from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from transformers import pipeline
import torch

app = FastAPI()

class TranscriptionPayload(BaseModel):
    text: str

# Load summarizer on startup
try:
    summarizer = pipeline(
        "summarization",
        model="knkarthick/MEETING_SUMMARY",
        torch_dtype=torch.float32,
        device="cpu",
    )
    print("✅ Summarizer model loaded successfully")
except Exception as e:
    summarizer = None
    print(f"❌ Error loading summarization model: {e}")

@app.post("/summarize")
async def summarize_text(payload: TranscriptionPayload):
    if not summarizer:
        raise HTTPException(status_code=503, detail="Summarizer model is not available.")

    summary = summarizer(payload.text, min_length=30, max_length=250, do_sample=False)
    return {"summary": summary[0]['summary_text']}