISRawObservation.entity_key == str(mmsi))
.order_by(AISRawObservation.observed_at.desc(), AISRawObservation.id.desc())
.limit(limit)
)
return list(result.scalars().all())
async def get_vessel_conflict_records(
db: AsyncSession,
mmsi: int,
) -> list[AISConflictRecord]:
result = await db.execute(
select(AISConflictRecord)
.where(AISConflictRecord.target_schema == VESSEL_AIS_SCHEMA)
.where(AISConflictRecord.entity_key == str(mmsi))
.order_by(AISConflictRecord.updated_at.desc(), AISConflictRecord.id.desc())
)
return list(result.scalars().all())

View File

@@ -0,0 +1,109 @@
"""v5 vessel enrichment service.
Read-only side: `get_vessel_enrichment_bundle` is the only path the
aggregation/detail endpoints use. It never reaches out to third parties; it
just returns whatever the upsert side has already cached. Expired rows are
filtered out so old data never leaks back into the live UI.
"""
from __future__ import annotations
from datetime import UTC, datetime
from typing import Any
from sqlalchemy.ext.asyncio import AsyncSession
from app.models.vessel_enrichment import VesselMediaEnrichment, VesselProfileEnrichment
def _coerce_datetime(value: Any) -> datetime | None:
if value in (None, ""):
return None
if isinstance(value, datetime):
return value if value.tzinfo else value.replace(tzinfo=UTC)
if isinstance(value, (int, float)):
ts = float(value)
if ts > 10_000_000_000:
ts /= 1000
return datetime.fromtimestamp(ts, UTC)
if isinstance(value, str):
try:
parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
return parsed if parsed.tzinfo else parsed.replace(tzinfo=UTC)
except ValueError:
return None
return None
def _build_payload(record, *, now: datetime) -> dict[str, Any] | None:
if record is None:
return None
expires_at = record.expires_at
if isinstance(expires_at, datetime):
if expires_at.tzinfo is None:
expires_at = expires_at.replace(tzinfo=UTC)
if expires_at < now:
return None
return record.to_dict()
async def get_vessel_enrichment_bundle(db: AsyncSession, mmsi: int) -> dict[str, Any]:
now = datetime.now(UTC)
profile = await db.get(VesselProfileEnrichment, mmsi)
media = await db.get(VesselMediaEnrichment, mmsi)
return {
"mmsi": mmsi,
"profile": _build_payload(profile, now=now),
"media": _build_payload(media, now=now),
}
async def upsert_vessel_profile_enrichment(
db: AsyncSession,
*,
mmsi: int,
payload: dict[str, Any],
) -> dict[str, Any]:
record = await db.get(VesselProfileEnrichment, mmsi)
if record is None:
record = VesselProfileEnrichment(mmsi=mmsi)
db.add(record)
return _apply_upsert(record, payload)
async def upsert_vessel_media_enrichment(
db: AsyncSession,
*,
mmsi: int,
payload: dict[str, Any],
) -> dict[str, Any]:
record = await db.get(VesselMediaEnrichment, mmsi)
if record is None:
record = VesselMediaEnrichment(mmsi=mmsi)
db.add(record)
return _apply_upsert(record, payload)
def _apply_upsert(record, payload: dict[str, Any]) -> dict[str, Any]:
if not isinstance(payload, dict):
raise ValueError("enrichment payload must be an object")
body = payload.get("payload")
if body is not None and not isinstance(body, dict):
raise ValueError("payload.payload must be an object")
if body is not None:
record.payload = body
if "source" in payload and isinstance(payload["source"], str) and payload["source"].strip():
record.source = payload["source"].strip()
fetched_at = _coerce_datetime(payload.get("fetched_at"))
record.fetched_at = fetched_at or datetime.now(UTC)
record.expires_at = _coerce_datetime(payload.get("expires_at"))
confidence = payload.get("confidence")
if confidence is not None:
try:
record.confidence = float(confidence)
except (TypeError, ValueError):
record.confidence = None
if "reference_url" in payload:
ref = payload.get("reference_url")
record.reference_url = str(ref) if ref else None
return record.to_dict()

View File

@@ -0,0 +1,31 @@
"""Shared AIS vessel type helpers."""
from typing import Any
VESSEL_TYPE_NAMES = {
30: "Fishing",
35: "Military",
60: "Passenger",
70: "Cargo",
80: "Tanker",
}
def normalize_vessel_type_name(vessel_type: Any) -> str:
"""Map AIS numeric vessel type codes to display buckets."""
try:
type_code = int(float(vessel_type))
except (TypeError, ValueError):
return "Other"
if 70 <= type_code <= 79:
return "Cargo"
if 80 <= type_code <= 89:
return "Tanker"
if 60 <= type_code <= 69:
return "Passenger"
if type_code == 30:
return "Fishing"
if type_code == 35:
return "Military"
return VESSEL_TYPE_NAMES.get(type_code, "Other")

View File

@@ -2,6 +2,7 @@ from __future__ import annotations
import argparse
import os
import shlex
import subprocess
import sys
import time
@@ -59,6 +60,8 @@ def wait_for_recovery(action: str) -> tuple[bool, str]:
recovery_mode = get_action_recovery_mode(action)
if recovery_mode == "backend":
return wait_for_http("http://localhost:8000/health"), "backend health recovery"
if recovery_mode == "frontend":
return wait_for_http("http://localhost:3000"), "frontend entrypoint recovery"
if recovery_mode == "ai-provider":
return wait_for_http("http://localhost:8010/health"), "ai provider health recovery"
if recovery_mode == "database":
@@ -108,8 +111,9 @@ def main() -> int:
)
append_task_log(args.task_id, "restart command started")
shell_command = shlex.join(command)
completed = subprocess.run(
command,
["zsh", "-ic", shell_command],
cwd=str(ROOT_DIR),
env=env,
capture_output=True,

View File

@@ -1,11 +1,14 @@
"""Unit tests for data collectors"""
import pytest
from datetime import datetime
from unittest.mock import AsyncMock, MagicMock, patch
from unittest.mock import AsyncMock, patch
from app.core.datasource_defaults import DEFAULT_DATASOURCES
from app.services.credential_guides import DEFAULT_CREDENTIAL_GUIDES
from app.services.collectors.top500 import TOP500Collector
from app.services.collectors.base import BaseCollector, HTTPCollector
from app.services.collectors.registry import collector_registry
from app.services.datasource_connectivity import SUPPORTED_CREDENTIAL_PROVIDERS
from app.models.task import CollectionTask
class TestBaseCollector:
@@ -19,6 +22,31 @@ class TestBaseCollector:
assert collector.module == "L1"
assert collector.frequency_hours == 4
@pytest.mark.asyncio
async def test_update_phase_progress_tracks_phase_fields(self, mock_db_session):
"""Test phase-level progress updates independently from record totals"""
collector = TOP500Collector()
task = CollectionTask(datasource_id=1, status="running", phase="fetching")
collector._current_task = task
collector._db_session = mock_db_session
with patch.object(collector, "_publish_task_update", new=AsyncMock()) as publish:
await collector.update_phase_progress(
current=512,
total=1024,
unit="bytes",
message="Downloading dataset",
commit=True,
)
assert task.phase_progress == 50.0
assert task.phase_current == 512
assert task.phase_total == 1024
assert task.phase_unit == "bytes"
assert task.phase_message == "Downloading dataset"
mock_db_session.commit.assert_awaited_once()
publish.assert_awaited_once()
class TestTOP500Collector:
"""Tests for TOP500Collector"""
@@ -119,3 +147,30 @@ class TestHTTPCollector:
assert hasattr(collector, "parse_response")
assert callable(collector.fetch)
assert callable(collector.parse_response)
def test_aisstream_collector_is_registered():
collector = collector_registry.get("aisstream_vessels")
assert collector is not None
assert collector.data_type == "vessel_ais"
def test_supported_credential_collectors_have_guides_and_connectivity_provider():
missing: list[str] = []
for source, info in DEFAULT_DATASOURCES.items():
if not info.get("requires_credentials"):
continue
if info.get("credential_status") != "supported":
continue
provider = info.get("credential_provider")
if not provider:
missing.append(f"{source}: missing credential_provider")
continue
if provider not in DEFAULT_CREDENTIAL_GUIDES:
missing.append(f"{source}: missing credential guide for {provider}")
if provider not in SUPPORTED_CREDENTIAL_PROVIDERS:
missing.append(f"{source}: missing connectivity provider for {provider}")
assert missing == []

View File

@@ -0,0 +1,149 @@
"""End-to-end integration test for the custom WebSocket datasource runner.
Boots an in-process WebSocket server that mimics the bun mock AIS server
(`scripts/mock-ais-ws-server.ts`) and runs the real
`run_mapped_websocket_config` against it. Catches regressions where the
runner stops connecting, fails to extract the configured message path,
or quietly drops mapped records before broadcasting.
"""
from __future__ import annotations
import asyncio
import json
from contextlib import asynccontextmanager
from datetime import UTC, datetime
from types import SimpleNamespace
from unittest.mock import AsyncMock
import pytest
import websockets
from app.models.datasource_config import DataSourceConfig
from app.services import custom_datasource_runtime
from app.services.custom_datasource_runtime import run_mapped_websocket_config
def _make_payload(seq: int) -> str:
return json.dumps(
{
"type": "vessel",
"sequence": seq,
"data": {
"mmsi": str(999_000_000 + seq),
"name": f"MOCK VESSEL {seq:03d}",
"lat": 36.20 + seq * 0.001,
"lon": 14.20 + seq * 0.001,
"sog": 12.0,
"cog": 90.0,
"heading": 90,
"vessel_type": 70,
"vessel_type_name": "Cargo",
"received_at": datetime.now(UTC).isoformat(),
},
}
)
@asynccontextmanager
async def _mock_ais_server(emit_count: int):
received_subscribe: list[str] = []
async def handler(ws):
try:
try:
msg = await asyncio.wait_for(ws.recv(), timeout=0.5)
received_subscribe.append(msg)
except (asyncio.TimeoutError, websockets.ConnectionClosed):
pass
for seq in range(1, emit_count + 1):
await ws.send(_make_payload(seq))
await asyncio.sleep(0.01)
# keep the socket open briefly so the runner observes the messages
await asyncio.sleep(0.05)
except websockets.ConnectionClosed:
return
async with websockets.serve(handler, "127.0.0.1", 0) as server:
port = next(iter(server.sockets)).getsockname()[1]
yield port, received_subscribe
@pytest.mark.asyncio
async def test_websocket_runner_streams_from_live_mock(monkeypatch):
mapping = SimpleNamespace(
id=11,
version=3,
target_schema="vessel_ais",
mapping_json={
"source": {"items_path": "$"},
"fields": {
"mmsi": {"path": "$.mmsi", "type": "integer"},
"lat": {"path": "$.lat", "type": "float"},
"lon": {"path": "$.lon", "type": "float"},
"name": {"path": "$.name", "type": "string"},
"vessel_type": {"path": "$.vessel_type", "type": "integer", "default": None},
"vessel_type_name": {"path": "$.vessel_type_name", "type": "string", "default": None},
"sog": {"path": "$.sog", "type": "float", "default": None},
"cog": {"path": "$.cog", "type": "float", "default": None},
"heading": {"path": "$.heading", "type": "integer", "default": None},
"received_at": {"path": "$.received_at", "type": "datetime"},
},
},
)
class FakeResult:
def scalar_one_or_none(self):
return mapping
class FakeDB:
async def execute(self, _stmt):
return FakeResult()
persist = AsyncMock(return_value=1)
monkeypatch.setattr(custom_datasource_runtime, "persist_mapped_records", persist)
async with _mock_ais_server(emit_count=3) as (port, received_subscribe):
result = await run_mapped_websocket_config(
FakeDB(),
DataSourceConfig(
id=99,
name="mock_ais_ws",
source_type="websocket",
endpoint=f"ws://127.0.0.1:{port}",
auth_type="none",
headers={},
config={
"ws_message_path": "$.data",
"ws_subscribe_message": {
"type": "subscribe",
"anchor": {"lat": 36.2, "lon": 14.2},
"spread_km": 50,
"rate_hz": 1,
},
"debug_max_messages": 2,
"delivery_mode": "realtime_stream",
"ws_reconnect": False,
},
),
use_config_debug_max_messages=True,
)
assert result["status"] == "success"
assert result["messages_seen"] == 2
assert result["written_count"] == 2
assert result["mapped_count"] == 2
assert result["target_schema"] == "vessel_ais"
# subscribe message must reach the server unchanged
assert received_subscribe, "runner did not forward ws_subscribe_message"
parsed = json.loads(received_subscribe[0])
assert parsed["type"] == "subscribe"
assert parsed["anchor"] == {"lat": 36.2, "lon": 14.2}
assert parsed["rate_hz"] == 1
# mapped records carry the real MMSIs from the mock stream
persisted_records = []
for call in persist.await_args_list:
persisted_records.extend(call.kwargs["records"])
assert {record["mmsi"] for record in persisted_records} == {999_000_001, 999_000_002}
assert all(record["vessel_type"] == 70 for record in persisted_records)
assert all(record["vessel_type_name"] == "Cargo" for record in persisted_records)

View File

@@ -0,0 +1,328 @@
from types import SimpleNamespace
import pytest
from unittest.mock import AsyncMock
from httpx import ASGITransport, AsyncClient
from app.api.v1.datasource_config import get_ai_provider_client
from app.core.websocket import broadcaster as broadcaster_module
from app.core.security import get_current_user
from app.core.target_schema_registry import get_target_schema, list_target_schemas
from app.main import app
from app.models.user import User
from app.models.datasource_config import DataSourceConfig
from app.services import custom_datasource_runtime
from app.services.custom_datasource_runtime import run_mapped_websocket_config
from app.services.datasource_mapping import execute_mapping, persist_mapped_records, redact_for_llm
SAMPLE_AIS = {
"data": [
{
"mmsi": "257123000",
"latitude": "59.91",
"longitude": "10.75",
"speedOverGround": "12.4",
"timestamp": "2026-04-28T00:00:00Z",
"api_token": "secret-value",
}
]
}
def test_registry_exposes_v1_target_schemas():
keys = {schema["key"] for schema in list_target_schemas()}
assert {"vessel_ais", "geo_points", "generic_records"}.issubset(keys)
assert get_target_schema("vessel_ais").destination == "vessel_position"
def test_mapping_engine_maps_and_validates_vessel_ais():
mapping = {
"source": {"items_path": "$.data[*]"},
"fields": {
"mmsi": {"path": "$.mmsi", "type": "integer"},
"lat": {"path": "$.latitude", "type": "float"},
"lon": {"path": "$.longitude", "type": "float"},
"sog": {"path": "$.speedOverGround", "type": "float"},
"received_at": {"path": "$.timestamp", "type": "datetime"},
},
}
result = execute_mapping(SAMPLE_AIS, mapping, "vessel_ais")
assert result["mapped_count"] == 1
assert result["failed_count"] == 0
assert result["records"][0]["mmsi"] == 257123000
assert result["records"][0]["lat"] == 59.91
def test_mapping_engine_reports_schema_errors():
mapping = {
"source": {"items_path": "$.data[*]"},
"fields": {
"mmsi": {"path": "$.mmsi", "type": "integer"},
"lat": {"path": "$.missing_lat", "type": "float"},
"lon": {"path": "$.longitude", "type": "float"},
},
}
result = execute_mapping(SAMPLE_AIS, mapping, "vessel_ais")
assert result["mapped_count"] == 0
assert result["failed_count"] == 1
assert any("lat" in error for error in result["errors"][0]["errors"])
def test_redact_for_llm_masks_secret_like_fields():
redacted = redact_for_llm(SAMPLE_AIS)
assert redacted["data"][0]["api_token"] == "[REDACTED]"
@pytest.mark.asyncio
async def test_persist_mapped_records_writes_generic_records():
class FakeDB:
def __init__(self):
self.added = []
self.committed = False
def add(self, value):
self.added.append(value)
async def commit(self):
self.committed = True
db = FakeDB()
count = await persist_mapped_records(
db,
datasource_name="custom_weather",
datasource_config_id=42,
target_schema="generic_records",
records=[{"source_id": "row-1", "data": {"temp": 25}}],
mapping_version=3,
)
assert count == 1
assert db.committed is True
assert db.added[0].source == "custom_weather"
assert db.added[0].data_type == "generic_records"
assert db.added[0].extra_data["mapping_version"] == 3
@pytest.mark.asyncio
async def test_persist_mapped_vessel_records_writes_raw_and_broadcasts(monkeypatch):
record_observation = AsyncMock(return_value=object())
update_health = AsyncMock()
broadcast_custom = AsyncMock()
monkeypatch.setattr(
"app.services.vessel_ais_aggregation.record_vessel_ais_observation",
record_observation,
)
monkeypatch.setattr(
"app.services.vessel_ais_aggregation.update_ais_source_health",
update_health,
)
monkeypatch.setattr(broadcaster_module, "broadcast_custom", broadcast_custom)
class FakeDB:
def __init__(self):
self.committed = False
async def commit(self):
self.committed = True
db = FakeDB()
count = await persist_mapped_records(
db,
datasource_name="mock_ais_ws",
datasource_config_id=42,
target_schema="vessel_ais",
records=[
{
"mmsi": 999000001,
"lat": 31.2,
"lon": 121.4,
"name": "MOCK VESSEL 001",
"received_at": "2026-05-01T00:00:00Z",
}
],
mapping_version=1,
delivery_mode="realtime_stream",
transport="websocket",
)
assert count == 1
assert db.committed is True
record_observation.assert_awaited_once()
assert record_observation.await_args.kwargs["source"] == "mock_ais_ws"
assert record_observation.await_args.kwargs["delivery_mode"] == "realtime_stream"
assert record_observation.await_args.kwargs["transport"] == "websocket"
update_health.assert_awaited_once()
broadcast_custom.assert_awaited_once()
assert broadcast_custom.await_args.args[0] == "vessels"
assert broadcast_custom.await_args.args[1]["vessels"][0]["mmsi_display"] == "999000001"
@pytest.mark.asyncio
async def test_custom_websocket_runner_maps_and_persists_vessel_records(monkeypatch):
mapping = SimpleNamespace(
id=7,
version=2,
target_schema="vessel_ais",
mapping_json={
"source": {"items_path": "$"},
"fields": {
"mmsi": {"path": "$.mmsi", "type": "integer"},
"lat": {"path": "$.lat", "type": "float"},
"lon": {"path": "$.lon", "type": "float"},
"name": {"path": "$.name", "type": "string"},
"received_at": {"path": "$.received_at", "type": "datetime"},
},
},
)
class FakeResult:
def scalar_one_or_none(self):
return mapping
class FakeDB:
async def execute(self, _stmt):
return FakeResult()
class FakeWebSocket:
async def __aenter__(self):
return self
async def __aexit__(self, *_args):
return None
async def send(self, _message):
return None
async def recv(self):
return (
'{"type":"vessel","data":{"mmsi":"999000001","name":"MOCK VESSEL 001",'
'"lat":31.2,"lon":121.4,"received_at":"2026-05-01T00:00:00Z"}}'
)
persist = AsyncMock(return_value=1)
monkeypatch.setattr(custom_datasource_runtime, "_connect_websocket", AsyncMock(return_value=FakeWebSocket()))
monkeypatch.setattr(custom_datasource_runtime, "persist_mapped_records", persist)
result = await run_mapped_websocket_config(
FakeDB(),
DataSourceConfig(
id=42,
name="mock_ais_ws",
source_type="websocket",
endpoint="ws://localhost:8787/ais",
auth_type="none",
headers={},
config={"ws_message_path": "$.data", "debug_max_messages": 1},
),
)
assert result["status"] == "success"
assert result["messages_seen"] == 1
assert result["written_count"] == 1
persist.assert_awaited_once()
assert persist.await_args.kwargs["datasource_name"] == "mock_ais_ws"
assert persist.await_args.kwargs["records"][0]["mmsi"] == 999000001
assert persist.await_args.kwargs["delivery_mode"] == "realtime_stream"
assert persist.await_args.kwargs["transport"] == "websocket"
@pytest.mark.asyncio
async def test_mapping_preview_api_uses_deterministic_engine():
def override_get_current_user():
return User(
id=1,
username="testuser",
email="test@example.com",
password_hash="hashed",
role="admin",
is_active=True,
)
app.dependency_overrides = {get_current_user: override_get_current_user}
transport = ASGITransport(app=app)
try:
async with AsyncClient(transport=transport, base_url="http://test") as client:
response = await client.post(
"/api/v1/datasources/mappings/preview",
json={
"sample_payload": SAMPLE_AIS,
"target_schema": "vessel_ais",
"mapping_json": {
"source": {"items_path": "$.data[*]"},
"fields": {
"mmsi": {"path": "$.mmsi", "type": "integer"},
"lat": {"path": "$.latitude", "type": "float"},
"lon": {"path": "$.longitude", "type": "float"},
},
},
},
)
finally:
app.dependency_overrides.clear()
assert response.status_code == 200
payload = response.json()
assert payload["success"] is True
assert payload["preview"]["records"][0]["mmsi"] == 257123000
@pytest.mark.asyncio
async def test_mapping_propose_api_redacts_sample_before_ai():
seen_context = {}
class FakeAIClient:
async def analyze(self, request, request_id=None):
seen_context.update(request.context)
return SimpleNamespace(
content=(
'{"source":{"items_path":"$.data[*]"},"fields":{'
'"mmsi":{"path":"$.mmsi","type":"integer"},'
'"lat":{"path":"$.latitude","type":"float"},'
'"lon":{"path":"$.longitude","type":"float"}}}'
)
)
def override_get_current_user():
return User(
id=1,
username="testuser",
email="test@example.com",
password_hash="hashed",
role="admin",
is_active=True,
)
def override_ai_client():
return FakeAIClient()
app.dependency_overrides = {
get_current_user: override_get_current_user,
get_ai_provider_client: override_ai_client,
}
transport = ASGITransport(app=app)
try:
async with AsyncClient(transport=transport, base_url="http://test") as client:
response = await client.post(
"/api/v1/datasources/mappings/propose",
json={
"sample_payload": SAMPLE_AIS,
"target_schema": "vessel_ais",
"use_ai": True,
},
)
finally:
app.dependency_overrides.clear()
assert response.status_code == 200
payload = response.json()
assert payload["mapping_json"]["meta"]["generated_by"] == "ai_provider"
assert seen_context["sample_payload"]["data"][0]["api_token"] == "[REDACTED]"

View File

@@ -121,6 +121,25 @@ class TestCollectionTaskModel:
)
assert task.records_processed == 100
def test_task_with_phase_progress(self):
"""Test collection task phase-level progress fields"""
task = CollectionTask(
datasource_id=1,
status="running",
phase="fetching",
phase_progress=42.5,
phase_message="Downloading dataset",
phase_current=1024,
phase_total=4096,
phase_unit="bytes",
)
assert task.phase == "fetching"
assert task.phase_progress == 42.5
assert task.phase_message == "Downloading dataset"
assert task.phase_current == 1024
assert task.phase_total == 4096
assert task.phase_unit == "bytes"
def test_task_error_message(self):
"""Test collection task with error message"""
task = CollectionTask(

View File

@@ -0,0 +1,161 @@
"""Tests for the v4 vessel_ais aggregation strategy."""
from datetime import datetime, timedelta, timezone
from unittest.mock import AsyncMock
import pytest
from app.models.vessel import AISRawObservation
from app.services.vessel_aggregation_strategy import (
DEFAULT_STRATEGY,
StrategyValidationError,
validate_strategy,
)
from app.services.vessel_ais_aggregation import aggregate_vessel_observations
def _obs(*, source: str, mmsi: int, observed_at: datetime, **payload) -> AISRawObservation:
payload = {"mmsi": mmsi, "lat": 50.0, "lon": 10.0, **payload}
delivery_mode = "realtime_stream" if source == "aisstream_vessels" else "polling"
transport = "websocket" if source == "aisstream_vessels" else "http"
return AISRawObservation(
target_schema="vessel_ais",
source=source,
entity_key=str(mmsi),
delivery_mode=delivery_mode,
transport=transport,
message_type="PositionReport",
observation_hash=f"{source}:{mmsi}:{observed_at.isoformat()}",
observed_at=observed_at,
collected_at=observed_at,
normalized_payload=payload,
raw_payload=payload,
quality_flags=[],
)
def test_validate_rejects_unknown_field():
with pytest.raises(StrategyValidationError, match="unknown vessel_ais field"):
validate_strategy({"vessel_ais": {"field_rules": {"definitely_not_a_field": {"mode": "newest"}}}})
def test_validate_rejects_dynamic_lock_without_flag():
with pytest.raises(StrategyValidationError, match="allow_dynamic_lock"):
validate_strategy(
{
"vessel_ais": {
"field_rules": {"lat": {"mode": "source_priority"}},
"allow_dynamic_lock": False,
}
}
)
def test_validate_allows_dynamic_lock_with_flag():
normalized = validate_strategy(
{
"version": 0,
"vessel_ais": {
"field_rules": {"lat": {"mode": "source_priority", "source_priority": ["barentswatch_vessels"]}},
"allow_dynamic_lock": True,
},
}
)
assert normalized["vessel_ais"]["field_rules"]["lat"]["mode"] == "source_priority"
assert normalized["version"] == 1
def test_validate_increments_version():
first = validate_strategy({"version": 5, "vessel_ais": {}})
assert first["version"] == 6
@pytest.mark.asyncio
async def test_strategy_field_rule_promotes_specific_source(monkeypatch):
now = datetime(2026, 5, 4, 12, 0, tzinfo=timezone.utc)
obs_a = _obs(
source="aisstream_vessels",
mmsi=257123000,
observed_at=now,
name="AISSTREAM ONE",
vessel_type_name="Cargo",
)
obs_b = _obs(
source="barentswatch_vessels",
mmsi=257123000,
observed_at=now - timedelta(seconds=1),
name="BARENTSWATCH ONE",
vessel_type_name="Cargo",
)
strategy = {
"version": 7,
"vessel_ais": {
"source_priority": [],
"field_rules": {
"name": {"mode": "source_priority", "source_priority": ["barentswatch_vessels", "aisstream_vessels"]},
},
"freshness": {"realtime_stream_seconds": 0, "polling_seconds": 0},
"allow_dynamic_lock": False,
},
}
db = AsyncMock()
vessels = await aggregate_vessel_observations(
db,
[obs_a, obs_b],
write_conflicts=False,
strategy=strategy,
)
assert len(vessels) == 1
vessel = vessels[0]
assert vessel["name"] == "BARENTSWATCH ONE"
assert vessel["field_sources"]["name"] == "barentswatch_vessels"
assert vessel["selected_reasons"]["name"] == "source_priority"
assert vessel["aggregation_strategy_version"] == 7
@pytest.mark.asyncio
async def test_strategy_freshness_falls_back_to_polling_when_realtime_stale():
now = datetime(2026, 5, 4, 12, 0, tzinfo=timezone.utc)
stale_realtime = _obs(
source="aisstream_vessels",
mmsi=257123000,
observed_at=now - timedelta(hours=1),
lat=58.0,
lon=10.0,
)
fresh_polling = _obs(
source="barentswatch_vessels",
mmsi=257123000,
observed_at=now - timedelta(seconds=30),
lat=60.0,
lon=11.0,
)
strategy = {
"version": 1,
"vessel_ais": {
"source_priority": ["aisstream_vessels", "barentswatch_vessels"],
"field_rules": {},
"freshness": {"realtime_stream_seconds": 900, "polling_seconds": 7200},
"allow_dynamic_lock": False,
},
}
db = AsyncMock()
vessels = await aggregate_vessel_observations(
db,
[stale_realtime, fresh_polling],
write_conflicts=False,
strategy=strategy,
)
assert vessels[0]["field_sources"]["lat"] == "barentswatch_vessels"
assert vessels[0]["lat"] == 60.0
def test_default_strategy_is_stable():
assert DEFAULT_STRATEGY["vessel_ais"]["allow_dynamic_lock"] is False
assert "freshness" in DEFAULT_STRATEGY["vessel_ais"]

View File

@@ -0,0 +1,155 @@
"""Tests for v5 enrichment + conflict promote-to-rule."""
from datetime import datetime, timedelta, timezone
from unittest.mock import AsyncMock
import pytest
from app.models.vessel import AISConflictRecord, AISRawObservation
from app.models.vessel_enrichment import VesselMediaEnrichment, VesselProfileEnrichment
from app.services.vessel_ais_aggregation import aggregate_vessel_observations
from app.services.vessel_enrichment import (
_apply_upsert,
get_vessel_enrichment_bundle,
)
class _StoreSession:
"""Minimal AsyncSession stand-in that tracks mmsi-keyed enrichment + a strategy."""
def __init__(self, *, profile=None, media=None, conflicts=None):
self.profile = profile
self.media = media
self.conflicts = list(conflicts or [])
self.added: list = []
self.committed = False
async def get(self, model, key):
if model is VesselProfileEnrichment:
return self.profile if self.profile and self.profile.mmsi == key else None
if model is VesselMediaEnrichment:
return self.media if self.media and self.media.mmsi == key else None
return None
@pytest.mark.asyncio
async def test_enrichment_bundle_filters_expired_records():
now = datetime.now(timezone.utc)
fresh = VesselProfileEnrichment(
mmsi=257123000,
source="local_cache",
payload={"vessel_subtype": "Container"},
fetched_at=now - timedelta(hours=1),
expires_at=now + timedelta(days=7),
confidence=0.9,
)
expired_media = VesselMediaEnrichment(
mmsi=257123000,
source="vesselfinder",
payload={"images": ["https://example.com/a.jpg"]},
fetched_at=now - timedelta(days=30),
expires_at=now - timedelta(days=1),
)
db = _StoreSession(profile=fresh, media=expired_media)
bundle = await get_vessel_enrichment_bundle(db, 257123000)
assert bundle["profile"]["payload"]["vessel_subtype"] == "Container"
assert bundle["media"] is None
def test_apply_upsert_preserves_payload_and_metadata():
record = VesselProfileEnrichment(mmsi=257123000)
out = _apply_upsert(
record,
{
"source": "vesselfinder",
"payload": {"vessel_subtype": "Container", "operator": "Maersk"},
"expires_at": "2026-12-31T00:00:00Z",
"confidence": 0.85,
"reference_url": "https://www.vesselfinder.com/vessels/257123000",
},
)
assert out["payload"]["operator"] == "Maersk"
assert out["confidence"] == 0.85
assert record.reference_url == "https://www.vesselfinder.com/vessels/257123000"
assert record.expires_at is not None
assert record.expires_at.year == 2026
def _obs(*, source: str, mmsi: int, observed_at, **payload) -> AISRawObservation:
payload = {"mmsi": mmsi, "lat": 60.0, "lon": 5.0, **payload}
delivery_mode = "realtime_stream" if source == "aisstream_vessels" else "polling"
transport = "websocket" if source == "aisstream_vessels" else "http"
return AISRawObservation(
target_schema="vessel_ais",
source=source,
entity_key=str(mmsi),
delivery_mode=delivery_mode,
transport=transport,
message_type="PositionReport",
observation_hash=f"{source}:{mmsi}:{observed_at.isoformat()}",
observed_at=observed_at,
collected_at=observed_at,
normalized_payload=payload,
raw_payload=payload,
quality_flags=[],
)
@pytest.mark.asyncio
async def test_promoted_rule_wins_during_aggregation():
"""Simulate the strategy that conflict-promote-to-rule writes."""
now = datetime.now(timezone.utc)
obs_a = _obs(
source="aisstream_vessels",
mmsi=257111000,
observed_at=now,
name="STREAM NAME",
vessel_type_name="Cargo",
)
obs_b = _obs(
source="barentswatch_vessels",
mmsi=257111000,
observed_at=now - timedelta(seconds=1),
name="REST NAME",
vessel_type_name="Cargo",
)
promoted_strategy = {
"version": 99,
"vessel_ais": {
"source_priority": [],
"field_rules": {
"name": {"mode": "source_priority", "source_priority": ["barentswatch_vessels"]}
},
"freshness": {"realtime_stream_seconds": 0, "polling_seconds": 0},
"allow_dynamic_lock": False,
},
}
db = AsyncMock()
vessels = await aggregate_vessel_observations(
db,
[obs_a, obs_b],
write_conflicts=False,
strategy=promoted_strategy,
)
assert vessels[0]["name"] == "REST NAME"
assert vessels[0]["selected_reasons"]["name"] == "source_priority"
assert vessels[0]["aggregation_strategy_version"] == 99
def test_conflict_record_holds_selected_source():
"""Sanity: the promote-to-rule API reads selected_source from this column."""
record = AISConflictRecord(
target_schema="vessel_ais",
entity_key="257111000",
field="name",
candidates={"a": "X", "b": "Y"},
selected_source="barentswatch_vessels",
selected_value="Y",
selected_reason="delivery_mode_priority",
)
serialized = record.to_dict()
assert serialized["selected_source"] == "barentswatch_vessels"
assert serialized["field"] == "name"

View File

@@ -0,0 +1,675 @@
from datetime import datetime, timedelta, timezone
from unittest.mock import AsyncMock
import pytest
from httpx import ASGITransport, AsyncClient
from app.api.v1 import visualization
from app.api.v1.visualization import convert_vessels_to_geojson
from app.db.session import get_db
from app.main import app
from app.models.vessel import AISRawObservation, VesselPosition, VesselStatic
from app.services import barentswatch
from app.services.collectors.aisstream import AISStreamCollector
from app.services.collectors.vessel_ais import VesselAISCollector
from app.services.vessel_ais_aggregation import (
aggregate_vessel_observations,
build_field_conflict_candidates,
build_observation_hash,
record_vessel_ais_observation,
)
def test_vessel_collector_transforms_barentswatch_like_records():
collector = VesselAISCollector()
records = collector.transform(
[
{
"mmsi": "257123000",
"lat": "59.91",
"lon": "10.73",
"sog": 12.4,
"cog": 214,
"nav_status": 0,
"shipType": 70,
"name": "OSLO TRADER",
},
{"mmsi": "bad", "lat": 120, "lon": 10},
]
)
assert len(records) == 1
assert records[0]["mmsi"] == 257123000
assert records[0]["vessel_type_name"] == "Cargo"
assert records[0]["lat"] == pytest.approx(59.91)
def test_vessel_observation_hash_is_stable_for_same_payload():
observed_at = datetime(2026, 4, 30, 12, 0, tzinfo=timezone.utc)
payload = {
"mmsi": 257123000,
"lat": 59.91,
"lon": 10.73,
"received_at": observed_at,
}
first = build_observation_hash(
source="barentswatch_vessels",
entity_key="257123000",
message_type="PositionReport",
observed_at=observed_at,
normalized_payload=payload,
)
second = build_observation_hash(
source="barentswatch_vessels",
entity_key="257123000",
message_type="PositionReport",
observed_at=observed_at,
normalized_payload=dict(reversed(payload.items())),
)
assert first == second
assert len(first) == 64
@pytest.mark.asyncio
async def test_record_vessel_ais_observation_skips_existing_hash():
observed_at = datetime(2026, 4, 30, 12, 0, tzinfo=timezone.utc)
class _Result:
def scalar_one_or_none(self):
return 123
class _Session:
def __init__(self):
self.added = []
async def execute(self, _stmt):
return _Result()
def add(self, item):
self.added.append(item)
db = _Session()
observation = await record_vessel_ais_observation(
db,
source="barentswatch_vessels",
normalized_payload={
"mmsi": 257123000,
"lat": 59.91,
"lon": 10.73,
"received_at": observed_at,
},
delivery_mode="polling",
transport="http",
observed_at=observed_at.isoformat(),
)
assert observation is None
assert db.added == []
def test_build_field_conflict_candidates_from_raw_observations():
observations = [
AISRawObservation(
source="barentswatch_vessels",
normalized_payload={"name": "OSLO TRADER", "flag": "NO"},
),
AISRawObservation(
source="aisstream_vessels",
normalized_payload={"name": "OSLO TRADER II", "flag": "NO"},
),
]
conflicts = build_field_conflict_candidates(observations)
assert conflicts == [
{
"field": "name",
"candidates": {
"aisstream_vessels": "OSLO TRADER II",
"barentswatch_vessels": "OSLO TRADER",
},
"status": "candidate",
}
]
@pytest.mark.asyncio
async def test_aggregate_vessel_observations_prefers_realtime_and_records_conflict():
observed_at = datetime.now(timezone.utc) - timedelta(minutes=5)
class _Result:
def scalar_one_or_none(self):
return None
class _Session:
def __init__(self):
self.added = []
async def execute(self, _stmt):
return _Result()
def add(self, item):
self.added.append(item)
db = _Session()
observations = [
AISRawObservation(
id=1,
source="barentswatch_vessels",
entity_key="257123000",
delivery_mode="polling",
transport="http",
observed_at=observed_at,
collected_at=observed_at,
normalized_payload={
"mmsi": 257123000,
"name": "OSLO TRADER",
"lat": 59.91,
"lon": 10.73,
},
),
AISRawObservation(
id=2,
source="aisstream_vessels",
entity_key="257123000",
delivery_mode="realtime_stream",
transport="websocket",
observed_at=observed_at + timedelta(seconds=10),
collected_at=observed_at + timedelta(seconds=10),
normalized_payload={
"mmsi": 257123000,
"vessel_type": 79,
"lat": 59.92,
"lon": 10.74,
},
raw_payload={"MetaData": {"ShipName": "OSLO TRADER II "}},
),
]
vessels = await aggregate_vessel_observations(db, observations)
assert vessels[0]["lat"] == pytest.approx(59.92)
assert vessels[0]["field_sources"]["lat"] == "aisstream_vessels"
assert vessels[0]["name"] == "OSLO TRADER II"
assert vessels[0]["vessel_type_name"] == "Cargo"
assert vessels[0]["source_summary"]["aisstream_vessels"]["observation_count"] == 1
assert vessels[0]["source_summary"]["barentswatch_vessels"]["delivery_mode"] == "polling"
assert vessels[0]["conflict_count"] == 0
assert db.added == []
@pytest.mark.asyncio
async def test_vessel_collector_writes_raw_observations_only(monkeypatch):
collector = VesselAISCollector()
collector.update_progress = AsyncMock()
record_observation = AsyncMock()
update_health = AsyncMock()
broadcast_custom = AsyncMock()
monkeypatch.setattr(
"app.services.collectors.vessel_ais.record_vessel_ais_observation",
record_observation,
)
monkeypatch.setattr(
"app.services.collectors.vessel_ais.update_ais_source_health",
update_health,
)
monkeypatch.setattr(
"app.services.collectors.vessel_ais.broadcaster.broadcast_custom",
broadcast_custom,
)
class _Session:
def __init__(self):
self.added = []
self.committed = False
async def get(self, *_args):
return None
def add(self, item):
self.added.append(item)
async def execute(self, _stmt):
return None
async def commit(self):
self.committed = True
db = _Session()
observed_at = datetime(2026, 4, 30, 12, 0, tzinfo=timezone.utc)
saved = await collector._save_data(
db,
[
{
"mmsi": 257123000,
"name": "OSLO TRADER",
"lat": 59.91,
"lon": 10.73,
"received_at": observed_at,
}
],
)
assert saved == 1
assert db.committed is True
# BarentsWatch must funnel through the unified AIS pipeline only — no legacy writes.
assert not any(isinstance(item, VesselStatic) for item in db.added)
assert not any(isinstance(item, VesselPosition) for item in db.added)
record_observation.assert_awaited_once()
assert record_observation.await_args.kwargs["source"] == "barentswatch_vessels"
assert record_observation.await_args.kwargs["normalized_payload"]["mmsi"] == 257123000
update_health.assert_awaited_once()
broadcast_custom.assert_awaited_once()
assert broadcast_custom.await_args.args[0] == "vessels"
assert broadcast_custom.await_args.args[1]["action"] == "upsert"
assert broadcast_custom.await_args.args[1]["vessels"][0]["mmsi_display"] == "257123000"
def test_aisstream_collector_normalizes_position_report():
collector = AISStreamCollector()
records = collector.transform(
[
{
"MessageType": "PositionReport",
"MetaData": {
"MMSI": 257123000,
"ShipName": "OSLO TRADER ",
"time_utc": "2026-04-30T12:00:00Z",
},
"Message": {
"PositionReport": {
"Latitude": 59.91,
"Longitude": 10.73,
"Sog": 12.4,
"Cog": 214,
"TrueHeading": 215,
"NavigationalStatus": 0,
}
},
}
]
)
assert len(records) == 1
assert records[0]["mmsi"] == 257123000
assert records[0]["lat"] == pytest.approx(59.91)
assert records[0]["name"] == "OSLO TRADER"
assert records[0]["_message_type"] == "PositionReport"
def test_aisstream_collector_maps_ship_static_type_name():
collector = AISStreamCollector()
records = collector.transform(
[
{
"MessageType": "ShipStaticData",
"MetaData": {
"MMSI": 257123000,
"time_utc": "2026-04-30T12:00:00Z",
},
"Message": {
"ShipStaticData": {
"Name": "OSLO TRADER",
"Type": 79,
"CallSign": "LAAB",
}
},
}
]
)
assert len(records) == 1
assert records[0]["vessel_type"] == 79
assert records[0]["vessel_type_name"] == "Cargo"
@pytest.mark.asyncio
async def test_aisstream_collector_writes_only_raw_observations(monkeypatch):
collector = AISStreamCollector()
collector.update_progress = AsyncMock()
record_observation = AsyncMock(return_value=object())
update_health = AsyncMock()
monkeypatch.setattr(
"app.services.collectors.aisstream.record_vessel_ais_observation",
record_observation,
)
monkeypatch.setattr(
"app.services.collectors.aisstream.update_ais_source_health",
update_health,
)
class _Session:
def __init__(self):
self.added = []
self.committed = False
def add(self, item):
self.added.append(item)
async def commit(self):
self.committed = True
db = _Session()
saved = await collector._save_data(
db,
[
{
"mmsi": 257123000,
"lat": 59.91,
"lon": 10.73,
"received_at": datetime(2026, 4, 30, 12, 0, tzinfo=timezone.utc),
"_message_type": "PositionReport",
}
],
)
assert saved == 1
assert db.added == []
assert db.committed is True
record_observation.assert_awaited_once()
assert record_observation.await_args.kwargs["source"] == "aisstream_vessels"
update_health.assert_awaited_once()
@pytest.mark.asyncio
async def test_aisstream_stream_record_broadcasts_vessel_delta(monkeypatch):
collector = AISStreamCollector()
record_observation = AsyncMock(return_value=object())
update_health = AsyncMock()
broadcast_custom = AsyncMock()
monkeypatch.setattr(
"app.services.collectors.aisstream.record_vessel_ais_observation",
record_observation,
)
monkeypatch.setattr(
"app.services.collectors.aisstream.update_ais_source_health",
update_health,
)
monkeypatch.setattr(
"app.services.collectors.aisstream.broadcaster.broadcast_custom",
broadcast_custom,
)
class _Session:
async def commit(self):
pass
created = await collector._save_stream_record(
_Session(),
{
"mmsi": 257123000,
"lat": 59.91,
"lon": 10.73,
"cog": 214,
"received_at": datetime(2026, 4, 30, 12, 0, tzinfo=timezone.utc),
},
)
assert created is True
record_observation.assert_awaited_once()
broadcast_custom.assert_awaited_once()
assert broadcast_custom.await_args.args[0] == "vessels"
assert broadcast_custom.await_args.args[1]["action"] == "upsert"
assert broadcast_custom.await_args.args[1]["vessels"][0]["mmsi_display"] == "257123000"
def test_barentswatch_reads_credentials_from_zshrc(tmp_path):
zshrc = tmp_path / ".zshrc"
zshrc.write_text(
"\n".join(
[
"export BARENTSWATCH_CLIENT_ID='client-from-zshrc'",
'export BARENTSWATCH_CLIENT_SECRET="secret-from-zshrc" # local dev credential',
]
),
encoding="utf-8",
)
values = barentswatch._read_zshrc_env(zshrc)
assert values["BARENTSWATCH_CLIENT_ID"] == "client-from-zshrc"
assert values["BARENTSWATCH_CLIENT_SECRET"] == "secret-from-zshrc"
@pytest.mark.asyncio
async def test_barentswatch_resolves_config_from_zshrc(tmp_path, monkeypatch):
zshrc = tmp_path / ".zshrc"
zshrc.write_text(
"\n".join(
[
"export BARENTSWATCH_CLIENT_ID=client-from-zshrc",
"export BARENTSWATCH_CLIENT_SECRET=secret-from-zshrc",
]
),
encoding="utf-8",
)
monkeypatch.delenv("BARENTSWATCH_CLIENT_ID", raising=False)
monkeypatch.delenv("BARENTSWATCH_CLIENT_SECRET", raising=False)
monkeypatch.delenv("BARRENTSWATCH_CLIENT_ID", raising=False)
monkeypatch.delenv("BARRENTSWATCH_CLIENT_SECRET", raising=False)
monkeypatch.setattr(barentswatch.Path, "home", lambda: tmp_path)
config = await barentswatch.resolve_barentswatch_config(None)
assert config.client_id == "client-from-zshrc"
assert config.client_secret == "secret-from-zshrc"
assert config.credential_source == "~/.zshrc"
def test_convert_vessels_to_geojson():
position = VesselPosition(
mmsi=257123000,
lat=59.91,
lon=10.73,
sog=12.4,
cog=214,
heading=215,
nav_status=0,
received_at=datetime(2026, 4, 28, 1, 0, tzinfo=timezone.utc),
)
static = VesselStatic(
mmsi=257123000,
name="OSLO TRADER",
vessel_type=70,
vessel_type_name="Cargo",
flag="NO",
length=185,
)
payload = convert_vessels_to_geojson([(position, static)])
assert payload["type"] == "FeatureCollection"
assert payload["features"][0]["geometry"]["coordinates"] == [10.73, 59.91]
assert payload["features"][0]["properties"]["mmsi"] == 257123000
assert payload["features"][0]["properties"]["vessel_type_name"] == "Cargo"
def test_convert_vessels_to_geojson_dedupes_mmsi_rows():
first = VesselPosition(
mmsi=257123000,
lat=59.91,
lon=10.73,
received_at=datetime(2026, 4, 28, 1, 0, tzinfo=timezone.utc),
)
duplicate = VesselPosition(
mmsi=257123000,
lat=60.01,
lon=10.83,
received_at=datetime(2026, 4, 28, 1, 0, tzinfo=timezone.utc),
)
other = VesselPosition(
mmsi=257456000,
lat=60.3,
lon=5.3,
received_at=datetime(2026, 4, 28, 0, 59, tzinfo=timezone.utc),
)
payload = convert_vessels_to_geojson(
[
(first, VesselStatic(mmsi=257123000, name="OSLO TRADER")),
(duplicate, VesselStatic(mmsi=257123000, name="OSLO TRADER DUP")),
(other, VesselStatic(mmsi=257456000, name="BERGEN FERRY")),
]
)
mmsis = [feature["properties"]["mmsi"] for feature in payload["features"]]
assert mmsis == [257123000, 257456000]
assert payload["features"][0]["geometry"]["coordinates"] == [10.73, 59.91]
@pytest.mark.asyncio
async def test_vessels_geojson_endpoint_filters_type_and_bbox():
now = datetime(2026, 4, 28, 1, 0, tzinfo=timezone.utc)
rows = [
(
VesselPosition(mmsi=1, lat=59.9, lon=10.7, received_at=now),
VesselStatic(mmsi=1, name="Cargo Ship", vessel_type=70, vessel_type_name="Cargo"),
),
(
VesselPosition(mmsi=2, lat=60.3, lon=5.3, received_at=now - timedelta(minutes=1)),
VesselStatic(mmsi=2, name="Passenger Ship", vessel_type=60, vessel_type_name="Passenger"),
),
]
class _Result:
def all(self):
return rows
class _FakeSession:
async def execute(self, _query):
return _Result()
async def override_get_db():
yield _FakeSession()
app.dependency_overrides[get_db] = override_get_db
transport = ASGITransport(app=app)
try:
async with AsyncClient(transport=transport, base_url="http://test") as client:
response = await client.get(
"/api/v1/visualization/geo/vessels",
params={"bbox": "0,50,20,70", "type": "cargo", "limit": 0},
)
assert response.status_code == 200
data = response.json()
assert data["count"] == 1
assert data["features"][0]["properties"]["name"] == "Cargo Ship"
assert data["stats"]["by_type"]["Cargo"] == 1
finally:
app.dependency_overrides.clear()
@pytest.mark.asyncio
async def test_vessels_geojson_merges_raw_and_legacy_sources(monkeypatch):
now = datetime(2026, 4, 28, 1, 0, tzinfo=timezone.utc)
monkeypatch.setattr(
visualization,
"get_aggregated_vessels",
AsyncMock(
return_value=[
{
"mmsi": 1,
"lat": 59.9,
"lon": 10.7,
"received_at": now,
"name": "AISSTREAM SHIP",
"vessel_type_name": "Cargo",
"source_summary": {"aisstream_vessels": {"message_types": ["PositionReport"]}},
}
]
),
)
rows = [
(
VesselPosition(mmsi=1, lat=60.0, lon=10.8, received_at=now),
VesselStatic(mmsi=1, name="LEGACY DUP", vessel_type_name="Cargo"),
),
(
VesselPosition(mmsi=2, lat=60.3, lon=5.3, received_at=now),
VesselStatic(mmsi=2, name="BARENTSWATCH ONLY", vessel_type_name="Passenger"),
),
]
class _Result:
def all(self):
return rows
class _FakeSession:
async def execute(self, _query):
return _Result()
async def override_get_db():
yield _FakeSession()
app.dependency_overrides[get_db] = override_get_db
transport = ASGITransport(app=app)
try:
async with AsyncClient(transport=transport, base_url="http://test") as client:
response = await client.get("/api/v1/visualization/geo/vessels")
assert response.status_code == 200
data = response.json()
names = {feature["properties"]["mmsi"]: feature["properties"]["name"] for feature in data["features"]}
assert data["count"] == 2
assert names == {1: "AISSTREAM SHIP", 2: "BARENTSWATCH ONLY"}
assert data["diagnostics"]["legacy_backfilled_mmsi"] == 1
finally:
app.dependency_overrides.clear()
@pytest.mark.asyncio
async def test_vessel_name_fallbacks_reports_mmsi_display_names(monkeypatch):
now = datetime(2026, 4, 28, 1, 0, tzinfo=timezone.utc)
monkeypatch.setattr(
visualization,
"get_aggregated_vessels",
AsyncMock(
return_value=[
{
"mmsi": 257123000,
"lat": 59.9,
"lon": 10.7,
"received_at": now,
"name": "MMSI 257123000",
"vessel_type_name": "Other",
"source_summary": {
"aisstream_vessels": {
"latest_observed_at": now,
"message_types": ["PositionReport"],
}
},
}
]
),
)
class _Result:
def all(self):
return []
class _FakeSession:
async def execute(self, _query):
return _Result()
async def override_get_db():
yield _FakeSession()
app.dependency_overrides[get_db] = override_get_db
transport = ASGITransport(app=app)
try:
async with AsyncClient(transport=transport, base_url="http://test") as client:
response = await client.get("/api/v1/visualization/vessels/name-fallbacks")
assert response.status_code == 200
data = response.json()
assert data["count"] == 1
assert data["items"][0]["mmsi"] == "257123000"
assert data["items"][0]["message_types"] == ["PositionReport"]
finally:
app.dependency_overrides.clear()

View File

@@ -215,3 +215,141 @@ async def test_compute_centers_geojson_endpoint_returns_stats():
assert data["features"][0]["properties"]["data_type"] == "compute_center"
finally:
app.dependency_overrides.clear()
@pytest.mark.asyncio
async def test_visualization_geo_summary_returns_counts(monkeypatch):
records = [
_build_record(
record_id=1,
source="arcgis_cables",
data_type="submarine_cable",
name="Test Cable",
country="",
city="",
latitude=0,
longitude=0,
metadata={
"route_coordinates": [[[0, 0], [1, 1]]],
"status": "active",
},
),
_build_record(
record_id=2,
source="arcgis_landing_points",
data_type="landing_point",
name="Test Landing",
country="United States",
city="New York",
latitude=40.7,
longitude=-74.0,
metadata={"city_id": 10},
),
_build_record(
record_id=3,
source="celestrak_tle",
data_type="satellite_tle",
name="TESTSAT",
country="",
city="",
latitude=0,
longitude=0,
metadata={
"norad_cat_id": 12345,
"tle_line1": "1 12345U 98067A 24001.00000000 .00000000 00000-0 00000-0 0 9991",
"tle_line2": "2 12345 51.6000 100.0000 0001000 10.0000 20.0000 15.50000000 01",
},
),
_build_record(
record_id=4,
source="top500",
data_type="supercomputer",
name="Frontier",
country="United States",
city="Oak Ridge",
latitude=35.93,
longitude=-84.31,
metadata={"rank": 1, "rmax": 1102000.0},
),
_build_record(
record_id=5,
source="epoch_ai_gpu",
data_type="gpu_cluster",
name="Colossus",
country="United States",
city="Memphis",
latitude=35.15,
longitude=-90.05,
metadata={"value": "20000", "unit": "TFlop/s"},
),
]
class _ScalarResult:
def __init__(self, rows=None, scalar_value=None):
self._rows = rows or []
self._scalar_value = scalar_value
def scalar(self):
return self._scalar_value
def all(self):
return list(self._rows)
def scalars(self):
class _Scalars:
def __init__(self, rows):
self._rows = rows
def all(self):
return self._rows
return _Scalars(self._rows)
class _FakeSession:
async def execute(self, query):
query_text = str(query).lower()
if "bgp_incidents" in query_text:
return _ScalarResult(scalar_value=2)
if "bgp_anomalies" in query_text:
return _ScalarResult(scalar_value=3)
if "ais_raw_observations" in query_text or "vessel_position" in query_text:
return _ScalarResult(rows=[])
return _ScalarResult(rows=records)
async def get(self, *_args, **_kwargs):
return None
async def override_get_db():
yield _FakeSession()
async def _fake_build_bgp_collector_coverage(*_args, **_kwargs):
return [
{"collector": "rrc00"},
{"collector": "rrc01"},
]
monkeypatch.setattr(
"app.api.v1.visualization.build_bgp_collector_coverage",
_fake_build_bgp_collector_coverage,
)
app.dependency_overrides[get_db] = override_get_db
transport = ASGITransport(app=app)
try:
async with AsyncClient(transport=transport, base_url="http://test") as client:
response = await client.get("/api/v1/visualization/geo/summary")
assert response.status_code == 200
stats = response.json()["stats"]
assert stats["cable_count"] == 1
assert stats["landing_point_count"] == 1
assert stats["satellite_count"] == 1
assert stats["compute_center_count"] == 2
assert stats["supercomputer_count"] == 1
assert stats["gpu_cluster_count"] == 1
assert stats["bgp_event_count"] == 2
assert stats["bgp_incident_count"] == 2
assert stats["bgp_anomaly_count"] == 3
assert stats["bgp_collector_count"] == 2
finally:
app.dependency_overrides.clear()

View File

@@ -0,0 +1,46 @@
import pytest
from app.core.websocket.manager import ConnectionManager
class FakeWebSocket:
def __init__(self):
self.accepted = False
self.sent = []
self.closed = False
async def accept(self):
self.accepted = True
async def send_json(self, message):
self.sent.append(message)
async def close(self):
self.closed = True
@pytest.mark.asyncio
async def test_channel_subscribers_receive_channel_broadcasts():
manager = ConnectionManager()
socket = FakeWebSocket()
await manager.connect(socket, "user-1")
manager.subscribe(socket, ["dashboard"])
await manager.broadcast({"type": "data_frame", "channel": "dashboard"}, channel="dashboard")
assert socket.accepted is True
assert socket.sent == [{"type": "data_frame", "channel": "dashboard"}]
@pytest.mark.asyncio
async def test_disconnect_removes_channel_subscriptions():
manager = ConnectionManager()
socket = FakeWebSocket()
await manager.connect(socket, "user-1")
manager.subscribe(socket, ["dashboard"])
manager.disconnect(socket, "user-1")
await manager.broadcast({"type": "data_frame", "channel": "dashboard"}, channel="dashboard")
assert socket.sent == []
assert "dashboard" not in manager.channel_subscriptions

View File

@@ -86,6 +86,12 @@ CREATE TABLE collection_tasks (
id BIGSERIAL PRIMARY KEY,
datasource_id INTEGER NOT NULL REFERENCES data_sources(id) ON DELETE CASCADE,
status task_status NOT NULL DEFAULT 'pending',
phase VARCHAR(30) DEFAULT 'queued',
phase_progress FLOAT,
phase_message VARCHAR(255),
phase_current BIGINT,
phase_total BIGINT,
phase_unit VARCHAR(30),
started_at TIMESTAMP WITH TIME ZONE,
completed_at TIMESTAMP WITH TIME ZONE,
records_processed INTEGER DEFAULT 0,

View File

@@ -18,6 +18,9 @@ services:
build:
context: .
dockerfile: aiprovider/Dockerfile
args:
PYTHON_IMAGE: ${PYTHON_IMAGE:-python:3.14-slim}
UV_IMAGE: ${UV_IMAGE:-ghcr.io/astral-sh/uv:latest}
container_name: planet_aiprovider
ports:
- "8010:8010"

View File

@@ -5,6 +5,12 @@ services:
build:
context: .
dockerfile: aiprovider/Dockerfile
args:
PYTHON_IMAGE: ${PYTHON_IMAGE:-python:3.14-slim}
UV_IMAGE: ${UV_IMAGE:-ghcr.io/astral-sh/uv:latest}
env_file:
- ./aiprovider/.env
- ${PLANET_AI_PROVIDER_RUNTIME_ENV_FILE:-./aiprovider/.env}
container_name: planet_aiprovider
ports:
- "8010:8010"

View File

@@ -5,8 +5,12 @@ services:
build:
context: .
dockerfile: aiprovider/Dockerfile
args:
PYTHON_IMAGE: ${PYTHON_IMAGE:-python:3.14-slim}
UV_IMAGE: ${UV_IMAGE:-ghcr.io/astral-sh/uv:latest}
env_file:
- ./aiprovider/.env
- ${PLANET_AI_PROVIDER_RUNTIME_ENV_FILE:-./aiprovider/.env}
container_name: planet_aiprovider
ports:
- "8010:8010"

View File

@@ -8,6 +8,222 @@ This project follows the repository versioning rule:
- `improvement` -> `+0.0.1`bugfix + 小功能混合)
- `bugfix` -> `+0.0.1`
## [0.48.0] — 2026-05-07
Released: 2026-05-07
### ✨ Highlights
- 自定义数据源新增 REST / WebSocket 映射运行时,并提供本地 AIS mock WebSocket用于实时船只 upsert 链路验证。
- AIS 原始观测、聚合策略、字段来源、冲突记录与船舶 enrichment 继续完善Earth 船只实时展示链路更接近生产数据形态。
- Earth 全球态势 summary 改为轻量 SQL 聚合,并在卫星 current 异常时回退到最近有效 TLE 批次,避免统计接口被大规模明细读取拖慢。
### 🔧 Improvements
- 修复 `/geo/summary``/geo/satellites` 在大表下加载慢或超时的问题,并补充 `collected_data` 与 AIS raw 相关索引。
- WebSocket 管理器支持匿名连接、频道订阅清理和更稳的连接生命周期测试,前端 WebSocket candidates / fallback 更可靠。
- `planet.sh` 强化端口释放、端口诊断和前端启动流程mock AIS server 提供 Bun 脚本入口。
---
## [0.47.0] — 2026-04-30
Released: 2026-04-30
### ✨ Highlights
- 新增 AISStream WebSocket 船只采集器,并将 AIS 多源数据写入原始观测层,由聚合接口统一去重、合并和解释字段来源。
- 设置页新增 AISStream API Key、采集范围 preset、运行状态、连接验证和凭证教程入口让全球 AIS 采集链路可配置、可观察。
- Earth 船只图层默认不再限制 5000 艘,并统一 marker 颜色、详情卡、hover 和搜索结果的船型归一化显示。
### 🔧 Improvements
- 聚合接口新增 `field_sources``selected_reasons``source_summary``quality_flags` 和冲突记录调试接口,动态字段默认优先采用更新的实时流观测。
- AISStream 标准化支持 `MetaData.ShipName` 船名兜底,并将 AIS 数字船型映射为 Cargo / Tanker / Passenger / Fishing / Military。
- 将仓库 docs 技能改为通用文档工作流Planet 专属白名单、双语、裸文件标题和凭证教程规则迁移到 `docs/documentation-coverage-rules.md`
- 更新 AIS v4/v5 TODO 与计划文档,明确后续聚合策略配置、船舶资料 enrichment 和媒体缓存边界。
---
## [0.46.3] — 2026-04-30
Released: 2026-04-30
### 🐛 Fixes
- 优化 Starlink footprint 显示后的地球拖拽性能,避免旋转地球时每帧重建 footprint 大网格,同时保持现有视觉效果不变。
- 恢复点击线缆后的呼吸透明度动画,让 locked / hover 线缆重新使用既有 pulse 配置。
---
## [0.46.2] — 2026-04-30
Released: 2026-04-30
### 🐛 Fixes
- 修复 Earth 启动时高清材质、云图和图层可见性绕过 `startupPriority` 的问题,统一由启动队列按文档顺序加载。
- 修复保存为关闭的高清材质/图层仍会先加载再关闭的问题,并保持海陆基座作为国界线图层的常驻底图。
- 修复搜索跳转会误关媒体面板、船只轨迹末端不贴合当前船只、Iridium footprint 被地表层遮挡等 Earth 交互问题。
### 📝 Documentation
- 更新 Earth 图层顺序、样式参考、使用手册和 AIS 聚合计划,补齐中英文说明与后续接入策略。
---
## [0.46.1] — 2026-04-30
Released: 2026-04-30
### 🐛 Fixes
- 修复新增 technical docs 文件存在但未进入 Docs 前端白名单时,侧栏不显示且 Markdown 链接无法解析到 `/docs/<slug>` 的问题。
- 补齐数据源/采集器连接验证与 Earth Interactable 使用说明的英文文档,保证公开 Docs 切换 EN 时同名页面可访问。
- 清理中英文 technical docs 中裸 `.md` 文件名链接标题,改为面向读者的语义标题。
### 📝 Documentation
- 将 Docs 前端白名单、公开文档双语配对、裸文件名链接标题三项检查写入 Claude 与 Codex 的 docs 技能流程。
---
## [0.46.0] — 2026-04-30
Released: 2026-04-30
### ✨ Highlights
- Earth 新增通用 Interactable 图标层船只、算力中心、BGP 事件与观测站统一使用批量 Points、屏幕拾取、状态 glow 和状态缩放。
- BGP 事件保留向外扩散圈,观测站保留雷达扫描层,并与 Interactable 主图标解耦到稳定的地表渲染层级。
- 登陆点回归黄色球形 Sprite贴近海缆层级并保持更稳定的地表显示和遮挡表现。
### 🔧 Improvements
- 新增 SVG asset 到 canvas texture 的 Interactable 资产加载路径,支持统一图标资源、缓存和可选染色。
- 同坐标 Interactable 自动做地表切向避让,降低重叠物件无法选择的问题。
- 优化 Earth toolbar 初始尺寸注入,避免首次显示原始尺寸后再跳到缩放尺寸。
- 补充 Interactable 计划、使用说明、图层顺序和 Earth 前端上下文文档。
- 修复船只 hover/locked 状态仅发光但放大反馈不明显的问题,将已有状态缩放接入通用图标层。
---
## [0.45.0] — 2026-04-29
### ✨ Highlights
- 采集任务新增阶段级量化进度,`fetching` 可展示百分比、阶段说明和字节下载量。
- AI Provider 启动链路支持从 `aiprovider/.env``~/.zshrc` 注入运行期配置,并避免密钥/模型变化触发镜像重建。
- AI Provider Docker build context 收敛到服务必需文件,`uv sync` 接入 BuildKit 缓存以减少重复下载。
### 🔧 Improvements
- IPtoASN、OpenGeoFeed、NRO delegated 下载型采集器接入真实字节进度上报。
- 数据源页、采集中任务弹窗和任务历史页展示阶段摘要,并在 tooltip 中保留完整进度细节。
- 调整 Earth 船只默认高度偏移,进一步贴近地表展示。
---
## [0.44.2] — 2026-04-29
### 📝 Documentation
- 补充 Earth 船只图层技术文档,记录分桶 `THREE.Points` 批量渲染、同尺寸交互 overlay 和屏幕空间 picking 的设计约束。
- 同步 Earth 渲染图层顺序和样式参考,明确 AIS 船只 renderOrder、depthTest、图标尺寸、航向分桶与 hover 命中半径。
- 更新船只渲染性能计划状态,标注 `0.44.1` 已落地的实现与后续全球 AIS / LOD 演进方向。
---
## [0.44.1] — 2026-04-29
### 🐛 Fixes
- 修复 Earth 船只图层拖动不跟手的问题,将普通船只从独立 Sprite 切换为按航向分桶的批量 Points 渲染。
- 修正船只 hover/click 拾取错位,改为屏幕空间命中检测并在拖拽/惯性期间跳过 hover 拾取。
- 统一 AIS 船只普通态与交互态方向,并让 hover/locked glow 与普通图标保持同尺寸覆盖。
- 恢复船只深度测试并收敛默认图标尺寸,避免北部岛屿/冰面附近出现明显压盖陆地的视觉问题。
---
## [0.44.0] — 2026-04-29
### ✨ Highlights
- 重构数据源与采集器设置边界:数据源页回归目录和采集触发,采集器 endpoint、请求头、凭证与连接验证统一进入设置页
- BarentsWatch AIS 完整接入凭证解析、连接检查、默认教程、AI 生成教程和船只采集/可视化链路
- Earth 新增船只图例、缩放反馈胶囊、缩放感知拖拽灵敏度,并将船只渲染性能优化方案沉淀到 plans
- 仪表盘重启服务新增前端重启 action并让 runner 通过 `~/.zshrc` 继承本地环境变量
### 🔧 Improvements
- 采集器连接状态改为基于成功采集或手动连接校验 checksum 判断,避免只依赖前端样式状态
- 数据源页新增采集中任务标签和任务进度弹窗,内置与自定义数据源统一展示
- Earth 国界线进一步贴近地表,并补充船只图层渲染顺序、样式和用户手册说明
- docs skill 与 Claude/Codex 文档流程补齐技术文档和 plans 的职责边界
---
## [0.43.1] — 2026-04-28
### 🐛 Fixes
- 修正 `planet.sh` 在全量 restart 后启动 AI Provider 时的提示语义,避免把预期内未就绪描述成异常不健康
---
## [0.43.0] — 2026-04-28
### ✨ Highlights
- 新增 Earth 船舶追踪链路,接入 BarentsWatch AIS 凭证配置、采集器、后端 vessel 模型/API 与前端 Earth 船舶图层
- 新增自定义数据源映射流程,支持样本抓取、目标 schema、AI 辅助生成映射、预览校验和映射执行
- Settings 拆分 AI Provider 与采集器凭证配置DataSources 只保留采集状态、运行参数和必要引导
### 🔧 Improvements
- AI Provider 支持运行时 LLM 配置、provider preset 下拉与刷新,并在 Playground 中引导到 AI 配置页
- Markdown 渲染器补齐代码块复制按钮、语言标签、任务列表、图片、自动链接、删除线和文档主题样式
- Docs 公开导航改为显式元数据白名单,避免开发任务文档自动出现在“其他”分组
- 将 Codex/Claude cleanup、docs、goal-driven、release 流程补充 CLI-first 约束,并把 `rules.md` 整理成可按模块加载的工程规则
---
## [0.42.2] — 2026-04-28
### 🐛 Fixes
- Docs 中文模式下补齐左侧分组、文档标题、页头分类与搜索结果分类翻译,并更新文档站品牌标题/副标题文案
---
## [0.42.1] — 2026-04-28
### 🐛 Fixes
- 修正 release skill 的 feature 版本计算规则minor 进位时 patch 必须重置为 `0`,例如 `0.41.2` 应发布为 `0.42.0`
---
## [0.42.0] — 2026-04-28
### ✨ Highlights
- 新增公开 `/docs` 文档站支持中英文技术文档、使用手册、Quickstart、搜索、目录锚点与浅色/深色/跟随系统主题
- Earth 在无高清材质时新增轻量 Fresnel 边缘提示,并调整卫星覆盖默认显示与地表材质可读性
### 🔧 Improvements
- 将技术文档整理为 `docs/technical/zh``docs/technical/en`,并补充控制台、`planet.sh`、Earth 与公共组件使用说明
- 新增 `SegmentedControl` 公共滑块组件,支持缩放参数,复用到 docs 语言与主题切换
- Markdown 渲染器接入自定义滚动条,表格与代码块在深色模式和 overflow 场景下保持可读
- Docs 搜索结果支持内部滚动、点击外部关闭、重新聚焦恢复上次搜索结果
- Earth 工具栏展开状态与设置持久化版本迁移继续收口,改善默认面板和快捷关闭行为
---
## [0.41.2] — 2026-04-27
### 🔧 Improvements
- `planet.sh` 启动链路新增 verbose 滚动输出窗口,并在后端端口占用时打印目标地址和监听进程诊断
- Docker 构建支持通过 build args 覆盖 Python 与 uv 镜像,方便 Docker Hub 不稳定时切换镜像源
### 🐛 Fixes
- Earth 海缆登陆点改为基于相机射线与地球遮挡判断可见性,修复旋转后 pin 可见性滞后一帧的问题
### 🔧 Improvements
- `docker-compose*.yml` 为 AI Provider 构建传入 `PYTHON_IMAGE` / `UV_IMAGE` 参数,默认仍使用官方镜像
- 后端启动失败遇到 `Address already in use` 时输出 `lsof``ss` 与 PID 命令行信息
- verbose 模式下 AI Provider build、后端与前端启动日志会在 spinner 下方保留最新 5 行滚动展示
---
## [0.41.1] — 2026-04-27
### 🐛 Fixes
- 修复新闻直播面板设置项持久化失效:`closeTransientMobileOverlays` 通过旁路路径隐藏面板导致下次 persist 快照到错误状态,改为不重新从 DOM 读取面板可见性
- 修复登陆点 pin 在地球侧面被半截遮挡改为在接近地平线前dot < 0.05)主动隐藏,避免深度测试切片
### 🔧 Improvements
- 将所有画布绘制的图标抽取为 SVG存入 `frontend/public/earth/assets/icons/`,新增图标规范到 `rules.md`
---
## [0.41.0] — 2026-04-27
### ✨ Highlights

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@@ -0,0 +1,117 @@
# Documentation Coverage Rules
This file contains Planet-specific documentation coverage rules. Documentation skills and agents should read this file before deciding which docs to update. Keep tool-specific workflow in skills; keep product and repository rules here.
## Scope Rules
- User-visible workflow changes must update `docs/technical/zh/manual.md` and usually `docs/technical/zh/quickstart.md`.
- If an English counterpart exists for user-facing docs such as `manual.md` or `quickstart.md`, update `docs/technical/en/...` enough that it does not contradict the Chinese source.
- Control console page responsibility changes must update `docs/technical/zh/frontend-admin-frontend-context.md`.
- Earth frontend behavior changes must update `docs/technical/zh/earth-frontend-context.md`.
- Earth layer additions, `renderOrder`, altitude/radius offsets, depth strategy, pointer picking, legend modes, or layer panel/startup ordering must update `docs/technical/zh/earth-render-layer-order.md`.
- Earth layer visual style or legend symbol/color semantics should also update `docs/technical/zh/earth-layer-style-reference.md` when that reference is affected.
- Collector, datasource, credential, settings, connectivity, scheduler, or API changes must update the relevant backend docs, especially `docs/technical/zh/backend-collectors.md` and any datasource/settings-specific doc.
- When a change turns an old plan assumption into current behavior, update the relevant `docs/plans/*.md` with a status note instead of leaving contradictory instructions.
- Search docs for stale terms introduced by the change, for example old tab names, old route responsibilities, obsolete auth assumptions, or renamed UI labels.
## Public Docs Rules
- If adding a new technical document, add it to `docs/technical/zh/README.md` when it should be discoverable from the technical docs index.
- If a technical document should be visible in the public Docs page or linked from a technical README, register it in `frontend/src/pages/Docs/docs-content.ts` under `DOCS_METADATA`. Files under `docs/technical/{zh,en}/` are not automatically routable.
- For every public technical doc, keep the bilingual file pair in sync by filename: `docs/technical/zh/<name>.md` and `docs/technical/en/<name>.md`. If content is intentionally Chinese-only or English-only, state that intentionally in the final note.
- Public docs should use readable link text, not raw filenames such as `manual.md`.
## Credential Collector Rules
- Any built-in collector marked `requires_credentials: true` and `credential_status: supported` must have:
- a `credential_provider` in `backend/app/core/datasource_defaults.py`;
- a default credential guide in `backend/app/services/credential_guides.py`;
- a supported connectivity provider in `backend/app/services/datasource_connectivity.py`;
- settings UI guidance or a credential form in `frontend/src/pages/Settings/Settings.tsx`;
- a regression test that fails if the guide/provider is missing.
## Recommended Checks
Run the checks that match the affected docs.
### Duplicate Bilingual Docs
```bash
python - <<'PY'
from pathlib import Path
same = []
for en in sorted(Path("docs/technical/en").glob("*.md")):
zh = Path("docs/technical/zh") / en.name
if zh.exists() and en.read_text() == zh.read_text():
same.append(en.name)
if same:
raise SystemExit("identical en/zh docs: " + ", ".join(same))
print("no identical en/zh docs")
PY
```
### Language-Less Technical Links
```bash
rg -n "/home/ray/dev/linkong/planet/docs/technical/(?!zh|en)" docs/technical/zh --pcre2
```
This should return no matches.
### Public Docs Registry
```bash
python - <<'PY'
import re
from pathlib import Path
metadata = Path("frontend/src/pages/Docs/docs-content.ts").read_text()
known = set(re.findall(r"'([^']+\.md)':\s*\{", metadata))
known.add("README.md")
missing = []
for readme in [Path("docs/technical/zh/README.md"), Path("docs/technical/en/README.md")]:
if not readme.exists():
continue
for href in re.findall(r"\]\(([^)]+\.md)\)", readme.read_text()):
path = Path(href)
if "docs/technical/" not in href:
continue
filename = path.name
if filename not in known:
missing.append(f"{readme}: {filename}")
if missing:
raise SystemExit("docs README links missing DOCS_METADATA: " + ", ".join(missing))
print("docs README links are whitelisted")
PY
```
### Public Bilingual Pairs
```bash
python - <<'PY'
import re
from pathlib import Path
metadata = Path("frontend/src/pages/Docs/docs-content.ts").read_text()
filenames = sorted(set(re.findall(r"'([^']+\.md)':\s*\{", metadata)) - {"README.md"})
missing = []
for filename in filenames:
for lang in ("zh", "en"):
path = Path("docs/technical") / lang / filename
if not path.exists():
missing.append(str(path))
if missing:
raise SystemExit("missing bilingual docs: " + ", ".join(missing))
print("public docs have zh/en file pairs")
PY
```
### Raw Filename Link Titles
```bash
rg -n "\[[^]]+\.md\]\(" docs/technical/zh docs/technical/en
```
This should return no matches for polished public docs.

View File

@@ -24,6 +24,11 @@
- [earth-webgl-instancing-satellites-plan.md](/home/ray/dev/linkong/planet/docs/plans/earth-webgl-instancing-satellites-plan.md)
- [earth-real-terrain-plan.md](/home/ray/dev/linkong/planet/docs/plans/earth-real-terrain-plan.md)
- [earth-news-source-configuration-and-collector-plan.md](/home/ray/dev/linkong/planet/docs/plans/earth-news-source-configuration-and-collector-plan.md)
- [earth-news-cruise-summary-plan.md](/home/ray/dev/linkong/planet/docs/plans/earth-news-cruise-summary-plan.md)
- [earth-vessel-rendering-performance-plan.md](/home/ray/dev/linkong/planet/docs/plans/earth-vessel-rendering-performance-plan.md)
- [AIS 多源采集、冲突记录与聚合接口计划](/home/ray/dev/linkong/planet/docs/plans/earth-vessel-ais-aggregation-plan.md)
- [earth-interactable-layer-plan.md](/home/ray/dev/linkong/planet/docs/plans/earth-interactable-layer-plan.md)
- [frontend-public-docs-site-plan.md](/home/ray/dev/linkong/planet/docs/plans/frontend-public-docs-site-plan.md)
- [frontend-ai-playground-development-plan.md](/home/ray/dev/linkong/planet/docs/plans/frontend-ai-playground-development-plan.md)
- [ue5-mvp-fused-plan.md](/home/ray/dev/linkong/planet/docs/plans/ue5-mvp-fused-plan.md)

View File

@@ -0,0 +1,384 @@
# Custom Source Live Mock 计划
**状态**:实施中
**创建日期**2026-05-01
**任务名**`Custom Source Live Mock`
**核心目标**:把自定义源升级为同时支持 REST 与 WebSocket 的可映射采集入口,并提供本地 AIS mock WebSocket 服务,用于验证 Earth 船只实时新增与 upsert 链路。
## 背景
真实 AIS 接口变化频率不可控,无法稳定验证 Earth 页面“不刷新也能看到新船只”的实时链路。当前系统已经有自定义源基础设施:
- `datasource_configs` 保存 endpoint、auth、headers、config。
- `datasource_mapping_templates` 保存目标 schema 的确定性映射模板。
- `run-mapped` 支持保存后的自定义 REST 源通过 active mapping 写入目标数据。
但现有能力主要面向 REST sample 和批量 mapping缺少以下能力
- 自定义源不能明确选择 `REST``WebSocket` 采集模式。
- WebSocket 长连接、订阅消息、重连、消息路径提取还没有通用 runtime。
- `vessel_ais` 自定义数据写入后需要进入 AIS raw observation 和 `vessels` WS channel才能真实验证 Earth 实时 upsert。
- 删除自定义源时没有清晰的数据清理选项。
- 设置中心里“采集调度 / 凭证 / 自定义源”入口混杂,用户很难判断该在哪里配置。
## 已确认决策
| 项目 | 决策 |
|-----|------|
| 计划名称 | `Custom Source Live Mock` |
| 自定义源传输类型 | 支持 `REST``WebSocket` |
| 采集写入方式 | 先映射到目标 schema再由 destination handler 写入 |
| AIS mock 目标 | 优先打通 `vessel_ais`,验证 Earth 船只实时新增和同 MMSI upsert |
| mock 服务 runtime | 使用 `bun` 启动本地 mock WS 服务 |
| 凭证配置 | 支持 headers、bearer、api key、basic并保留 query/header API key 位置配置 |
| 删除策略 | 删除自定义源时允许选择是否删除该源写入的数据 |
| 合并语义 | 自定义源必须选择“合并到哪个内置数据”,作为内置源的补充数据进入同一聚合链路 |
| UI 方向 | 自定义源创建和维护放在“配置中心 > 采集器设置”的采集器下拉框内联入口;数据源页保留总览与运行控制 |
## 范围
### 本阶段要做
- 自定义源可选择 `REST``WebSocket`
- 自定义源支持请求头、凭证、query params、body、WS subscribe message。
- WebSocket 自定义源支持长连接、重连、消息解析、mapping、写入。
- `vessel_ais` 自定义源写入 AIS raw observations并广播 `vessels` channel。
- 提供 mock AIS WS 服务,持续发送新增 MMSI 和位置变更。
- 删除自定义源时提供“是否删除该源数据”的选项。
- 梳理设置中心信息架构,明确后续 UI 重构方向。
### 暂不做
- 不新增任意动态数据库表。
- 不允许用户提交可执行脚本作为 mapping。
- 不让 LLM 进入正式采集链路。
- 不把 mock 数据直接写 legacy `vessel_position`,优先写 AIS raw observations保持可追踪和可删除。
- 不在本阶段完成完整 `Earth Live Sync`,但要为后续 summary invalidation 留出 hook。
## 现状入口
| 能力 | 当前位置 |
|-----|----------|
| 自定义源配置模型 | `backend/app/models/datasource_config.py` |
| 自定义源 mapping 模型 | `backend/app/models/datasource_mapping.py` |
| 自定义源 API | `backend/app/api/v1/datasource_config.py` |
| 目标 schema registry | `backend/app/core/target_schema_registry.py` |
| mapping engine | `backend/app/services/datasource_mapping.py` |
| 数据源总览 UI | `frontend/src/pages/DataSources/DataSources.tsx` |
| 采集器设置 UI | `frontend/src/pages/Settings/Settings.tsx` |
## 目标架构
```mermaid
flowchart LR
A[Custom Source Config] --> B{source_type}
B -->|rest| C[Mapped REST Runner]
B -->|websocket| D[Mapped WS Runner]
C --> E[Mapping Engine]
D --> E
E --> F[Target Schema Validator]
F --> G{Destination Handler}
G -->|vessel_ais| H[AIS Raw Observations]
H --> I[AIS Aggregation]
H --> J[vessels WS Channel]
J --> K[Earth Vessel Upsert]
```
## 数据配置设计
短期可以继续复用 `DataSourceConfig`,避免大迁移。语义约定如下:
| 字段 | 用途 |
|-----|------|
| `name` | 自定义源唯一名称,例如 `mock_ais_ws` |
| `source_type` | `rest``websocket` |
| `endpoint` | `http(s)://...``ws(s)://...` |
| `auth_type` | `none``bearer``api_key``basic` |
| `auth_config` | token、api_key、key name、basic username/password 等 |
| `headers` | 静态请求头 |
| `config` | method、params、body、timeout、retry、WS 订阅消息、重连策略、消息路径等 |
建议 `config` 结构:
```json
{
"transport": "websocket",
"delivery_mode": "realtime_stream",
"merge_target_source": "barentswatch_vessels",
"target_schema": "vessel_ais",
"method": "GET",
"params": {},
"body": null,
"timeout": 30,
"retry": 3,
"ws_subscribe_message": {"type": "subscribe", "channel": "vessels"},
"ws_message_path": "$.data",
"ws_items_path": "$.vessels[*]",
"ws_reconnect": true,
"reconnect_delay_seconds": 3,
"debug_max_messages": null,
"delete_policy": "config_only"
}
```
## 后端实施计划
### Phase 1 — 自定义源类型与连接测试
- 允许 `source_type``rest``websocket`
- REST 连接测试保留现有 HTTP 请求逻辑。
- WebSocket 连接测试新增:
- 校验 endpoint 必须是 `ws://``wss://`
- 注入 headers 和 auth。
- 连接后可选发送 `ws_subscribe_message`
- 读取一条消息或超时返回诊断。
### Phase 2 — Mapped REST Runner 补齐
现有 `run-mapped` 继续作为 REST 一次性采集入口,补齐:
- `GET/POST` method。
- query params。
- JSON body。
- headers 和 auth 注入。
- sample limit 与响应大小限制。
- `vessel_ais` destination handler。
### Phase 3 — Mapped WebSocket Runner
新增通用 WebSocket runner读取 `DataSourceConfig + active mapping`
- 建立长连接。
- 发送可选订阅消息。
- 循环接收消息。
- JSON parse。
-`ws_message_path/ws_items_path` 提取 item 或 list。
- 使用 mapping engine 转换。
- 使用 target schema validator 校验。
- 调用 destination handler 写入。
- 更新采集任务状态:
- `connecting`
- `streaming`
- `reconnecting`
- `stopped`
- 维护运行指标:
- `messages_seen`
- `records_written`
- `unique_entities`
- `last_message_at`
- `last_error`
- 后台长连接不读取 `config.debug_max_messages`;该字段只用于显式的一次性调试运行,避免正式 WS 流被测试上限截断。
### Phase 4 — Destination Handler
为 target schema 建立明确写入处理器。
`vessel_ais` handler
- 写入 `AISRawObservation`
- `source = datasource.name`
- `delivery_mode` 来自 config默认 WS 为 `realtime_stream`、REST 为 `polling`
- `transport` 来自 `source_type`
- 生成幂等 observation hash。
- 更新 AIS source health。
- 广播 `vessels` channelpayload 使用当前 Earth 已支持的 upsert 格式。
`generic_records` handler
- 写入通用 collected data 或后续 generic store。
- 不直接进入 Earth。
### Phase 5 — 删除与数据清理
删除自定义源时新增清理策略:
| 选项 | 行为 |
|-----|------|
| 只删除配置 | 删除 `datasource_configs`,保留 mapping 和历史数据需要另行处理 |
| 删除配置和 mapping | 删除配置及对应 `datasource_mapping_templates` |
| 删除配置、mapping 和该源数据 | 同时删除该源写入的数据 |
数据删除范围:
- `collected_data.source == datasource.name`
- `ais_raw_observations.source == datasource.name`
- `ais_source_health.source == datasource.name`
不建议直接删除 legacy `vessel_position`,因为当前 legacy 表不带 source无法安全归因。自定义 AIS 源应优先只写 raw observations。
删除数据后应触发:
- `vessels` channel 的 reload/invalidation 事件,提示 Earth 重新拉船只聚合。
- 后续接入 `Earth Live Sync` 后,触发 `earth_summary` invalidation。
### Phase 6 — Mock AIS WebSocket 服务
新增脚本:
`scripts/mock-ais-ws-server.ts`
运行方式建议:
```bash
bun run mock:ais-ws
```
服务行为:
- 监听 `ws://localhost:8787/ais`
- 接受任意客户端连接。
- 可记录收到的 subscribe message。
- 每 1-2 秒发送一条 AIS-like JSON。
- 每隔 N 条生成新 MMSI验证船只数量增长。
- 已存在 MMSI 随时间改变 `lat/lon/cog/heading`,验证同 MMSI upsert。
- 支持固定 seed保证测试可复现。
示例 payload
```json
{
"type": "vessel",
"data": {
"mmsi": "999000001",
"name": "MOCK VESSEL 001",
"lat": 31.23,
"lon": 121.47,
"sog": 12.4,
"cog": 86,
"heading": 90,
"received_at": "2026-05-01T00:00:00Z"
}
}
```
## 前端实施计划
### 信息架构调整
自定义源不作为割裂的新入口,而是作为内置采集器的补充源,直接纳入“配置中心 > 采集器设置”的采集器选择器:
- 采集器下拉框同时展示内置采集器和自定义补充源。
- 下拉框右侧提供加号按钮,用于添加自定义源。
- 新建自定义源时必须选择“合并到内置数据”,例如合并到 `barentswatch_vessels`
- 选择自定义源后右侧基础配置区域沿用正常采集器配置形态支持连接测试、保存、endpoint、headers、auth、高级 JSON。
- 自定义源比内置源多一个“删除自定义源”按钮。
- 删除时弹出确认框,可勾选“同时删除该自定义源生成的所有数据”。
数据源页保留:
- 内置源总览。
- 内置源最近状态。
- 内置源手动触发。
- 不展示自定义源管理入口;自定义源创建、维护、删除统一在采集器设置中完成。
### 自定义源表单
新增或重构自定义源表单:
- 源名称。
- 类型:`REST` / `WebSocket`
- 合并到内置数据:必选,用于声明该源补充哪个内置数据域。
- endpoint。
- method/body/params仅 REST 显示。
- subscribe message/message path/items path仅 WS 显示。
- auth type。
- headers。
- target schema。
- sample/test 按钮。
- mapping assistant/preview。
- 保存并运行。
### 删除确认
删除自定义源时弹出确认:
- 默认只删除配置。
- 可勾选删除 mapping。
- 可勾选删除该源写入的数据。
- 显示将删除的数据范围和不可恢复提示。
## 验证方案
### Mock WS 验证路径
1. 启动 mock 服务:
```bash
bun run mock:ais-ws
```
2. 新建自定义源:
| 字段 | 值 |
|-----|----|
| name | `mock_ais_ws` |
| source_type | `websocket` |
| endpoint | `ws://localhost:8787/ais` |
| merge_target_source | `barentswatch_vessels` |
| target_schema | `vessel_ais` |
| ws_message_path | `$.data` |
3. 保存 active mapping
```json
{
"source": {
"items_path": "$"
},
"fields": {
"mmsi": {"path": "$.mmsi", "type": "integer"},
"name": {"path": "$.name", "type": "string"},
"lat": {"path": "$.lat", "type": "float"},
"lon": {"path": "$.lon", "type": "float"},
"sog": {"path": "$.sog", "type": "float", "default": null},
"cog": {"path": "$.cog", "type": "float", "default": null},
"heading": {"path": "$.heading", "type": "integer", "default": null},
"received_at": {"path": "$.received_at", "type": "datetime", "default": null}
}
}
```
4. 启动自定义源。
5. 打开 Earth 船只图层,不刷新页面观察:
- `vessels` WS channel 收到 `source = mock_ais_ws`
- HUD 船只数在新 MMSI 到达时增加。
- 地球出现 `MOCK VESSEL`
- 同 MMSI 后续消息更新位置和航向,不重复叠加。
### 自动化测试
后端测试:
- WebSocket 自定义源连接测试。
- WS message path 和 items path 提取。
- mapping 到 `vessel_ais`
- 写入 AIS raw observation。
- 广播 `vessels` channel。
- 删除自定义源时按策略删除 mapping 和源数据。
前端测试:
- REST/WS 表单条件显示。
- 删除确认选项。
- mock 源配置保存 payload。
- mapping preview 展示错误和成功记录。
## 风险与约束
- WebSocket 自定义源是长连接,不能沿用一次性 REST 进度条。
- 如果 mock 源写 legacy vessel 表,删除会变得不安全,因此先只写 raw observations。
- 自定义 WS 可能消息量很大,必须有 backpressure、日志限流和任务取消能力。
- 任意外部 WS 不能信任 payload必须经过 mapping 和 schema validation。
- headers/auth 不能进入 LLM mapping prompt。
## 交付顺序
1. Mock AIS WS 服务。
2. 后端自定义 WS runner。
3. `vessel_ais` destination handler 和 `vessels` broadcast。
4. 删除自定义源及数据清理。
5. 设置中心采集器下拉框内联自定义源 UI。
6. 配置中心信息架构重整。
7.`Earth Live Sync` 对接 summary invalidation。

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# 自定义 API 数据源与 LLM 映射系统 — 实施计划
**状态**:规划中
**创建日期**2026-04-28
**核心原则**LLM 辅助生成映射配置;生产采集使用确定性转换引擎
## 已确认决策
| 项目 | 决策 |
|-----|------|
| 自定义 API 的定位 | 作为内置数据源的补充入口,不直接等同于 Earth 新功能 |
| LLM 的职责 | 探索未知 API、分析样本 JSON、生成 mapping 草案 |
| 采集时是否调用 LLM | 不调用;采集链路必须确定性、可审计、可复现 |
| 自定义数据如何进入 Earth | 必须映射到已支持的目标 schema或先进入通用数据沉淀 |
| 外部凭证放置位置 | Settings / 外部集成统一管理 provider tokenDataSources 引用 provider profile |
| TimescaleDB | 放入 TODO高频时序数据稳定后再评估迁移 |
---
## 一、背景与问题
当前系统已经有 `datasource_configs`,可以配置自定义数据源的 endpoint、auth、headers、config也已经有部分 collector 会读取这些配置。但这只能解决“怎么请求数据”,还没有解决以下问题:
- API 返回 JSON 后,如何转换成系统已有领域模型。
- 自定义数据源是补充已有能力,还是全新数据沉淀。
- 转换规则由谁生成、谁校验、谁执行。
- 未知数据是否能自动在 Earth 上展示。
- 外部 token 是放在全局配置中心,还是放在每个 datasource 下。
专业做法是把“请求配置”“外部凭证”“目标 schema”“字段映射”“采集执行”拆开
- Settings 管外部集成凭证,例如 AI Provider、BarentsWatch、未来付费 AIS API。
- DataSources 管具体数据源实例,例如 endpoint、调度频率、目标 schema、mapping 版本。
- LLM 只在配置阶段辅助生成 mapping不进入生产采集链路。
- Earth 只消费明确 schema 的数据,不消费任意未知 JSON。
---
## 二、目标架构
### 2.1 自定义 API 数据源生命周期
```mermaid
flowchart LR
A[配置 endpoint/auth/request] --> B[抓取 sample JSON]
B --> C[选择目标 schema]
C --> D[LLM 生成 mapping 草案]
D --> E[确定性 mapping engine 预览]
E --> F[schema validation]
F --> G[保存 mapping version]
G --> H[scheduler 执行 mapped collector]
H --> I[写入目标表或 generic_records]
```
### 2.2 目标 schema 分层
| schema | 用途 | Earth 可视化 |
|-------|------|-------------|
| `vessel_ais` | 船只 AIS 位置、航速、航向、MMSI 等 | 进入船舶图层 |
| `geo_points` | 通用点位数据,包含经纬度、名称、类型、时间 | 进入通用 geo layerTODO |
| `news_events` | 新闻/事件类数据,带时间、地点、摘要、来源 | 复用新闻/事件链路 |
| `compute_centers` | 算力中心、机房、数据中心数据 | 复用算力中心图层 |
| `generic_records` | 未知结构化数据沉淀 | 不直接展示 |
v1 建议优先实现:
- `vessel_ais`
- `geo_points`
- `generic_records`
其他 schema 可先在 registry 中预留名称,但不承诺完整落库与可视化。
### 2.3 LLM 的边界
LLM 可以做:
- 根据 API 文档或 sample JSON 解释字段含义。
- 推荐目标 schema。
- 生成 mapping JSON 草案。
- 给出字段置信度和需要人工确认的字段。
- 帮用户发现分页、数组路径、时间字段、坐标字段。
LLM 不应该做:
- 在正式采集时参与每批数据转换。
- 生成并执行 Python/JavaScript 代码。
- 接触 API key、bearer token、basic auth password。
- 自动创建新的 Earth 图层或数据库表。
---
## 三、后端实施计划
### Phase 1 — Target Schema Registry
新增代码级 registry统一描述系统支持的目标数据类型。
每个 target schema 至少包含:
- `key`:例如 `vessel_ais`
- `label`:前端展示名称。
- `description`:适用场景。
- `fields`:字段名、类型、是否必填、说明、示例。
- `validator`Pydantic 或等价校验器。
- `destination`:写入目标,例如 vessel 表、generic_records、future geo layer。
示例概念:
```json
{
"key": "vessel_ais",
"fields": [
{"name": "mmsi", "type": "integer", "required": true},
{"name": "lat", "type": "float", "required": true},
{"name": "lon", "type": "float", "required": true},
{"name": "sog", "type": "float", "required": false},
{"name": "cog", "type": "float", "required": false},
{"name": "received_at", "type": "datetime", "required": false}
]
}
```
### Phase 2 — Mapping Template Model
新增 mapping 配置持久化表,建议命名为 `datasource_mapping_templates`
关键字段:
- `id`
- `datasource_config_id`
- `target_schema`
- `mapping_json`
- `sample_payload_hash`
- `validation_status`
- `version`
- `is_active`
- `created_at`
- `updated_at`
`mapping_json` 是声明式 DSL不允许任意代码执行。
示例:
```json
{
"source": {
"items_path": "$.data.vessels[*]"
},
"fields": {
"mmsi": {"path": "$.mmsi", "type": "integer"},
"lat": {"path": "$.latitude", "type": "float"},
"lon": {"path": "$.longitude", "type": "float"},
"sog": {"path": "$.speedOverGround", "type": "float", "default": null},
"received_at": {"path": "$.timestamp", "type": "datetime"}
}
}
```
### Phase 3 — Deterministic Mapping Engine
实现独立 mapping engine输入 sample/raw payload 和 mapping JSON输出目标 schema 记录。
v1 支持能力:
- JSONPath/JMESPath 风格路径提取。
- 数组展开。
- 默认值。
- 基础类型转换string、integer、float、boolean、datetime。
- 坐标范围校验。
- 简单枚举映射。
- 错误收集:缺字段、类型转换失败、路径不存在。
明确不支持:
- 任意表达式执行。
- 用户提交脚本。
- LLM runtime 修复。
### Phase 4 — LLM Mapping Assistant API
新增配置阶段 API
- `POST /api/v1/datasources/custom/sample`
- 按 datasource 请求配置抓取 sample JSON。
- `GET /api/v1/datasources/target-schemas`
- 返回可选目标 schema 和字段说明。
- `POST /api/v1/datasources/mappings/propose`
- 输入 sample JSON + target schema调用 AI provider 生成 mapping 草案。
- `POST /api/v1/datasources/mappings/preview`
- 使用确定性 mapping engine 预览转换结果。
- `POST /api/v1/datasources/mappings`
- 保存 mapping 版本。
- `PUT /api/v1/datasources/mappings/{id}`
- 更新 mapping生成新版本或覆盖草稿。
- `POST /api/v1/datasources/{id}/run-mapped`
- 手动触发一次 mapped collector。
安全要求:
- `propose` 请求发送给 LLM 前必须脱敏 sample。
- auth headers、token、password 不进入 prompt。
- LLM 返回结果必须再经过 mapping schema 校验。
### Phase 5 — Generic Mapped HTTP Collector
新增通用 collector
- 读取 `DataSourceConfig` 请求配置。
- 读取 active mapping template。
- 拉取 API 数据。
- 使用 mapping engine 转换。
- 使用 target schema validator 校验。
- 调用 destination handler 写入目标表或 generic storage。
- 将失败记录写入错误日志或 dead-letter 结构。
对于 `generic_records`
- 保存 datasource id。
- 保存 target schema。
- 保存 normalized JSON。
- 保存 raw payload 摘要或 raw reference。
- 保存采集时间、source timestamp、mapping version。
---
## 四、前端实施计划
### Phase 1 — Settings 外部集成
Settings 中保留统一外部集成配置:
- AI Providerbase URL、model、API key。
- BarentsWatchclient id/client secret 或 bearer token。
- 未来付费接口AISHub、MarineTraffic、VesselFinder 等 provider profile。
DataSources 不直接管理全局 secret只引用 provider profile。
### Phase 2 — Settings 自定义源向导
自定义数据源配置入口应放在 `/settings` 的“采集器设置”或后续专门的自定义采集器设置区。`/datasources` 保持数据源目录和采集触发职责,不再承载编辑入口。
自定义数据源配置改成向导或右侧 drawer
1. Request
- endpoint
- method
- auth profile
- headers
- query/body config
- schedule
2. Sample
- 点击抓取 sample
- 展示 JSON tree
- 支持选择数组根路径
3. Target Schema
- 选择 `vessel_ais``geo_points``generic_records`
- 展示该 schema 必填字段
4. Mapping Proposal
- 调用 LLM 生成 mapping 草案
- 显示字段匹配置信度
- 标出需要人工确认的字段
5. Preview
- 用确定性 engine 预览前 N 条转换结果
- 展示校验错误
6. Save & Enable
- 保存 mapping version
- 启用调度或仅保存草稿
### Phase 3 — 运维视图
为 mapped datasource 展示:
- 上次运行时间。
- 成功记录数。
- 失败记录数。
- 当前 mapping version。
- 目标 schema。
- 最近错误。
- 手动运行按钮。
---
## 五、数据库与存储策略
### v1继续使用 PostgreSQL
PostgreSQL 可以承载当前规模的采集、关系查询、JSONB 沉淀和基础时序查询。v1 不必因为“时序数据”立刻引入 TimescaleDB。
适合继续用 PostgreSQL 的场景:
- 数据量可控。
- 最近状态查询为主。
- 历史保留窗口较短。
- 查询模式还没稳定。
- 需要快速迭代 schema 与 mapping。
### TODOTimescaleDB
以下条件满足后,再评估 TimescaleDB
- AIS、遥测、轨迹类数据达到高频持续写入。
- 需要按时间窗口做聚合、降采样、retention policy。
- 单表时间序列查询明显成为瓶颈。
- 历史轨迹保留从 24h 扩展到数周或数月。
候选迁移对象:
- `vessel_position`
- future telemetry tables
- future generic time-series records
备选方案:
- PostgreSQL 原生按天/月分区。
- TimescaleDB hypertable。
- 热数据 PostgreSQL冷数据对象存储。
---
## 六、安全与治理
### Secret 管理
- Settings 中保存 provider credentials。
- API 返回配置时必须 mask secret。
- LLM prompt 只能包含脱敏 sample 和 schema 说明。
- 后续 TODO引入字段级加密或 KMS。
### Mapping 治理
- 每次 mapping 变更保留版本。
- active mapping 只能有一个。
- 允许保存 draft mapping。
- 运行记录关联 mapping version。
- 校验失败不能自动启用。
### 错误处理
常见错误类型:
- API 401/403凭证错误或过期。
- API 429限流需要调整 schedule。
- JSON path 不存在:上游结构变化。
- 类型转换失败mapping 规则错误。
- schema validation failed转换结果不满足目标模型。
每次运行需要记录:
- datasource id。
- mapping version。
- started_at / finished_at。
- fetched count。
- mapped count。
- written count。
- failed count。
- error summary。
---
## 七、测试计划
### Backend Unit Tests
- mapping engine
- path 提取。
- 数组展开。
- 默认值。
- 类型转换。
- datetime parse。
- 枚举映射。
- 缺字段错误。
- target schema registry
- `vessel_ais` 必填字段校验。
- `geo_points` 经纬度范围校验。
- `generic_records` 接受未知结构。
- LLM assistant
- mock provider 返回 mapping。
- 验证 secret 不进入 prompt。
- 验证非法 mapping 被拒绝。
### Backend Integration Tests
- sample JSON -> propose mapping -> preview -> save mapping。
- mapped collector 使用保存的 mapping 写入 `generic_records`
- `vessel_ais` sample 写入船舶相关目标结构。
- 上游 JSON 结构变化时,运行失败并记录错误。
### Frontend Tests
- 自定义数据源向导完整流程。
- 未配置 AI Provider 时,提示去 Settings 配置,但允许手写 mapping。
- LLM 返回不完整 mapping 时Preview 阶段显示校验错误。
- 保存 mapping 后展示 active version 和运行状态。
---
## 八、分期工作量
| 阶段 | 内容 | 估算 |
|-----|------|------|
| Phase 0 | 完成本规划、确认 schema registry 设计 | 0.5 天 |
| Phase 1 | target schema registry + mapping template model | 12 天 |
| Phase 2 | deterministic mapping engine | 23 天 |
| Phase 3 | sample/propose/preview/save API | 23 天 |
| Phase 4 | DataSources 自定义源向导 | 35 天 |
| Phase 5 | generic mapped collector + run history | 24 天 |
| Phase 6 | vessel_ais / geo_points destination handler | 24 天 |
---
## 九、当前差距与下一步
当前差距:
- `datasource_configs` 只描述请求配置,不描述目标 schema 和 mapping。
- 自定义源没有 sample -> schema -> mapping -> preview -> save 的闭环。
- 生产采集还没有通用 mapped collector。
- Settings 与 DataSources 的职责边界需要在 UI 上进一步明确。
- Earth 还没有通用 `geo_points` 图层。
下一步建议:
1. 先实现 target schema registry 和 mapping engine不急着接 LLM。
2. 用固定 sample JSON 做 `vessel_ais``generic_records` 的单元测试。
3. 再接 LLM propose API让 LLM 产出的只是 mapping 草案。
4. 最后做前端向导,把人工确认和 preview 放到启用之前。

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# Earth Interactable Layer Plan
## 背景
状态Phase 1 已经开始落地Phase 2 的 BGP 事件 / 观测站迁移和 Phase 3 的算力中心迁移也已完成。`frontend/public/earth/js/interactable.js` 已新增AIS 船只、BGP 事件、BGP 观测站和算力中心图层已经改为通过 `createInteractableLayer()` 使用通用批量 `Points`、hover / locked overlay、默认 glow、状态更新、asset icon 预加载、屏幕空间 picking、固定 / 距离缩放和跨 Interactable 同坐标避让。登陆点因 `THREE.Points` 边缘深度裁切和贴地层级要求,已退回专用 `THREE.Sprite` 黄色球路径,并与海缆同高度同 renderOrder。后续阶段聚焦把可复用的扩圈 / 雷达扇形动画正式沉淀成 `animations` 扩展。
当前实现说明和接入示例见:
- [earth-interactable-usage.md](/home/ray/dev/linkong/planet/docs/technical/zh/earth-interactable-usage.md)
当前 AIS 船只图层已经形成了一个适合作为基准的交互图标模式:
- 普通态使用批量 `THREE.Points` 渲染,避免每个对象一个 `Sprite` 带来的 draw call 和透明排序压力。
- hover / locked 态使用单点 overlay 叠加 glow不改变普通批次交互反馈清晰且成本低。
- moving / anchored 船只通过 canvas 点纹理表达不同形状moving 船只还按航向分桶。
- 拾取走屏幕空间命中,拖动和惯性期间跳过高频 hover picking。
- 图层高度贴近地表,仅保留很小的深度余量,避免“浮在表面层”的观感。
这个模式不应该只服务船只。后续 BGP 事件、BGP 观测站、算力中心、新闻事件、告警、地面传感器等都可能需要“图标类可交互元素”。如果每个图层继续各写一套 icon、glow、hover、locked、动画、picking 和图例逻辑,视觉会漂移,性能策略也会重复分叉。登陆点已经验证为例外:需要完整贴地且不被球面边缘裁切时,专用 Sprite 路径比通用 `Points` 更合适。
目标是把船只图层的成功做法抽象成一个通用接口:业务图层只描述“要画什么、在哪里、怎么交互”,底层统一负责批量渲染、默认 glow、状态 overlay、动画槽位、拾取和生命周期。
## 目标
1. 建立统一的 Earth 交互图标接口,作为未来地表图标类元素的默认入口。
2. 以 AIS 船只 glow 为默认 glow 视觉,其它图标默认沿用同一套 glow 质感。
3. 保留图标颜色、状态颜色、hover 放大、locked 强调、dimmed 聚焦、动画扩展等能力。
4. 支持 canvas / SVG / image icon不强行要求所有图标都可重着色。
5. 保持船只当前性能路线:批量绘制普通态,少量 overlay 处理交互态。
6. 给 BGP 事件扩圈、BGP 观测站雷达扇形等补充动画留出正式扩展点。
## 非目标
- 不在第一阶段重写所有 Earth 图层。
- 不把卫星、海缆、国家边界、真实地形这类非图标图层纳入同一个接口。
- 不为了抽象牺牲业务图标的差异表达例如船只航向、BGP 事件严重级别、观测站雷达扫掠。
- 不要求图片图标支持运行时重着色;图片图标只能通过预制多状态图片或 overlay tint 做有限表达。
## 核心设计
建议新增一个通用模块,例如:
```text
frontend/public/earth/js/interactable.js
```
它导出一个工厂或注册函数:
```js
createInteractableLayer({
id,
earth,
renderOrder,
altitudeOffset,
icon,
scale,
glow,
colors,
states,
animations,
picking,
data,
getPosition,
getKind,
getRotation,
getPayload,
});
```
业务模块仍保留自己的数据加载、图例、详情卡字段和业务语义。例如 `vessels.js` 负责 AIS 数据和船型映射,但 icon 渲染、hover overlay、locked overlay、默认 glow 和屏幕空间 picking 可以逐步迁入 `interactable.js`
## 参数草案
| 参数 | 类型 / 示例 | 默认值 | 说明 |
| --- | --- | --- | --- |
| `id` | `"vessels"` | 必填 | 图层唯一标识,用于 debug、picking、legend 和状态缓存。 |
| `earth` | `THREE.Object3D` | 必填 | 图层挂载目标,通常是 Earth root。 |
| `renderOrder` | `4.4` | `4` | 普通 icon 批次和 overlay 的基础渲染顺序。 |
| `altitudeOffset` | `0.2` | `0.2` | 图层高度,语义为 `CONFIG.earthRadius + altitudeOffset`。地表图标默认贴近真实地形基础层。 |
| `icon` | `{ type, source, draw, size, bins }` | 必填 | 图标来源。支持 canvas draw、SVG URL、image URL、内置 shape。 |
| `icon.fitSize` | `60``{ width: 60, height: 60 }` | `atlasCellSize` | asset 图标在 atlas canvas 内的最大绘制尺寸,默认居中等比 contain。SVG / 图片文件只负责原始形状,不需要为了显示大小手写 transform。 |
| `scale` | `{ base, min, max }` | `{ base: 1 }` | 基础缩放和距离稳定范围。当前船只可映射到 `VESSEL_POINT_SIZE` / `baseScale`。 |
| `sizeMode` | `"fixed" / "distance"` | `"fixed"` | 是否固定屏幕像素尺寸;非 fixed 时按相机到地表距离做比例缩放。 |
| `sizeScale` | `{ min, max, referenceFov }` | `{ min: 0.12, max: 3, referenceFov: 75 }` | `sizeMode !== "fixed"` 时的缩放限制和参考视角。 |
| `glow.enabled` | `true / false` | `true` | 是否启用默认 glow。默认 glow 以船只 hover / locked overlay 为基准。 |
| `glow.intensity` | `0.0 - 2.0` | `1` | glow 强度,内部映射到 canvas `shadowBlur`、opacity 或 shader uniform。 |
| `glow.colorMode` | `"state" / "icon" / "fixed"` | `"state"` | glow 颜色来源,默认跟随状态颜色。 |
| `hover.scale` | `1.0 - 2.0` | `1.18` | hover 放大倍率。当前船只保持同尺寸 glow overlay接口仍保留放大能力供其它图层使用。 |
| `hover.mode` | `"scale" / "glow-only" / "custom"` | `"scale"` | hover 反馈方式。船只可用 `"glow-only"`,其它图标默认放大。 |
| `colors.normal` | `"#4A90D9"` | icon 原色 | 普通态颜色。只有可上色 icon 生效。 |
| `colors.hover` | `"#7dd3fc"` | normal | hover 态颜色。 |
| `colors.locked` | `"#ffffff"` | hover | locked 态颜色。 |
| `colors.dimmed` | `"#9B9B9B"` | normal | 聚焦其它对象时的弱化颜色。 |
| `colors.byKind` | `{ cargo: "#4A90D9" }` | `{}` | 按业务类型着色如船型、BGP 严重级别。 |
| `colorable` | `true / false` | 由 icon 类型推断 | canvas shape 和 SVG mask 通常可上色;图片默认不可上色。 |
| `opacity` | `{ normal, hover, locked, dimmed }` | 船只当前值 | 各状态透明度。 |
| `rotation` | `{ enabled, bins, getAngle }` | disabled | 是否按角度分桶,例如船只按 COG 分 32 桶。 |
| `animations` | `IconAnimationSpec[]` | `[]` | 补充动画列表,例如扩圈、雷达扇形、脉冲、轨迹尾迹。 |
| `picking.radiusPx` | `22` | `20` | 屏幕空间命中半径。 |
| `picking.throttleMs` | `100` | `80` | hover picking 节流。 |
| `picking.skipWhileDragging` | `true` | `true` | 拖动和惯性期间跳过 hover picking。 |
| `zIndexPolicy` | `"surface-icon"` | `"surface-icon"` | 预设层级策略,避免每个业务图层手写高度和 renderOrder。 |
| `avoidance.enabled` | `true / false` | `true` | 是否参与跨 Interactable 的同坐标避让。默认开启,同一经纬度下的图标会沿地表切平面小幅排开,方便辨认和选择。 |
| `avoidance.radius` | `number` | `1.1` | 同坐标避让的第一圈半径,单位为地球本地坐标单位。 |
| `avoidance.precision` | `number` | `4` | 经纬度归并精度,默认约等于只处理几乎完全重叠的图标。 |
| `legend` | `{ label, color, shape }[]` | `[]` | 可选图例声明,业务层也可以继续自己导出。 |
| `metadata` | object | `{}` | 业务扩展数据,不参与渲染但参与 tooltip / info-card / search。 |
## Icon 规格
图标输入建议分三类:
```js
{
type: "canvas-shape",
size: 128,
draw(ctx, state) {
// draw triangle / dot / custom shape
},
}
```
```js
{
type: "svg-mask",
source: "/earth/assets/icons/bgp-event-dot.svg",
colorable: true,
}
```
```js
{
type: "image",
source: "/earth/assets/icons/vendor-logo.png",
colorable: false,
stateSources: {
hover: "/earth/assets/icons/vendor-logo-hover.png",
},
}
```
颜色策略:
- `canvas-shape` 默认可上色,适合船只、事件点、雷达站这类符号。
- `svg-mask` 如果能作为 mask 使用,则可上色;如果是完整多色 SVG则按图片处理。
- `image` 默认不可上色;需要状态变化时使用 `stateSources` 或额外 glow / ring。
## 默认 Glow 规范
默认 glow 以当前船只 overlay 为视觉基准:
- 普通态尽量不启用 glow保持地图干净。
- hover / locked 态叠加同位置 overlay。
- glow 颜色默认跟随状态颜色或业务类型颜色。
- glow blur 应该稳定,不随 camera zoom 夸张膨胀。
- 允许通过 `glow.intensity` 控制强度,但不要让业务图层各自发明完全不同的光晕语言。
建议内部把 glow 拆成两个层次:
1. `textureGlow`canvas texture 里的 `shadowBlur`,适合小图标 hover / locked。
2. `effectGlow`:额外 ring / halo / pulse适合告警、BGP 事件和锁定强调。
## 状态模型
通用状态至少包含:
| 状态 | 触发 | 默认表现 |
| --- | --- | --- |
| `normal` | 普通显示 | 批量 Points使用 normal 颜色和 opacity。 |
| `hover` | 指针悬停 | 默认放大并显示 glow船只可配置为同尺寸 glow-only。 |
| `locked` | 点击锁定 / 详情打开 | 强 glow、更高 opacity可选 ring 或 pulse。 |
| `dimmed` | 聚焦其它对象 | 降低 opacity保留上下文。 |
| `hidden` | 图层关闭或过滤 | 不参与绘制和 picking。 |
| `alert` | 业务告警 | 可叠加动画,不替代 locked 状态。 |
状态更新需要增量化:只在 hover 目标、locked 目标、过滤条件、数据版本或相机距离阈值变化时更新,不在每帧遍历全部 icon 写材质属性。
## 动画扩展
动画不直接塞进 icon 基础参数,而是作为 `animations` 列表注册。每个动画声明自己的 geometry / material / update 策略:
```js
{
type: "expanding-ring",
when: ["alert", "locked"],
color: "state",
radiusPx: [10, 42],
durationMs: 1400,
opacity: [0.8, 0],
}
```
```js
{
type: "radar-sweep",
when: ["normal", "hover", "locked"],
angleDeg: 72,
rotationMs: 2600,
opacity: 0.36,
}
```
首批建议内置动画:
| 动画 | 用例 | 说明 |
| --- | --- | --- |
| `pulse-ring` | locked、告警点 | 原地呼吸环,强调选中对象。 |
| `expanding-ring` | BGP 事件 | 向外扩散的事件波纹。 |
| `radar-sweep` | BGP 观测站 | 扇形扫描,可持续旋转。 |
| `orbiting-dot` | 数据流 / collector 活跃态 | 小点绕 icon 环绕,表达活动状态。 |
| `trail` | 移动目标 | 可选短尾迹,船只或飞机类目标使用。 |
动画必须支持批量或分组绘制,避免为每个对象创建独立的高频更新对象。只有 locked / hover / 少量 alert 对象可以使用单对象 overlay。
## 渲染策略
### 普通态
普通态优先使用分桶 `THREE.Points`
- 按 icon 类型、可上色策略、旋转分桶、纹理 key 分组。
- 每组一个 `BufferGeometry`,存 `position``color`、必要的 `payloadIndex`
- `PointsMaterial.sizeAttenuation = false`,保持屏幕尺寸稳定。
- `depthTest = true``depthWrite = false`,避免遮挡关系破坏地表。
### 交互态
hover / locked 使用少量 overlay
- overlay 复用 `THREE.Points` 单点对象或小型 ring mesh。
- overlay texture 从统一 cache 获取。
- overlay 更新只写当前 hover / locked 的 position、texture、opacity、size。
### 高密度升级
当某类图标超过分桶 Points 的舒适区,才考虑升级:
- `InstancedBufferGeometry` billboard。
- 自定义 shader 支持 per-instance rotation / scale / opacity。
- 视口 bbox / LOD / cluster。
这个升级不应该改变业务接口,只替换底层 renderer。
## Picking 策略
沿用船只当前方向:
- 默认屏幕空间 picking而不是 Three.js 对每个 Sprite / Points 做 raycast。
- 每个 icon 保留世界坐标和业务 payload。
- 每次 pointer move 将候选点投影到屏幕,按半径和深度判断命中。
- 拖动、惯性旋转、相机剧烈变化期间跳过 hover picking。
- click 时允许做一次更精确的 picking。
后续可以按图层或经纬度网格增加空间索引,减少候选点数量。
## 与现有图层的迁移路径
### Phase 1抽出船只基准能力
-`vessels.js` 提取 texture cache、canvas icon draw、overlay glow、分桶 Points 创建、状态增量更新。
- 保持 `vessels.js` 的公开 API 不变:`loadVessels()``toggleVessels()``getVesselMarkers()` 等继续可用。
- 新模块先只服务船只,确保视觉没有回退。
### Phase 2迁移 BGP 事件和观测站
- BGP 事件使用 `canvas-shape`,已接入 `Interactable`
- 严重级别映射到 `colors.byKind`,并通过通用 `getPointSizeMultiplier` 保留严重级别尺寸倍率。
- 当前扩圈效果保留在 BGP 业务动画中,并跟随 `Interactable` marker 位置更新。
- BGP 观测站主图标已接入 `Interactable`,活跃度映射到颜色和 `getPointSizeMultiplier`
- BGP 观测站 halo / 覆盖扇形继续由 BGP 业务动画表达扫描,并跟随 `Interactable` marker 位置更新。
### Phase 3迁移算力中心并评估登陆点
- 算力中心保留现有业务 icon但接入统一 hover / locked / glow。已完成
- 登陆点曾接入同一套 `Points` 渲染,但 pin 类 SVG 在地球边缘会被深度测试裁切;当前保留专用 `THREE.Sprite`,并使用 canvas 生成黄色扁平球,贴到海缆层级。
- TODO登陆点暂不迁移到完整 Interactable。后续若要统一交互接口优先考虑 Sprite-backed adapter只对齐 `getMarkers()``getPointerIntersections()``setMarkerState()``updateVisualState()` 等外观协议,不强行复用 `THREE.Points`、atlas 和跨图层避让。
- 检查图例、搜索和 info-card 是否只依赖业务 payload而不是依赖渲染对象类型。
### Phase 4形成 Earth 图标层规范
-`docs/technical/zh/earth-frontend-context.md` 记录当前实现入口。
-`docs/technical/zh/earth-layer-style-reference.md` 记录默认 glow、状态颜色、默认高度和动画参数。
-`docs/technical/zh/earth-render-layer-order.md` 记录 surface icon renderOrder 范围。
## 风险与约束
- 过早抽象可能让船只这种高质量基准被平均化,因此第一阶段必须以船只视觉不回退为验收标准。
- 图片 icon 不可上色,接口需要明确 `colorable = false` 的行为,避免业务层误以为颜色一定生效。
- 动画如果默认开启过多,会重新引入 overdraw 和每帧更新压力;默认只给 hover / locked 或少量 alert 使用。
- 地形开启时,贴地 icon 需要在高度、`depthTest``polygonOffset` 和 renderOrder 之间保持平衡。
- 统一 glow 不等于所有图标一模一样;业务可以调强度和颜色,但不应破坏整体视觉语言。
## 验收标准
1. 船只迁入通用接口后普通态、hover、locked、航向、颜色、轨迹和 picking 行为保持一致。
2. 新增一个 BGP 事件示例图层配置,不需要复制船只渲染代码即可得到 icon、glow、hover 和扩圈动画。
3. 新增一个 BGP 观测站示例图层配置,不需要自写独立动画循环即可得到雷达扇形。
4. 关闭图层后对应 icon、overlay、动画和 picking 全部停止。
5. 高密度数据下普通态仍走批量绘制hover / locked 只更新少量 overlay。
6. 文档同步说明默认高度、默认 glow、状态模型和动画扩展点。
## 相关文件
| 文件 | 当前角色 | 未来关系 |
| --- | --- | --- |
| `frontend/public/earth/js/vessels.js` | 船只基准实现,包含分桶 Points、hover / locked overlay、默认 glow 形态 | Phase 1 的抽象来源 |
| `frontend/public/earth/js/constants.js` | 保存船只高度、颜色、透明度、轨迹参数 | 后续可加入通用 surface icon 默认配置 |
| `frontend/public/earth/js/bgp.js` | BGP 事件和观测站视觉逻辑 | BGP 事件和观测站主图标已接入 Interactable扩圈、halo 和覆盖扇形仍保留业务动画 |
| `frontend/public/earth/js/compute-centers.js` | 算力中心 icon 和交互 | 已通过 Interactable 接入统一 Points、overlay、glow 和 picking |
| `frontend/public/earth/js/cables.js` | 登陆点 icon 和海缆线 | 登陆点当前使用专用 `THREE.Sprite` 黄色球,不再走 Interactable海缆线仍独立渲染 |
| `frontend/public/earth/js/main.js` | 当前集中处理 hover、click、locked 和 info-card 入口 | 后续需要接入通用 icon picking 结果 |
| `docs/technical/zh/earth-layer-style-reference.md` | 当前视觉参数参考 | 实现后同步默认 glow 和通用参数 |
| `docs/technical/zh/earth-render-layer-order.md` | 当前层级参考 | 实现后同步 surface icon 层级范围 |

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# Earth 新闻巡航摘要增强计划
## 背景
`Earth` 的新闻巡航模式目前直接消费 `/api/v1/news/earth-feed` 返回的 `items[].summary`。这个字段主要来自 RSS/Atom 的 `description``summary``content`,再经过 HTML 清理与长度截断。
这个实现足够轻量,但在巡航展示里有三个问题:
- 不是所有新闻源都会提供摘要,部分源只返回标题和链接。
- 聚合源的摘要质量不稳定,可能只是重复标题、来源署名或片段文本。
- 巡航模式需要更稳定的“态势说明”,否则新闻卡片的 `SUMMARY` 区域会显得空或信息密度不足。
目标不是把所有新闻都交给大模型,而是建立一个分层摘要管线:能用新闻源自带内容时零成本处理,需要增强时优先用本地模型,云端 LLM 只作为可控兜底。
## 当前相关实现
| 文件 | 作用 |
| --- | --- |
| `backend/app/services/earth_news.py` | 拉取 RSS/Atom 新闻源、解析标题/摘要、按区域聚合并返回 Earth 新闻 payload |
| `backend/app/api/v1/news.py` | 暴露 `/api/v1/news/earth-feed` |
| `frontend/public/earth/js/news.js` | 拉取新闻 payload 并渲染媒体面板新闻列表 |
| `frontend/public/earth/js/news-cruise-adapter.js` | 将新闻条目映射为巡航事件,并把 `summary` 传给信息卡 |
| `frontend/public/earth/js/info-card.js` | 展示新闻巡航卡片中的 `SUMMARY` |
当前摘要生成逻辑集中在 `earth_news.py`
```python
summary = _extract_item_text(node, "description", "content")
clean_summary = _truncate(_strip_html(summary), 180)
```
这意味着后端还没有区分“摘要来自哪里”“质量是否足够”“是否需要异步增强”。
## 总体方案
采用四级摘要来源:
| 优先级 | 来源 | 成本 | 适用情况 | 风险 |
| --- | --- | --- | --- | --- |
| 1 | 新闻源自带 summary / description | 低 | RSS/Atom 已提供可读摘要 | 字段可能为空或重复标题 |
| 2 | 本地规则提取 | 低 | 有正文片段但没有可靠摘要 | 只能抽取,不能真正概括 |
| 3 | 本地 Gemma/Ollama 摘要 | 中 | 巡航会展示且前两级质量不足 | 本地模型质量与机器性能相关 |
| 4 | 云端 LLM 兜底 | 高 | 用户手动增强、重点新闻、失败补偿 | 成本与网络依赖 |
推荐默认策略:
```text
provider summary -> extractive summary -> cached local model summary -> async local model summary -> optional cloud LLM
```
巡航 UI 永远先展示已有摘要,不等待模型调用。模型摘要在后台补齐,写入缓存后下一轮巡航或刷新时使用。
## 数据结构
后端应把原来的 `summary: str` 升级为可追踪的摘要元信息,同时为了兼容前端保留顶层 `summary` 字段。
建议新增结构:
```json
{
"summary": "短摘要文本",
"summary_meta": {
"source": "provider",
"quality": "good",
"generated_at": "2026-04-29T00:00:00Z",
"content_hash": "sha256:...",
"model": null,
"language": "zh-CN"
}
}
```
字段说明:
| 字段 | 可选值 | 说明 |
| --- | --- | --- |
| `source` | `provider` / `extractive` / `local_llm` / `cloud_llm` / `fallback` | 摘要来源 |
| `quality` | `good` / `partial` / `poor` | 后端对摘要可用性的判断 |
| `generated_at` | ISO 时间 | 模型或规则生成时间 |
| `content_hash` | SHA-256 | 用于缓存命中和判断内容变化 |
| `model` | 字符串或 `null` | 例如 `gemma3:4b` |
| `language` | 语言代码 | 默认 `zh-CN`,也可跟随新闻语言 |
前端第一阶段不需要显示 `summary_meta`,但可以用于后续调试面板或质量标记。
## 后端设计
### NewsSummaryService
新增 `backend/app/services/news_summary.py`,提供统一入口:
```python
async def resolve_news_summary(item: ParsedNewsItem, *, mode: str) -> NewsSummaryResult:
...
```
核心职责:
- 标准化新闻输入标题、URL、来源、发布时间、摘要片段、正文片段。
- 判断 provider summary 是否可用。
- 生成本地规则摘要。
- 查询模型摘要缓存。
- 在允许时调用本地 Ollama/Gemma。
- 在增强模式或手动触发时调用云端 LLM。
- 返回摘要文本与 `summary_meta`
### 摘要质量判断
第一版可以用轻量规则:
- 少于 30 个字符:`poor`
- 与标题高度重复:`partial`
- 包含明显来源署名或聚合噪声:`partial`
- 60-180 个字符且不重复标题:`good`
伪代码:
```python
def score_summary(title: str, summary: str) -> SummaryQuality:
if len(summary.strip()) < 30:
return "poor"
if normalized_overlap(title, summary) > 0.75:
return "partial"
if looks_like_source_attribution(summary):
return "partial"
return "good"
```
### 本地规则摘要
如果新闻源没有摘要,但有 `content``description``snippet` 或正文片段:
- 清理 HTML。
- 去掉标题重复内容。
- 去掉来源署名、发布时间、图片说明。
- 优先取前 1-2 个完整句子。
- 控制在 80-140 个中文字符或 40-80 个英文词。
### 本地 Gemma/Ollama Provider
不要在业务里写死 Gemma抽象为 `LocalLLMSummaryProvider`,默认可以指向 Ollama
```env
NEWS_SUMMARY_PROVIDER=ollama
OLLAMA_BASE_URL=http://localhost:11434
NEWS_SUMMARY_MODEL=gemma3:4b
NEWS_SUMMARY_TIMEOUT_SECONDS=20
NEWS_SUMMARY_MAX_INPUT_CHARS=5000
NEWS_SUMMARY_MAX_PER_HOUR=60
```
Ollama 请求示例:
```http
POST /api/generate
Content-Type: application/json
{
"model": "gemma3:4b",
"prompt": "...",
"stream": false,
"options": {
"temperature": 0.2,
"num_predict": 180
}
}
```
摘要 prompt 要强调“只基于原文”,避免模型补事实:
```text
你是新闻摘要器。只根据输入新闻内容生成摘要,不要添加原文没有的信息。
输出中文1-2 句话80-140 字。
如果原文信息不足,只概括已知事实,不要推测。
标题:{title}
来源:{source}
发布时间:{published_at}
正文或片段:
{content}
```
### 缓存
需要缓存模型摘要,避免重复花时间和费用。
缓存 key
```text
sha256(url + title + published_at + normalized_content)
```
建议新增表或复用系统设置缓存。若要可查询与清理,推荐独立表:
```text
news_summary_cache
- id
- cache_key
- url
- title
- content_hash
- summary
- source
- quality
- provider
- model
- generated_at
- expires_at
- failure_count
- last_error
```
缓存策略:
- 同一 `cache_key` 命中后直接返回。
- `provider` / `extractive` 可以短期缓存。
- `local_llm` / `cloud_llm` 可以长缓存,内容 hash 变化才重算。
- LLM 失败后记录 `failure_count`,短时间内不重复调用。
## 前端与巡航行为
前端第一阶段只需要继续使用 `item.summary`,不阻塞现有逻辑。
后续可选增强:
- `news.js` 在渲染新闻列表时,如果 `summary_meta.quality === "poor"`,可以用更紧凑的标题卡样式。
- `news-cruise-adapter.js` 选择巡航项时,可以优先选择 `summary_meta.quality !== "poor"` 的新闻。
- `info-card.js` 不显示“AI 生成中”这类文案,避免把系统内部状态暴露给用户。
如果后端异步生成完成,可以通过下一次 `/api/v1/news/earth-feed` 刷新自然更新。第一版不需要 WebSocket。
## 调用策略
默认使用“省钱模式”:
- 只处理本次 payload 中即将进入巡航队列的前 N 条。
- `provider``extractive` 达到 `good` 时不调用模型。
- 本地模型失败时不影响新闻 payload。
- 云端 LLM 默认关闭,只允许手动增强或后台配置开启。
推荐限制:
| 配置 | 默认值 | 说明 |
| --- | --- | --- |
| `NEWS_SUMMARY_MODE` | `economy` | `off` / `economy` / `enhanced` / `manual` |
| `NEWS_SUMMARY_CRUISE_PREFETCH_LIMIT` | `10` | 每次新闻 payload 预热多少条巡航摘要 |
| `NEWS_SUMMARY_MAX_PER_HOUR` | `60` | 本地模型每小时最多处理数量 |
| `NEWS_SUMMARY_CLOUD_MAX_PER_DAY` | `20` | 云端 LLM 每天最多处理数量 |
| `NEWS_SUMMARY_TIMEOUT_SECONDS` | `20` | 单条模型摘要超时 |
| `NEWS_SUMMARY_MAX_INPUT_CHARS` | `5000` | 输入截断上限 |
## Gemma 本地部署建议
Gemma 适合作为“本地省钱层”,但不应成为强绑定依赖。建议通过 Ollama 接入,未来可切换 Qwen、Llama 或其他本地模型。
开发环境:
```bash
ollama pull gemma3:4b
ollama serve
```
集成原则:
- 后端只依赖 Ollama HTTP API不直接依赖 Gemma SDK。
- 模型名称来自配置,不写死在代码里。
- 健康检查访问 `/api/tags` 或执行一条极短测试 prompt。
- 如果 Ollama 不可用,摘要管线自动退回 `provider` / `extractive`
中文新闻较多时,需要单独评估 Gemma 与 Qwen 系本地模型的中文摘要质量。不要只看单条效果,至少抽样 50 条新闻比较:
- 事实准确性
- 中文自然度
- 长度稳定性
- 延迟
- 是否会补充原文没有的信息
## 云端 LLM 兜底
云端 LLM 不作为默认路径,只用于:
- 用户点击“增强摘要”。
- 管理员开启增强模式。
- 本地模型连续失败且新闻进入重点巡航队列。
云端结果同样写入 `news_summary_cache`,并受每日限额控制。
## 分阶段实施
### 第一阶段:零成本摘要质量增强
-`earth_news.py` 中引入 `summary_meta`
- 增加 provider summary 质量判断。
- 增加本地规则摘要兜底。
- `/api/v1/news/earth-feed` 保持兼容,继续返回顶层 `summary`
- 前端无需大改。
验收标准:
- 没有摘要的新闻也能尽量得到短摘要。
- `summary_meta.source``summary_meta.quality` 可用于调试。
- 现有新闻面板和巡航模式不破坏。
### 第二阶段:本地 Gemma/Ollama 摘要
- 新增 `LocalLLMSummaryProvider`
- 接入 Ollama `/api/generate`
- 添加超时、输入截断、错误退避。
- 增加模型摘要缓存。
- 巡航 payload 后台预热前 N 条摘要。
验收标准:
- Ollama 可用时,低质量摘要能被本地模型增强。
- Ollama 不可用时,新闻接口仍然正常返回。
- 同一新闻不会重复调用模型。
### 第三阶段:设置与可观测性
- 在设置中增加新闻摘要模式:
- `关闭`
- `省钱模式`
- `增强模式`
- `仅手动`
- 增加本地模型连通性检查。
- 暴露缓存命中率、模型调用次数、失败次数。
- 日志记录摘要来源和失败原因。
验收标准:
- 用户可以不改环境变量就知道本地摘要服务是否可用。
- 管理员能看出成本和失败情况。
### 第四阶段:云端 LLM 兜底
- 接入现有 AI Provider 或新增 cloud summary provider。
- 增加每日限额与手动增强入口。
- 对云端生成结果落缓存。
验收标准:
- 云端调用可控、可关闭、可限流。
- 云端失败不影响巡航。
## 风险与防护
| 风险 | 防护 |
| --- | --- |
| 本地模型生成不存在的事实 | prompt 明确禁止扩写;摘要只作为原文概括;保留来源链接 |
| 本地模型慢导致新闻接口卡住 | 模型摘要异步化;接口先返回已有摘要 |
| 成本失控 | 默认不启用云端;按小时/天限流;缓存命中优先 |
| 摘要语言不一致 | 配置目标语言,默认 `zh-CN` |
| 新闻源正文不足 | 只概括标题和片段,不强行扩写 |
| 模型服务不可用 | 自动回退,不影响巡航主流程 |
## 推荐优先级
先做第一阶段和第二阶段的最小闭环:
1. `summary_meta` + 质量判断。
2. 本地规则摘要。
3. Ollama provider。
4. 缓存。
5. 巡航前 N 条异步预热。
云端 LLM 和设置页可以后置。这样能先验证“摘要缺失比例、本地模型质量、实际延迟”三个关键问题,再决定是否投入更重的 UI 与云端增强。

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@@ -96,3 +96,11 @@ GEO 轨道点数高,采样率需要按轨道类型分层。
2. 解锁后轨道立即清除
3. 不同轨道类型下点数可控
4. 页面切换回来不会闪出旧轨道残留
## Satellite Footprint Follow-Up Items
从技术文档迁出的 footprint 后续项,作为卫星覆盖能力的计划 backlog
1.`iridium-next` 新建独立 footprint adapter。
2. 在 UI 上补一个只读提示,让用户知道当前卫星是否支持 footprint。
3. 如果未来拿到 GEO beam contour / operator metadata再为 GEO 开 operator-specific footprint。

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@@ -25,6 +25,49 @@
- 状态和渲染更新散落在多个模块
- 后续再加新图层时容易复制旧逻辑
## Current High-Frequency Risks
### 1. Visual state and business state drift apart
Earth 里最常见的 bug 不是“没渲染”,而是状态没有一起收口:
- 图层关了tooltip 还在
- 锁定对象隐藏了info card 还在
- legend 没跟图层切换
- loading 已结束,但按钮还像没开
后续架构治理需要把这类同步责任从临时 UI patch 转为统一状态流。
### 2. HUD layout fixes skip structure analysis
Earth HUD 历史上反复出现:
- 面板只剩一条缝
- markdown 被裁掉
- tabs / iframe 被 `overflow: hidden` 吃掉
这类问题应纳入布局治理计划,而不是散落在单个功能改动里临时修。
### 3. Transitional paths keep accumulating
Earth 已经经历过多轮 HUD、toolbar、media panel 重构,容易留下:
- 旧 helper
- 旧 class
- 旧 fallback 逻辑
- 已废弃变体
架构分离阶段需要把 cleanup pass 作为计划项,而不是让技术上下文承担提醒职责。
### 4. Cruise logic and business events couple too deeply
巡航相关风险是通用巡航层继续混入业务事件细节,导致 BGP、新闻、卫星、海缆各自复制一套状态机。
架构目标应保持:
- 通用巡航层管理目标、队列、focus、停留、隐藏和切换
- 业务模块只提供队列、坐标、卡片内容和高亮副作用
## Target Architecture
Earth 对每类对象都尽量拆成三层:

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# AIS 多源采集、冲突记录与聚合接口计划
**状态**v0-v3 已实现v3.1-v3.4 为 v4/v5 前置稳定化任务v4 / v5 已落最小可用子集
**创建日期**2026-04-30
**核心原则**:采集器只写原始观测;去重、合并、冲突解释放在聚合接口中完成
## 已确认决策
| 项目 | 决策 |
|-----|------|
| AISStream 接入方式 | 单独实现 WebSocket 采集器,不塞进现有 BarentsWatch HTTP collector |
| 采集器职责 | 连接上游、标准化字段、写入原始观测,不直接决定最终展示值 |
| 去重合并位置 | 放在聚合服务和聚合 API 中,而不是散落在每个 collector 的保存逻辑里 |
| 冲突处理 | 先记录冲突事实和当前选择原因,后续再开放用户规则配置 |
| 默认可信度 | 同类 AIS 数据源优先按 `delivery_mode` 评估:`realtime_stream` 优于 `batch_stream`,再优于 `polling``snapshot` |
| 过期保护 | 实时流源断流超过 freshness 窗口后,不能仅凭“实时源”身份压过更新的轮询数据 |
| 源健康状态 | 聚合时必须参考采集器健康状态,不能只看配置中的理论优先级 |
| 媒体富化 | 船只图片等媒体信息不进入 AIS 实时聚合主链路,后续单独做 enrichment |
| v4/v5 顺序 | 在聚合完整性、AISStream 实时链路、采集状态语义和基础身份信息显示修好之前,不进入策略配置和 enrichment UI |
## 背景
当前 AIS 链路以 BarentsWatch 为主。它是 HTTP polling 模式,覆盖挪威附近海域,适合作为稳定的免费起点,但不适合承担全球实时船只数据的全部职责。后续接入 AISStream 后,会出现同一个 MMSI 被多个来源同时上报的情况:
- 位置、航速、航向可能在多个来源之间存在秒级差异。
- 船名、IMO、呼号、船型、尺寸等静态字段可能不完整甚至互相冲突。
- WebSocket 或其他实时流通常更接近实时,但也可能断流或批量延迟。
- 如果每个 collector 自己做去重合并,规则会分散、不可审计,也很难让用户后续配置“某个字段信任哪个来源”。
因此第一阶段不应让采集器直接覆盖最终船只表。更稳的方式是先保留观测事实,再由聚合接口统一给出当前展示视图。
## 目标架构
```mermaid
flowchart LR
A[BarentsWatch HTTP collector] --> D[AIS raw observations]
B[AISStream WebSocket collector] --> D
C[Custom mapped vessel_ais sources] --> D
D --> E[AIS aggregation service]
E --> F[Conflict records]
E --> G[GeoJSON vessels API]
E --> H[Vessel detail API]
I[Aggregation strategy config] --> E
```
### 原始观测层
原始观测层保存每个来源看到的事实。建议模型包含:
| 字段 | 用途 |
|-----|------|
| `target_schema` | 例如 `vessel_ais` |
| `source` | 例如 `barentswatch_vessels``aisstream_vessels` |
| `entity_key` | AIS 使用 MMSI |
| `delivery_mode` | `realtime_stream``batch_stream``polling``snapshot` |
| `transport` | `websocket``sse``http``file` 等 |
| `observed_at` | 上游数据时间,优先使用 AIS 消息时间 |
| `collected_at` | 本系统接收或采集时间 |
| `source_message_id` | 上游消息 ID 或可推导 ID没有则为空 |
| `observation_hash` | 幂等去重指纹,用于防止同一来源重复写入同一条观测 |
| `normalized_payload` | 标准化后的 AIS JSON |
| `raw_payload` | 可选,保存原始或裁剪后的上游记录 |
| `quality_flags` | 观测级质量标记,例如 `stale``position_jump``future_timestamp` |
`delivery_mode``transport` 不应混为一谈。WebSocket 是传输方式streaming 是交付模式。聚合可信度主要看 `delivery_mode``transport` 只作为辅助信息。
原始观测层需要做存储级幂等去重,但这里的去重不是业务合并。推荐使用 `source + entity_key + message_type + observed_at + payload_hash` 或上游稳定消息 ID 作为唯一约束,避免 WebSocket 重连、HTTP 重试或批量回放导致同一事实重复入库。
### 源健康状态
每个采集器应维护独立的健康状态,供聚合服务读取:
| 字段 | 用途 |
|-----|------|
| `source` | 采集器标识 |
| `connection_state` | `connected``reconnecting``disconnected``disabled` 等 |
| `last_seen_at` | 最近收到上游消息或响应的时间 |
| `last_success_at` | 最近成功写入观测的时间 |
| `last_error` | 最近错误摘要 |
| `message_rate` | 最近窗口内的消息速率 |
| `lag_seconds` | 上游观测时间与本系统接收时间的延迟 |
聚合优先级不能只看 `source_priority`。例如 `aisstream_vessels` 默认优先于 `barentswatch_vessels`,但如果它处于 `disconnected``lag_seconds` 超过 freshness 窗口,则动态字段应回退到更新的可用来源。
### 身份键边界
v1 可以继续用 MMSI 作为 `entity_key`,因为它是 AIS 动态消息里最稳定、最容易获得的主键。但文档和模型都要为后续扩展留出口MMSI 可能复用、填错或缺少静态信息,后续身份解析应结合 `mmsi + imo + callsign + name + dimensions` 判断是否需要拆分或合并实体。
### 冲突记录层
聚合服务发现同一个实体、同一个字段存在多个非空不同值时,写入冲突记录。冲突记录不代表错误,只代表“有多个可用候选值”。
```json
{
"target_schema": "vessel_ais",
"entity_key": "257123000",
"field": "name",
"candidates": {
"barentswatch_vessels": "OSLO TRADER",
"aisstream_vessels": "OSLO TRADER II"
},
"selected_source": "aisstream_vessels",
"selected_value": "OSLO TRADER II",
"selected_reason": "delivery_mode_priority",
"resolved_by": "system",
"status": "open"
}
```
第一阶段只需要记录冲突和当前选择原因,不需要做人工逐条确认。后续 UI 的目标也不是让用户处理每条冲突,而是把冲突沉淀成字段级规则。
## 聚合规则
### 字段分类
| 类型 | 字段 | 默认策略 |
|-----|------|----------|
| 动态位置 | `lat``lon``sog``cog``heading``nav_status` | 优先最新 `observed_at`,同时间再按来源优先级 |
| 静态身份 | `name``callsign``imo``flag` | 非空优先,再按字段策略或来源优先级 |
| 静态规格 | `vessel_type``vessel_type_name``length``width``draught` | 非空优先;冲突时记录候选值 |
| 轨迹点 | `track_points` | 按时间线合并;同一时间窗口内相近点去重;保留点级 `source` |
| 元信息 | `field_sources``conflict_count``selected_reasons``quality_flags` | 聚合接口生成,便于调试和后续 UI 展示 |
### 默认优先级
默认优先级应使用两个维度:
```yaml
delivery_mode_priority:
- realtime_stream
- batch_stream
- polling
- snapshot
transport_priority:
- websocket
- sse
- http
- file
```
`delivery_mode_priority` 是主判断。比如 AISStream 如果提供实时推送,应标记为 `realtime_stream + websocket`BarentsWatch 当前是 `polling + http`
### 断流保护
实时流不能永久凭身份占优。聚合时需要 freshness 窗口:
```yaml
freshness:
realtime_stream_seconds: 900
polling_seconds: 3600
```
如果 `aisstream_vessels` 最近 15 分钟没有该 MMSI 的新观测,而 BarentsWatch 轮询源有更新位置,则位置类字段应采用 BarentsWatch 的更新观测,并记录选择原因 `newest_observation``freshness_fallback`
### 异常位置保护
多源 AIS 接入后,聚合服务必须过滤或降权明显异常的位置观测:
- 经纬度必须在合法范围内。
- `observed_at` 不能明显来自未来。
- 同一 MMSI 短时间内跨越不合理距离时,标记 `position_jump`,默认不直接采用该点。
- 当异常点来自当前优先源时,应记录 `selected_reason = anomaly_rejected`,再回退到其他可用来源。
异常保护不应静默丢弃事实。原始观测仍应保留,聚合结果通过 `quality_flags` 和冲突记录解释为什么没有采用它。
### 轨迹聚合
轨迹接口不能简单拼接所有来源,否则前端会出现折返、抖动和重复点。默认规则:
-`observed_at` 排序,生成统一时间线。
- 同一来源的完全重复点通过 `observation_hash` 去重。
- 多来源在短时间窗口内上报的相近位置视为同一轨迹点,优先选择 freshness 和 source priority 更高的一条。
- 每个轨迹点保留 `source``selected_reason` 和必要的 `quality_flags`
- 对被判定为 `position_jump` 的点,默认不进入展示轨迹,但可通过调试参数查看。
## 聚合接口
现有展示接口应逐步改为消费聚合服务,而不是自己直接拼 `VesselPosition + VesselStatic`
```text
GET /api/v1/visualization/geo/vessels
GET /api/v1/visualization/vessels/{mmsi}
GET /api/v1/visualization/vessels/{mmsi}/track
GET /api/v1/visualization/vessels/{mmsi}/conflicts
```
GeoJSON properties 建议增加:
```json
{
"mmsi": 257123000,
"name": "OSLO TRADER",
"lat": 59.91,
"lon": 10.73,
"received_at": "2026-04-30T10:00:00Z",
"field_sources": {
"name": "aisstream_vessels",
"lat": "aisstream_vessels",
"lon": "aisstream_vessels",
"vessel_type": "barentswatch_vessels"
},
"selected_reasons": {
"name": "delivery_mode_priority",
"lat": "newest_observation",
"vessel_type": "non_empty_priority"
},
"quality_flags": [],
"conflict_count": 2
}
```
## 开放配置计划
### Phase 1 — 内置默认策略和只读解释
- 实现后端默认策略。
- 聚合接口返回 `field_sources``selected_reasons``conflict_count`
- 冲突记录可查询,但不允许用户修改。
- 保持现有前端船只图层接口形状基本兼容,新增字段只作为调试和后续 UI 输入。
### Phase 2 — 系统设置中的 JSON/YAML 策略配置
新增系统设置项,例如:
```yaml
collector_aggregation:
vessel_ais:
source_priority:
- aisstream_vessels
- barentswatch_vessels
field_rules:
name:
mode: source_priority
vessel_type:
mode: source_priority
source_priority:
- barentswatch_vessels
- aisstream_vessels
lat:
mode: newest
lon:
mode: newest
```
配置校验要求:
- 未知 source 只警告,不阻断保存,便于先配置后启用。
- 未知 field 必须拒绝,避免拼写错误悄悄失效。
- 动态位置字段默认不允许被固定来源永久锁死,除非显式开启高级选项。
- 空值不覆盖非空值是全局保护,不建议开放关闭。
### Phase 3 — 冲突治理 UI
基于冲突记录提供页面或 drawer
- 查看某个 MMSI 的冲突字段。
- 查看每个字段的候选来源和值。
- 查看当前选择原因。
- 将一次人工选择保存成字段规则,而不是只处理单条冲突。
- 支持恢复默认策略。
## AISStream 采集器计划
AISStream 采集器单独实现,建议命名为 `aisstream_vessels`。它的职责是:
- 维护 WebSocket 连接、订阅范围和重连。
- 将上游 AIS 消息标准化为 `vessel_ais` payload。
- 标记 `delivery_mode = realtime_stream``transport = websocket`
- 写入原始观测层。
- 不直接 upsert 最终展示数据。
配置应放入采集器设置,而不是硬编码:
```yaml
aisstream_vessels:
api_key: "${AISSTREAM_API_KEY}"
bounding_boxes:
- [[-180, -90], [180, 90]]
message_types:
- PositionReport
- ShipStaticData
```
默认不建议直接订阅全球范围。AISStream 采集器应支持以下订阅策略:
- 使用配置的固定 `bounding_boxes`
- 后续支持按 Earth 当前视口或关注区域动态调整订阅范围。
- 支持限制 `message_types`,避免静态信息、位置报告和扩展消息全量涌入。
- 断线后使用指数退避重连,并把连接状态写入源健康状态。
- 重连后可能收到重复或回放消息,因此必须依赖原始观测层的幂等去重。
### 媒体富化边界
VesselFinder 等服务里的船只图片不属于 AIS 实时数据本身。图片、船籍详情、公司信息等后续应作为独立 enrichment 链路:
- 通过 MMSI、IMO、船名等字段异步查询。
- 使用独立缓存和授权配置。
- 不阻塞 `vessel_ais` 实时观测入库。
- 聚合接口只暴露已经缓存好的媒体引用,不在请求链路中现场抓取。
## 版本拆分
计划先按 v0-v3 建立基础能力,再用 v3.1-v3.4 修复当前稳定性缺口,最后进入 v4/v5
### v0 — 聚合基础设施(已实现)
目标是不改变前端展示行为,先把数据底座铺好。
1. 新增原始观测模型、冲突记录模型和源健康状态模型。
2. 为现有 BarentsWatch collector 写入原始观测,同时保留现有 `vessel_position` / `vessel_static` 兼容写入。
3. 实现存储级 `observation_hash` 幂等去重。
4. 补基础管理命令或调试接口,用于查看某个 MMSI 的原始观测和冲突候选。
### v1 — 聚合读接口(已实现)
目标是让展示接口开始消费聚合结果,但前端形状保持兼容。
1. 实现 AIS 聚合服务,先兼容读取现有表,再逐步切换到原始观测层。
2.`/geo/vessels``/vessels/{mmsi}` 改为走聚合服务。
3.`/vessels/{mmsi}/track` 改为走轨迹聚合逻辑。
4. 返回 `field_sources``selected_reasons``quality_flags``conflict_count`
5. 加入 freshness fallback 和异常位置保护。
### v2 — AISStream WebSocket collector已实现
目标是接入第二个真实 AIS 来源,并验证多源冲突和回退逻辑。
1. 实现 `aisstream_vessels` collector。
2. 支持 API key、订阅范围、消息类型、重连和限流配置。
3. 将 AISStream 写入原始观测层,不直接 upsert 最终展示表。
4. 接入源健康状态和 message rate 统计。
5. 提供 AISStream API Key 获取教程、设置页入口和连接验证支持。
6. 为重复消息、断流回退、WS 优先级写集成测试。
### v3 — AISStream 可用性与配置体验(已实现)
目标是让 AISStream 从“能采集”变成日常可观察、可调试、可配置的数据源。
1. 设置页展示 AISStream 运行状态:连接状态、最近收到、最近成功、本轮消息数、延迟和最近错误。
2. AISStream 设置页提供常用采集范围 preset并保留自定义 Bounding Boxes JSON。
3. 聚合结果返回 `source_summary`,展示每艘船的来源、观测数量、最新观测时间、传输模式和消息类型。
4. 保留 `field_sources``selected_reasons`,用于解释动态字段来自实时流、静态字段来自可用非空来源。
5. 船名标准化会读取 AISStream `MetaData.ShipName`;船型展示会从 `vessel_type_name` 和 AIS 数字 `vessel_type` 共同归一化,保证 marker 颜色、详情卡、hover 和搜索结果一致。
6. `/geo/vessels` 不再默认限制 5000 艘;不传 `limit` 或传 `limit=0` 表示全量返回,前端默认也不再二次裁剪到 5000。
### v3.1 — 聚合完整性修复v4 前置)
目标是先保证“所有已采集到的船都能显示”BarentsWatch 不因为接入 AISStream 而被 raw observation 聚合结果遮蔽。
当前风险是 `/geo/vessels` 只要 raw observation 聚合返回非空,就直接使用 raw 聚合结果,不再补读兼容层 `vessel_position + vessel_static`。如果 raw observation 中只存在 AISStream 的几百艘船,或 BarentsWatch 历史数据没有完整回填到 raw 层,最终 Earth 就会只显示 AISStream 子集。
1. `/geo/vessels` 必须合并 raw observation 聚合结果和 legacy latest position 结果。
2. raw 与 legacy 同一 MMSI 同时存在时只显示一艘,优先使用 raw 聚合结果及其 `field_sources` / `selected_reasons`
3. raw 中不存在的 BarentsWatch-only MMSI 必须从 `vessel_position + vessel_static` 补齐。
4. `bbox``type``limit` 过滤必须作用在合并后的最终集合上;不传 `limit``limit=0` 仍表示全量返回。
5. 增加诊断统计,至少能看到 raw AISStream unique MMSI、raw BarentsWatch unique MMSI、legacy unique MMSI、final merged unique MMSI 和被 legacy 补齐的数量。
6. 为 raw 只有 AISStream 子集、legacy 有更多 BarentsWatch 船只的场景补回归测试。
### v3.2 — AISStream 真实时链路v4 前置)
目标是把 AISStream 从“一次 collector 收一批消息后结束”改成真正的 WebSocket 长连接实时数据源,并把实时变化推送到 Earth。
当前 `aisstream_vessels` 只在 collector `fetch()` 中连接 `wss://stream.aisstream.io/v0/stream`,默认收 `max_messages = 500` 条后结束。这不符合 WebSocket 流式数据源的运行语义,也不能保证新船、位置变化和航向变化实时出现在前端。
1. 为 AISStream 增加 streaming service / long-running runner不再依赖单次 `fetch -> transform -> save -> completed` 表达实时采集。
2. 外部 AISStream WebSocket 保持长连接,断线后指数退避重连,并持续更新 `AISSourceHealth`
3. 每条或小批量 AIS 消息标准化后写入 `ais_raw_observations`,按时间或数量短周期 commit避免长事务堆积。
4. 将新增船只、位置变化、航向变化和静态字段补充转换成 vessel delta。
5. 通过应用内部 `/ws``vessels` channel 广播 delta复用 `DataBroadcaster.broadcast_custom("vessels", payload)`
6. Earth 前端订阅 `vessels` channel`vessels.js` 支持按 MMSI upsert marker而不是每次全量 reload。
7. 船只改变航向时,前端必须更新 course bin / marker bucket避免 marker 方向滞后。
8. freshness 超时或 AISStream 健康异常时,动态字段可回退到 BarentsWatch 最新可用观测。
### v3.3 — Streaming 采集状态语义v4 前置)
目标是让采集页面正确表达 AISStream 这类长连接数据源,不再使用一次性 REST collector 的完成型进度条。
REST collector 的自然状态是 `fetch -> transform -> save -> progress 0..100 -> completed`。AISStream 的自然状态应是 `connecting -> streaming -> reconnecting -> stopped/failed`,没有固定总量,也不应在收到一批消息后显示“采集完成”。
1. AISStream 采集状态使用 indeterminate / streaming 状态,而不是百分比完成进度条。
2. 设置页运行状态卡展示连接状态、已运行时长、本轮消息数、新增观测数、unique MMSI、message rate、最近消息时间、延迟和最近错误。
3. `phase_message` 使用“正在接收 AISStream 实时消息”“重连中”“已停止”等长连接语义。
4. 停止、重连和配置变更要有明确操作入口;配置变化后必须安全重订阅。
5. 后端任务状态不能因为没有 `total_records` 就长期显示 `0%` 或误判失败。
6. WebSocket 健康状态和 collector task 状态要分离:上游短暂断线是 `reconnecting`,不是普通采集任务完成或失败。
### v3.4 — 船只身份字段和名称聚合修复v4 前置)
目标是把 MMSI、IMO、callsign 这类身份编号按字符串显示,并把仍然使用 MMSI 作为船名的记录视为信息聚合未完成,而不是正常船名。
1. 前端详情卡、hover、搜索结果和日志中的 `mmsi``imo``callsign` 必须作为 identifier 字段展示,禁止走 `toLocaleString()` 或数字千分位格式。
2. GeoJSON 可增加 `mmsi_display` / `imo_display` 等字符串字段,但前端仍必须对 identifier key 做兜底格式保护。
3. 聚合服务生成船名时,不能把 `MMSI 257123000` 当成真实 `name` 的成功结果;它只能作为 display fallback。
4. 增加诊断查询,列出所有当前仍以 MMSI 号码或 `MMSI <number>` 作为船只名称的记录,包括:
- `vessel_static.name` 为空或等于 MMSI fallback 的 MMSI
- raw observation 中没有任何非空 `name` / `MetaData.ShipName` / `ShipStaticData.Name` 的 MMSI
- 聚合结果最终 `name` 仍为 fallback 的 MMSI
- 每个 MMSI 的可用来源、最近观测时间、message types 和缺失原因。
5. 对这些 fallback-name 船只建立待修复集合,优先通过 AISStream `ShipStaticData`、BarentsWatch 静态字段和后续 enrichment 缓存补齐。
6. 船只详情面板需要区分“真实船名”和“显示兜底”:真实船名缺失时展示 `MMSI <id>` 可以继续作为标题,但字段来源应标注为 `fallback`,避免误以为聚合成功。
7. 为 MMSI 千分位格式、fallback-name 诊断和名称来源解释补回归测试。
### v4 — 策略配置v0 可用)
目标是开放系统级配置,但仍以安全默认值兜底。
已落地的最小子集:
1. 策略持久化在 `system_settings.category = 'vessel_aggregation_strategy'`,保存时自动版本递增。
2. `app/services/vessel_aggregation_strategy.py` 暴露 `load_strategy / save_strategy / reset_strategy / validate_strategy`,并维护 `DEFAULT_STRATEGY` 兜底。
3. 校验规则:
- 未知 `field_rules.<name>``400 unknown vessel_ais field`
- 未知 mode → `400 mode must be one of ...`
- 动态字段(`lat/lon/sog/cog/heading/nav_status`)使用非 `newest` mode 时必须显式 `allow_dynamic_lock=true`,否则拒绝;
- `freshness.realtime_stream_seconds` / `polling_seconds` 必须为非负整数;
- `mode=locked` 必须带非空 `locked_source`
4. 聚合服务 `vessel_ais_aggregation.py``_select_position_observation` 中按 `freshness` 把过期实时流降级到 stale 候选;在 `_select_static_field` 中按 `field_rules.mode = source_priority / locked / newest / non_empty` 选源。
5. 聚合输出每条 vessel 携带 `aggregation_strategy_version`,并在 `/geo/vessels` GeoJSON properties + `/vessels/{mmsi}` 详情中暴露。
6. API
- `GET /api/v1/vessel-aggregation/strategy`
- `PUT /api/v1/vessel-aggregation/strategy`(校验失败 400
- `DELETE /api/v1/vessel-aggregation/strategy`(恢复默认并 bump version
未做项(留给 v4 后续):
- 系统设置 UI 中的策略编辑器尚未做,目前直接调 API
- `transport_priority``quality_flags` 级别的策略尚未引入;
- `source_priority` 中的未知 source 不强校验,留给后续 warn-only 提示。
### v5 — 船舶资料 enrichment 与冲突治理v0 可用)
目标是把 AIS 实时流里不稳定或低频出现的静态信息,补成可缓存、可审计的船舶资料层,同时把冲突解释变成可操作能力。
已落地的最小子集:
1. 新增模型 `app/models/vessel_enrichment.py::VesselProfileEnrichment` + `VesselMediaEnrichment`:以 `mmsi` 为主键,记录 `source / payload / fetched_at / expires_at / confidence / reference_url`;通过 `Base.metadata.create_all``init_db` 中建表。
2. 服务 `app/services/vessel_enrichment.py` 提供 `upsert_vessel_profile_enrichment` / `upsert_vessel_media_enrichment` / `get_vessel_enrichment_bundle`;读路径只读缓存,过期记录(`expires_at < now`)直接过滤为 `None`,永不联网。
3. 聚合接口在 `/api/v1/visualization/vessels/{mmsi}` 响应中追加 `enrichment.profile``enrichment.media` 字段(含 `source / fetched_at / expires_at / confidence / reference_url`);命中失败时返回 `null`,不阻塞 AIS 实时链路。
4. 冲突治理 API
- `POST /api/v1/vessel-aggregation/conflicts/{mmsi}/{field}/promote-to-rule` 读取最近 `AISConflictRecord.selected_source`,写入 `field_rules[field] = {mode: source_priority, source_priority: [<source>]}` 并 bump version
- `DELETE` 对应路径移除该 field 的覆盖,恢复默认。
5. 前端 Earth `info-card.js` 渲染 `船舶资料` 区块profile.payload 标量字段平铺、媒体 `images` 数组缩略图、来源 / 更新时间 / 置信度元数据;缓存命中失败回退到 `资料缓存中`;常规字段在 `field_sources` 命中时附带来源 tag。
未做项(留给 v5 后续):
- 没有真正的异步 enrichment 抓取作业;当前依赖外部脚本/管理 API 写入缓存;
- 冲突治理 UI 还没接入设置中心,目前只暴露 API
- enrichment 命中状态尚未广播到 `vessels` channel详情面板首次打开时按需请求即可。
## 测试计划
- 同一来源同一 `mmsi + observed_at + lat + lon` 重复记录只聚合一次。
- 多来源同一 MMSI 的位置字段优先选择最新观测。
- 实时流和轮询源同时间冲突时,实时流优先。
- 实时流过期后,更新的轮询源可以接管动态字段。
- 实时流源健康状态异常时,动态字段可以回退到更新的可用来源。
- 静态字段不会被空值覆盖。
- 静态字段冲突会写入冲突记录。
- 明显异常位置不会进入默认展示轨迹,并会留下 `quality_flags`
- 同一时间窗口内多来源相近轨迹点只展示一个点。
- AISStream 重连或回放导致的重复消息不会重复进入聚合结果。
- raw observation 聚合结果和 legacy latest position 结果会按 MMSI 合并BarentsWatch-only 船只不会因为 AISStream 子集存在而消失。
- 不传 `limit` 或传 `limit=0` 时,`/geo/vessels` 全量返回合并后的船只集合。
- AISStream 长连接收到新船、位置变化和航向变化后,会通过内部 `/ws``vessels` channel 推送增量。
- AISStream streaming 状态不会显示成固定百分比完成进度条,也不会在收到一批消息后误报采集完成。
- `mmsi``imo``callsign` 等身份编号在前端不显示千分位符。
- 聚合结果中仍以 MMSI fallback 作为船名的记录可以被诊断查询完整列出,并带来源和缺失原因。
- 字段级配置可以覆盖默认来源优先级。
- 聚合接口在没有冲突表时仍可返回兼容 GeoJSON。
## 相关文件
- [实时船只监控系统计划](/home/ray/dev/linkong/planet/docs/plans/earth-vessel-tracking-plan.md)
- [自定义 API 数据源与 LLM 映射系统计划](/home/ray/dev/linkong/planet/docs/plans/datasource-custom-api-mapping-plan.md)
- [BarentsWatch AIS collector](/home/ray/dev/linkong/planet/backend/app/services/collectors/vessel_ais.py)
- [船只模型](/home/ray/dev/linkong/planet/backend/app/models/vessel.py)
- [可视化 API](/home/ray/dev/linkong/planet/backend/app/api/v1/visualization.py)

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# Earth Vessel Rendering Performance Plan
## 当前状态
该计划的前端核心部分已经在 `0.44.1` 落地,但最终实现不是原文设想的 `InstancedBufferGeometry` quad而是更稳的分桶 `THREE.Points` 方案:
- 普通船只按 moving / anchored 和 `VESSEL_COURSE_BINS` 航向分桶,使用 `PointsMaterial` 批量绘制。
- 航行船只仍是带方向的三角形,停泊或低速船只仍是圆点。
- hover / locked 不再放大成世界尺寸 Sprite而是在原点位叠加同尺寸单点 glow overlay。
- picking 改为屏幕空间命中,拖动和惯性期间跳过 hover picking。
- 普通态关闭 glow交互态才显示 glow降低 overdraw 并让默认地图更干净。
后续如果需要全球 AIS 或更高船只密度,再评估是否从分桶 `Points` 升级到真正 instanced quad 或视口 bbox / LOD。
## 背景
Earth 船只图层已经形成了一套较好的视觉语言:
- 航行船只使用三角形标记
- 标记按航向旋转
- 停泊或低速船只使用圆点
- 不同船型使用不同颜色
- hover / locked 状态有 glow、透明度和聚焦反馈
- 标记带有轻微 glow / soft edge和 Earth HUD 的观感一致
当前性能问题不应通过降级成无方向、无船型语义的普通小点来解决。目标是在保留现有观赏性的前提下,把底层从“每艘船一个 Sprite 对象”优化为批量绘制和轻量交互。
## 当前问题判断
卫星图层能承载几万个对象,是因为它主要走 `THREE.Points` / `BufferGeometry` / instanced trail 路径。船只图层目前每艘船创建一个 `THREE.Sprite` 和独立 `SpriteMaterial`,这会带来:
- draw call 随船只数量增长
- 透明 sprite 排序和 overdraw 成本上升
- 每帧遍历所有船只更新 opacity / scale / visible
- pointer move 时对船只 sprite 做对象级 raycast
- hover reset 时全量遍历 marker
因此,即使免费 BarentsWatch AIS 只开放挪威周边数据,前端仍可能因为对象级 sprite、raycast 和每帧全量更新出现地球拖动卡顿。
## 目标
1. 保留当前船只标记的视觉质量。
2. 保留 hover tooltip、点击详情、lock、轨迹等交互。
3. 显著降低 draw call、每帧 JS 遍历和 pointer picking 成本。
4. 为后续全球 AIS 或更高船只数量预留扩展空间。
## 非目标
- 不把船只降级为普通无方向 `Points`
- 不取消船型颜色、航向三角和停泊圆点。
- 不为了短期性能直接删除 hover / click 交互。
## Phase 1交互路径止血
这一阶段不改视觉,只减少 pointer move 和 hover 状态开销。
### 1. 拖动和惯性期间跳过船只 picking
地球拖动时用户主要关注视角变化,不需要每个 pointer move 都命中船只。
处理方式:
- `isDragging === true` 时跳过船只 hover picking。
- 惯性旋转期间也跳过船只 hover picking。
- 拖动结束后再恢复 hover 检测。
### 2. vessel hover picking 节流
对船只 hover 命中增加节流,例如 `80ms ~ 120ms` 一次。鼠标高速移动时复用上一次 hover 状态,不在每个 pointer event 上都做 raycast。
### 3. hover reset 从全量遍历改为增量更新
当前 `resetTransientVesselStates()` 会遍历所有船只。改为记录:
- `hoveredVessel`
- `lockedObject`
当 hover 目标变化时,只更新旧 hover 和新 hover。
### 4. 点击路径只在 click 时做一次精确 picking
点击仍保留精确命中,但只在 click 事件里执行,不参与拖动和高频 pointer move。
## Phase 2每帧更新减负
这一阶段仍保留 `Sprite` 外观,但减少每帧对全部 marker 的写操作。
### 1. `updateVesselVisualState()` 增量化
当前每帧都会遍历船只并写:
- `marker.material.opacity`
- `marker.scale`
- `marker.visible`
优化方向:
- 图层关闭时直接 return。
- 没有船只时直接 return。
- 只有以下状态变化时才更新 marker
- show/hide 变化
- hover 变化
- locked 变化
- camera zoom / distance scale 变化超过阈值
- focus dim 状态变化
### 2. 缓存 distance scale
`getDistanceScale(camera)` 可以按 camera distance 或 zoom 阈值缓存。缩放没有明显变化时,不必每帧重设所有船只 scale。
### 3. 降低透明 overdraw
在不破坏视觉的前提下微调:
- marker 基础尺寸
- glow blur 半径
- 最大 size stabilization
目标是减少屏幕空间重叠面积,而不是改变符号设计。
## Phase 3保留视觉的批量渲染已落地为分桶 Points
原设想是把每艘船的视觉从 `THREE.Sprite` 迁移为 instanced sprite batch。实际落地时选择了更稳的分桶 `THREE.Points`
- 不依赖自定义 shader。
- 不依赖 `Points` 自带 raycaster。
- 用 canvas 纹理保留三角、圆点、船型颜色和航向。
- 用 hover / locked 单点 overlay 保留交互 glow。
如果未来全球 AIS 导致分桶 `Points` 仍不够,再升级到 instanced quad。
### 1. 原候选方案instanced quad
每艘船仍然显示为带贴图/软边的 billboard但底层使用
- `THREE.InstancedBufferGeometry`
- 每类船只一个或少量 material
- per-instance attributes
可按形状和船型拆 batch
- moving cargo
- moving tanker
- moving passenger
- moving fishing
- moving military
- moving other
- anchored / slow dot
这样 draw call 从“每艘船一个”变为“每类船只一个”。
### 2. 原候选方案per-instance attributes
每个 instance 存:
- position
- color
- rotation
- scale
- opacity
- state
- mmsi / data index
hover、locked、dimmed 可通过更新少量 instance attribute 实现,不再逐个修改 material。
### 3. 当前落地方案:分桶 `THREE.Points`
当前实现按以下方式复刻视觉:
- moving 船只按 `VESSEL_COURSE_BINS` 做航向分桶。
- anchored / slow 船只使用圆点分桶。
- 每个分桶生成一组 `THREE.Points`,共享 `PointsMaterial` 和 canvas 点纹理。
- `VESSEL_CONFIG.colors` 仍通过 vertex colors 表示船型颜色。
- hover / locked 在原位置叠加同尺寸单点 overlay普通态不带 glow交互态才带 glow。
这样 draw call 从“每艘船一个”变为“每个形状 / 航向分桶一组”,同时避免自定义 shader 的兼容风险。
### 4. 复刻当前视觉
视觉上继续使用当前 canvas texture 或等效 shader
- moving 使用三角形纹理
- anchored 使用圆点纹理
- 保留 soft glow
- 保留航向 rotation
- 保留 hover / locked 放大
因此用户看到的效果应与当前船只图层基本一致。
## Phase 4picking 改造
批量渲染后不再适合对所有 sprite object 做 `raycaster.intersectObjects()`
### 1. 屏幕空间 picking
参考卫星 picking
1. 过滤背面船只。
2. 将候选船只世界坐标投影到屏幕。
3. 用鼠标位置计算距离。
4. 取距离最近且小于半径阈值的船只。
### 2. 可选空间索引
如果后续船只数量明显上升,可增加轻量空间索引:
- 经纬度网格 bucket
- 屏幕空间 bucket
- viewport bbox 过滤
第一阶段不必引入复杂索引。
## Phase 5数据层和 LOD
当接入全球 AIS 或船只数量显著增加时,再做数据层优化。
### 1. 请求视口范围
前端请求 `/api/v1/visualization/geo/vessels` 时带上当前视口 `bbox`,减少无关船只。
### 2. 后端排序策略
从单纯 `received_at desc` 改为综合排序:
- 数据新鲜度
- 船型优先级
- 当前视口相关性
- 是否正在航行
### 3. 远景聚合
远景可显示聚合或 top N近景展开单船。
## 验收指标
1. 船只视觉效果保持当前质量三角、圆点、颜色、航向、hover、lock 都保留。
2. 开启船只图层后拖动地球不应明显掉帧。
3. pointer move 不应因为船只 hover 导致卡顿。
4. 船只数量达到 `1000` 级别时仍可顺畅旋转地球。
5. `renderer.info.render.calls` 相比 Sprite 版本显著下降。
6. hover / click 命中体验不低于当前版本。
## 建议落地顺序
1. 先做 Phase 1快速恢复地球拖动手感。
2. 再做 Phase 2减少每帧 JS 写操作。
3. Phase 3 和 Phase 4 已按分桶 `THREE.Points` + 屏幕空间 picking 落地。
4. Phase 5 等全球船只数据或数量压力出现后再推进。
5. 如果分桶 `THREE.Points` 达到瓶颈,再评估 instanced quad。

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# 实时船只监控系统 — 实施计划
**状态**:规划中
**创建日期**2026-04-27
**优先数据源**BarentsWatch AIS免费但需要 OAuth client credentials→ AISHub / MarineTrafficTODO付费
## 已确认决策
| 项目 | 决策 |
|-----|------|
| 数据源 | BarentsWatch 先行AISHub / MarineTraffic TODO |
| 船只规模 | BarentsWatch 阶段全部显示;全球数据接入后按需加船型过滤(默认 Cargo + Tanker + Passenger |
| 更新频率 | 准实时:前端 5 分钟轮询,后端 Collector 每分钟拉取写库 |
| 历史轨迹 | 保留(`vessel_position` 表保留 24h后期按需扩展 |
| 推送方式 | 前端展示仍可先用 HTTP 拉取聚合结果AISStream 等实时源应单独实现 WebSocket 采集器 |
---
## 一、技术背景
船只通过 AIS自动识别系统每 210 秒广播位置、航速、航向、目的地等信息。全球约 50 万艘持证船只在线,实时数据通过以下方式获取:
| 来源类型 | 典型服务 | 覆盖范围 | 成本 | 状态 |
|---------|---------|---------|------|------|
| **BarentsWatch AIS API** | live.ais.barentswatch.no | 挪威海域实时 | 免费,需要 AIS API client credentials | **当前使用** |
| **AISHub** | aishub.net | 全球实时 | 免费/小额 | TODO付费接入 |
| **MarineTraffic API** | marinetraffic.com | 全球实时 | $50$500/月 | TODO评估 tier |
| **VesselFinder API** | vesselfinder.com | 全球实时 | $50$300/月 | TODO备选 |
| **自建 SDR 接收** | RTL-SDR + AIS-catcher | 仅本地 3050km | 硬件 $30 | 不考虑 |
| **NOAA 历史数据** | Marine Cadastre | 美国近海历史 | 免费 | 可用于冷启动 |
### BarentsWatch AIS API
- 端点:`https://live.ais.barentswatch.no/v1/latest/combined`
- 需要在 BarentsWatch developer portal 创建 `AIS - API` client通过 client credentials 获取 `scope=ais` 的 access token 后请求 AIS endpoint
- 字段mmsi, lat, lon, sog, cog, heading, nav_status, name, vessel_type, flag
- 刷新频率:数据约 3060s 更新一次,可随意轮询
### TODO多源 AIS 与实时流接入
- [ ] 接入 AISStream WebSocket 采集器,作为 BarentsWatch 覆盖不足的实时补充
- [ ] 将 BarentsWatch、AISStream、自定义 `vessel_ais` 映射源统一写入原始观测层
- [ ] 通过聚合接口做去重、字段合并、冲突记录和默认来源选择
- [ ] 开放字段级聚合策略配置,让用户决定不同字段优先信任哪个来源
- [ ] 评估 AISHub 订阅(全球覆盖,约 $30/月),接入全球实时流
- [ ] 评估 MarineTraffic API tier对比 AISHub 数据质量与成本
- [ ] 实现多数据源适配器,通过 `datasource_config` 切换
- [ ] 真实高频 AIS 稳定接入后,评估将 `vessel_position` 迁移为 TimescaleDB hypertable保留 Postgres 原生分区作为备选)
多源 AIS 的详细设计见 [AIS 多源采集、冲突记录与聚合接口计划](/home/ray/dev/linkong/planet/docs/plans/earth-vessel-ais-aggregation-plan.md)。
---
## 二、实施计划
### Phase 0 — 数据源验证与链路打通12 天)
- 接入 BarentsWatch AIS API验证 OAuth token、数据格式与字段
- 构建全球 mock 数据生成器(用于前端渲染压测,补充 BarentsWatch 的地域限制)
- 确认前端可渲染船只点,整条链路走通
### Phase 1 — 后端基础设施34 天)
#### 1.1 数据库 Schema
```sql
-- 船只静态信息(每 6h 刷新一次)
CREATE TABLE vessel_static (
mmsi BIGINT PRIMARY KEY,
name VARCHAR(128),
callsign VARCHAR(16),
vessel_type SMALLINT,
vessel_type_name VARCHAR(64),
flag VARCHAR(4), -- ISO 国家码
length FLOAT,
width FLOAT,
draught FLOAT,
imo BIGINT,
updated_at TIMESTAMPTZ
);
-- 船只实时位置(高频写入,保留 24h 轨迹)
CREATE TABLE vessel_position (
id BIGSERIAL PRIMARY KEY,
mmsi BIGINT NOT NULL,
lat FLOAT NOT NULL,
lon FLOAT NOT NULL,
sog FLOAT, -- Speed over ground
cog FLOAT, -- Course over ground
heading SMALLINT, -- 真北航向
nav_status SMALLINT, -- 0=航行 1=锚泊 5=停靠 ...
received_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
CREATE INDEX idx_vessel_pos_mmsi_time ON vessel_position(mmsi, received_at DESC);
CREATE INDEX idx_vessel_pos_time ON vessel_position(received_at DESC);
-- 最新位置物化视图(地图渲染主数据源,避免全表扫描)
CREATE MATERIALIZED VIEW vessel_latest AS
SELECT DISTINCT ON (mmsi)
vp.*, vs.name, vs.vessel_type_name, vs.flag, vs.length
FROM vessel_position vp
LEFT JOIN vessel_static vs USING (mmsi)
ORDER BY mmsi, received_at DESC;
CREATE UNIQUE INDEX ON vessel_latest(mmsi);
```
> 后期如需完整历史轨迹查询,迁移 `vessel_position` 到 TimescaleDB 或按天分区。
#### 1.2 CollectorVesselAISCollector
文件:`backend/app/services/collectors/vessel_ais.py`
- 继承 `BaseCollector`,注册到 `collector_registry`
- 轮询间隔3060s由数据源限速决定
- 支持多数据源切换,通过 `datasource_config` 配置 URL + API Key
- 写入逻辑upsert `vessel_latest`append `vessel_position`
- 接入现有调度系统(`scheduler.py`
#### 1.3 API 端点
```
GET /api/v1/visualization/geo/vessels
?bbox=lon_min,lat_min,lon_max,lat_max # 视口裁剪
?type=cargo,tanker,passenger # 船型过滤
?limit=0 # 可选;不传或 0 表示不裁剪数量
→ GeoJSON FeatureCollectionPoint
GET /api/v1/visualization/vessels/{mmsi} # 单船详情
GET /api/v1/visualization/vessels/{mmsi}/track # 历史轨迹(默认 6h
?hours=6
→ GeoJSON LineString
```
GeoJSON Feature 格式:
```json
{
"type": "Feature",
"geometry": { "type": "Point", "coordinates": [lon, lat] },
"properties": {
"mmsi": 123456789,
"name": "EVER GIVEN",
"vessel_type": 70,
"vessel_type_name": "Cargo",
"flag": "PA",
"sog": 12.4,
"cog": 247.0,
"heading": 245,
"nav_status": 0,
"length": 400,
"received_at": "2026-04-27T10:00:00Z"
}
}
```
#### 1.4 更新机制
**前端聚合结果拉取 + 后端实时采集**
- 前端 `setInterval(fetchVessels, 5 * 60 * 1000)` 定期拉取最新快照
- 后端 BarentsWatch collector 继续以 HTTP polling 方式采集
- AISStream 等实时源以独立 WebSocket collector 写入原始观测层
- 展示接口从聚合服务读取当前船只视图,而不是由单个 collector 决定最终展示值
- 前端默认不再给 `/geo/vessels``limit=5000``VESSEL_CONFIG.maxRenderedMarkers = 0` 表示不做前端数量裁剪;后续如性能不足再引入显式 LOD 上限
- marker 颜色、详情卡、hover 和搜索结果必须共享 `vessel_type_display` 船型归一化结果,避免 AIS 数字类型码已驱动颜色但卡片仍显示 `Other`
- 前端是否升级为 WebSocket delta push 是独立优化,不影响后端采集器可以使用 WebSocket 接上游实时源
---
### Phase 2 — 前端渲染34 天)
文件:`frontend/public/earth/js/vessels.js`
#### 2.1 渲染方案
参考现有卫星系统(`satellites.js`)的 InstancedMesh 模式:
- `THREE.InstancedMesh`:每个实例 = 一艘船,矩阵包含位置 + 旋转(朝向 COG
- 行进船:三角箭头图标,朝向 COG 方向
- 静止/锚泊船:圆点图标
- SVG 图标输出到 `frontend/public/earth/assets/icons/vessel-arrow.svg``vessel-dot.svg`
#### 2.2 船型颜色规范
| 船型 | 颜色 |
|-----|------|
| 货轮 Cargo | `#4A90D9` 蓝 |
| 油轮 Tanker | `#E85D04` 橙红 |
| 客船 Passenger | `#06D6A0` 绿 |
| 渔船 Fishing | `#FFD166` 黄 |
| 军舰 Military | `#73797E` 灰 |
| 其他 | `#9B9B9B` 浅灰 |
| 锚泊/停靠 | 降低饱和度 0.4x |
#### 2.3 LOD相机距离细节层次
| 相机距离 | 渲染策略 |
|---------|---------|
| > 400 | 默认渲染当前接口返回的全部船只;如性能不足,再引入可配置 LOD 上限 |
| 200400 | 默认渲染当前接口返回的全部船只;如性能不足,再引入可配置 LOD 上限 |
| < 200 | 渲染当前视口 bbox 内全部船只 |
前端根据相机位置动态计算 bbox附加到 API 请求中。
#### 2.4 图层集成
接入现有图层系统,新增"船只"图层项,支持:
- 图层开/关,状态持久化
- 子过滤(按船型选择显示哪类,可在图例或设置面板中配置)
- 与海缆、BGP、卫星层级共存renderOrder 待定,参考现有层级文档)
#### 2.5 Info Card
复用 `showInfoCard` 机制,点击船只弹出:
```
EVER GIVEN 🚢
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
MMSI 123456789
IMO 9811000
旗帜 巴拿马 🇵🇦
船型 散货轮
当前航速 12.4 kn
航向 247°
状态 航行中
目的地 ROTTERDAM
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[ 查看轨迹 ] [ MarineTraffic ↗ ]
```
#### 2.6 轨迹可视化
点击"查看轨迹" → 请求 `/vessels/{mmsi}/track` → 用 `THREE.CatmullRomCurve3` 渲染插值轨迹线,风格与海缆一致。
---
### Phase 3 — 功能完善23 天)
| 功能 | 说明 |
|-----|------|
| **船只搜索** | 接入现有搜索面板,按名称 / MMSI 搜索 |
| **统计 HUD** | 显示当前在线船只数、各类型分布 |
| **密度热图** | 超低 zoom 时切换为 hex-bin 热力图(避免点云爆炸) |
| **港口标注** | 加载 WorldPorts 数据集,显示主要港口标记 |
| **关键水道监控** | 马六甲、霍尔木兹、苏伊士等高亮 + 流量统计 |
---
### Phase 4 — 性能与生产化23 天)
- `vessel_position` 按天分区7 天自动清理
- TODO真实数据量达到百万级/日后,将 `vessel_position` 升级为 TimescaleDB hypertable配置 retention policy 与压缩策略
- GeoJSON endpoint 用 Redis 缓存 15s
- 若需 bbox 精确查询,引入 PostGIS `geography` + `ST_DWithin`
- InstancedMesh + frustum culling目标 5 万船只 60fps
---
## 三、工作量估算
| Phase | 内容 | 估计时间 |
|-------|-----|---------|
| Phase 0 | 数据源验证、mock | 12 天 |
| Phase 1 | 后端 Schema + Collector + API | 34 天 |
| Phase 2 | 前端渲染InstancedMesh + 图层 + Info Card | 34 天 |
| Phase 3 | 搜索 + 统计 + 轨迹 | 23 天 |
| Phase 4 | 性能优化 + 生产数据源接入 | 23 天 |
| **合计** | | **约 23 周** |
---
## 四、参考资料
- BarentsWatch AIS API 文档https://www.barentswatch.no/en/developer/ais-api/
- MarineTraffic APIhttps://www.marinetraffic.com/en/ais-api-services
- AISHubhttps://www.aishub.net/api
- AIS 导航状态码ITU-R M.1371-5
- 船型编码vessel_typeITU/IMO AIS Message 5 Type and Cargo
- WorldPorts 数据集https://msi.nga.mil/Publications/WPI

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# Markdown 渲染器完善计划
## 背景
Planet 控制台当前有三类主要 Markdown 使用场景:
- 文档中心:技术文档、计划文档、运行手册。
- AI Playground模型回复、分析结果、代码片段。
- BGP 简报:由系统生成并保存的态势报告。
这些场景都复用 `frontend/src/components/MarkdownRenderer/MarkdownRenderer.tsx`。因此 Markdown 能力应该集中在共享渲染器内完成,页面只负责传入内容、链接转换和布局约束,不能让每篇文档或每个页面手写复制按钮、表格样式、列表样式等交互细节。
## 目标
建设一个稳定、可复用、适合技术文档和 AI 输出的 Markdown 渲染器,优先覆盖常用语法、代码块操作和清晰的阅读样式,并为后续语法高亮、锚点导航、内容安全策略留出接口。
## 成功标准
- 代码块支持 fenced language、语言标签、复制按钮、复制成功状态和横向滚动。
- 常用块语法稳定渲染:标题 1-6、段落、引用、分割线、表格、无序列表、有序列表、任务列表。
- 常用行内语法稳定渲染:链接、自动链接、图片、行内代码、粗体、斜体、删除线。
- 文档中心、AI Playground、BGP 简报继续复用同一个组件,不出现页面级重复实现。
- 样式在普通业务面板和文档中心都有合理表现,文档中心可以通过 `.docs-markdown` 覆盖主题变量。
- 前端 TypeScript build 通过,`git diff --check` 无空白错误。
## 当前实施范围
### 第一阶段:共享渲染器补齐
-`MarkdownRenderer` 内解析 fenced code block 的语言信息。
- 引入 `MarkdownCodeBlock` 子组件,负责语言标签、复制按钮和复制状态。
- 保留现有 `Scrollbar` 横向滚动能力,避免长代码撑破页面。
- 扩展标题渲染到 h1-h6并保留 `getHeadingId` 对文档目录的支持。
- 扩展列表解析,支持 `-``*``+``1.``1)` 和 GitHub 风格任务列表。
- 扩展行内解析,支持图片、自动链接、删除线。
### 第二阶段:样式统一
- 全局 Markdown 样式覆盖业务场景,保持紧凑、清晰、可扫描。
- 文档中心用 `.docs-markdown` 适配主题变量,避免硬编码颜色破坏明暗主题。
- 代码块 toolbar 和 copy button 不依赖具体页面。
- 图片默认响应式展示,避免超出内容区域。
### 第三阶段:验证
- 使用前端 build 验证 TypeScript 和 Vite 构建。
- 使用 `git diff --check` 验证补丁格式。
- 手动检查至少一个文档页中代码块复制按钮、语言标签和表格滚动是否出现。
## 后续增强项
### 语法高亮
当前不新增高亮依赖,避免一次性引入过重运行时代码。后续可以在以下方案中二选一:
- `shiki`:适合文档中心,视觉质量高,但包体和初始化成本更高。
- `highlight.js`:接入简单,覆盖语言广,但样式控制需要额外约束。
建议当文档代码块数量稳定增加后再引入,并做按需加载或懒加载。
### 更完整 CommonMark 支持
当前渲染器覆盖 Planet 常见内容,不追求完整 CommonMark 兼容。后续如果需要完整规范,建议切换到成熟生态:
- `react-markdown`
- `remark-gfm`
- `rehype-sanitize`
- `rehype-slug`
切换前需要评估:链接转换、目录 ID、现有样式、AI 输出安全策略和包体影响。
### 安全策略
目前渲染器不解析原始 HTML这是正确默认值。后续如需支持 HTML必须先明确
- 是否允许用户输入 Markdown。
- 是否需要 HTML 白名单。
- 是否需要 `rehype-sanitize`
- 图片和链接是否需要域名策略。
### 文档页能力
可继续补齐:
- 标题锚点悬浮复制。
- Mermaid 图表。
- 代码块折叠。
- 文档内搜索结果定位到代码块。
- 复制按钮埋点,用于判断文档片段是否真正被使用。
## 维护约束
- Markdown 语法能力优先放在共享渲染器,不在具体文档页面散落实现。
- 文档内容只表达内容,不承载 UI 行为。
- 新增 Markdown 能力必须同时考虑文档中心、AI Playground、BGP 简报三个调用方。
- 不解析原始 HTML除非同步引入明确的 sanitize 策略。
- 与主题相关的样式优先走页面容器变量覆盖,不在组件内写死文档中心颜色。

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# Frontend Public Docs Site Plan
## 目标
新增一个公开访问的 `/docs` 页面,作为 Planet 的开发设计文档与使用手册入口。
这个页面应类似常见开源软件文档站:
- 不需要登录即可访问
-`/earth` 和 admin 后台平级,但视觉和信息架构独立
- 直接整理并展示仓库内 `docs/technical` 的 Markdown 文档
- 支持搜索、分类导航、文档目录和内部跳转
-`docs/technical` 继续作为文档真源,避免页面内容和仓库文档漂移
## 非目标
本阶段不做:
- 后端全文搜索服务
- 数据库驱动的 CMS
- 独立文档构建系统,例如 Docusaurus / VitePress
- 每篇文档单独手写 React 页面
- 用户权限、编辑器、在线保存或评论功能
-`docs/plans``docs/deprecated` 全量公开为正式手册
后续可以再决定是否把 plans / deprecated 做成独立的“路线图 / 历史归档”分区。
## 技术路线
### 推荐方案Markdown 直接渲染
使用 Vite 在前端构建阶段直接加载 `docs/technical/**/*.md`
```ts
const modules = import.meta.glob('../../../docs/technical/**/*.md', {
query: '?raw',
import: 'default',
})
```
这样每篇 Markdown 文件仍然留在仓库文档目录中,`/docs` 页面只是读取、索引和渲染这些文档。
当前项目已经满足主要前提:
- 前端使用 Vite + React
- `frontend/vite.config.ts` 已配置 `server.fs.allow: ['..']`
- 已有 `MarkdownRenderer` 可作为基础
- `docs/technical` 文档数量较少,前端本地搜索足够
### 不推荐方案:每篇文档单独写 React
不建议把每篇文档重写成 `.tsx` 页面,因为:
- 文档会出现两份真源
- 修改技术文档时还要同步 UI 页面
- 计划文档、技术上下文、变量表这类内容天然适合 Markdown
- 后续新增文档的成本会变高
只有当某篇文档需要强交互演示、实时图表或复杂 UI 时,才考虑给该文档补充一个 React 组件扩展。
## 信息架构
### 公开路由
新增:
- `/docs`
- `/docs/:slug`
路由行为:
- `/docs` 默认打开 `docs/technical/README.md`,或打开人工指定的首页文档
- `/docs/:slug` 打开对应技术文档
- 未找到文档时显示 docs 专属 404而不是跳回 admin
- `/docs` 加入 `App.tsx` 的公开路由白名单
### 文档分类
`docs/technical` 中的现有文档整理进以下分组:
#### Overview
- `README.md`
#### Earth
- `earth-frontend-context.md`
- `earth-layer-style-reference.md`
- `earth-render-layer-order.md`
- `earth-satellite-footprint-policy.md`
- `earth-bgp-context.md`
- `earth-news-live-streams-collector-format.md`
#### Frontend
- `frontend-admin-frontend-context.md`
- `frontend-layout-guidelines.md`
#### Backend
- `backend-collectors.md`
- `backend-system-service-control.md`
#### Agents
- `agents-aiprovider.md`
#### Ops
- `ops-docker-compose-buildx-upgrade.md`
### 页面布局
桌面端:
- 顶部:产品名、搜索框、当前文档标题
- 左侧:文档分组导航
- 中间Markdown 正文
- 右侧:当前文档目录,也就是 h2 / h3 anchors
移动端:
- 顶部固定搜索入口
- 导航折叠为抽屉或下拉
- 正文单列显示
- 当前文档目录折叠为“本文目录”
视觉风格:
- 像开源软件 docs 页面,清晰、安静、可长时间阅读
- 不复用 admin 后台的重操作感布局
- 不做 Earth 的沉浸式深色 HUD 风格
- 优先阅读性、扫描效率和代码/表格可读性
## 前端实现设计
### 文件结构
建议新增:
```text
frontend/src/pages/Docs/
Docs.tsx
docs-content.ts
docs-search.ts
docs-slugs.ts
Docs.css
```
可选拆分:
```text
frontend/src/pages/Docs/components/
DocsSidebar.tsx
DocsSearch.tsx
DocsToc.tsx
DocsMarkdown.tsx
```
如果初版代码量不大,可以先保持在 `Docs.tsx` + 少量 helper 文件中,避免过度拆分。
### 文档注册表
创建一个 registry负责将 Markdown 文件路径映射为文档元信息:
```ts
interface DocsEntry {
slug: string
path: string
title: string
group: string
order: number
loader: () => Promise<string>
}
```
slug 规则:
- `docs/technical/README.md` -> `overview`
- `docs/technical/earth-layer-style-reference.md` -> `earth-layer-style-reference`
- 只暴露稳定 slug不暴露本机绝对路径
标题规则:
- 优先读取 Markdown 第一个 `# heading`
- 没有 h1 时用人工 registry title
- 再 fallback 到文件名转换标题
### Markdown 渲染
初版可以复用现有:
- [frontend/src/components/MarkdownRenderer/MarkdownRenderer.tsx](/home/ray/dev/linkong/planet/frontend/src/components/MarkdownRenderer/MarkdownRenderer.tsx)
但建议增强或包装为 docs 专用渲染:
- heading 生成稳定 `id`
- 右侧 TOC 使用同一套 heading 解析结果
- 内部 Markdown 链接转换为 `/docs/:slug`
- 外部链接保留 `target="_blank" rel="noreferrer"`
- 表格横向滚动
- 代码块保留等宽字体和语言标记
- 支持 GitHub 风格的相对文档链接
内部链接转换示例:
- `earth-render-layer-order.md` -> `/docs/earth-render-layer-order`
- `./earth-layer-style-reference.md` -> `/docs/earth-layer-style-reference`
- `/home/ray/dev/linkong/planet/docs/technical/foo.md` -> `/docs/foo`
对非 `docs/technical` 的链接:
- 初版可保留原始链接文本
- 或显示为不可跳转的 repo path
- 后续再扩展为跨文档区导航
### 搜索
初版使用纯前端本地搜索。
索引字段:
- title
- slug
- group
- headings
- markdown 正文纯文本
搜索策略:
- 页面首次加载后异步加载所有 `docs/technical` Markdown
- 生成内存索引
- 用户输入时本地过滤
- 简单打分即可:
- 标题命中权重最高
- heading 命中其次
- 文件名 / slug 命中其次
- 正文命中最低
搜索结果展示:
- 文档标题
- 分组
- 命中的 heading 或正文摘要
- 点击跳转到文档
当前只有 13 篇文档,不需要 Lunr、Fuse 或后端搜索。后续文档数量显著增长时,再考虑引入轻量搜索库。
### 路由接入
修改:
- [frontend/src/App.tsx](/home/ray/dev/linkong/planet/frontend/src/App.tsx)
新增 lazy import
```ts
const Docs = lazy(() => import('./pages/Docs/Docs'))
```
公开路由:
```ts
const publicPaths = new Set(['/', '/earth', '/docs'])
```
注意:`/docs/:slug` 不能只用精确匹配 `Set`
建议改为:
```ts
const isPublicRoute =
window.location.pathname === '/' ||
window.location.pathname === '/earth' ||
window.location.pathname === '/docs' ||
window.location.pathname.startsWith('/docs/')
```
新增 routes
```tsx
<Route path="/docs" element={<Docs />} />
<Route path="/docs/:slug" element={<Docs />} />
```
### 样式
建议独立 `Docs.css`,不依赖 admin 页面布局。
核心样式要求:
- 文档正文最大宽度控制在适合阅读的范围
- 表格横向滚动,不撑破布局
- 代码块横向滚动
- 左侧导航固定或 sticky
- 右侧 TOC sticky
- 移动端隐藏右侧 TOC导航折叠
- 搜索结果浮层或独立面板不遮挡正文阅读
注意:
- 不做营销 hero
- 不做卡片堆叠式首页
- 首页第一屏应直接是文档入口和内容,而不是宣传页
## 实施阶段
### Phase 1基础文档站
目标:
- `/docs` 可公开访问
- 能看到 `docs/technical` 文档列表
- 能打开每篇 Markdown
- 能基本渲染标题、段落、列表、代码块、表格
任务:
- 新增 `Docs` 页面
- 新增 docs registry
- 接入 Vite raw Markdown loading
- 接入 `/docs``/docs/:slug`
- 加入公开路由白名单
- 初版 CSS 布局
验收:
- 未登录访问 `/docs` 不跳转登录
- `/docs/earth-layer-style-reference` 可打开样式参考文档
- `/docs/backend-collectors` 可打开后端采集器文档
- 构建通过:`source ~/.zshrc && bun run build`
### Phase 2搜索与 TOC
目标:
- 支持本地搜索所有 technical 文档
- 当前文档右侧显示目录
- 搜索结果可跳转
任务:
- 实现 heading parser
- 实现 TOC 组件
- 实现 search index
- 搜索结果显示文档标题、分组和摘要
- 当前文档标题与 active nav 高亮
验收:
- 搜索 `Fresnel` 能找到 Earth 图层样式文档
- 搜索 `collector` 能找到 backend collectors
- 点击搜索结果进入对应文档
- 右侧 TOC 点击后滚动到对应 heading
### Phase 3链接清理与文档体验
目标:
- Markdown 内部链接在 docs 站内自然跳转
- 长表格、代码块、绝对路径链接的显示更友好
任务:
- 转换 `docs/technical/*.md` 相对链接
- 转换 repo 内 technical 文档绝对路径
- 外链新窗口打开
- 文件路径链接以代码样式显示
- 增强空状态和 404
验收:
-`docs/technical/README.md` 点击 technical 文档链接进入 `/docs/:slug`
- 不支持的 repo 内路径不会导致前端崩溃
- 外部链接行为正常
### Phase 4文档内容整理
目标:
- `docs/technical` 的首页适合作为公开手册入口
- 每篇文档标题、摘要和分类清晰
任务:
- 检查每篇文档是否有唯一 h1
- 给 README 补公开手册导览
- 必要时补文档摘要
- 保持文档内容仍然服务开发维护,不改成营销语气
验收:
- `/docs` 首页能说明各技术文档用途
- 左侧分类和 README 内容一致
- 没有明显重复、过期或找不到的主入口
## 需要改动的文件
预计新增:
- `frontend/src/pages/Docs/Docs.tsx`
- `frontend/src/pages/Docs/Docs.css`
- `frontend/src/pages/Docs/docs-content.ts`
- `frontend/src/pages/Docs/docs-search.ts`
预计修改:
- `frontend/src/App.tsx`
- `frontend/src/components/MarkdownRenderer/MarkdownRenderer.tsx` 或新增 docs 专用 wrapper
- `docs/technical/README.md`
可选修改:
- `frontend/src/index.css`,只放全局极少量 docs shell reset 时才需要
- `docs/CHANGELOG.md`,实施完成后记录
- `docs/version-history.md`,若进入版本发布流程再更新
## 风险与注意事项
### 构建路径风险
Vite 从 `frontend/src` 读取 `../../../docs/technical/**/*.md` 时,需要确认开发和生产构建都可解析。
缓解:
- 使用相对路径 glob
- 构建验证必须跑 `source ~/.zshrc && bun run build`
- 不使用运行时 `fetch('/docs/...')` 读取仓库文件,避免生产环境缺文件
### Markdown 能力不足
现有 `MarkdownRenderer` 是轻量实现,可能不完整支持所有 GitHub Markdown。
缓解:
- 初版优先覆盖当前 `docs/technical` 实际用到的语法
- 若后续需要脚注、嵌套列表、复杂代码高亮,再考虑引入 `react-markdown` 等依赖
### Bundle 体积
把所有 Markdown 打进前端 bundle 会增加体积。
当前文档数量少,风险可接受。
缓解:
- 使用 lazy page chunk
- Markdown loader 保持异步
- 搜索索引在 `/docs` 页面内初始化,不影响 `/earth` 和 admin 首屏
### 公开内容边界
`docs/technical` 会被公开展示,需要避免包含密钥、内部机器地址、临时方案或不应公开的操作细节。
缓解:
- 实施前快速审阅 `docs/technical`
- 暂不公开 `docs/plans``docs/deprecated`
- 以后如需公开更多文档,先建立 allowlist
## 验收清单
- `/docs` 未登录可访问
- `/docs/:slug` 未登录可访问
- `/docs` 不影响 `/earth`
- 未登录访问 admin 仍然跳登录
- 左侧导航包含所有 `docs/technical` 文档
- 文档按 Overview / Earth / Frontend / Backend / Agents / Ops 分类
- Markdown 表格正常显示并可横向滚动
- 代码块正常显示并可横向滚动
- 搜索可搜索标题、heading 和正文
- 搜索结果点击可跳转
- 当前文档 TOC 可跳转
- 不存在的 slug 显示 docs 404
- `source ~/.zshrc && bun run build` 通过
## 后续增强
- 给文档页面增加复制 heading 链接按钮
- 给代码块增加复制按钮
- 增加“上一页 / 下一页”导航
- 增加最近更新信息
- 从 git metadata 读取文档更新时间
- 引入轻量全文搜索库
- 支持 plans / deprecated 独立分区
- 增加页面内反馈入口

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@@ -1,29 +0,0 @@
# Technical Docs
这里放“当前实现和当前结构”的文档,重点回答:
- 现在代码是怎么组织的
- 当前入口在哪
- 状态和组件如何工作
- 后续改动应该沿着哪条实现边界继续走
适合放入这里的内容:
- 前端上下文
- Earth 前端结构
- Earth 卫星 footprint 策略
- Earth 渲染图层顺序
- Earth 图层样式属性索引
- 后端运行控制
- collector 现状
- 采集格式约定
不适合放入这里的内容:
- 尚未完成的 roadmap
- 未来迭代方案
- 大范围重构计划
这些应放入:
- [docs/plans/README.md](/home/ray/dev/linkong/planet/docs/plans/README.md)

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# Technical Docs
This directory holds "current implementation and current structure" documentation, focusing on:
- How the code is organized right now
- Where the current entry points are
- How state and components work
- Which implementation boundaries future changes should follow
What belongs here:
- Quickstart and user manual
- Frontend context
- Earth frontend structure
- Earth satellite footprint policy
- Earth render layer order
- Earth layer style property index
- Backend runtime control
- Collector status
- Collector settings and connectivity validation
- Earth Interactable integration
- Collection format conventions
## Entry Points
- [Quickstart](/home/ray/dev/linkong/planet/docs/technical/en/quickstart.md): The shortest path to getting Planet running from scratch
- [Planet Manual](/home/ray/dev/linkong/planet/docs/technical/en/manual.md): Complete usage guide for the console, `planet.sh`, Earth, and Docs
- [Collector Settings and Connectivity Validation](/home/ray/dev/linkong/planet/docs/technical/en/datasource-collector-settings-connectivity.md): Data source catalog, collector settings, connectivity validation, and BarentsWatch credentials
- [Earth Interactable Usage](/home/ray/dev/linkong/planet/docs/technical/en/earth-interactable-usage.md): API, lifecycle, and integration examples for Earth surface icon Interactable
What does not belong here:
- Incomplete roadmaps
- Future iteration plans
- Large-scale refactor proposals
Those belong in:
- [Plans Index](/home/ray/dev/linkong/planet/docs/plans/README.md)

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# Data Collectors
## I. System Architecture
```
┌─────────────────────────────────────────────────────────────────┐
│ Data Collection Architecture │
├─────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ TOP500 │ │ Epoch AI │ │ HuggingFace │ │
│ │ Collector │ │ Collector │ │ Collector │ │
│ └──────┬──────┘ └──────┬──────┘ └──────┬──────┘ │
│ │ │ │ │
│ └───────────────────┼───────────────────┘ │
│ ▼ │
│ ┌─────────────────────┐ │
│ │ BaseCollector │◄── Base class (unified) │
│ │ run() method │ │
│ └─────────┬───────────┘ │
│ │ │
│ ┌─────────────────┼─────────────────┐ │
│ ▼ ▼ ▼ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │ fetch() │ │transform()│ │ _save_data│ │
│ │ raw data │ │ transform │ │ save to DB│ │
│ └───────────┘ └───────────┘ └───────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────┐ │
│ │ CollectedData table│◄── Unified storage │
│ └─────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ Scheduler (APScheduler) │ │
│ │ Scheduled tasks: every 4h/6h/12h/1d auto-execute │ │
│ └─────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
```
## II. Pipeline
```python
# 1. Scheduler triggers (scheduled or manual)
# ↓
# 2. run() executes the full pipeline
async def run(self, db):
# 2.1 Check if collector is enabled
if not collector_registry.is_active(self.name):
return {"status": "skipped"}
# 2.2 Record task start
task = CollectionTask(status="running")
db.add(task)
await db.commit()
# 2.3 FETCH — get raw data (implemented by subclass)
raw_data = await self.fetch()
# 2.4 TRANSFORM — convert to unified format
data = self.transform(raw_data)
# 2.5 SAVE — persist to database
records_count = await self._save_data(db, data)
# 2.6 Record task completion
task.status = "success"
task.records_processed = records_count
await db.commit()
```
**Core file**: `backend/app/services/collectors/base.py`
## III. Collector List
| Collector | Data type | Content | Frequency |
|-----------|-----------|---------|-----------|
| TOP500 | supercomputer | Global supercomputer rankings (compute, performance) | 4 hours |
| Epoch AI | gpu_cluster | GPU compute cluster info | 6 hours |
| HuggingFace Models | model | AI model information | 12 hours |
| HuggingFace Datasets | dataset | Dataset information | 12 hours |
| HuggingFace Spaces | space | Demo applications | 1 day |
| PeeringDB | ixp/network/facility | Internet exchange points / networks / facilities | 1-2 days |
| TeleGeography | submarine_cable | Submarine cable information | 7 days |
| BarentsWatch AIS | vessel | AIS vessel positions, speed, heading, MMSI, and related fields | Collector settings |
| AISStream Vessels | vessel_ais | AIS WebSocket realtime stream, written to the raw observation layer and displayed through aggregation | Collector settings |
## IV. Data Format (stored in CollectedData table)
```python
# Each collector's parse_response() return format
{
"source_id": "top500_1", # Original system ID (required)
"name": "El Capitan", # Name (required)
"description": "System desc...", # Description
"country": "United States", # Country
"city": "Livermore, CA", # City
"latitude": "37.6819", # Latitude (string)
"longitude": "-121.7681", # Longitude (string)
"value": "1742.00", # Performance value (e.g. compute)
"unit": "PFlop/s", # Unit
"metadata": { # Extra data (JSON)
"rank": 1,
"r_peak": 2746.38,
"cores": 11039616
},
"reference_date": "2025-11-01" # Data reference date
}
```
## V. Database Schema
**CollectedData table** (`collected_data`)
| Field | Type | Description |
|-------|------|-------------|
| id | SERIAL | Primary key |
| source | VARCHAR(100) | Data source name (top500, huggingface, etc.) |
| source_id | VARCHAR(100) | Original data ID |
| data_type | VARCHAR(50) | Data type (supercomputer, model, etc.) |
| name | VARCHAR(500) | Name |
| title | VARCHAR(500) | Title |
| description | TEXT | Description |
| country | VARCHAR(100) | Country |
| city | VARCHAR(100) | City |
| latitude | VARCHAR(50) | Latitude |
| longitude | VARCHAR(50) | Longitude |
| value | VARCHAR(100) | Performance value |
| unit | VARCHAR(20) | Unit |
| metadata | JSONB | Extra metadata |
| collected_at | TIMESTAMP | Collection time |
| reference_date | TIMESTAMP | Data reference date |
| is_valid | INTEGER | Whether valid |
**Core file**: `backend/app/models/collected_data.py`
## VI. TOP500 Collector Example (full pipeline)
```python
# 1. fetch() — get HTML from the web
async def fetch(self):
url = "https://top500.org/lists/top500/list/2025/11/"
response = await client.get(url)
return response.text # returns HTML
# 2. parse_response() — parse HTML into unified format
def parse_response(self, html):
soup = BeautifulSoup(html, "html.parser")
table = soup.find("table")
for row in table.find_all("tr")[1:]: # skip header
cells = row.find_all("td")
entry = {
"source_id": f"top500_{cells[0].text}",
"name": cells[1].text.strip(),
"country": cells[2].text.strip(),
"city": "",
"latitude": "",
"longitude": "",
"value": "1742.00",
"unit": "PFlop/s",
"metadata": {
"rank": 1,
"cores": "11340000"
},
"reference_date": "2025-11-01"
}
data.append(entry)
return data
# 3. run() automatically calls _save_data() to save to database
```
**Core file**: `backend/app/services/collectors/top500.py`
## VII. Scheduler
```python
# Register all collectors into scheduled tasks at startup
def start_scheduler():
for name, collector in collectors.items():
if collector_registry.is_active(name):
scheduler.add_job(
run_collector_task,
trigger=IntervalTrigger(hours=collector.frequency_hours),
id=name,
name=name
)
```
| Collector | Frequency |
|-----------|-----------|
| TOP500 | Every 4 hours |
| Epoch AI | Every 6 hours |
| HuggingFace | Every 12 hours |
| PeeringDB | Every 1-2 days |
| TeleGeography | Every 7 days |
**Core file**: `backend/app/services/scheduler.py`
## VIII. Code Files
```
backend/app/services/collectors/
├── base.py # Base class: run() pipeline, _save_data() persistence
├── registry.py # Collector registry
├── scheduler.py # Scheduled task dispatch (APScheduler)
├── top500.py # TOP500 collector
├── epoch_ai.py # Epoch AI collector
├── huggingface.py # HuggingFace collector
├── peeringdb.py # PeeringDB collector
└── telegeraphy.py # TeleGeography submarine cable collector
backend/app/models/
└── collected_data.py # Unified data model
```
## IX. Data Usage
Collected data ultimately:
1. **Visualization** — displays supercomputers, GPU clusters, and submarine cables' geographic positions
2. **Situational analysis** — global compute distribution statistics and growth trends
3. **Alert system** — detects changes to important nodes
## X. Collector Registration
Collectors are automatically registered at application startup:
```python
# backend/app/services/collectors/__init__.py
collector_registry.register(TOP500Collector())
collector_registry.register(EpochAIGPUCollector())
collector_registry.register(HuggingFaceModelCollector())
collector_registry.register(HuggingFaceDatasetCollector())
collector_registry.register(HuggingFaceSpacesCollector())
collector_registry.register(PeeringDBIXPCollector())
collector_registry.register(PeeringDBNetworkCollector())
collector_registry.register(PeeringDBFacilityCollector())
collector_registry.register(TeleGeographyCableCollector())
collector_registry.register(TeleGeographyLandingPointCollector())
collector_registry.register(TeleGeographyCableSystemCollector())
```
**Core file**: `backend/app/services/collectors/registry.py`
## XI. Triggering Collection
### Method 1: Scheduled
At startup, APScheduler automatically creates scheduled tasks based on each collector's `frequency_hours` setting.
### Method 2: Manual API trigger
```bash
# Trigger TOP500 collection
curl -X POST http://localhost:8000/api/v1/datasources/1/trigger \
-H "Authorization: Bearer <token>"
```
**Core file**: `backend/app/api/v1/datasources.py`

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# Collector Settings and Connectivity Validation
## Background
The console now separates the "data source catalog" from "collector configuration":
- `/datasources`
- Lists all data sources, including built-in and custom sources.
- Clicking a name only opens an information drawer.
- Focuses on status, manual collection, and running collection tasks.
- `/settings?tab=collector_credentials`
- Displays as "Collector Settings".
- Owns endpoint, headers, base parameters, and credentials.
- Every collector exposes a connection button for health checks.
This reduces first-use confusion: API endpoints, headers, credentials, and custom source configuration all belong to collector settings instead of being scattered across the data source list and system settings.
## User-Facing Rules
Connection state is not a frontend styling state. The backend derives it from the current configuration checksum and previously validated records.
A built-in collector is considered "connected" when either condition is true:
- The current configuration has successfully collected data.
- The user clicked the connection button for the current configuration and backend validation succeeded.
If endpoint, headers, base configuration, or credential fingerprint changes after the last successful validation, the state returns to "needs reconnection".
## Frontend Entry Points
### Data Source Catalog
Files:
- [DataSources.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/DataSources/DataSources.tsx)
- [index.css](/home/ray/dev/linkong/planet/frontend/src/index.css)
Current behavior:
- Built-in and custom data sources are merged into a `UnifiedDataSource` list.
- The table only keeps view, collect, and status actions.
- Clicking the name opens a read-only drawer.
- The drawer shows:
- Whether the source is built in
- Whether it is enabled
- Module, priority, and frequency
- Endpoint
- Headers
- Base configuration
- Whether credentials are required
- When tasks are running, the top progress area shows a clickable `Collecting N` pill.
- Clicking `Collecting N` opens a task list modal with per-task progress.
`data-source-bulk-toolbar__running-pill` is the styling entry point for the "Collecting" pill. It is aligned with other status tags, while hover treatment, arrow affordance, and blue outline indicate interactivity.
### Collector Settings
File:
- [Settings.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/Settings/Settings.tsx)
Current behavior:
- The `collector_credentials` tab is displayed as "Collector Settings".
- A select lists all built-in collectors.
- The only button beside the select is a plug icon for health checks.
- Status tags below the select show:
- `Credentials required` / `No credentials required`
- Module
- `Enabled` / `Disabled`
- `Unchecked` / `Available` / `Unavailable`
- Whether the endpoint is overridden
- Collectors that require credentials place the credential card above base configuration.
- Collectors without credentials only show base configuration.
The connection button uses an inline Tabler-style plug icon with `plug-connected` semantics, avoiding the older refresh icon for a connection action.
## Backend APIs
### Data Source Configuration List
```http
GET /api/v1/datasources/configs/all
```
Returns a merged view of YAML default data sources and database overrides. This route must be declared before `/configs/{config_id}`; otherwise FastAPI treats `all` as a path parameter and returns 422.
Returned fields include:
- `name`
- `default_url`
- `endpoint`
- `is_overridden`
- `is_active`
- `source_type`
- `auth_type`
- `headers`
- `config`
- `config_id`
- `description`
Before returning `config`, internal connectivity validation fields are removed so the frontend does not display validation metadata as user configuration.
### Built-In Collector Connection Status
```http
POST /api/v1/datasources/configs/builtin/connection-status
```
Purpose:
- Accept a candidate configuration.
- Compute its checksum.
- Determine whether the current configuration is already connected.
The current frontend mostly performs an immediate check through the connection button and does not strongly depend on this endpoint. It remains the backend basis for future save-button disabling and restoring initial page state.
### Built-In Collector Connectivity Validation
```http
POST /api/v1/datasources/configs/builtin/connect
```
Purpose:
- Free collectors request the endpoint directly.
- Credentialed collectors go through their credential provider.
- Successful validation writes a system-level connection record.
Successful responses include:
- `success`
- `connected`
- `checksum`
- `stage`
- `message`
- `response_time_ms`
- `credential_provider`
- `credential_source`
### BarentsWatch AIS Connectivity Validation
```http
POST /api/v1/settings/integrations/barentswatch/connect
GET /api/v1/settings/integrations/barentswatch/connectivity
```
BarentsWatch uses separate endpoints because draft credentials must be validated before saving:
- Use draft `client_id` / `client_secret` to fetch a token.
- Use that token to request the AIS endpoint.
- After success, write a built-in collector connection record using the draft credential fingerprint.
## Connectivity Validation Service
File:
- [datasource_connectivity.py](/home/ray/dev/linkong/planet/backend/app/services/datasource_connectivity.py)
Core responsibilities:
- Compute built-in collector configuration checksums.
- Read credentials from environment variables and `~/.zshrc`.
- Determine whether the current configuration is already connected.
- Run endpoint health checks.
- Save successful connection records.
### Checksum Inputs
The checksum includes:
- Collector name
- Endpoint
- Auth type
- Headers
- Config after removing internal validation fields
- Credential provider
- Credential fingerprint
The credential fingerprint is a hash of credential content. Plaintext credentials are not written into connection records.
### Connection Records
Successful connection records are written to `SystemSetting`:
```text
category = datasource_connectivity_validations
```
The payload uses collector source as the key:
```json
{
"barentswatch_vessels": {
"checksum": "...",
"status": "success",
"validated_at": "2026-04-29T00:00:00+00:00",
"status_code": 200,
"credential_source": "datasource_config",
"connected_by": "connection_button"
}
}
```
`connected_by` currently has two sources:
- `connection_button`: the user manually clicked the connection button.
- `collection`: a collection task completed successfully, so the system recorded the current effective configuration as connected.
### Successful Collection Means Connected
After a successful collection, the scheduler writes a connection record:
- [scheduler.py](/home/ray/dev/linkong/planet/backend/app/services/scheduler.py)
This prevents collectors that already have data from asking the user to validate again. Reconnection is only required when the configuration checksum changes.
## BarentsWatch AIS Credential Chain
Files:
- [barentswatch.py](/home/ray/dev/linkong/planet/backend/app/services/barentswatch.py)
- [vessel_ais.py](/home/ray/dev/linkong/planet/backend/app/services/collectors/vessel_ais.py)
Resolution priority:
1. `DataSourceConfig.auth_config`
2. `DataSourceConfig.config`
3. Environment variables
4. `~/.zshrc`
Supported environment variables:
```bash
export BARENTSWATCH_CLIENT_ID="..."
export BARENTSWATCH_CLIENT_SECRET="..."
```
Historical misspellings are also supported:
```bash
export BARRENTSWATCH_CLIENT_ID="..."
export BARRENTSWATCH_CLIENT_SECRET="..."
```
Token request rules:
- Token URL: `https://id.barentswatch.no/connect/token`
- `Content-Type`: `application/x-www-form-urlencoded`
- Body:
- `grant_type=client_credentials`
- `client_id`
- `client_secret`
- `scope=ais`
AIS request rules:
- Default endpoint: `https://live.ais.barentswatch.no/v1/latest/combined`
- Header: `Authorization: Bearer <access_token>`
`VesselAISCollector` no longer reads environment variables directly. It goes through `resolve_barentswatch_config()` and `fetch_barentswatch_access_token()` so settings, connectivity validation, and collection do not fork into three credential flows.
## AISStream Collector Chain
Files:
- [aisstream.py](/home/ray/dev/linkong/planet/backend/app/services/collectors/aisstream.py)
- [vessel_ais_aggregation.py](/home/ray/dev/linkong/planet/backend/app/services/vessel_ais_aggregation.py)
AISStream uses a WebSocket realtime stream. The collector writes only to the `ais_raw_observations` raw observation layer; it does not directly overwrite the final vessel display table. The aggregation API handles multi-source deduplication, field selection, and conflict records.
Configuration:
- `api_key`: stored in `DataSourceConfig.auth_config`, or provided through `AISSTREAM_API_KEY`.
- `endpoint`: defaults to `wss://stream.aisstream.io/v0/stream`.
- `message_types`: defaults to `PositionReport` and `ShipStaticData`.
- `bounding_boxes`: AISStream format is `[[[lat_min, lon_min], [lat_max, lon_max]]]`; the settings page provides global, Norway / North Sea, Europe coast, East Asia, and North America coast presets.
- `max_messages` and `receive_timeout_seconds`: control the batch-style WebSocket collection window.
Normalization:
- `PositionReport` mainly provides position, speed, course, heading, and navigation status.
- Vessel names can be filled from `MetaData.ShipName` even when the message body has no `name`.
- Vessel type usually comes from lower-frequency `ShipStaticData.Type`; the backend maps AIS numeric type codes to Cargo / Tanker / Passenger / Fishing / Military.
- If a vessel has not yet produced a static message, its aggregated type can still be `Other`; v5 vessel profile enrichment is planned to fill that gap.
## Credential Guide
File:
- [credential_guides.py](/home/ray/dev/linkong/planet/backend/app/services/credential_guides.py)
APIs:
```http
GET /api/v1/settings/credential-guides/{provider}
POST /api/v1/settings/credential-guides/{provider}/generate
POST /api/v1/settings/credential-guides/{provider}/reset
```
Currently supported:
- `barentswatch`
- `aisstream`
The default guide includes the official BarentsWatch tutorial:
```text
https://developer.barentswatch.no/docs/tutorial
```
If the user clicks that the tutorial is not useful, the backend sends the default prompt to AI Provider, generates a new Chinese tutorial, and saves it to `SystemSetting`:
```text
category = collector_credential_guides
```
Reset deletes the custom tutorial and restores the default guide.
## Save Rules
When built-in collector configuration is saved, the internal `connectivity_validation` field is removed so validation state does not mix with user configuration.
BarentsWatch `client_secret` has special handling:
- The input shows a masked preview.
- If the submitted value still matches the masked preview, the backend keeps the old secret.
- If a new value is submitted, the secret is replaced.
- The previous separate "clear current secret" checkbox is no longer provided.
## Test Coverage
Related tests:
- [test_vessels.py](/home/ray/dev/linkong/planet/backend/tests/test_vessels.py)
Added coverage:
- BarentsWatch credentials can be parsed from `~/.zshrc`.
- When environment variables are empty, `resolve_barentswatch_config()` can fall back to `~/.zshrc`.
- Vessel data conversion and GeoJSON output remain compatible.
## Current Provider Coverage
Credential providers currently supported:
- `barentswatch`
- `spacetrack`
Other collectors with `requires_credentials=true` return that their credential chain has not been wired yet, and the frontend shows `Unavailable`.

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@@ -187,7 +187,7 @@ Current reality:
- that is expected, because incidents are aggregated and de-noised
- but incident-first rendering makes the Earth view look too quiet unless there is another always-available activity layer
Implementation detail for the recommended `activity layer` is expanded in [bgp-region-aggregation-plan.md](/home/ray/dev/linkong/planet/docs/plans/earth-bgp-region-aggregation-plan.md).
Implementation detail for the recommended `activity layer` is expanded in the [BGP Region Aggregation Plan](/home/ray/dev/linkong/planet/docs/plans/earth-bgp-region-aggregation-plan.md).
So the immediate next milestone is:

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# Earth Frontend Context
This document describes the current real structure of the Earth display frontend. The focus is on helping future changes to the HUD, layers, media panel, real terrain, and BGP visualization avoid repeating past structural and state-sync pitfalls.
Related references:
- [Project Rules](/home/ray/dev/linkong/planet/rules.md)
- [Frontend Layout Guidelines](/home/ray/dev/linkong/planet/docs/technical/en/frontend-layout-guidelines.md)
## Current Goal
The Earth frontend is not an ordinary admin page — it is an independent large-screen display frontend. Current product goals:
- Maintain the spatial depth and readability of the globe view
- Keep HUD, layers, media panel, BGP, satellites, cables, and similar elements in a unified interaction model
- Clearly represent states like loading, enabled, hidden, and locked
## Current Entry Point
React route entry:
- [Earth.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/Earth/Earth.tsx)
The current approach is simple:
- The React page only provides a full-screen `iframe`
- The actual Earth application runs at:
- [index.html](/home/ray/dev/linkong/planet/frontend/public/earth/index.html)
Earth frontend is essentially a standalone static application under `public/earth`.
## Current File Layers
### 1. Page Entry and Structure
- [index.html](/home/ray/dev/linkong/planet/frontend/public/earth/index.html)
Responsibilities:
- Base HUD DOM
- Layer panel
- Media panel
- Toolbar
- Settings dialog
- Legacy element ID compatibility
### 2. Main Runtime
- [main.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/main.js)
Responsibilities:
- Globe initialization
- Three.js scene assembly
- Data loading and refresh
- Layer module integration
- Earth-level state synchronization
### 3. Earth Control Layer
- [controls.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/controls.js)
Responsibilities:
- Toolbar interaction
- Layer panel interaction
- Rotation / zoom / layout
- HUD panel drag
- Layer toggle state machine
- Earth settings read, persist, and reset
This is currently the most critical UI control entry point for the Earth frontend.
### 4. UI and Status Messages
- [ui.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/ui.js)
Responsibilities:
- Loading panel
- Status message
- Tooltip / error / cleanup logic
### 5. Globe and Terrain
- [earth.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/earth.js)
- [terrain.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/terrain.js)
Responsibilities:
- Globe sphere, cloud layer, atmosphere
- Real terrain mesh
- Terrain tile fetch, decode, displacement, and shading
### 6. Layer Modules
- [satellites.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/satellites.js)
- [cables.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/cables.js)
- [vessels.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/vessels.js)
- [bgp.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/bgp.js)
- [bgp-cruise-adapter.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/bgp-cruise-adapter.js)
- [compute-centers.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/compute-centers.js)
- [country-boundaries.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/country-boundaries.js)
Each module is responsible for its own:
- Data fetching
- Three.js mesh creation and update
- State tracking (loaded, visible, hover, locked)
- Self-cleanup (dispose on scene destroy)
### AIS Vessel Layer
The vessel layer fetches `/api/v1/visualization/geo/vessels` and renders the aggregated AIS GeoJSON through `createInteractableLayer()`. By default it does not send a `limit` parameter, and `VESSEL_CONFIG.maxRenderedMarkers = 0` means the frontend does not clip the result to 5000 vessels. A positive `options.limit` or positive `maxRenderedMarkers` can still be used as an explicit temporary cap.
Vessel color and vessel type text must use the same normalized classification. `vessels.js` derives `type` from both `vessel_type_name` and the AIS numeric `vessel_type` code; that `type` drives marker color. It also derives `vessel_type_display`, which `main.js` uses for the info card, hover summary, and search result subtitle. Do not make the info card read only the raw `vessel_type_name`, because AISStream can provide a numeric type while the raw name is still `Other`.
AISStream `PositionReport` messages commonly carry live position and `MetaData.ShipName`, while vessel type usually comes from lower-frequency `ShipStaticData.Type`. The backend normalizes `MetaData.ShipName` into the vessel name and maps numeric type codes into Cargo / Tanker / Passenger / Fishing / Military where available. Missing type detail should wait for a static AIS message or the planned vessel profile enrichment; the frontend should not invent a more specific type.
### 7. HUD Panels and Search
- [hud-panels.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/hud-panels.js)
- [info-card.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/info-card.js)
- [search.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/search.js)
- [legend.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/legend.js)
### 8. Cruise Mode
- [cruise-sequencer.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/cruise-sequencer.js)
- [callout-connector.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/callout-connector.js)
The cruise sequencer handles generic logic: current target, queue order, camera focus, and dwell / hide / switch. Business modules supply target queues and content — they should not contain camera control logic.
### 9. Constants
- [constants.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/constants.js)
All material, layer, satellite, BGP, cable, terrain, celestial, and other style parameters are maintained here. Do not scatter magic numbers in module files.
## Current Style Layers
CSS files in `frontend/public/earth/css/` each correspond to a specific component scope. Do not write global Earth styles into `base.css` unless they genuinely apply to everything.
## Current Layer Toggle State Semantics
### `data-status-target`
Layer toggle buttons use `data-status-target` attributes to link button state to layer state. The state machine in `controls.js` handles:
- `loading`: showing the loading indicator
- `enabled`: layer is active
- `hidden`: layer is hidden
- `error`: layer failed to load
This is the canonical way to synchronize button visual state with actual layer state. Do not maintain separate boolean flags for button display.
## Current Settings Persistence
Earth settings are stored in `localStorage`. The key is typically a namespaced string defined in `constants.js`. `controls.js` handles read, write, and reset.
Settings that affect visual layers (terrain opacity, day/night mode, satellite display style, etc.) are read during initialization and applied immediately.
## Current Terrain Pipeline
1. `terrain.js` creates a sphere geometry with enough segments
2. On load, fetches Terrarium-format elevation tiles from the backend
3. Decodes R/G/B into elevation values
4. Displaces vertex positions radially based on elevation
5. Applies a vertex alpha that fades terrain edges at coastlines
6. Terrain writes to the scene as a mesh above the HD texture layer
When HD texture is off, terrain is temporarily hidden and its state is remembered. When HD texture comes back on, terrain restores its prior visibility.
## Current High-Frequency Risk Points
### 1. Visual State and Business State Out of Sync
The most common class of Earth bugs:
- Button shows "loaded," but layer has no objects rendered
- Button shows "hidden," but objects are still visible
- Loading ended, but button still looks like it hasn't
All future changes must prioritize checking state sync.
### 2. HUD Layout: Check Structure First, Not CSS Patches
Earth HUD has repeatedly experienced:
- Panel compressed to a sliver
- Markdown content clipped
- Tabs/iframe content consumed by `overflow: hidden`
Inspection order:
1. Who is responsible for height
2. Who is responsible for scrolling
3. Which layer is doing the clipping
Do not immediately add `overflow: hidden` or extra wrapper layers.
### 3. Transitional Paths Must Be Closed Off
Earth has gone through multiple rounds of HUD, toolbar, and media panel refactoring, making it easy to accumulate:
- Old helpers
- Old classes
- Old fallback logic
- Deprecated variants
After each major feature is complete, do a cleanup pass.
### 4. Cruise Mode and Business Events Must Not Be Deeply Coupled
The correct boundary:
- The generic cruise layer only knows:
- Current target
- Queue order
- Camera focus
- Dwell / hide / switch
- Business modules only supply:
- Target queues
- Focus coordinates
- Card content
- Highlight / layer side effects
If future cable, satellite, or news cruise is added, do not copy a new set of `main.js` state variables. Instead reuse:
- [cruise-sequencer.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/cruise-sequencer.js)
- [callout-connector.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/callout-connector.js)
- The business adapter pattern from [bgp-cruise-adapter.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/bgp-cruise-adapter.js)
## Recommended Change Approach
For future Earth changes:
1. First identify what you're changing:
- Three.js rendering layer
- HUD structure layer
- Layer state layer
- Panel content layer
2. If involving layer buttons, connect to the unified state machine
3. If involving visibility toggle, check whether tooltip / legend / info-card / lock all close together
4. If involving panel layout, check structure before touching CSS
## Current Boundary with the Console Frontend
The Earth frontend and the console frontend are not the same UI system:
- Console frontend: React + Ant Design workbench
- Earth frontend: native HUD + Three.js display under `public/earth`
Therefore:
- Earth should not directly reuse Ant Table / AppLayout semantics
- The console should not copy Earth HUD animations and glass-layer design language
For console structure, see:
- [Admin Frontend Context](/home/ray/dev/linkong/planet/docs/technical/en/frontend-admin-frontend-context.md)

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# Earth Interactable Usage
`Interactable` is the shared rendering entry point for icon-like interactive elements on the Earth surface. It extracts the pattern proven by the vessel layer into reusable behavior: normal state uses batched `THREE.Points`, hover and locked states use small overlays, picking uses screen-space hit testing, icon assets are normalized into canvas textures, and the shared layer handles glow, state, size, ground rendering, and same-coordinate avoidance.
Currently integrated layers:
| Layer | Business File | Icon Source | Extra Animation |
| --- | --- | --- | --- |
| AIS vessels | `frontend/public/earth/js/vessels.js` | canvas draw, moving triangle / anchored dot | Vessel tracks are still maintained by the business layer |
| Compute centers | `frontend/public/earth/js/compute-centers.js` | `assets/icons/compute-*.svg` | Estimated-location `?` badge is added through `icon.afterDraw()` |
| BGP events | `frontend/public/earth/js/bgp.js` | canvas draw, symbol by event type | Expanding rings are still maintained by the BGP business layer |
| BGP observers | `frontend/public/earth/js/bgp.js` | `assets/icons/bgp-broadcast-pin.svg` | Halo, activity core, coverage wedge, and radar sweep remain in the BGP business layer |
Landing sites were previously attempted on Interactable, but pin-style SVGs were fragmented by `THREE.Points` depth testing near the Earth edge. They now use a dedicated `THREE.Sprite` path with a yellow flat-sphere texture generated by canvas. The old SVG assets remain in `assets/icons/`, but landing sites no longer depend on SVG at runtime.
## Why Interactable Exists
Before this layer, each surface icon layer could easily reimplement its own version of:
- icon texture generation
- hover / locked state
- glow styling
- picking radius
- zoom-dependent size strategy
- overlap avoidance for identical coordinates
When this logic is scattered across business files, visual behavior drifts and later tuning becomes layer-by-layer repair. The boundary of `Interactable` is: the shared layer owns how icons remain stable on Earth and how they are selected; the business layer owns where data comes from, what the icon means, what detail cards show, and whether extra animation exists.
## Entry Point
```javascript
import { createInteractableLayer } from "./interactable.js";
```
Core call shape:
```javascript
const layer = createInteractableLayer({
id: "example",
objectType: "example_object",
renderOrder: 4.4,
altitudeOffset: 0.2,
pointSize: 34,
icon: {
draw(context, options) {
// draw canvas icon
},
},
getPosition: (item) => ({
latitude: item.latitude,
longitude: item.longitude,
}),
getKind: (item) => item.kind || "default",
});
```
Business modules usually expose only a thin wrapper:
```javascript
export function getExampleMarkers() {
return layer.getMarkers();
}
export function getExamplePointerIntersections(options) {
return layer.getPointerIntersections(options);
}
export function setExampleMarkerState(marker, state = "normal") {
layer.setMarkerState(marker, state);
}
export function updateExampleVisualState(lockedObjectType, lockedObject, camera) {
layer.updateVisualState(lockedObjectType, lockedObject, camera);
}
```
## Configuration
| Option | Default | Description |
| --- | --- | --- |
| `id` | required | Unique layer id used for group name, avoidance registration, and debug. |
| `objectType` | `id` | Business type written to `marker.userData.type`; the main interaction layer uses it to identify locked objects. |
| `renderOrder` | `4` | Base render order for normal points and hover / locked overlays. |
| `altitudeOffset` | `0.2` | Business altitude, used as `CONFIG.earthRadius + altitudeOffset` for the original surface position. |
| `pointSize` | `32` | Base screen pixel size used by both normal points and overlays. |
| `sizeMode` | `"fixed"` | Fixed screen size by default; non-`"fixed"` modes scale by camera distance. |
| `sizeScale` | `{ referenceFov: 75, min: 0.12, max: 3 }` | Scaling bounds when `sizeMode !== "fixed"`. |
| `atlasCellSize` | `128` | Canvas texture cell size for icons. |
| `colors` | `{}` | Supports `normal`, flattened kind keys, and `byKind`. |
| `opacity` | `{ normal: 0.88, dimmed: 0.26, hover: 0.98, locked: 1 }` | Opacity per state. |
| `stateScale` | `{ hover: 1, locked: 1, dimmed: 1 }` | Size multiplier per state. |
| `pulse` | `{}` | Optional locked-state breathing scale, with `enabled`, `speed`, and `amplitude`. |
| `avoidance` | `{ enabled: true, precision: 4, radius: 1.1, step: 0.35 }` | Same-coordinate avoidance across Interactable layers. |
| `icon` | required | Icon source, supporting canvas draw, SVG / image asset, state asset, anchor, and post-processing. |
| `getPosition(item)` | required | Returns `{ latitude, longitude }` or `THREE.Vector3`. |
| `getKind(item)` | `item.type || "default"` | Returns a business kind for color and texture buckets. |
| `getRotationBin(marker)` | `0` | Returns a rotation bucket, such as 32 heading buckets for vessels. |
| `getBucketKey(marker)` | `String(getRotationBin(marker))` | Returns a texture / geometry bucket key. |
| `getPointSizeMultiplier(marker)` | `1` | Per-marker size multiplier. BGP events use severity; observers use activity. |
| `getUserData(item)` | `item` | Business fields written onto the marker. |
## Icon Configuration
`icon.anchor` is optional and defaults to `{ x: 0.5, y: 0.5 }`, meaning the texture center aligns with the marker coordinate. It is only suitable for small visual anchor offsets. If the icon body is large and must remain fully visible at the Earth edge, such as the old landing-site pin, it should not be forced through `THREE.Points + depthTest`; the body will be clipped by Earth depth.
### Canvas Icons
Canvas icons fit vessels and BGP events where symbols need to be drawn dynamically by state or rotation:
```javascript
const vesselIconLayer = createInteractableLayer({
id: "vessels",
objectType: "vessel",
pointSize: 34,
icon: {
draw(context, { marker, rotationBin = 0, glow = false, color = "#ffffff" }) {
if (!marker.userData.anchored) {
context.rotate((rotationBin / 32) * Math.PI * 2);
}
context.fillStyle = color;
context.shadowColor = color;
context.shadowBlur = glow ? 14 : 0;
context.beginPath();
context.moveTo(0, -37);
context.lineTo(28, 32);
context.lineTo(0, 17);
context.lineTo(-28, 32);
context.closePath();
context.fill();
},
},
getRotationBin: getCourseBin,
getBucketKey: (marker) => `${marker.userData.anchored ? "anchored" : "moving"}:${getCourseBin(marker)}`,
});
```
When `icon.coordinates !== "canvas"`, `Interactable` translates the context to the atlas center first. Vessel-style icons that already draw around center coordinates do not need to declare `coordinates`.
### SVG / Image Asset Icons
Asset icons fit facilities such as compute centers and BGP observers:
```javascript
const computeCenterIconLayer = createInteractableLayer({
id: "computeCenters",
objectType: "compute_center",
pointSize: 36,
atlasCellSize: 128,
icon: {
coordinates: "canvas",
colorable: false,
fitSize: 60,
glowBlur: 16,
getSource({ marker, item }) {
const siteType = marker?.userData?.site_type || item?.site_type || "gpu_cluster";
return COMPUTE_CENTER_ICON_SOURCES[siteType];
},
afterDraw(context, { marker, item }) {
if (marker?.userData?.is_estimated ?? item?.is_estimated) {
drawComputeCenterEstimatedBadge(context, true);
}
},
},
});
```
Asset conventions:
- SVG / image files live in `frontend/public/earth/assets/icons/` and are referenced as `/earth/assets/icons/name.svg`.
- Original SVGs should keep a standard `viewBox` and paths; avoid hard-coding transform only for display size.
- Display size is controlled by `icon.fitSize`; it can be a number, `{ width, height }`, or a function.
- If `icon.colorable !== false` and state colors are provided, the shared layer first draws the asset to a temporary canvas and then tints it with `source-in`.
- Multicolor images or SVGs that should not be tinted must set `colorable: false`.
## Lifecycle
Typical load flow:
```javascript
export async function loadExampleLayer(_scene, earth) {
clearExampleData(earth);
const markerData = await fetchExampleData();
await layer.preloadAssets(markerData);
layer.setData(markerData);
layer.attach(earth);
layer.setVisible(showExampleLayer);
return { totalCount: layer.getCount() };
}
```
Method responsibilities:
| Method | Description |
| --- | --- |
| `preloadAssets(items)` | Collects asset sources that may be used by normal / hover / locked states and preloads them with browser `Image`. Canvas-drawn icons can skip this. |
| `setData(items)` | Clears old points, creates markers, registers avoidance, and rebuilds `THREE.Points` by bucket. |
| `attach(parent)` | Mounts the layer group onto the Earth root. |
| `setVisible(next)` | Controls visibility for the group, points, and overlays. |
| `setMarkerState(marker, state)` | Sets `normal` / `hover` and other states, then invalidates visual state. |
| `updateVisualState(focusType, focusObject, camera)` | Updates normal opacity / size and refreshes hover / locked overlays. |
| `getPointerIntersections(options)` | Runs screen-space picking and returns hits sorted by pixel distance. |
| `clearData(parent)` | Unregisters avoidance, disposes geometry / material, clears markers, and removes the group from the parent. |
## Picking Integration
`Interactable` does not depend on the default Three.js raycast for `Points`. The main interaction layer passes Earth, camera, pointer, and hit radius:
```javascript
const intersects = getVesselPointerIntersections({
earth,
camera,
pointer,
radiusPx: 22,
width: window.innerWidth,
height: window.innerHeight,
});
```
The shared layer:
1. Converts the camera position into Earth-local coordinates.
2. Skips markers on the back side.
3. Projects marker world position into screen coordinates.
4. Uses `radiusPx` for pixel-distance hits.
5. Returns the nearest candidate objects.
Earth dragging, inertia, and hover throttling still belong to `main.js` because they depend on global input state.
## Same-Coordinate Avoidance
Avoidance is enabled by default and applies to all layers created through `createInteractableLayer()`. The shared layer builds an `icon_avoidance_key` from latitude / longitude or `THREE.Vector3`, then arranges markers with the same key into a small circle along the surface tangent plane.
Key points:
- `icon_base_position` keeps the original business position.
- Avoidance only changes rendering and picking position. It does not change business latitude / longitude.
- When a single marker returns to its original position, it uses the business surface position computed from `altitudeOffset`.
- When multiple markers share coordinates, the first ring uses `avoidance.radius`; later rings add `avoidance.step`.
If a business layer must stay exactly on the original point, disable avoidance explicitly:
```javascript
createInteractableLayer({
id: "strict-layer",
avoidance: { enabled: false },
});
```
## Business Animation Boundary
`Interactable` currently owns only the icon body and common hover / locked overlays. Complex animations remain in business modules, but should follow the Interactable marker position:
- BGP event expanding rings are independent ring sprites created by `bgp.js`, updated every frame with `position.copy(marker.position)`.
- BGP observer halo, status core, coverage halo, and coverage wedge are managed by `bgp.js`; the icon body is managed by Interactable.
- Vessel tracks remain in `vessels.js` because they depend on track data loaded after a click.
This boundary avoids pushing every animation type into the shared interface too early. If multiple layers reuse the same animation type later, it can move into an Interactable `animations` extension.
## New Layer Checklist
1. Prepare marker data in the business file and keep required business fields.
2. Choose an icon type: canvas draw, SVG / image asset, or dynamic `getSource()`.
3. Configure `pointSize`, `icon.fitSize`, `colors`, `opacity`, and `stateScale`.
4. Provide `getPointSizeMultiplier()` if business-specific size variation is needed.
5. Provide `getRotationBin()` and a stable `getBucketKey()` if rotation exists.
6. During load, call `preloadAssets()` before `setData()`, `attach()`, and `setVisible()`.
7. Wire `getPointerIntersections()` in `main.js` and reuse the existing hover / locked state update flow.
8. Record altitude, `renderOrder`, `pointSize`, and animation ordering in the layer style index and render order documents.

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# Earth Layer Style Property Index
This document records the material, color, opacity, line width, radius offset, and `renderOrder` style properties of all Earth frontend layers. For layer ordering relationships, see [Earth Render Layer Order](/home/ray/dev/linkong/planet/docs/technical/en/earth-render-layer-order.md).
## Naming Conventions
| Category | Convention | Example |
| --- | --- | --- |
| Global config objects | `*_CONFIG` | `COUNTRY_BOUNDARY_CONFIG` |
| Layer radius offsets | `*AltitudeOffset` / `radiusOffset` | `lineAltitudeOffset`, `GRID_CONFIG.radiusOffset` |
| Opacity | `*Opacity` | `hoverLineOpacity` |
| Render order | `*RenderOrder` | `textureOverlayRenderOrder` |
| Color | `*Color`, hex number or CSS color value | `lineColor`, `colors.supercomputer` |
| Line width | `lineWidth` / `*LineWidth` | `GRID_CONFIG.lineWidth` |
## Earth Base and HD Texture
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Earth base radius | `CONFIG.earthRadius` | `100` | `earth.js:createEarth()` |
| Earth base color | `EARTH_MATERIAL_CONFIG.color` | `0x010609` | `MeshPhongMaterial.color` |
| Earth base emissive | `EARTH_MATERIAL_CONFIG.emissive` | `0x010609` | `MeshPhongMaterial.emissive` |
| Earth base specular | `EARTH_MATERIAL_CONFIG.specular` | `0x1a2d45` | `MeshPhongMaterial.specular` |
| Earth base shininess | `EARTH_MATERIAL_CONFIG.shininess` | `12` | `MeshPhongMaterial.shininess` |
| Earth base opacity | `EARTH_MATERIAL_CONFIG.opacity` | `1` | `MeshPhongMaterial.opacity` |
| HD texture radius offset | `EARTH_MATERIAL_CONFIG.textureOverlayAltitudeOffset` | `0.1` | Standalone HD texture sphere radius |
| HD texture opacity | `EARTH_MATERIAL_CONFIG.textureOverlayOpacity` | `0.88` | HD texture `MeshPhongMaterial.opacity` |
| HD texture renderOrder | `EARTH_MATERIAL_CONFIG.textureOverlayRenderOrder` | `0.96` | `_earthTextureOverlay.renderOrder` |
| HD texture specular | `EARTH_MATERIAL_CONFIG.textureOverlaySpecular` | `0x05080d` | Reduces specular highlight in direct-light areas to avoid blown-out texture |
| HD texture shininess | `EARTH_MATERIAL_CONFIG.textureOverlayShininess` | `4` | Reduces specular concentration |
| HD texture color multiplier | inline | `0xffffff` | `_earthTextureOverlayMaterial.color` |
## Earth Occluder and Day/Night
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Occluder radius factor | `EARTH_MATERIAL_CONFIG.occluderRadiusFactor` | `0.999` | Depth occluder sphere radius |
| Occluder segments | `EARTH_MATERIAL_CONFIG.occluderSegments` | `48` | Occluder geometry segments |
| Occluder renderOrder | inline | `-1` | `occluder.renderOrder` |
| Day/night sun direction | `EARTH_MATERIAL_CONFIG.dayNight.sunDirection` | `{ x: 1, y: 0.2, z: 0.4 }` | Custom day/night shader |
| Night-side minimum brightness | `EARTH_MATERIAL_CONFIG.dayNight.nightFloor` | `0.24` | Shader uniform |
| Day-side boost | `EARTH_MATERIAL_CONFIG.dayNight.dayBoost` | `1.12` | Shader uniform |
| Twilight width | `EARTH_MATERIAL_CONFIG.dayNight.twilightWidth` | `0.2` | Shader uniform |
| Twilight intensity | `EARTH_MATERIAL_CONFIG.dayNight.twilightIntensity` | `0.14` | Shader uniform |
| Twilight color | `EARTH_MATERIAL_CONFIG.dayNight.twilightColor` | `0x4ea0ff` | Shader uniform |
| Night tint color | `EARTH_MATERIAL_CONFIG.dayNight.nightTintColor` | `0x0b1830` | Shader uniform |
| Night tint intensity | `EARTH_MATERIAL_CONFIG.dayNight.nightTintIntensity` | `0.08` | Shader uniform |
## Atmospheric Glow and Clouds
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Inner atmosphere radius factor | `EARTH_MATERIAL_CONFIG.atmosInnerRadiusFactor` | `1.01` | `atmosInnerGeo` |
| Inner atmosphere segments | `EARTH_MATERIAL_CONFIG.atmosInnerSegments` | `64` | `atmosInnerGeo` |
| Inner atmosphere color | `EARTH_MATERIAL_CONFIG.atmosInnerColor` | `[0.25, 0.62, 1.0]` | Shader RGB |
| Inner atmosphere rim power | `EARTH_MATERIAL_CONFIG.atmosInnerRimPower` | `3.2` | Shader rim falloff |
| Inner atmosphere intensity | `EARTH_MATERIAL_CONFIG.atmosInnerIntensity` | `0.18` | Shader alpha multiplier |
| Outer atmosphere radius factor | `EARTH_MATERIAL_CONFIG.atmosOuterRadiusFactor` | `1.016` | `atmosOuterGeo` |
| Outer atmosphere segments | `EARTH_MATERIAL_CONFIG.atmosOuterSegments` | `48` | `atmosOuterGeo` |
| Outer atmosphere color | `EARTH_MATERIAL_CONFIG.atmosOuterColor` | `[0.18, 0.45, 0.9]` | Shader RGB |
| Outer atmosphere rim power | `EARTH_MATERIAL_CONFIG.atmosOuterRimPower` | `5.0` | Shader rim falloff |
| Outer atmosphere intensity | `EARTH_MATERIAL_CONFIG.atmosOuterIntensity` | `0.02` | Shader alpha multiplier |
| Atmosphere blending | inline | `THREE.AdditiveBlending` | `ShaderMaterial.blending` |
| Atmosphere renderOrder | inline | `1` | `atmosInner/Outer.renderOrder` |
| No-HD-texture rim glow color | `EARTH_MATERIAL_CONFIG.rimGlowColor` | `[0.35, 0.65, 1.0]` | Fresnel shell RGB when HD texture is hidden or unavailable |
| No-HD-texture rim glow power | `EARTH_MATERIAL_CONFIG.rimGlowPower` | `3.8` | Shader rim falloff; higher = narrower edge |
| No-HD-texture rim glow intensity | `EARTH_MATERIAL_CONFIG.rimGlowIntensity` | `0.28` | Shader alpha multiplier |
| No-HD-texture rim glow segments | `EARTH_MATERIAL_CONFIG.rimGlowSegments` | `64` | `earth-rim-glow` geometry segments |
| Cloud layer radius offset | `CLOUD_LAYER_CONFIG.radiusOffset` | `3` | Cloud sphere radius |
| Cloud layer segments | `CLOUD_LAYER_CONFIG.widthSegments / heightSegments` | `64 / 64` | Cloud sphere geometry |
| Cloud layer opacity | `CLOUD_LAYER_CONFIG.opacity` | `0.15` | `MeshPhongMaterial.opacity` |
| Cloud texture | `CLOUD_LAYER_CONFIG.textureUrl` | `"./assets/earth_clouds_1024.png"` | Cloud texture map |
| Cloud blending | inline | `THREE.AdditiveBlending` | `MeshPhongMaterial.blending` |
## Land/Ocean Base and Country Borders
The land/ocean base is an Earth base-map asset and preloads at startup; the "Border Lines" layer toggle only controls normal border lines, hover lines, and interactive hover.
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Country border data path | `COUNTRY_BOUNDARY_CONFIG.dataPath` | `"/earth/data/countries-admin0.min.geojson"` | GeoJSON input |
| Ocean fill color | local `OCEAN_HEX` | `0x010609` | Land/ocean base canvas background |
| Land fill color | `COUNTRY_BOUNDARY_CONFIG.landColor` | `0x080f1b` | Land/ocean base canvas land |
| Land/ocean base opacity | `COUNTRY_BOUNDARY_CONFIG.landOpacity` | `1.0` | `MeshBasicMaterial.opacity` |
| Land/ocean base radius offset | `COUNTRY_BOUNDARY_CONFIG.landAltitudeOffset` | `0.08` | `country-land-ocean` radius |
| Land/ocean base renderOrder | `COUNTRY_BOUNDARY_CONFIG.landRenderOrder` | `0.86` | `country-land-ocean.renderOrder` |
| Land/ocean mask size | `landMaskWidth / landMaskHeight` | `2048 / 1024` | Canvas / DataTexture size |
| Country tint color | `COUNTRY_BOUNDARY_CONFIG.tintColor` | `0x0b1830` | Tint when HD texture is off |
| Country tint radius offset | `COUNTRY_BOUNDARY_CONFIG.tintAltitudeOffset` | `0.04` | `country-tint` radius |
| Country tint renderOrder | `COUNTRY_BOUNDARY_CONFIG.tintRenderOrder` | `0.2` | `country-tint.renderOrder` |
| Border line color | `COUNTRY_BOUNDARY_CONFIG.lineColor` | `0x7fc7ff` | Normal border line |
| Border line opacity | `COUNTRY_BOUNDARY_CONFIG.lineOpacity` | `0.58` | Normal border line opacity |
| Border dimmed opacity on hover | `COUNTRY_BOUNDARY_CONFIG.dimmedLineOpacity` | `0.18` | Normal border opacity during hover |
| Border line radius offset | `COUNTRY_BOUNDARY_CONFIG.lineAltitudeOffset` | `0.115` | Normal border line radius; slightly above HD texture `0.10` and below terrain base `0.16` to reduce floating |
| Border line renderOrder | `COUNTRY_BOUNDARY_CONFIG.lineRenderOrder` | `2.2` | Normal border line level |
| Border hover color | `COUNTRY_BOUNDARY_CONFIG.hoverLineColor` | `0xff3b1f` | Neon red-orange |
| Border hover opacity | `COUNTRY_BOUNDARY_CONFIG.hoverLineOpacity` | `1.0` | Hover line opacity |
| Border hover radius offset | `COUNTRY_BOUNDARY_CONFIG.hoverAltitudeOffset` | `0.14` | Hover line radius; close to the surface but above normal border lines |
| Border hover renderOrder | `COUNTRY_BOUNDARY_CONFIG.hoverLineRenderOrder` | `2.3` | Hover line level |
| Border hover glow opacity | `COUNTRY_BOUNDARY_CONFIG.hoverGlowOpacity` | `0.38` | Glow line opacity |
| Border hover glow line width | `COUNTRY_BOUNDARY_CONFIG.hoverGlowLineWidth` | `3` | Glow `LineBasicMaterial.linewidth` |
| Border hover glow level offset | `COUNTRY_BOUNDARY_CONFIG.hoverGlowRenderOrderOffset` | `0.01` | Glow renderOrder = `2.29` |
| Border hover glow radius offset | `COUNTRY_BOUNDARY_CONFIG.hoverGlowRadiusOffset` | `0.04` | Glow radius = hover radius + 0.04 |
## Real Terrain
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Terrain tile size | `TERRAIN_CONFIG.tileSize` | `256` | Terrarium tile read size |
| Terrain base zoom | `TERRAIN_CONFIG.baseZoom` | `4` | Terrain sampling zoom |
| Terrain geometry segments | `geometryWidthSegments / geometryHeightSegments` | `320 / 320` | Terrain sphere geometry |
| Terrain base radius offset | `TERRAIN_CONFIG.baseRadiusOffset` | `0.16` | Terrain overlays HD texture |
| Terrain exaggeration | `TERRAIN_CONFIG.exaggeration` | `34` | Elevation to world units |
| Terrain land fade height | `TERRAIN_CONFIG.landRevealFadeMeters` | `220` | Vertex alpha for coastline fade |
| Terrain opacity | `TERRAIN_CONFIG.opacity` | `0.68` | `MeshPhongMaterial.opacity` |
| Terrain color | `TERRAIN_CONFIG.color` | `0x8aa884` | `MeshPhongMaterial.color` |
| Terrain emissive | `TERRAIN_CONFIG.emissive` | `0x030704` | Reduces self-emission to preserve terrain shading |
| Terrain specular | `TERRAIN_CONFIG.specular` | `0x344438` | Gives terrain local sheen without boosting HD texture brightness |
| Terrain shininess | `TERRAIN_CONFIG.shininess` | `16` | Tightens terrain highlight |
| Terrain renderOrder | inline | `1.2` | `terrain.renderOrder` |
| Terrain polygonOffset | inline | `factor -1`, `units -1` | Reduces z-fighting near sphere surface |
## Grid Lines
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Grid radius offset | `GRID_CONFIG.radiusOffset` | `0.14` | Grid sphere radius |
| Grid color | `GRID_CONFIG.color` | `0xc0e0ff` | `LineBasicMaterial.color` |
| Grid opacity | `GRID_CONFIG.opacity` | `0.08` | `LineBasicMaterial.opacity` |
| Grid line width | `GRID_CONFIG.lineWidth` | `1` | `LineBasicMaterial.linewidth` |
| Grid renderOrder | `GRID_CONFIG.renderOrder` | `2.05` | Grid level |
| Latitude step | `GRID_CONFIG.latitudeStep` | `15` | Latitude line generation step |
| Longitude step | `GRID_CONFIG.longitudeStep` | `30` | Longitude line generation step |
| Segment sample step | `GRID_CONFIG.segmentStep` | `5` | Grid line sample step |
## Submarine Cables and Landing Points
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Default cable color | `CABLE_COLORS.default` | `0xffff44` | Used when no data color available |
| Cable radius offset | `CABLE_CONFIG.line.altitudeOffset` | `0.2` | Cable line radius |
| Cable line width | `CABLE_CONFIG.line.lineWidth` | `1` | `LineBasicMaterial.linewidth` |
| Cable opacity | `CABLE_CONFIG.line.opacity` | `1.0` | Cable line opacity |
| Cable renderOrder | `CABLE_CONFIG.line.renderOrder` | `1` | Cable line level |
| Landing point radius offset | `CABLE_CONFIG.landingPoint.altitudeOffset` | `0.2` | Same surface height as cable lines, avoiding a floating marker |
| Landing point sprite height | local `LANDING_POINT_SPRITE_HEIGHT` | `3` | `THREE.Sprite` base height |
| Landing point reference FOV | local `LANDING_POINT_SIZE_REFERENCE_FOV` | `75` | Matches the current Earth camera FOV |
| Landing point scale minimum | local `LANDING_POINT_SIZE_SCALE_MIN` | `0.16` | Minimum multiplier after roughly 200% zoom, limiting high-zoom screen footprint; `3 * 0.16 = 0.48` |
| Landing point scale maximum | local `LANDING_POINT_SIZE_SCALE_MAX` | `3` | Maximum multiplier at far distance; current minimum zoom reaches roughly `2.50` |
| Landing point atlas size | local `LANDING_POINT_ATLAS_CELL_SIZE` | `128` | Canvas flat shaded sphere texture size |
| Landing point color | `CABLE_CONFIG.landingPoint.color` | `0xffaa00` | `SpriteMaterial.color` |
| Landing point opacity | `CABLE_CONFIG.landingPoint.opacity` | `1.0` | `SpriteMaterial.opacity` |
| Landing point renderOrder | `CABLE_CONFIG.landingPoint.renderOrder` | `1` | Same level as cable lines; `depthTest: false` keeps the ball whole, while camera-to-center globe occlusion hides back-side points |
| Landing point dim brightness | `landingPointVisual.dimBrightness` | `0.62` | Dim state color multiplier |
| Related landing point opacity | `landingPointVisual.related.opacityBase / opacityPulse` | `0.8 / 0.2` | Highlight pulse |
| Dimmed landing point color | `landingPointVisual.dimmed.colorRGB` | `{ r: 180, g: 116, b: 28 }` | Dim state color; avoids dark base showing through as a dark hole |
| Dimmed landing point opacity | `landingPointVisual.dimmed.opacity` | `0.78` | Dim state opacity; no longer uses low alpha blending with dark base |
## Satellites, Trails, and Footprints
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Satellite display radius offset | `SATELLITE_CONFIG.displayAltitudeOffset` | `8` | Satellite point position |
| Satellite dot base pixel size | `SATELLITE_CONFIG.dotBaseSize` | `2.8` | Point shader size |
| Satellite backdrop dot scale | `SATELLITE_CONFIG.dotBackdropScale` | `1.28` | Backdrop dot size |
| Satellite dot opacity range | `dotOpacityMin / dotOpacityMax` | `0.7 / 1.0` | Breathing animation |
| Satellite dot breathing speed | `SATELLITE_CONFIG.dotBreathingSpeed` | `0.12` | Dot opacity animation |
| Satellite backdrop renderOrder | inline | `5` | `satelliteBackdropPoints.renderOrder` |
| Satellite dot renderOrder | inline | `6` | `satellitePoints.renderOrder` |
| Satellite trail length | `SATELLITE_CONFIG.trailLength` | `10` | Trail buffer |
| Satellite trail line width | `SATELLITE_CONFIG.trailLineWidth` | `3` | Ribbon shader uniform |
| Selected ring size | `SATELLITE_CONFIG.ringSize` | `0.07` | Hover / locked ring sprite |
| Satellite overlay renderOrder | `SATELLITE_CONFIG.overlayRenderOrder` | `12` | Locked ring / halo / orbit |
| Footprint renderOrder | local `GROUND_FOOTPRINT_RENDER_ORDER` | `3` | Starlink footprint fill and Iridium coverage ring; must stay above land / texture / terrain surface layers |
## AIS Vessels
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Vessel radius offset | `VESSEL_CONFIG.altitudeOffset` | `0.2` | Normal marker position, close to the real terrain base layer |
| Vessel track radius offset | `VESSEL_CONFIG.track.altitudeOffset` | `0.2` | Selected vessel track line, aligned to the vessel marker radius; the frontend anchors the track endpoint to the current marker position |
| Vessel renderOrder | local `VESSEL_RENDER_ORDER` | `4.4` | Normal marker and interactive overlay |
| Vessel track renderOrder | `VESSEL_RENDER_ORDER - 0.1` | `4.3` | Below vessel markers |
| Vessel point pixel size | local `VESSEL_POINT_SIZE` | `34` | Shared size for normal markers and hover / locked overlays |
| Default vessel render cap | `VESSEL_CONFIG.maxRenderedMarkers` | `0` | `0` means the frontend does not clip by default; positive values send `limit` and clip markers |
| Vessel texture canvas size | local `VESSEL_ATLAS_CELL_SIZE` | `128` | Canvas point texture |
| Course bucket count | local `VESSEL_COURSE_BINS` | `32` | Moving vessels are bucketed by COG to reduce draw calls while preserving direction |
| Vessel hover picking throttle | local `VESSEL_HOVER_PICK_INTERVAL_MS` | `100` | `main.js` hover picking |
| Vessel screen hit radius | local `VESSEL_POINTER_RADIUS_PX` | `22` | `main.js` screen-space picking |
AIS vessel markers use batched `THREE.Points`, not one `THREE.Sprite` per vessel. Moving vessels stay triangular, anchored or slow vessels stay circular, and hover / locked states add a same-size glow overlay. Vessel type color and info-card type text must come from the same normalized result: `vessels.js` reads both backend `vessel_type_name` and AIS numeric `vessel_type`, derives the color-driving `type`, then exposes `vessel_type_display` for the info card, hover summary, and search results.
## Compute Centers
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Compute center radius offset | `COMPUTE_CENTER_CONFIG.altitudeOffset` | `0.48` | Marker position |
| Compute center point size | local `COMPUTE_CENTER_POINT_SIZE` | `36` | Shared Interactable base size for normal markers and hover / locked overlays |
| Compute center asset fit size | local `COMPUTE_CENTER_ICON_FIT_SIZE` | `60` | Maximum SVG asset draw size inside the `128x128` atlas canvas, controlled by `icon.fitSize` |
| Compute center base opacity | `COMPUTE_CENTER_CONFIG.marker.baseOpacity` | `0.88` | Normal `PointsMaterial.opacity` |
| Supercomputer marker scale | `COMPUTE_CENTER_CONFIG.marker.supercomputerScale` | `12` | Legacy Sprite scale; not directly used by the current Interactable path |
| GPU cluster marker scale | `COMPUTE_CENTER_CONFIG.marker.gpuClusterScale` | `12` | Legacy Sprite scale; not directly used by the current Interactable path |
| Hover scale | `COMPUTE_CENTER_CONFIG.marker.hoverScale` | `1.16` | Hover overlay size multiplier |
| Locked scale | `COMPUTE_CENTER_CONFIG.marker.lockedScale` | `1.22` | Locked overlay size multiplier, with pulse |
| Dimmed scale / opacity | `dimmedScale / dimmedOpacity` | `0.82 / 0.34` | Dim state |
| Supercomputer color | `COMPUTE_CENTER_CONFIG.colors.supercomputer` | `"#38bdf8"` | Marker texture |
| GPU cluster color | `COMPUTE_CENTER_CONFIG.colors.gpu_cluster` | `"#2dd4bf"` | Marker texture |
| Linked color | `COMPUTE_CENTER_CONFIG.colors.linked` | `"#f8fafc"` | Linked state |
| Compute center renderOrder | local `COMPUTE_CENTER_RENDER_ORDER` | `4.5` | Surface facility below satellites |
## BGP Observation
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| BGP event radius offset | `BGP_CONFIG.altitudeOffset` | `0.48` | BGP event Interactable marker |
| BGP collector radius offset | `BGP_CONFIG.collectorAltitudeOffset` | `0.2` | BGP collector Interactable marker, aligned with the vessel layer |
| BGP event point size | local `BGP_EVENT_POINT_SIZE` | `34` | Event Interactable base size, adjusted by severity through `getPointSizeMultiplier()` |
| BGP event symbol draw size | local `BGP_EVENT_SYMBOL_SIZE` | `60` | Event canvas symbol draw size inside the `128x128` atlas |
| BGP collector point size | local `BGP_COLLECTOR_POINT_SIZE` | `36` | Collector Interactable base size, adjusted by activity through `getPointSizeMultiplier()` |
| BGP collector asset fit size | local `BGP_COLLECTOR_ICON_FIT_SIZE` | `60` | Maximum `bgp-broadcast-pin.svg` draw size inside the atlas canvas |
| Event base scale | `BGP_CONFIG.marker.eventBaseScale` | `6.2` | Event ring anchor |
| Collector base scale | `BGP_CONFIG.marker.collectorBaseScale` | `7.4` | Collector halo / coverage animation anchor |
| Hover / dim scale | `hoverScale / dimmedScale` | `1.16 / 0.92` | Interaction states |
| Normal event opacity | `BGP_CONFIG.opacity.normal` | `0.78` | BGP event Interactable normal state |
| Hover opacity | `BGP_CONFIG.opacity.hover` | `1.0` | Hover state |
| Dimmed opacity | `BGP_CONFIG.opacity.dimmed` | `0.24` | Dim state |
| Collector opacity | `BGP_CONFIG.opacity.collector` | `0.62` | Collector state |
| Critical color | `BGP_CONFIG.severityColors.critical` | `0xff4d4f` | Critical event |
| High color | `BGP_CONFIG.severityColors.high` | `0xff9f43` | High-severity event |
| Medium color | `BGP_CONFIG.severityColors.medium` | `0xffd166` | Medium-severity event |
| Low color | `BGP_CONFIG.severityColors.low` | `0x4dabf7` | Low-severity event |
| Collector base color | `BGP_CONFIG.collectorColor` | `0x6db7ff` | Default collector color |
| Region color | `BGP_CONFIG.regionColor` | `0x2dd4bf` | Region overlay |
## Celestial and Starfield
| Name | Variable | Current Value | Location / Notes |
| --- | --- | --- | --- |
| Sky sphere radius | `CELESTIAL_CONFIG.skyRadius` | `2600` | Celestial background |
| Sky opacity | `CELESTIAL_CONFIG.skyOpacity` | `1` | Background material |
| Sun distance / scale | `sunDistance / sunScale` | `2150 / 78` | Sun sprite |
| Moon distance / scale | `moonDistance / moonScale` | `2050 / 38` | Moon sprite |
| Sun halo scale | `CELESTIAL_CONFIG.sunHaloScale` | `136` | Sun halo |
| Moon halo scale | `CELESTIAL_CONFIG.moonHaloScale` | `62` | Moon halo |
| Sun light color / intensity | `sunLightColor / sunLightIntensity` | `0xfff4df / 1.02` | Scene light |
| Back light color / intensity | `backLightColor / backLightIntensity` | `0x2b4c78 / 0.3` | Scene light |
| Star count | `STARFIELD_CONFIG.count` | `8000` | `createStars()` |
| Star radius range | `minRadius + radiusJitter` | `800 + 200` | Random distribution |
| Star color | `STARFIELD_CONFIG.color` | `0xffffff` | `PointsMaterial.color` |
| Star size | `STARFIELD_CONFIG.size` | `0.5` | `PointsMaterial.size` |

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# News Live Streams Collector Format
The `news_live_streams` collector accepts a "channel directory JSON" as input rather than scraping web pages directly.
Goals:
- Allow the backend to stably ingest live news streams from around the world
- Ensure the Earth page TV module always consumes a consistent structure
- Make it easy to integrate channel directories like `worldmonitor` that mix YouTube / HLS / iframe sources
## Recommended JSON Structure
```json
{
"sources": [
{
"id": "bbc-world-news",
"name": "BBC World News",
"provider": "BBC",
"region": "UK",
"language": "en",
"source_type": "youtube",
"youtube_video_id": "dQw4w9WgXcQ",
"youtube_channel": "https://www.youtube.com/@BBCNews",
"embed_url": "",
"stream_url": "",
"homepage_url": "https://www.youtube.com/@BBCNews/live",
"poster_url": "",
"sort_order": 220,
"is_enabled": true,
"notes": "Primary English global news channel"
},
{
"id": "france24-en",
"name": "France 24 English",
"provider": "France 24",
"region": "France",
"language": "en",
"source_type": "hls",
"stream_url": "https://example.com/live.m3u8",
"homepage_url": "https://www.france24.com/en/live",
"sort_order": 230,
"is_enabled": true
},
{
"id": "cctv4-page",
"name": "CCTV-4 Chinese International",
"provider": "CCTV",
"region": "China",
"language": "zh-CN",
"source_type": "iframe",
"embed_url": "https://tv.cctv.com/live/cctv4/",
"homepage_url": "https://tv.cctv.com/live/cctv4/",
"sort_order": 10,
"is_enabled": true
}
]
}
```
## Field Conventions
- `id`: unique identifier, should be stable
- `name`: channel display name
- `provider`: provider name
- `region`: country or region
- `language`: language code
- `source_type`: `iframe` / `hls` / `video` / `external` / `youtube`
- `embed_url`: page suitable for iframe embedding
- `stream_url`: direct video stream URL
- `homepage_url`: official website or channel page
- `youtube_video_id`: YouTube live video ID
- `youtube_channel`: YouTube channel handle or channel URL
- `poster_url`: cover image, optional
- `sort_order`: sort value, smaller = higher in the list
- `is_enabled`: whether enabled
- `notes`: brief notes
## Panel Behavior Conventions
- `youtube`
- Prefers `youtube_video_id`
- When embedding is not possible, at least keep `youtube_channel` or `homepage_url` for external opening
- `hls` / `video`
- Prefers `stream_url`
- `iframe`
- Prefers `embed_url`
- `external`
- No embedding attempt; only keeps external open link
## Current Implementation Status
- The backend settings page supports manually maintaining channel directories
- The Earth TV module merges:
- Manually configured sources
- Sources collected by the `news_live_streams` collector
- The current default fallback source is CCTV-4 Chinese International
- When no override is configured, `news_live_streams` defaults to `iptv-org`:
- `channels.json`
- `streams.json`
- `logos.json`
and automatically filters for news-category channel directories
## Collector Configuration
`news_live_streams` does not need a separate new page; it reuses Collector Settings under `/settings`:
- `endpoint`
- Channel directory JSON API URL
- `auth_type`
- `none` / `bearer` / `api_key` / `basic`
- `headers`
- Additional request headers
- `config`
- Collector request and parsing behavior
### Supported `config` Fields
```json
{
"timeout": 30,
"method": "GET",
"params": {
"region": "global"
},
"body_type": "json",
"body": {
"include_disabled": false
},
"response_path": "payload.channels"
}
```
- `timeout`: request timeout in seconds
- `method`: `GET` or `POST`
- `params`: query parameter object
- `body_type`: `json` or `form`
- `body`: request body for `POST`
- `json_body`: explicit JSON request body, takes priority over `body`
- `form_body`: explicit form request body, takes priority over `body`
- `response_path`: path to the channel array in the response JSON, supports dot notation, e.g.:
- `payload.channels`
- `data.items`
- `result.streams`
### Authentication Details
- `bearer`: uses `Authorization: Bearer <token>`
- `api_key`: sent as request header by default; if `auth_config.in = "query"`, sent as query param
- `basic`: uses HTTP Basic Authorization
## Compatible Response Structures
The collector first tries to read:
- Top-level array
- Or an array under these common fields:
- `sources`
- `streams`
- `channels`
- `items`
- `results`
- `data`
It also accepts these field aliases:
- `id` / `source_id` / `slug` / `channel_id` / `code`
- `name` / `title` / `channel` / `display_name`
- `provider` / `publisher` / `network`
- `stream_url` / `stream` / `playback_url` / `hls_url` / `m3u8_url`
- `embed_url` / `embed` / `page_url`
- `homepage_url` / `source_url` / `website`
- `language` / `lang` / `locale`
- `youtube_video_id` / `video_id`
- `youtube_channel` / `channel_handle`

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# Earth Render Layer Order
This document records the current Earth renderer's layer order and the intent of each layer. When adjusting `renderOrder`, radius offsets, depth strategy, or pointer interaction, update this document accordingly.
Note: the layer control panel order and the registration / startup load order are two separate semantics.
| Order type | Current sequence | Notes |
| --- | --- | --- |
| Control panel order | Cables → Trails → Satellites → Compute Centers → BGP → Terrain → HD Texture → Cloud Layer → Border Lines → Grid | Controlled by `displayOrder`, sorted by operational relevance. |
| Registration / startup load order | Grid → Border Lines / Land-Ocean Base → HD Texture → Cloud Layer → Cables → Compute Centers → BGP → Satellites | Controlled by registration order and `startupPriority`, sorted surface-to-sky; the startup queue reads persisted layer visibility first, skips normal layers explicitly saved as hidden, and HD Texture does not download the texture when disabled; Border Lines are the exception: the land-ocean base always preloads, while the persisted state only controls interactive border lines and hover; Trails and Terrain are dependency/optional display layers and do not participate in normal startup data loading. |
## Surface Layer Stack
| Order | Layer | Source | Render / Radius Strategy | Depth / Interaction Strategy | Notes |
| --- | --- | --- | --- | --- | --- |
| -1000 | Celestial background mesh | `celestial.js` | Background sphere | Not part of surface picking | Behind all Earth content. |
| -1 | Earth occluder sphere | `earth.js` | Invisible inner sphere | Writes depth buffer | Occludes objects behind the Earth. |
| 0 | Earth base sphere | `earth.js` | `CONFIG.earthRadius` | Surface picking fallback target | Dark base; still visible when all optional map layers are off. |
| 0.2 | Country dark tint | `country-boundaries.js` | `tintAltitudeOffset` | Raycast disabled | Used when HD texture is off. |
| 0.86 | Land/ocean base fill | `country-boundaries.js` | `landAltitudeOffset`; ocean `#010609`, land `#080f1b` | Raycast disabled | Base map remains usable even when country borders are off. |
| 0.96 | HD Earth texture | `earth.js` | `textureOverlayAltitudeOffset` | Surface picking target when visible | HD texture always overlays the land/ocean base fill. |
| 1 | Atmospheric glow and clouds | `earth.js` | Atmosphere / cloud spheres | Not in normal object selection path | Cloud layer controlled by the "Cloud Layer" toggle. |
| 1 | Submarine cables | `cables.js` | `CABLE_CONFIG.line.renderOrder` | Cable picking path | Preserves existing cable layer level. |
| 1.2 | Real terrain | `earth.js`, `terrain.js` | `TERRAIN_CONFIG.baseRadiusOffset` plus terrain displacement | Raycast disabled | Terrain overlays HD texture; temporarily hidden when HD texture is off, restores to prior state when re-enabled. |
| 2.05 | Grid lines | `earth.js` | `CONFIG.earthRadius + 0.14` | Raycast disabled | Low-opacity lines over HD texture. |
| 2.2 | Country borders | `country-boundaries.js` | `lineAltitudeOffset` | Raycast disabled | Only needs to stay above HD texture. |
| 2.29 | Country border hover glow | `country-boundaries.js` | Hover radius + glow offset | `depthTest: false`, raycast disabled | Additive glow to reinforce border edge and terrain hover visibility. |
| 2.3 | Country border hover line | `country-boundaries.js` | `hoverAltitudeOffset` | `depthTest: false`, raycast disabled | Neon red-orange hover line; China and Taiwan share the same highlight group. |
| 3 | Satellite footprint fill / Iridium coverage ring | `satellites.js`, `iridium-footprint-adapter.js` | `GROUND_FOOTPRINT_RENDER_ORDER` | depth-tested; Iridium adapter fill / ring use the same renderOrder | Footprint above land / texture / terrain and country borders, below compute centers and satellites. |
| 3-5 | BGP markers and overlays | `bgp.js` | Each marker's own renderOrder | BGP picking path | Preserves existing BGP visual level. |
| 4.5 | Compute centers | `compute-centers.js` | `COMPUTE_CENTER_RENDER_ORDER` | Compute center picking path | Surface facilities, below satellites. |
| 5 | Satellite background dot | `satellites.js` | Fixed renderOrder | Screen-space satellite picking | Below satellite dots. |
| 6 | Satellite dots | `satellites.js` | Fixed renderOrder | Screen-space satellite picking | Satellite dots above footprints and compute centers. |
| 12+ | Satellite locked ring, halo, predicted orbit | `satellites.js` | `SATELLITE_CONFIG.overlayRenderOrder` and offsets | Satellite overlay path | Used for selected/locked satellite emphasis. |
| 98-100 | Sun / moon halo and sprite | `celestial.js` | Fixed renderOrder | Celestial picking disabled | Foreground celestial sprites. |
## Toggle Behavior
| Toggle | Behavior |
| --- | --- |
| HD texture off | Hides HD texture, enables country tint / base surface, disables terrain and day/night toggle interaction, and remembers terrain and day/night previous states. |
| HD texture on | Restores HD texture and the remembered terrain / day/night states. |
| Terrain on | Displayed above HD texture, but below country border hover, footprints, satellites, and other emphasis layers. |
| Cloud layer | Only controls cloud mesh visibility. |
| Border Lines off | Hides only interactive border lines and hover, clearing hover state; the land/ocean base fill remains as the Earth base map. |
## Interaction Rules
| Interaction | Current Rule |
| --- | --- |
| Earth coordinate hover | When HD texture is visible, uses the HD texture overlay as the surface picking target; otherwise uses the Earth base sphere. |
| Country border hover | Converts surface pick coordinates to lat/lon, then uses GeoJSON point-in-polygon; the border hover line itself does not receive raycasts. |
| Country border hover visual | On hover, dims normal border lines and draws no-depth-test glow and solid lines. |
| China / Taiwan hover | `CHN` and `TWN` are grouped in the same hover highlight group; the tooltip still shows the actually-hit feature. |
| Terrain | Acts as a visual layer only; `terrain.raycast` is disabled. |
| Satellites | Uses screen-space satellite picking to prevent footprints or surface layers from blocking satellite clicks. |

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# Earth Satellite Footprint Policy
This document records the current product boundary, data rationale, and implemented behavior for `footprint` in the Earth satellite layer. The goal is to prevent the Starlink-specific ground coverage model from being misapplied to other constellations.
Related context:
- [Earth Frontend Context](/home/ray/dev/linkong/planet/docs/technical/en/earth-frontend-context.md)
- [Backend Collectors](/home/ray/dev/linkong/planet/docs/technical/en/backend-collectors.md)
- [backend/app/services/collectors/celestrak.py](/home/ray/dev/linkong/planet/backend/app/services/collectors/celestrak.py)
- [frontend/public/earth/js/satellites.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/satellites.js)
## Current Goal
- Define which non-Starlink satellites should not show a ground footprint
- Define which constellations may have their own footprint in the future but cannot reuse the Starlink bowtie / GSO-gap model
- Solidify this policy as an executable implementation boundary, not leave it scattered across visual parameters
## Current Local Categories
Current CelesTrak satellite groups in [backend/app/services/collectors/celestrak.py](/home/ray/dev/linkong/planet/backend/app/services/collectors/celestrak.py) include:
- `starlink`
- `gps-ops`
- `galileo`
- `glonass`
- `beidou`
- `leo`
- `geo`
- `iridium-next`
Non-Starlink categories:
- `gps-ops`
- `galileo`
- `glonass`
- `beidou`
- `leo`
- `geo`
- `iridium-next`
## Research Conclusions
### 1. GNSS / RNSS: `gps-ops`, `galileo`, `glonass`, `beidou`
Do not draw a localized ground footprint by default.
Reason:
- Public sources emphasize `Earth-pointing`, `Earth coverage`, `continuous global coverage`
- The public semantic of these systems is global navigation / timing coverage, not the localized spot footprint associated with Starlink's end-user service
More appropriate representation:
- Default: show only the satellite body and orbit
- If future needs require showing "service reachability," only a weak global coverage semantic is appropriate — do not draw a localized ground spot
References:
- [GPS III EC Antenna Patterns](https://www.navcen.uscg.gov/sites/default/files/pdf/gps/GPS_ZIP/GPS_III_EC_Antenna_Patterns_SVN_74_75_76_77_78.pdf)
- [ESA Galileo satellites](https://www.esa.int/Applications/Satellite_navigation/Galileo/Galileo_satellites)
- [Navipedia Galileo General Introduction](https://gssc.esa.int/navipedia/index.php/Galileo_General_Introduction)
- [BeiDou official overview](https://www.beidou.gov.cn/xt/gfxz/201812/P020190117356387956569.pdf)
- [GPS.gov GNSS overview](https://www.gps.gov/systems/gnss/)
### 2. `iridium-next`
Can have a footprint, but cannot reuse Starlink's single bowtie footprint.
Reason:
- Iridium NEXT public documentation emphasizes a fixed multi-spot beam system
- Public examples commonly show `48 fixed spot beams in 4 tiers`
- This is not the same problem as Starlink's "single satellite, single primary footprint, with GSO gap" business visualization
More appropriate representation:
- Default: still do not draw a Starlink-style ground footprint
- Future implementation: connect an independent Iridium multi-beam adapter layer
- Visually closer to multi-beam clusters / honeycomb / layered beams, not a single bowtie spot
Reference:
- [Iridium Satellite Spot Beam Coverage on the US](https://www.mathworks.com/help/phased/ug/iridium-satellite-spot-beam-coverage-on-the-us-1.html)
### 3. `geo`
Do not draw a unified footprint by default.
Reason:
- GEO communication satellites may use global beam, zone beam, spot beam, or steerable spot beam
- Without operator / payload / beam contour metadata, drawing a unified footprint is very likely incorrect
More appropriate representation:
- Default: show only the GEO belt and satellite parking position semantics
- Only allow footprint drawing when beam contour / operator metadata is available
Reference:
- [ITU Handbook on Satellite](https://www.itu.int/dms_pub/itu-r/opb/hdb/R-HDB-42-2002-PDF-E.pdf)
### 4. `leo` (generic)
Do not draw a footprint by default.
Reason:
- The `leo` group is too mixed — it may include communication, remote sensing, experimental, and observation satellites
- Without mission / payload / antenna pattern metadata, there is no basis for a service-coverage visualization
More appropriate representation:
- Default: show only the satellite and orbit
- Future: if subdivided by operator / mission subtype, decide then whether to introduce an independent coverage mode
## Product Policy
Current unified policy:
- `Starlink`
- Keep the current dedicated `ground_footprint` logic
- `Iridium NEXT`
- Reserve an independent adapter layer
- Do not reuse Starlink footprint currently
- `GPS / Galileo / GLONASS / BeiDou`
- No ground footprint
- `GEO`
- No footprint without beam metadata
- `Generic LEO`
- No footprint without mission metadata
## Implemented Behavior
This implementation only does the minimum executable version and does not change existing Starlink visual parameters:
1. Backend passes constellation group and footprint policy hint to the frontend
- CelesTrak collector stores `GROUP` in `metadata.constellation_group`
- Visualization API outputs:
- `properties.constellation_group`
- `properties.footprint_policy`
Current policy values:
- `starlink_ground_footprint`
- `iridium_coverage_ring`
- `none`
Relevant code:
- [backend/app/services/collectors/celestrak.py](/home/ray/dev/linkong/planet/backend/app/services/collectors/celestrak.py)
- [backend/app/api/v1/visualization.py](/home/ray/dev/linkong/planet/backend/app/api/v1/visualization.py)
2. Frontend makes footprint a capability-gated renderer
- `ground_footprint` is only actually enabled when `footprint_policy === starlink_ground_footprint`
- `iridium-next` no longer falls back to a placeholder branch; it goes through an independent Iridium coverage ring adapter
- Other non-Starlink satellites automatically fall back to `self_glow` even if the user globally selects `ground_footprint`
Relevant code:
- [frontend/public/earth/js/satellites.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/satellites.js)
- [frontend/public/earth/js/iridium-footprint-adapter.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/iridium-footprint-adapter.js)
3. Satellite info card shows capability, not just orbital parameters
- Satellite details now clearly display:
- `Constellation / Group`
- `Coverage Capability`
- `Current Display`
- `Coverage Model`
- Users can directly see:
- Whether the current satellite supports footprint
- Whether the current display has been fallen back due to capability gating
- That Iridium and Starlink use different models
Relevant code:
- [frontend/public/earth/js/main.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/main.js)
- [frontend/public/earth/js/info-card.js](/home/ray/dev/linkong/planet/frontend/public/earth/js/info-card.js)
## Current Implementation Boundary
This boundary must be maintained:
- Starlink's footprint parameters and shader logic serve Starlink only
- Non-Starlink capability decisions belong to the "policy layer / adapter layer"
- Do not re-mix different constellations' coverage models into the same parameter set
- `iridium-next` has been separated into an independent adapter and should continue along this boundary rather than adding more if/else to the existing Starlink bowtie
## Recommended Next Steps
If continuing forward, the recommended order is:
1. Create a dedicated footprint adapter for `iridium-next`
2. Add a read-only indicator in the UI to tell users whether the current satellite supports footprint
3. If GEO beam contour / operator metadata becomes available, enable operator-specific footprint for GEO

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# Admin Frontend Context
This document describes the current real structure of the console frontend. The goal is to help future page development, table refactoring, layout governance, and state consolidation quickly find the right entry points.
Related references:
- [Project Rules](/home/ray/dev/linkong/planet/rules.md)
- [Frontend Layout Guidelines](/home/ray/dev/linkong/planet/docs/technical/en/frontend-layout-guidelines.md)
## Current Goal
The console frontend is a backend workbench, not a display-style dashboard. Current constraints:
- Pages default to a single-screen work area
- Primary interaction happens through in-module scrolling, not relying on the whole page growing infinitely
- Lists, tables, and analysis pages prioritize keeping the main work area visible
- Common layout, scrollbar, and table scroll behavior should be reused across pages
## Current Route Entry Points
Main entry point:
- [App.tsx](/home/ray/dev/linkong/planet/frontend/src/App.tsx)
Current admin-related routes:
- `/admin`
- `/users`
- `/datasources`
- `/data`
- `/alerts/system`
- `/alerts/bgp`
- `/alerts/situational`
- `/bgp`
- `/playground`
- `/settings`
`/earth` is a standalone display page and is not part of the console shell.
## Current Page Shell
The console shared shell is at:
- [AppLayout.tsx](/home/ray/dev/linkong/planet/frontend/src/components/AppLayout/AppLayout.tsx)
Responsibilities:
- Left-side navigation
- Collapse and expand
- Current account / version information
- Content area height closure
- Site-wide unified sidebar scrollbar
Current structure:
```tsx
<Layout className="dashboard-layout">
<Sider className="dashboard-sider">...</Sider>
<Layout>
<Content className="dashboard-content">
<div className="dashboard-content-inner">{children}</div>
</Content>
</Layout>
</Layout>
```
Future console pages should adapt to this shell rather than redefining full-page height semantics.
## Current Shared Components
### 1. `Scrollbar`
File:
- [Scrollbar.tsx](/home/ray/dev/linkong/planet/frontend/src/components/Scrollbar/Scrollbar.tsx)
Purpose:
- Ordinary content containers like the console sidebar
- Internally manages visibility, thumb size, drag, and dual-axis overflow detection
Current constraint:
- The scrollbar must be a floating overlay that does not participate in layout
- Should leave no visible trace when there is no overflow
- Real scrolling is still handled by the native container; only the visible layer and interaction layer are replaced
### 2. `ScrollbarOverlay`
File:
- [ScrollbarOverlay.tsx](/home/ray/dev/linkong/planet/frontend/src/components/Scrollbar/ScrollbarOverlay.tsx)
Purpose:
- Areas like Ant Table that already have an internal scroll container
- Does not take over scroll semantics; only adds a new scrollbar visible layer
Current usage:
- Data sources
- Collected data
- User management
- Settings page
- Alerts page
- BGP page
### 3. `TableScrollRegion`
File:
- [TableScrollRegion.tsx](/home/ray/dev/linkong/planet/frontend/src/components/Scrollbar/TableScrollRegion.tsx)
Purpose:
- Provides a unified wrapper for table scroll areas
- New table pages should reuse this rather than repeating the "table area + overlay scrollbar" boilerplate
### 4. `SegmentedControl`
Files:
- [SegmentedControl.tsx](/home/ray/dev/linkong/planet/frontend/src/components/SegmentedControl/SegmentedControl.tsx)
- [SegmentedControl.css](/home/ray/dev/linkong/planet/frontend/src/components/SegmentedControl/SegmentedControl.css)
Purpose:
- Segmented controls for language, theme, mode, or other 2 to 3 option settings
- Settings that need the shared animated slider, active state, and compact button layout
- The `/docs` footer language switcher and theme switcher already reuse it
Interface semantics:
- `options`: each option contains `value` and `label`, with optional `icon` and `title`
- `value`: current active value
- `onChange`: called when the selected option changes
- `ariaLabel`: accessible name for the control
- `className`: page-level hook for size or local style overrides
Current constraints:
- The component owns slider count, position, and spring-like transition
- Feature pages should only pass options and state, not recreate private slider DOM
- Prefer CSS variable overrides for colors instead of hard-coding theme colors in feature components
- Best for a small set of mutually exclusive choices; do not use it as a long list, navigation menu, or select replacement
### 5. `MarkdownRenderer`
File:
- [MarkdownRenderer.tsx](/home/ray/dev/linkong/planet/frontend/src/components/MarkdownRenderer/MarkdownRenderer.tsx)
Purpose:
- Renders Markdown content for `/docs`
- Supports headings, lists, blockquotes, code blocks, tables, and basic inline formatting
- Code blocks and tables reuse `Scrollbar` so horizontal content does not blow out the docs page
Current constraints:
- It is not a full GitHub Markdown engine; it only covers the syntax currently needed by project docs
- Internal document links should be converted to `/docs/:slug` through `transformLink`
- Heading anchors are injected through `getHeadingId`, keeping route state outside the renderer
### 6. `TableActions`
File:
- [TableActions.tsx](/home/ray/dev/linkong/planet/frontend/src/components/TableActions/TableActions.tsx)
Purpose:
- Shared action entry for table operation columns
- Shows inline actions when expanded
- Uses a more-actions dropdown when collapsed
Companion export:
- `actionCellProps`: for action-column `onCell`, preventing action buttons from being ellipsized or wrapped
## Current State Sources
### 1. Auth State
File:
- [auth.ts](/home/ray/dev/linkong/planet/frontend/src/stores/auth.ts)
Responsibilities:
- Token
- Current user
- Login / logout
`App.tsx` uses it to decide whether to redirect to the login page.
### 2. Business Data Gateway
AI / situational awareness related services are currently in:
- [http-gateway.ts](/home/ray/dev/linkong/planet/frontend/src/services/situational-awareness/http-gateway.ts)
- [port.ts](/home/ray/dev/linkong/planet/frontend/src/services/situational-awareness/port.ts)
- [types.ts](/home/ray/dev/linkong/planet/frontend/src/services/situational-awareness/types.ts)
Constraints:
- Pages must not scatter URL construction directly
- Define boundaries through port/types first
- Then implement via http/mock gateway
## Current Page Layer Recommendations
### 1. Dashboard and Summary Pages
Example:
- [Dashboard.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/Dashboard/Dashboard.tsx)
Priority goals:
- Stable header
- Summary cards compact first
- Main work area occupies primary height
### 2. Table Pages
Examples:
- [DataSources.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/DataSources/DataSources.tsx)
- [DataList.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/DataList/DataList.tsx)
- [Users.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/Users/Users.tsx)
- [Settings.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/Settings/Settings.tsx)
Constraints:
- Prefer internal scrolling
- Do not let tables blow out the full page
- New table areas should reuse `TableScrollRegion` / `ScrollbarOverlay`
### 3. Complex Workspace Pages
Examples:
- [BGP.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/BGP/BGP.tsx)
- [Playground.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/Playground/Playground.tsx)
Constraints:
- Tab content must not share the same height logic
- Table tabs, Markdown tabs, and config tabs each need their own scroll responsibility
- AI result areas and long text areas should maintain a minimum readable height
## Current Layout Constraints
These principles have been repeatedly validated in the project:
1. Parent container height chain must close
2. `min-height: 0` must not be omitted
3. Overflow responsibility must be explicit
4. Do not use `overflow: hidden` to mask structural issues
5. Do not compress the main work area to make summary cards show completely
6. Custom scrollbars must be floating overlays; they must not squeeze content width
For detailed experience, see:
- [Frontend Layout Guidelines](/home/ray/dev/linkong/planet/docs/technical/en/frontend-layout-guidelines.md)
## Recommended Change Approach
For future console page changes:
1. Confirm whether the page is a summary page, table page, or complex workspace
2. Integrate into the existing shell and scroll semantics first
3. Reuse shared scroll components
4. Handle visual and detail interactions last
Do not write local CSS patches first, then retrofit the structure.
## Current Clear Boundary
The console frontend and the Earth frontend are not the same system:
- Console frontend: React + Ant Design workbench
- Earth frontend: independent native HUD system under `public/earth`
Therefore:
- Do not move Earth's HUD / animations / state machine directly into the console
- Do not force the console's table / scroll strategy onto the Earth HUD
For Earth-related structure, see:
- [Earth Frontend Context](/home/ray/dev/linkong/planet/docs/technical/en/earth-frontend-context.md)

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# Frontend Layout Guidelines
Admin pages in this project default to a "single-screen workspace" layout standard. The goal is not to prevent all overflow, but to ensure that under common desktop viewports:
- The main page structure is visible within one screen
- The user can simultaneously see the page header, summary area, and main workspace
- Overflow content scrolls within its module, rather than stretching the entire page vertically
Current recommended reference implementations:
- [frontend/src/pages/BGP/BGP.tsx](/home/ray/dev/linkong/planet/frontend/src/pages/BGP/BGP.tsx)
- [frontend/src/index.css](/home/ray/dev/linkong/planet/frontend/src/index.css)
## Core Principles
### 1. Pages Should Prioritize a Single-Screen Workspace
Admin pages default to:
- Header: title, description, main actions
- Main workspace: stats cards, tables, charts, lists, tabs
Recommended structure:
```tsx
<AppLayout>
<div className="page-shell">
<div className="page-shell__header">...</div>
<div className="page-shell__body">...</div>
</div>
</AppLayout>
```
Total page height should be bounded within the `AppLayout` content area, not allowed to grow naturally downward without limit.
### 2. Scrolling Should Happen Inside Modules
If tables, logs, long lists, or chart details overflow their space:
- Let the card scroll internally
- Let the table scroll internally
- Let the tab content area scroll internally
Do not rely on full-page scrolling to "solve" the space problem.
### 3. The Main Workspace Must Get the Most Space
The most important module on a page must be the visual and spatial lead. Typically ensure:
- Header always visible
- Summary area height controlled
- Main table / chart / analysis area occupies more than 50% of visible height
If a page has multiple large modules, priority order is:
1. First compress the description and summary areas
2. Then move secondary modules into tabs or switch views
3. Only then consider adding more full-page scrolling
### 4. Small Screens and High Zoom Must Enter Compact Mode
When window height is low, width is narrow, or system zoom is high, actively switch to a compact layout:
- Reduce card padding
- Reduce header and cell spacing
- Convert summary area to a more compact single-row or horizontal-scroll layout
- Move secondary modules into tabs, drawers, or collapsed areas
Compact mode goal: maintain usability, not just shrink all text and controls.
### 5. Overflow Responsibility Must Be Explicit
Large content blocks on the page must explicitly define:
- Who is responsible for filling remaining height
- Who is responsible for clipping
- Who is responsible for scrolling
Common requirements:
- Parent container chain needs `min-height: 0`
- Workspace containers typically need `display: flex`
- The real scroll node must explicitly use `overflow: auto`
### 6. Cards Must Not Be Compressed to Unreadable
Historical problems have not been "missing scrollbars," but:
- Cards compressed by `flex` to only a tiny visible area
- Text can render but cannot be read completely
- Content exists but is cut off by `overflow: hidden`
Future constraints:
- First ensure cards have a readable minimum height
- If further compression affects readability, switch to internal scrolling
- Do not compress body text, tables, or description areas into unreadable strips just to "maintain one screen"
### 7. Tabs Are Not Inherently Safe Layout Containers
Historical regressions with Tabs include:
- Hidden tab panes reappearing due to custom `display: flex`
- All tabs having the same height/overflow rules forced on them
- Table tabs work, but markdown / help / diagnostics tabs get crushed
Constraints:
- Each type of content inside `Tabs` must define its own layout strategy
- Table tab: "fixed height + internal scrolling"
- Docs/Markdown tab: better as "tab pane self-scrolls + content normal document flow"
- If overriding component library styles, verify the hidden state still holds
### 8. Summary Areas Should Enter Compact Mode First, Not Compress Body
Historical experience shows the top summary cards are most often mishandled:
- They frequently get forcibly narrowed to "fit everything"
- Then the body, tables, and AI result areas all lose their main space
Unified constraint:
- On small screens or high zoom, summary cards should first:
- Reduce padding
- Switch to horizontal scrolling
- Switch to a more compact grid
- Do not sacrifice the main workspace's visible area first
### 9. Long-Document Content Should Prioritize Reading Experience
Content like the following cannot directly apply "table workspace" logic:
- AI briefs
- Runtime logs
- Raw JSON
- Help text
- Multi-paragraph descriptive text
These areas should prioritize:
- Stable title and meta information visibility
- Body has a clear minimum readable height
- Body scroll strategy defined separately
- Support for Markdown tables, dividers, quotes, code blocks
### 10. Height Critical Paths Should Use Fewer Wrapper Layers
Many scroll problems historically were not in the component itself, but came from an extra wrapper layer:
- Height chain broken
- `min-height: 0` not passed down
- `overflow` responsibility absorbed
Therefore:
- For height-critical areas, prefer the most direct DOM structure
- When using `Space`, extra wrapper `div`, or third-party layout containers, verify they don't change scroll and height semantics
- If an area shows "content is there but only a sliver is visible," first suspect an intermediate wrapper layer
## Historical Pitfalls
From Earth, Playground, BGP, DataSources page bugfixes, several high-frequency pitfall types:
### 1. Using `overflow: hidden` to Mask Layout Problems
Superficially the page looks "clean," but actually causes:
- Content getting clipped
- Tab content reduced to a sliver
- Panel renders successfully but users can't see it
Correct approach:
- Let the real content node scroll
- Don't let upper containers unconditionally clip all child content
### 2. Treating All Tabs as the Same Content Type
Tables, Markdown, help cards, and log streams have completely different space requirements.
Correct approach:
- Table: fixed workspace + internal scrolling
- Document: normal flow content + pane-level scrolling
- Side description: content-driven height, not forced to fill
### 3. Only Doing Visual Shrinking, Not Space Reallocation
This causes:
- Card text truncated
- Table shows only 1-2 rows
- Buttons and filters crammed together
Correct approach:
- Compact mode prioritizes re-layout
- Summary area horizontal scrolling
- Collapse / hide secondary modules
### 4. Incomplete Parent Container Height Chain
This is the most common cause of internal scrolling failing.
Inspection order:
1. Does the outer layer actually have a determined height?
2. Does the flex parent have `min-height: 0`?
3. Does the real scroll node explicitly use `overflow: auto`?
4. Have intermediate wrapper layers silently changed layout semantics?
### 5. UI State and Display State Out of Sync
Repeated in Earth-related changes:
- Layer hidden, but hover/lock still active
- Tooltip still showing stale object
- Legend not switching with the state
These constraints also apply to admin pages:
- Hidden, unmounted, or switched-out content should not retain active interaction state
## Recommended Implementation Patterns
### Page Shell
Reuse existing common structures in the project:
- `.dashboard-content-inner`
- `.page-shell`
- `.page-shell__header`
- `.page-shell__body`
- `.table-scroll-region`
Do not invent a completely different height and scroll semantics for each page.
### Table Workspace
Recommended pattern:
```tsx
<Card>
<div className="table-scroll-region" ref={tableRegionRef}>
<Table
pagination={false}
scroll={{ x: 1200, y: tableHeight }}
/>
</div>
</Card>
```
Requirements:
- Tables should scroll inside their card
- `scroll.y` should come from actual available height calculation, not a completely static magic number
- Parent container chain must ensure header, body, content overflow all close inside the table
### Multi-Module Pages
If a page has:
- Summary cards
- Table
- Anomaly details
- Recent events
Do not simply stack all modules vertically. Prefer:
- Top summary + single main workspace at bottom
- Tab-switch multiple secondary data views
- Left-right split with each column scrolling independently
## Discouraged Patterns
The following patterns are considered non-compliant with this project's page standard:
- Relying on full-page vertical scrolling to display the main workspace
- Stacking 3-4 large cards vertically on one page, each wanting to display fully
- Table without internal scrolling, causing only 1-2 rows visible after zoom
- Parent container missing `min-height: 0`, causing internal scrolling to fail
- Only doing visual shrinking without addressing real space allocation
## Page Acceptance Checklist
Before submitting, check at minimum:
- Can page header, summary area, and main workspace appear simultaneously?
- Does the main workspace get the most height on the page?
- When table or detail overflows, does the scrollbar appear inside the module?
- Is the card compressed to the point where text doesn't display completely? If so, has it switched to internal scrolling?
- Is it still usable at browser zoom `125%` / `150%`?
- In a low-height window, is there still a reasonable number of visible content rows?
- Are Tabs, Card, Table still operable when overflowing?
- Do non-table tabs (Markdown, help text, logs) have their own independent and reasonable scroll strategy?
## Implementation Order
When adding or refactoring admin pages, design in this order:
1. Define the main workspace first
2. Determine which modules must always be visible
3. Then handle styling and visual hierarchy
Simply put:
- First ensure correct space allocation
- Then handle scroll boundaries
- Finally handle aesthetics

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# Planet Manual
This manual is for daily use, demos, development integration, and local operations. It covers four core entry points:
- `planet.sh`: local start, stop, restart, health check, and log access
- Earth: public 3D situational awareness page
- Console: admin backend (login required)
- Docs: public developer documentation and manual
For the shortest path to getting started, see [Quickstart](/home/ray/dev/linkong/planet/docs/technical/en/quickstart.md).
## Entry Overview
After a default startup, the common URLs are:
| Name | URL | Login Required | Description |
| --- | --- | --- | --- |
| Earth | `http://localhost:3000/earth` | No | 3D globe, layers, BGP, satellites, cables, news situational awareness |
| Docs | `http://localhost:3000/docs` | No | Developer docs, technical reference, usage manual |
| Console | `http://localhost:3000/admin` | Yes | Data, config, alerts, logs, and situational observation |
| AI Playground | `http://localhost:3000/playground` | Yes | AI Provider status and debugging |
| Backend API Docs | `http://localhost:8000/docs` | Depends on endpoint | FastAPI / OpenAPI documentation |
## planet.sh
`planet.sh` is the main control script for local development and demos. Use it to manage services rather than manually starting frontend, backend, database, and AI Provider separately.
### Start
```bash
./planet.sh start
```
Default behavior:
- Starts PostgreSQL and Redis
- Starts AI Provider
- Starts the backend API
- Starts the frontend Vite dev server
- Outputs Earth, console, Playground, and backend API doc URLs
Specify custom ports:
```bash
./planet.sh start -b 8001 -f 3001 -a 8101
```
Parameters:
| Flag | Meaning |
| --- | --- |
| `-b <port>` | Backend port |
| `-f <port>` | Frontend port |
| `-a <port>` | AI Provider port |
| `--allow-lan` | Enable LAN access |
| `--verbose` | Show more command output during execution |
### AI Provider Environment and Builds
AI Provider runtime configuration can live in `aiprovider/.env` or in matching variables in `~/.zshrc`. `planet.sh` reads simple `export AI_...=...` / `AI_...=...` lines and passes them to the container at startup.
Changing model, API key, or base URL does not rebuild the image. Restart only AI Provider to pick up runtime configuration changes:
```bash
./planet.sh restart -a
```
For complex shell expansion in `~/.zshrc`, opt in explicitly:
```bash
PLANET_LOAD_ZSHRC_ENV=source ./planet.sh start -a
```
To ignore `~/.zshrc` during troubleshooting:
```bash
PLANET_LOAD_ZSHRC_ENV=0 ./planet.sh start -a
```
The AI Provider Docker build context is intentionally limited to the files required by the service, and `uv sync` uses a BuildKit cache mount so dependency downloads are reused after the first build.
### Stop
```bash
./planet.sh stop
```
Stops:
- Backend
- AI Provider
- Frontend
- PostgreSQL
- Redis
### Restart
Full restart:
```bash
./planet.sh restart
```
Per-module restart:
```bash
./planet.sh restart -b
./planet.sh restart -f
./planet.sh restart -a
./planet.sh restart -d
```
| Flag | Effect |
| --- | --- |
| `-b` | Backend only |
| `-f` | Frontend only |
| `-a` | AI Provider only |
| `-d` | Database only |
Per-module restarts are preferred during development — they avoid interrupting unrelated services.
### Create User
```bash
./planet.sh createuser
```
Used to create a console login account before first use. The script interactively prompts for username, password, and role.
### Health Check
```bash
./planet.sh health
```
Checks:
- `planet_*` container status
- Backend `/health`
- AI Provider `/health`
- Frontend reachability
If something shows offline, check the corresponding logs first.
### Logs
Recent logs:
```bash
./planet.sh log
```
Follow logs:
```bash
./planet.sh log -f
./planet.sh log -b
./planet.sh log -a
```
| Flag | Log source |
| --- | --- |
| `-f` / `--frontend` | `/tmp/planet_frontend.log` |
| `-b` / `--backend` | `/tmp/planet_backend.log` |
| `-a` / `--ai-provider` | `planet_aiprovider` container logs |
### LAN Access
```bash
./planet.sh start --allow-lan
```
Useful for:
- Starting in WSL, accessing from Windows browser
- Demos on phone or tablet
- Another machine on the same LAN accessing the same dev instance
After starting, check your firewall and WSL network forwarding if access fails.
## Earth
Earth is the public 3D situational awareness page, accessed at:
```text
http://localhost:3000/earth
```
It is a standalone frontend. The actual page lives at:
- `frontend/public/earth/index.html`
- `frontend/public/earth/js/`
- `frontend/public/earth/css/`
The React route `/earth` simply hosts it in an iframe.
### Main Uses
Earth is used to observe in a single globe view:
- BGP events, anomalies, and situational posture
- Satellites and orbital trails
- Submarine cables and landing points
- Compute centers
- AIS vessels
- Border lines, grid lines, HD texture, cloud layer, terrain
- Live news streams and situational news
- Search and focused object details
### Layer Control
The right-side layer panel toggles visualization layers on or off.
Common layers include:
- Grid lines
- Border lines
- HD texture
- Atmospheric cloud layer
- Submarine cables
- Compute centers
- BGP observation
- AIS vessels
- Satellites
- Orbital trails
- Terrain
Some layers have dependencies:
- Terrain requires HD texture
- Trails require Satellites
- When HD texture is off, the globe shows the base map and edge glow effect
### Legend
The lower-left legend follows the currently focused or enabled layer.
Current legend modes include:
- Cables
- Satellites
- Border lines
- Compute centers
- BGP
- AIS vessels
AIS vessel legend entries are grouped by vessel type: cargo, tanker, passenger, fishing, military, anchored/slow, and other. Triangle markers represent moving vessels; dots represent anchored or slow vessels.
### Search
Earth search finds current globe objects, such as:
- Submarine cables
- Landing points
- Satellites
- Compute centers
- BGP events
- BGP collectors
Search results can be used to quickly locate objects and open their details.
### Settings
The settings panel contains:
- Rotation mode / cruise mode
- Cruise modules: BGP, News
- Satellite display style: self-glow, real ground footprint
- Day/night mode
- Panel visibility toggles
- Globe default size
- Terrain opacity
- Reset settings
These settings are stored in browser local storage. They revert to defaults if you switch browsers or clear site data.
### View Controls
Earth supports mouse, touchpad, and touchscreen interaction.
Common controls:
| Action | Result |
| --- | --- |
| Left-button drag | Rotates the globe |
| One-finger drag | Rotates the globe on touch devices |
| Mouse wheel | Zooms the view in or out |
| Two-finger pinch | Zooms the view on touch devices |
| Zoom buttons | Adjust zoom in fixed steps |
| Click the zoom percent | Resets to the default zoom |
When zooming, the top capsule briefly shows the current zoom level, for example `Zoom 180%`. This indicates view zoom only, not data loading progress. Loading status takes priority and will not be interrupted by zoom feedback.
Drag sensitivity adjusts automatically based on the current zoom. Around the default view it keeps the normal rotation feel; when zoomed in, dragging becomes progressively finer for inspecting a region, vessel, satellite, or BGP event; when zoomed out, dragging is slightly faster for global browsing.
### Cruise Mode
Cruise mode makes Earth automatically cycle through focus targets.
Current cruise modules:
- BGP
- News
Suitable for demos, monitoring displays, or unattended presentations.
### Mobile
Earth has a mobile drawer layout. On small screens:
- Layer controls open in a mobile drawer
- Search, settings, and details use mobile panels
- Main interactions remain centered on globe object clicks, search, and layer toggles
### Common Issues
#### Earth Won't Open
Check whether the frontend is online:
```bash
./planet.sh health
./planet.sh log -f
```
If the frontend port is not `3000`, use the actual port shown at startup.
#### Layer Has No Data
Check the backend and data sources:
```bash
./planet.sh health
./planet.sh log -b
```
Then open the console and check:
- `/datasources`
- `/data`
- `/bgp`
#### Satellites, BGP, or Cables Load Slowly
These layers may depend on backend APIs, external data sources, or first-run collection tasks. Wait for startup tasks to finish before checking logs and console data source status.
## Console
Console entry point:
```text
http://localhost:3000/admin
```
The console requires login. Create a user first if this is your first time:
```bash
./planet.sh createuser
```
### Page Structure
The console uses React + Ant Design, with a left-side menu organized by work domain.
Common pages:
| Page | Route | Purpose |
| --- | --- | --- |
| Dashboard | `/admin` | System overview |
| Earth | `/earth` | Opens the public Earth page |
| Data Sources | `/datasources` | View data sources and trigger collection |
| Collected Data | `/data` | View collected data |
| BGP Observation | `/bgp` | BGP situational data |
| System Alerts | `/alerts/system` | System-level alerts |
| BGP Alerts | `/alerts/bgp` | BGP-related alerts |
| Situational Alerts | `/alerts/situational` | Situational assessment alerts |
| AI Playground | `/playground` | AI Provider debugging |
| System Logs | `/logs` | View system logs (typically super admin only) |
| Users | `/users` | User management |
| Settings | `/settings` | System config and TV live stream sources |
### Data Sources
`/datasources` shows collection sources and triggers collection. It is now a data source directory that lists built-in and custom sources in one table.
Common operations:
- View data source status
- Trigger collection
- View recent collection tasks
- Open the read-only detail drawer for endpoint, headers, runtime config, and built-in/custom source type
If a category of objects is missing on Earth, start here to confirm the data source is available.
The data source name opens an information drawer only. Endpoint, credentials, headers, and custom source configuration are maintained under `/settings` collector settings.
When collection tasks are running, the progress area shows a clickable `Collecting N` pill. Clicking it opens a modal with each running task's phase, progress, and processed count.
### Collected Data
`/data` shows the collected data table.
Useful for diagnosing:
- Whether data has entered the system
- Whether data update times match expectations
- Whether a data source produced valid records
### BGP Observation
`/bgp` is the BGP-focused page.
It complements the BGP layer on Earth:
- Earth emphasizes spatial posture and visual focus
- The console BGP page emphasizes lists, status, details, and assessment
### Alerts
Alert entry points:
- `/alerts/system`
- `/alerts/bgp`
- `/alerts/situational`
Used to view system, network, and situational alerts.
### System Settings
`/settings` manages system-level configuration.
Current common uses:
- System settings
- TV live stream source configuration
- Collector settings
- External integrations and AI Provider configuration
Available configuration depends on the current user's role.
#### Collector Settings
`/settings?tab=collector_credentials` is currently displayed as Collector Settings. It manages connection settings for all collectors, not only credentials.
Use it to:
1. Select a collector from the dropdown.
2. Review tags such as `Requires credentials`, module, enabled state, and `Unchecked` / `Available` / `Unavailable`.
3. Click the plug icon next to the selector to run a health check.
4. Edit endpoint, request headers, timeout, and retry settings.
5. Save the collector settings.
Free collectors are checked by requesting their endpoint directly. Credentialed collectors use their credential provider. If endpoint or credential fingerprint changes after the last successful validation, the collector must be checked again.
The system treats a collector as connected when the current configuration has either collected data successfully or passed the manual connection check.
#### BarentsWatch AIS Credentials
`BarentsWatch AIS` is a credentialed built-in collector. Its credential card appears above the basic configuration card.
Configured fields:
- `Client ID`
- `Client Secret`
- `Endpoint`
If a secret is already configured, the input shows a masked preview. Keeping that preview unchanged preserves the stored secret; entering a new value replaces it.
BarentsWatch AIS credentials can be read from:
1. Collector settings saved in the console.
2. Backend environment variables:
- `BARENTSWATCH_CLIENT_ID`
- `BARENTSWATCH_CLIENT_SECRET`
- historical spellings: `BARRENTSWATCH_CLIENT_ID`, `BARRENTSWATCH_CLIENT_SECRET`
3. matching `export` lines in `~/.zshrc`.
If connection fails, the page opens the credential guide. The guide can be regenerated through AI Provider or reset to the default guide. The default guide points users to the official BarentsWatch tutorial and emphasizes selecting `AIS - API`, not the regular `BarentsWatch - API`.
### System Logs
`/logs` views system logs. If the menu item is not visible, the current user likely lacks the required role.
Common troubleshooting sequence:
```bash
./planet.sh health
./planet.sh log
```
Then open `/logs` for more structured runtime information.
## Docs
Public documentation site:
```text
http://localhost:3000/docs
```
Current public content comes from:
```text
docs/technical/zh/ (Chinese)
docs/technical/en/ (English)
```
Docs supports:
- Category navigation
- Markdown rendering
- Tables and code blocks
- In-document table of contents
- Local search
- Internal links between technical documents
When adding a new technical document, check:
- Does it have a clear top-level heading
- Does it need to be added to the `/docs` manual category and ordering
- Does it contain information that should not be publicly displayed
## Development Command Conventions
Frontend commands must use Bun:
```bash
cd frontend
bun install
bun run dev
bun run build
```
Do not use `npm run ...`. The project uses Bun in WSL / Windows mixed environments to avoid Node/npm path compatibility issues.
Verify the frontend build:
```bash
source ~/.zshrc && bun run build
```
## Troubleshooting Order
When something goes wrong, follow this sequence:
1. Check service status:
```bash
./planet.sh health
```
2. Check recent logs:
```bash
./planet.sh log
```
3. Check per-module logs:
```bash
./planet.sh log -f
./planet.sh log -b
./planet.sh log -a
```
4. Restart only the affected module:
```bash
./planet.sh restart -f
./planet.sh restart -b
./planet.sh restart -a
```
5. If database or cache is abnormal, restart the database:
```bash
./planet.sh restart -d
```
6. If still unrecovered, do a full restart:
```bash
./planet.sh restart
```
## Related Docs
- [Quickstart](/home/ray/dev/linkong/planet/docs/technical/en/quickstart.md)
- [Admin Frontend Context](/home/ray/dev/linkong/planet/docs/technical/en/frontend-admin-frontend-context.md)
- [Earth Frontend Context](/home/ray/dev/linkong/planet/docs/technical/en/earth-frontend-context.md)
- [Earth Layer Style Reference](/home/ray/dev/linkong/planet/docs/technical/en/earth-layer-style-reference.md)
- [System Service Control](/home/ray/dev/linkong/planet/docs/technical/en/backend-system-service-control.md)
- [Backend Collectors](/home/ray/dev/linkong/planet/docs/technical/en/backend-collectors.md)

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