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from pydantic import BaseModel
from typing import List
from fastapi import FastAPI
from ai_agent import get_response_from_ai_agent
import uvicorn
class RequestState(BaseModel):
model_name: str
model_provider: str
system_prompt: str
messages: List[str]
allow_search: bool
ALLOWED_MODEL_NAMES=["llama3-70b-8192", "mixtral-8x7b-32768", "llama-3.3-70b-versatile", "gpt-4o-mini"]
app=FastAPI(title="LangGraph AI Agent")
@app.post("/chat")
def chat_endpoint(request: RequestState):
if request.model_name not in ALLOWED_MODEL_NAMES:
return {"error": "Invalid model name. Kindly select a valid AI model"}
llm_id = request.model_name
query = request.messages
allow_search = request.allow_search
system_prompt = request.system_prompt
provider = request.model_provider
response=get_response_from_ai_agent(llm_id, query, allow_search, system_prompt, provider)
return response
if __name__ == "__main__":
uvicorn.run(app, host="127.0.0.1", port=9999)
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