Create main.py

main.py

@@ -0,0 +1,24 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import pipeline
+
+app = FastAPI()
+
+# Load sentiment analysis model
+sentiment_pipeline = pipeline("sentiment-analysis")
+
+class SentimentRequest(BaseModel):
+    text: str
+
+class SentimentResponse(BaseModel):
+    label: str
+    score: float
+
+@app.get("/")
+def home():
+    return {"message": "Sentiment Analysis API is running!"}
+
+@app.post("/predict/", response_model=SentimentResponse)
+def predict(request: SentimentRequest):
+    result = sentiment_pipeline(request.text)
+    return SentimentResponse(label=result[0]['label'], score=result[0]['score'])