Introduce Project ID for context management, finalizing the stateful API pipeline from file submission to graph construction.

backend/app/utils/llm_client.py

@@ -0,0 +1,91 @@
+"""
+LLM客户端封装
+统一使用OpenAI格式调用
+"""
+
+import json
+from typing import Optional, Dict, Any, List
+from openai import OpenAI
+
+from ..config import Config
+
+
+class LLMClient:
+    """LLM客户端"""
+    
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        base_url: Optional[str] = None,
+        model: Optional[str] = None
+    ):
+        self.api_key = api_key or Config.LLM_API_KEY
+        self.base_url = base_url or Config.LLM_BASE_URL
+        self.model = model or Config.LLM_MODEL_NAME
+        
+        if not self.api_key:
+            raise ValueError("LLM_API_KEY 未配置")
+        
+        self.client = OpenAI(
+            api_key=self.api_key,
+            base_url=self.base_url
+        )
+    
+    def chat(
+        self,
+        messages: List[Dict[str, str]],
+        temperature: float = 0.7,
+        max_tokens: int = 4096,
+        response_format: Optional[Dict] = None
+    ) -> str:
+        """
+        发送聊天请求
+        
+        Args:
+            messages: 消息列表
+            temperature: 温度参数
+            max_tokens: 最大token数
+            response_format: 响应格式（如JSON模式）
+            
+        Returns:
+            模型响应文本
+        """
+        kwargs = {
+            "model": self.model,
+            "messages": messages,
+            "temperature": temperature,
+            "max_tokens": max_tokens,
+        }
+        
+        if response_format:
+            kwargs["response_format"] = response_format
+        
+        response = self.client.chat.completions.create(**kwargs)
+        return response.choices[0].message.content
+    
+    def chat_json(
+        self,
+        messages: List[Dict[str, str]],
+        temperature: float = 0.3,
+        max_tokens: int = 4096
+    ) -> Dict[str, Any]:
+        """
+        发送聊天请求并返回JSON
+        
+        Args:
+            messages: 消息列表
+            temperature: 温度参数
+            max_tokens: 最大token数
+            
+        Returns:
+            解析后的JSON对象
+        """
+        response = self.chat(
+            messages=messages,
+            temperature=temperature,
+            max_tokens=max_tokens,
+            response_format={"type": "json_object"}
+        )
+        
+        return json.loads(response)
+