# app/main.py
import uvicorn
from fastapi import FastAPI, HTTPException, File, UploadFile
from pydantic import BaseModel
from app import models, openai_integration

app = FastAPI(title="Materials AI Extraction API")

# Pydantic models for request/response bodies
class ExtractionRequest(BaseModel):
    text: str

class QueryRequest(BaseModel):
    query: str

class SummarizeRequest(BaseModel):
    text: str

@app.post("/extract")
async def extract_data(request: ExtractionRequest):
    try:
        # Use our domain-specific model (e.g. MatSciBERT or BatteryBERT) for token classification
        extracted = models.extract_entities(request.text)
        return {"entities": extracted}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.post("/query")
async def query_data(request: QueryRequest):
    try:
        # This endpoint performs a Q&A on the provided query using the domain models
        answer = models.answer_question(request.query)
        return {"answer": answer}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.post("/summarize")
async def summarize(request: SummarizeRequest):
    try:
        summary = openai_integration.generate_summary(request.text)
        return {"summary": summary}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)