release: bump version to 0.62.0

aiprovider/main.py

@@ -45,6 +45,7 @@ def get_provider_service(
     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),
+    x_ai_model_provider_apis: str | None = Header(default=None),
 ) -> ProviderService:
     overrides = {
         "provider": x_ai_provider,
@@ -53,6 +54,7 @@ def get_provider_service(
         "api_key": x_ai_api_key,
         "model": x_ai_model,
         "anthropic_version": x_ai_anthropic_version,
+        "model_provider_apis": x_ai_model_provider_apis,
     }
     if x_ai_max_tokens:
         overrides["max_tokens"] = x_ai_max_tokens

aiprovider/provider_service.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import asyncio
+import json
 from typing import Any
 
 import httpx
@@ -14,7 +15,6 @@ from aiprovider.schemas import (
     SituationalAnalysisResponse,
 )
 
-
 def _normalize_provider(value: str) -> str:
     return (value or "disabled").strip().lower()
 
@@ -62,6 +62,9 @@ class ProviderService:
         self.anthropic_version = str(
             overrides.get("anthropic_version") or settings.AI_ANTHROPIC_VERSION
         )
+        self.model_provider_apis = self._parse_model_provider_apis(
+            overrides.get("model_provider_apis")
+        )
 
     def get_status(self) -> AIProviderStatusResponse:
         enabled = self.provider != "disabled"
@@ -93,11 +96,13 @@ class ProviderService:
 
         prompt = self._build_prompt(payload)
 
-        if self.provider_api == "openai-completions":
+        provider_api = self._resolve_model_provider_api(model)
+
+        if provider_api == "openai-completions":
             data = await self._request_openai_compatible(model, prompt, payload.system_prompt)
             content = self._extract_openai_content(data)
             content_blocks = self._extract_openai_blocks(data)
-        elif self.provider_api == "anthropic-messages":
+        elif provider_api == "anthropic-messages":
             data = await self._request_anthropic_messages(
                 model,
                 prompt,
@@ -106,7 +111,7 @@ class ProviderService:
             )
             content = self._extract_anthropic_content(data)
             content_blocks = self._extract_anthropic_blocks(data)
-        elif self.provider_api == "ollama-generate":
+        elif provider_api == "ollama-generate":
             data = await self._request_ollama(model, prompt, payload.system_prompt)
             content = self._extract_ollama_content(data)
             content_blocks = self._extract_ollama_blocks(data)
@@ -132,6 +137,26 @@ class ProviderService:
     def _requires_api_key(self) -> bool:
         return self.provider_api != "ollama-generate"
 
+    def _resolve_model_provider_api(self, model: str) -> str:
+        return self.model_provider_apis.get(model) or self.provider_api
+
+    def _parse_model_provider_apis(self, value: Any) -> dict[str, str]:
+        if isinstance(value, dict):
+            raw = value
+        elif isinstance(value, str) and value.strip():
+            try:
+                parsed = json.loads(value)
+            except json.JSONDecodeError:
+                return {}
+            raw = parsed if isinstance(parsed, dict) else {}
+        else:
+            raw = {}
+        return {
+            str(model): _normalize_provider_api(str(provider_api))
+            for model, provider_api in raw.items()
+            if model and provider_api
+        }
+
     def _build_prompt(self, payload: SituationalAnalysisRequest) -> str:
         sections = [
             f"任务标题:\n{payload.title}",
@@ -314,13 +339,19 @@ class ProviderService:
         message = choices[0].get("message") or {}
         content = message.get("content")
         if isinstance(content, str):
-            return content
+            if content:
+                return content
+            reasoning_content = message.get("reasoning_content")
+            return reasoning_content if isinstance(reasoning_content, str) else ""
         if isinstance(content, list):
             return "".join(
                 item.get("text", "")
                 for item in content
                 if isinstance(item, dict)
             )
+        reasoning_content = message.get("reasoning_content")
+        if isinstance(reasoning_content, str):
+            return reasoning_content
         return ""
 
     def _extract_openai_blocks(self, payload: dict[str, Any]) -> list[AIContentBlock]:
@@ -331,9 +362,14 @@ class ProviderService:
         message = choices[0].get("message") or {}
         content = message.get("content")
         if isinstance(content, str):
-            return [AIContentBlock(type="text", text=content)]
+            blocks = [AIContentBlock(type="text", text=content)] if content else []
+            reasoning_content = message.get("reasoning_content")
+            if isinstance(reasoning_content, str) and reasoning_content:
+                blocks.append(AIContentBlock(type="thinking", thinking=reasoning_content))
+            return blocks
         if not isinstance(content, list):
-            return []
+            reasoning_content = message.get("reasoning_content")
+            return [AIContentBlock(type="thinking", thinking=reasoning_content)] if isinstance(reasoning_content, str) and reasoning_content else []
 
         blocks: list[AIContentBlock] = []
         for item in content:
@@ -346,7 +382,11 @@ class ProviderService:
                     metadata={k: v for k, v in item.items() if k not in {"type", "text"}},
                 )
             )
+        reasoning_content = message.get("reasoning_content")
+        if isinstance(reasoning_content, str) and reasoning_content:
+            blocks.append(AIContentBlock(type="thinking", thinking=reasoning_content))
         return blocks
+
     def _extract_anthropic_content(self, payload: dict[str, Any]) -> str:
         content = payload.get("content")
         if isinstance(content, str):