app.py

from fastapi import FastAPI
from pydantic import BaseModel
from transformers import pipeline

app = FastAPI()

# Load pretrained sentiment model
classifier = pipeline("sentiment-analysis")

# Input format
class TextRequest(BaseModel):
    text: str

@app.get("/")
async def root():
    return {"message": "Sentiment API is running"}

@app.post("/predict")
async def predict(request: TextRequest):
    result = classifier(request.text)[0]
    return {
        "label": result["label"],
        "score": float(result["score"])
    }