# app.py 
import os
import uvicorn
from fastapi import FastAPI
from pydantic import BaseModel


os.environ['HF_HOME'] = '/tmp/huggingface'
os.environ['TRANSFORMERS_CACHE'] = '/tmp/huggingface'
os.environ['HUGGINGFACE_HUB_CACHE'] = '/tmp/huggingface'

# Create cache directory
os.makedirs('/tmp/huggingface', exist_ok=True)


from agents import TutorAgent, BioUser

# Initialize FastAPI
app = FastAPI(title="Bioinformatics Tutor API")

# Initialize agents 
try:
    user_agent = BioUser()
    tutor_agent = TutorAgent()
    agents_loaded = True
except Exception as e:
    print(f"Error loading agents: {e}")
    agents_loaded = False

# Request model
class QueryRequest(BaseModel):
    question: str

# Response model
class QueryResponse(BaseModel):
    answer: str

@app.post("/ask", response_model=QueryResponse)
def ask_tutor(request: QueryRequest):
    """
    Ask the Bioinformatics Tutor a question.
    """
    if not agents_loaded:
        return QueryResponse(answer="Error: Agents not loaded. Please check the server logs.")
    
    try:
        answer = tutor_agent.process_query(request.question)
        return QueryResponse(answer=answer)
    except Exception as e:
        return QueryResponse(answer=f"Error processing query: {str(e)}")

@app.get("/")
def root():
    return {"message": "Bioinformatics Tutor API is running.", "agents_loaded": agents_loaded}

@app.get("/health")
def health_check():
    return {"status": "healthy", "agents_loaded": agents_loaded}