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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)
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