Add FastAPI backend with agent system

backend/app/services/llm_service.py

@@ -0,0 +1,145 @@
+"""
+LLM 服务 - 支持多种 LLM 提供商
+OpenAI / Claude / Ollama / DeepSeek / 任意 OpenAI 兼容接口
+"""
+
+from abc import ABC, abstractmethod
+from typing import AsyncIterator
+from langchain_core.messages import BaseMessage, AIMessage
+from langchain_openai import ChatOpenAI
+from langchain_anthropic import ChatAnthropic
+from langchain_ollama import ChatOllama
+from app.config import settings
+import httpx
+import os
+
+os.makedirs(settings.DATA_DIR, exist_ok=True)
+os.makedirs(settings.CHROMA_PERSIST_DIR, exist_ok=True)
+
+
+class LLMService(ABC):
+    @abstractmethod
+    async def invoke(self, messages: list[BaseMessage]) -> AIMessage:
+        raise NotImplementedError
+
+    @abstractmethod
+    async def stream(self, messages: list[BaseMessage]) -> AsyncIterator[str]:
+        raise NotImplementedError
+
+    @abstractmethod
+    def get_model_name(self) -> str:
+        raise NotImplementedError
+
+
+class OpenAICompatibleService(LLMService):
+    """
+    OpenAI 兼容接口
+    支持 OpenAI、DeepSeek、硅基流动、任意 OpenAI API 兼容服务
+    """
+    def __init__(
+        self,
+        api_key: str | None = None,
+        model: str | None = None,
+        base_url: str | None = None,
+    ):
+        self.api_key = api_key or settings.OPENAI_API_KEY
+        self.model = model or settings.OPENAI_MODEL
+        self.base_url = base_url or settings.OPENAI_BASE_URL
+        self._llm = ChatOpenAI(
+            api_key=self.api_key,
+            model=self.model,
+            base_url=self.base_url,
+            timeout=httpx.Timeout(60.0, connect=10.0),
+        )
+
+    async def invoke(self, messages: list[BaseMessage]) -> AIMessage:
+        return await self._llm.ainvoke(messages)
+
+    async def stream(self, messages: list[BaseMessage]) -> AsyncIterator[str]:
+        async for chunk in self._llm.astream(messages):
+            if chunk.content:
+                yield chunk.content
+
+    def get_model_name(self) -> str:
+        return self.model
+
+
+class ClaudeService(LLMService):
+    def __init__(
+        self,
+        api_key: str | None = None,
+        model: str | None = None,
+        max_tokens: int = 8192,
+    ):
+        self.api_key = api_key or settings.ANTHROPIC_API_KEY
+        self.model = model or settings.CLAUDE_MODEL
+        self._llm = ChatAnthropic(
+            api_key=self.api_key,
+            model=self.model,
+            max_tokens=max_tokens,
+            timeout=httpx.Timeout(60.0, connect=10.0),
+        )
+
+    async def invoke(self, messages: list[BaseMessage]) -> AIMessage:
+        return await self._llm.ainvoke(messages)
+
+    async def stream(self, messages: list[BaseMessage]) -> AsyncIterator[str]:
+        async for chunk in self._llm.astream(messages):
+            if chunk.content:
+                yield chunk.content
+
+    def get_model_name(self) -> str:
+        return self.model
+
+
+class OllamaService(LLMService):
+    def __init__(
+        self,
+        base_url: str | None = None,
+        model: str | None = None,
+    ):
+        self.base_url = base_url or settings.OLLAMA_BASE_URL
+        self.model = model or settings.OLLAMA_MODEL
+        self._llm = ChatOllama(
+            base_url=self.base_url,
+            model=self.model,
+            timeout=httpx.Timeout(120.0, connect=10.0),
+        )
+
+    async def invoke(self, messages: list[BaseMessage]) -> AIMessage:
+        return await self._llm.ainvoke(messages)
+
+    async def stream(self, messages: list[BaseMessage]) -> AsyncIterator[str]:
+        async for chunk in self._llm.astream(messages):
+            if chunk.content:
+                yield chunk.content
+
+    def get_model_name(self) -> str:
+        return self.model
+
+
+# 单例缓存
+_llm_instance: LLMService | None = None
+
+
+def get_llm() -> LLMService:
+    """根据配置获取 LLM 实例"""
+    global _llm_instance
+    if _llm_instance is None:
+        provider = settings.LLM_PROVIDER
+        if provider == "openai":
+            _llm_instance = OpenAICompatibleService()
+        elif provider == "deepseek":
+            _llm_instance = OpenAICompatibleService(
+                base_url="https://api.deepseek.com/v1",
+                model="deepseek-chat",
+            )
+        elif provider == "custom":
+            _llm_instance = OpenAICompatibleService()
+        elif provider == "claude":
+            _llm_instance = ClaudeService()
+        elif provider == "ollama":
+            _llm_instance = OllamaService()
+        else:
+            raise ValueError(f"Unknown LLM provider: {provider}")
+    return _llm_instance