app.py

import os
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from langchain_ollama import ChatOllama
from langchain.schema import StrOutputParser
from langchain.prompts import ChatPromptTemplate
import logging
from functools import lru_cache

# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

app = FastAPI()

MODEL_NAME = 'tinyllama'

@lru_cache()
def get_llm():
    return ChatOllama(model=MODEL_NAME)

@lru_cache()
def get_chain():
    llm = get_llm()
    prompt = ChatPromptTemplate.from_template("Question: {question}\n\nAnswer:")
    return prompt | llm | StrOutputParser()

class Question(BaseModel):
    text: str

@app.get("/")
def read_root():
    return {"Hello": f"Welcome to {MODEL_NAME} FastAPI"}

@app.post("/ask")
async def ask_question(question: Question):
    try:
        logger.info(f"Received question: {question.text}")
        chain = get_chain()
        response = chain.invoke({"question": question.text})
        logger.info("Response generated successfully")
        return {"answer": response}
    except Exception as e:
        logger.error(f"Error in /ask endpoint: {str(e)}")
        raise HTTPException(status_code=500, detail=str(e))

@app.on_event("startup")
async def startup_event():
    logger.info(f"Starting up with model: {MODEL_NAME}")
    # Warm up the cache
    get_chain()

@app.on_event("shutdown")
async def shutdown_event():
    logger.info("Shutting down")