from fastapi import FastAPI
from transformers import pipeline

app = FastAPI()

# Load the model once when the server starts
# This is "Sentiment Analysis" by default
classifier = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")

@app.get("/")
def home():
    return {"status": "Level 2 Live", "model": "DistilBERT Sentiment"}

@app.post("/predict")
def predict(data: dict):
    text = data.get("text", "")
    if not text:
        return {"error": "No text provided"}
    
    # Run the model
    result = classifier(text)
    return {"input": text, "result": result[0]}