Add application file

app.py

@@ -1,7 +1,25 @@
-from fastapi import FastAPI
+from fastapi import FastAPI, Query
+from transformers import pipeline
+
+# Initialize the sentiment analysis pipeline
+pipe = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-sentiment")
 
 app = FastAPI()
 
 @app.get('/')
 def home():
-    return {"hello": "Abinesh"}
+    return {"message": "Welcome to the Sentiment Analysis API"}
+
+@app.get('/analyze')
+def analyze(tweet: str = Query(..., description="The tweet to analyze")):
+    # Use the pipeline to analyze the sentiment of the tweet
+    results = pipe(tweet)
+    
+    # Format the output to include labels and their corresponding scores
+    sentiment_scores = {result['label']: result['score'] for result in results}
+    
+    return sentiment_scores
+
+# To run this app on Hugging Face Spaces:
+# 1. Save this code as `app.py`.
+# 2. Deploy it to a new Hugging Face Space, and the Space will automatically start your FastAPI app.

requirements.txt

@@ -1,2 +1,6 @@
 fastapi[standard]
 uvicorn[standard]
+transformers[standard]
+torch[standard]
+torchvision[standard]
+torchaudio[standard]