feat: 模型改用openAI

Author: keqian

.env.example

@@ -9,6 +9,12 @@ CHAT_MODEL_NAME=qwen3:8b
 EMBEDDING_MODEL_NAME=bge-m3:latest
 MODEL_TEMPERATURE=0
 
+# ===========================================
+# OPENAI模型
+# ===========================================
+OPENAI_API_KEY=
+OPENAI_API_BASE=
+
 # ===========================================
 # 数据库配置 (Database Configuration)  
 # ===========================================

.env.template

@@ -9,6 +9,12 @@ CHAT_MODEL_NAME=qwen3:8b
 EMBEDDING_MODEL_NAME=bge-m3:latest
 MODEL_TEMPERATURE=0
 
+# ===========================================
+# OPENAI模型
+# ===========================================
+OPENAI_API_KEY=
+OPENAI_API_BASE=
+
 # ===========================================
 # 数据库配置 (Database Configuration)
 # ===========================================

.gitignore

@@ -204,4 +204,5 @@ secrets.json
 # Local development
 local_*
 .python-version
-qdrant_data
+qdrant_data
+CLAUDE.md

agent.py

@@ -7,6 +7,7 @@
 
 from langchain.agents import AgentExecutor, create_openai_tools_agent
 from langchain_community.chat_message_histories import RedisChatMessageHistory
+from langchain_openai import ChatOpenAI
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import MessagesPlaceholder, ChatPromptTemplate
 from langchain_core.runnables import RunnableLambda, RunnableWithMessageHistory, RunnableConfig
@@ -41,11 +42,16 @@ def __init__(self, session_id: Optional[str] = None):
 
         # 初始化 Agent 执行器
         self.agent_executor = self._init_agent_executor()
-    
-    def _init_chat_model(self) -> ChatOllama:
+
+    def _init_chat_model(self) -> ChatOpenAI:
+        # def _init_chat_model(self) -> ChatOllama:
         """初始化聊天模型"""
-        model_config = config.get_model_config()
-        return ChatOllama(**model_config)
+        # model_config = config.get_model_config()
+        # return ChatOllama(**model_config)
+        return ChatOpenAI(
+            model="gpt-4o-mini",
+            temperature=0.2,
+        )
 
     def _init_agent_executor(self) -> RunnableWithMessageHistory:
         """初始化 Agent 执行器"""

requirements.txt

@@ -12,6 +12,7 @@ langchain-core==0.3.69
 langchain-ollama==0.3.5
 langchain-qdrant==0.2.0
 langchain-text-splitters==0.3.8
+langchain-openai==0.3.29
 
 # Database and storage
 redis==6.2.0

server.py

@@ -216,7 +216,7 @@ async def websocket_endpoint(websocket: WebSocket):
     import uvicorn
 
     server_logger.info("🔮 算命师机器人服务启动中...")
-    server_logger.info(f"📍 服务地址: http://localhost:8000")
-    server_logger.info(f"🌐 API 文档: http://localhost:8000/docs")
+    server_logger.info(f"📍 服务地址: http://localhost:8001")
+    server_logger.info(f"🌐 API 文档: http://localhost:8001/docs")
 
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+    uvicorn.run(app, host="0.0.0.0", port=8001)

services/tools.py

@@ -3,14 +3,14 @@
 使用配置管理和更好的错误处理
 """
 import requests
-from typing import Optional
 
 from langchain.agents import tool
 from langchain_community.utilities import SerpAPIWrapper
 from langchain_core.output_parsers import JsonOutputParser, StrOutputParser
 from langchain_core.prompts import ChatPromptTemplate, PromptTemplate
 from langchain_core.runnables import RunnableLambda
 from langchain_ollama import OllamaEmbeddings, ChatOllama, OllamaLLM
+from langchain_openai import OpenAI, ChatOpenAI
 from langchain_qdrant import QdrantVectorStore
 from qdrant_client import QdrantClient
 
@@ -96,8 +96,12 @@ def bazi_cesuan(query: str) -> str:
 
         # 创建模型
         model_config = config.get_model_config()
-        model = ChatOllama(**model_config, format="json")
-        
+        # model = ChatOllama(**model_config, format="json")
+        model = ChatOpenAI(
+            model="gpt-4o-mini",
+            temperature=0.2,
+        )
+
         # 构建处理链
         chain = prompt | model | parser
         data = chain.invoke({"query": query})
@@ -151,8 +155,12 @@ def jiemeng(query: str) -> str:
 
         # 创建关键词提取模型
         model_config = config.get_model_config()
-        llm = OllamaLLM(**model_config)
-        
+        # llm = OllamaLLM(**model_config)
+        llm = OpenAI(
+            model="gpt-4o-mini",
+            temperature=0.2
+        )
+
         # 直接使用统一管理的模板
         dream_prompt_template = SystemPrompts.DREAM_KEYWORD_EXTRACTION_PROMPT