release: bump version to 0.74.5

aiprovider/README.md

@@ -4,7 +4,7 @@
 
 完整使用说明见:
 
-- [docs/agents/aiprovider.md](/home/ray/dev/linkong/planet/docs/agents/aiprovider.md)
+- [AI Provider 指南](../docs/technical/zh/agents-aiprovider.md)
 
 当前支持:
 
@@ -15,6 +15,7 @@
   - `AI_PROVIDER=ollama`
 - request adapter:
   - `AI_PROVIDER_API=openai-completions`
+  - `AI_PROVIDER_API=openai-responses`
   - `AI_PROVIDER_API=anthropic-messages`
   - `AI_PROVIDER_API=ollama-generate`
 

aiprovider/provider_service.py

@@ -3,6 +3,7 @@ from __future__ import annotations
 import asyncio
 import json
 from typing import Any
+from uuid import NAMESPACE_URL, uuid4, uuid5
 
 import httpx
 from fastapi import HTTPException, status
@@ -65,6 +66,7 @@ class ProviderService:
         self.model_provider_apis = self._parse_model_provider_apis(
             overrides.get("model_provider_apis")
         )
+        self.session_id = str(uuid4())
 
     def get_status(self) -> AIProviderStatusResponse:
         enabled = self.provider != "disabled"
@@ -95,6 +97,8 @@ class ProviderService:
             )
 
         prompt = self._build_prompt(payload)
+        if payload.context.get("session_id") is not None:
+            self.session_id = str(uuid5(NAMESPACE_URL, f"planet:{payload.context['session_id']}"))
 
         provider_api = self._resolve_model_provider_api(model)
 
@@ -102,6 +106,10 @@ class ProviderService:
             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 provider_api == "openai-responses":
+            data = await self._request_openai_responses(model, prompt, payload.system_prompt)
+            content_blocks = self._extract_responses_blocks(data)
+            content = "".join(block.text for block in content_blocks if block.text)
         elif provider_api == "anthropic-messages":
             data = await self._request_anthropic_messages(
                 model,
@@ -200,6 +208,39 @@ class ProviderService:
             request_body=request_body,
         )
 
+    async def _request_openai_responses(
+        self, model: str, prompt: str, system_prompt: str | None = None,
+    ) -> dict[str, Any]:
+        request_body: dict[str, Any] = {
+            "model": model, "input": prompt, "max_output_tokens": self.max_tokens, "store": False,
+        }
+        resolved_system_prompt = self._resolve_system_prompt(system_prompt)
+        if resolved_system_prompt:
+            request_body["instructions"] = resolved_system_prompt
+        return await self._post(
+            path="/responses",
+            headers={"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"},
+            request_body=request_body,
+        )
+
+    def _extract_responses_blocks(self, payload: dict[str, Any]) -> list[AIContentBlock]:
+        blocks: list[AIContentBlock] = []
+        for item in payload.get("output") or []:
+            if not isinstance(item, dict):
+                continue
+            if item.get("type") == "message":
+                for part in item.get("content") or []:
+                    if not isinstance(part, dict):
+                        continue
+                    text = part.get("text") or part.get("refusal")
+                    if isinstance(text, str) and text:
+                        blocks.append(AIContentBlock(type="text", text=text))
+            elif item.get("type") == "reasoning":
+                for part in item.get("summary") or []:
+                    if isinstance(part, dict) and isinstance(part.get("text"), str):
+                        blocks.append(AIContentBlock(type="thinking", thinking=part["text"]))
+        return blocks
+
     async def _request_anthropic_messages(
         self,
         model: str,
@@ -226,7 +267,7 @@ class ProviderService:
         resolved_system_prompt = self._resolve_system_prompt(system_prompt)
         if resolved_system_prompt:
             request_body["system"] = resolved_system_prompt
-        resolved_thinking = self._resolve_anthropic_thinking(thinking)
+        resolved_thinking = self._resolve_anthropic_thinking(thinking, model)
         if resolved_thinking:
             request_body["thinking"] = resolved_thinking
         if self.provider == "minimax" and self.base_url.endswith("/anthropic"):
@@ -243,8 +284,12 @@ class ProviderService:
             request_body=request_body,
         )
 
-    def _resolve_anthropic_thinking(self, thinking: dict[str, Any] | None) -> dict[str, Any] | None:
+    def _resolve_anthropic_thinking(
+        self, thinking: dict[str, Any] | None, model: str,
+    ) -> dict[str, Any] | None:
         if thinking:
+            if model.casefold() == "minimax-m3" and thinking.get("type") == "enabled":
+                return {"type": "adaptive"}
             return thinking
 
         # OpenClaw treats MiniMax's Anthropic-compatible path specially:
@@ -295,6 +340,9 @@ class ProviderService:
         headers: dict[str, str],
         request_body: dict[str, Any],
     ) -> dict[str, Any]:
+        headers = {"User-Agent": "Planet/1.0", **headers}
+        if self.provider == "opencode-go":
+            headers["x-opencode-session"] = self.session_id
         last_error: Exception | None = None
         for attempt in range(1, self.http_retry_attempts + 1):
             try: