| from fastapi import FastAPI
|
| from pydantic import BaseModel
|
| from typing import List
|
| from langchain_community.tools.tavily_search import TavilySearchResults
|
| import os
|
| from langgraph.prebuilt import create_react_agent
|
| from langchain_openai import AzureChatOpenAI
|
| from dotenv import load_dotenv
|
| load_dotenv()
|
| os.environ['AZURE_OPENAI_API_KEY'] = os.getenv('AZURE_OPENAI_API_KEY')
|
| os.environ['OPENAI_API_VERSION'] = os.getenv('OPENAI_API_VERSION')
|
| os.environ['AZURE_OPENAI_ENDPOINT'] = os.getenv('AZURE_OPENAI_ENDPOINT')
|
| os.environ['TAVILY_API_KEY'] = os.getenv('TAVILY_API_KEY')
|
|
|
| MODEL_NAME = [
|
| "gpt-4o"
|
| ]
|
|
|
| tool = TavilySearchResults(max_results=5)
|
|
|
| tools = [tool, ]
|
|
|
| app = FastAPI()
|
|
|
| class RequestState(BaseModel):
|
| model_name: str
|
| system_prompt: str
|
| messages: List[str]
|
|
|
| @app.post("/chat")
|
| def chat_endpoint(request: RequestState):
|
| """API Endpoint to chat with bot"""
|
| if request.model_name not in MODEL_NAME:
|
| return {"error": "Model not found"}
|
|
|
| llm = AzureChatOpenAI(
|
| azure_deployment="gpt-4o",
|
| temperature=0,
|
| max_tokens=None,
|
| timeout=None,
|
| max_retries=2,
|
| )
|
| agent = create_react_agent(llm, tools=tools, prompt=request.system_prompt)
|
| state = {"messages": request.messages}
|
| result = agent.invoke(state)
|
| return result
|
|
|
| if __name__ == "__main__":
|
| import uvicorn
|
| uvicorn.run(app, host="0.0.0.0", port=8000)
|
|
|
