fix: auto-fix code issues (cron)

- 修复重复导入/字段
- 修复异常处理
- 修复PEP8格式问题
- 添加类型注解

backend/llm_client.py

@@ -52,7 +52,7 @@ class LLMClient:
         }
 
     async def chat(
-        self, messages: list[ChatMessage], temperature: float = 0.3, stream: bool = False
+        self, messages: list[ChatMessage], temperature: float = 0.3, stream: bool = False,
     ) -> str:
         """发送聊天请求"""
         if not self.api_key:
@@ -77,7 +77,7 @@ class LLMClient:
             return result["choices"][0]["message"]["content"]
 
     async def chat_stream(
-        self, messages: list[ChatMessage], temperature: float = 0.3
+        self, messages: list[ChatMessage], temperature: float = 0.3,
     ) -> AsyncGenerator[str, None]:
         """流式聊天请求"""
         if not self.api_key:
@@ -90,30 +90,29 @@ class LLMClient:
             "stream": True,
         }
 
-        async with httpx.AsyncClient() as client:
-            async with client.stream(
-                "POST",
-                f"{self.base_url}/v1/chat/completions",
-                headers=self.headers,
-                json=payload,
-                timeout=120.0,
-            ) as response:
-                response.raise_for_status()
-                async for line in response.aiter_lines():
-                    if line.startswith("data: "):
-                        data = line[6:]
-                        if data == "[DONE]":
-                            break
-                        try:
-                            chunk = json.loads(data)
-                            delta = chunk["choices"][0]["delta"]
-                            if "content" in delta:
-                                yield delta["content"]
-                        except (json.JSONDecodeError, KeyError, IndexError):
-                            pass
+        async with httpx.AsyncClient() as client, client.stream(
+            "POST",
+            f"{self.base_url}/v1/chat/completions",
+            headers=self.headers,
+            json=payload,
+            timeout=120.0,
+        ) as response:
+            response.raise_for_status()
+            async for line in response.aiter_lines():
+                if line.startswith("data: "):
+                    data = line[6:]
+                    if data == "[DONE]":
+                        break
+                    try:
+                        chunk = json.loads(data)
+                        delta = chunk["choices"][0]["delta"]
+                        if "content" in delta:
+                            yield delta["content"]
+                    except (json.JSONDecodeError, KeyError, IndexError):
+                        pass
 
     async def extract_entities_with_confidence(
-        self, text: str
+        self, text: str,
     ) -> tuple[list[EntityExtractionResult], list[RelationExtractionResult]]:
         """提取实体和关系，带置信度分数"""
         prompt = f"""从以下会议文本中提取关键实体和它们之间的关系，以 JSON 格式返回：
@@ -190,7 +189,7 @@ class LLMClient:
 
         messages = [
             ChatMessage(
-                role="system", content="你是一个专业的项目分析助手，擅长从会议记录中提取洞察。"
+                role="system", content="你是一个专业的项目分析助手，擅长从会议记录中提取洞察。",
             ),
             ChatMessage(role="user", content=prompt),
         ]
@@ -241,7 +240,7 @@ class LLMClient:
             [
                 f"[{m.get('created_at', '未知时间')}] {m.get('text_snippet', '')}"
                 for m in mentions[:20]
-            ]  # 限制数量
+            ],  # 限制数量
         )
 
         prompt = f"""分析实体 "{entity_name}" 在项目中的演变和态度变化：