release: bump version to 0.59.0

aiprovider/config.py

@@ -17,9 +17,6 @@ class Settings(BaseSettings):
     AI_HTTP_RETRY_ATTEMPTS: int = 2
     AI_MAX_TOKENS: int = 1200
     AI_ANTHROPIC_VERSION: str = "2023-06-01"
-    AI_ANALYSIS_SYSTEM_PROMPT: str = (
-        "你是态势感知分析助手。请基于输入的上下文、观测与约束，输出结构化、克制、可执行的分析。"
-    )
 
     AI_PROVIDER_SERVICE_TOKEN: str = ""
 

aiprovider/provider_service.py

@@ -62,7 +62,6 @@ class ProviderService:
         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:
         enabled = self.provider != "disabled"
@@ -95,15 +94,20 @@ class ProviderService:
         prompt = self._build_prompt(payload)
 
         if self.provider_api == "openai-completions":
-            data = await self._request_openai_compatible(model, prompt)
+            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":
-            data = await self._request_anthropic_messages(model, prompt, payload.thinking)
+            data = await self._request_anthropic_messages(
+                model,
+                prompt,
+                payload.thinking,
+                payload.system_prompt,
+            )
             content = self._extract_anthropic_content(data)
             content_blocks = self._extract_anthropic_blocks(data)
         elif self.provider_api == "ollama-generate":
-            data = await self._request_ollama(model, prompt)
+            data = await self._request_ollama(model, prompt, payload.system_prompt)
             content = self._extract_ollama_content(data)
             content_blocks = self._extract_ollama_blocks(data)
         else:
@@ -139,18 +143,26 @@ class ProviderService:
             sections.append("约束条件:\n" + "\n".join(f"- {item}" for item in payload.constraints))
         if payload.context:
             sections.append(f"附加上下文:\n{payload.context}")
-        sections.append(
-            "请输出: 1) 态势摘要 2) 关键风险 3) 研判依据 4) 建议动作 5) 还缺少的数据。"
-        )
         return "\n\n".join(sections)
 
-    async def _request_openai_compatible(self, model: str, prompt: str) -> dict[str, Any]:
+    def _resolve_system_prompt(self, system_prompt: str | None) -> str | None:
+        resolved = str(system_prompt or "").strip()
+        return resolved or None
+
+    async def _request_openai_compatible(
+        self,
+        model: str,
+        prompt: str,
+        system_prompt: str | None = None,
+    ) -> dict[str, Any]:
+        messages = []
+        resolved_system_prompt = self._resolve_system_prompt(system_prompt)
+        if resolved_system_prompt:
+            messages.append({"role": "system", "content": resolved_system_prompt})
+        messages.append({"role": "user", "content": prompt})
         request_body = {
             "model": model,
-            "messages": [
-                {"role": "system", "content": self.system_prompt},
-                {"role": "user", "content": prompt},
-            ],
+            "messages": messages,
             "temperature": 0.2,
             "max_tokens": self.max_tokens,
         }
@@ -168,10 +180,10 @@ class ProviderService:
         model: str,
         prompt: str,
         thinking: dict[str, Any] | None = None,
+        system_prompt: str | None = None,
     ) -> dict[str, Any]:
         request_body = {
             "model": model,
-            "system": self.system_prompt,
             "messages": [
                 {
                     "role": "user",
@@ -186,6 +198,9 @@ class ProviderService:
             "max_tokens": self.max_tokens,
             "temperature": 0.2,
         }
+        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)
         if resolved_thinking:
             request_body["thinking"] = resolved_thinking
@@ -219,20 +234,28 @@ class ProviderService:
         model: str,
         prompt: str,
         thinking: dict[str, Any] | None = None,
+        system_prompt: str | None = None,
     ) -> dict[str, Any]:
-        return await self._request_anthropic_messages(model, prompt, thinking)
+        return await self._request_anthropic_messages(model, prompt, thinking, system_prompt)
 
-    async def _request_ollama(self, model: str, prompt: str) -> dict[str, Any]:
+    async def _request_ollama(
+        self,
+        model: str,
+        prompt: str,
+        system_prompt: str | None = None,
+    ) -> dict[str, Any]:
         request_body = {
             "model": model,
             "stream": False,
-            "system": self.system_prompt,
             "prompt": prompt,
             "options": {
                 "temperature": 0.2,
                 "num_predict": self.max_tokens,
             },
         }
+        resolved_system_prompt = self._resolve_system_prompt(system_prompt)
+        if resolved_system_prompt:
+            request_body["system"] = resolved_system_prompt
         return await self._post(
             path="/api/generate",
             headers={

aiprovider/schemas.py

@@ -13,10 +13,11 @@ class AIContentBlock(BaseModel):
 
 class SituationalAnalysisRequest(BaseModel):
     title: str = Field(..., min_length=1, max_length=200)
-    objective: str = Field(..., min_length=1, max_length=1000)
+    objective: str = Field(..., min_length=1, max_length=20000)
     context: dict[str, Any] = Field(default_factory=dict)
     observations: list[str] = Field(default_factory=list)
     constraints: list[str] = Field(default_factory=list)
+    system_prompt: str | None = Field(default=None, max_length=8000)
     preferred_model: str | None = Field(default=None, max_length=200)
     thinking: dict[str, Any] | None = None