Created app.py

app.py

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+import gradio as ui
+from transformers import pipeline
+
+# 1. Load the sentiment analysis pipeline
+# (Hugging Face Spaces will cache this so it only loads once on startup)
+pipe = pipeline(
+    "text-classification", model="tabularisai/multilingual-sentiment-analysis"
+)
+
+
+# 2. Define the prediction function
+def analyze_sentiment(text):
+    if not text.strip():
+        return "Please enter some text to analyze."
+
+    # Run the pipeline
+    result = pipe(text)[0]
+
+    # Extract label and score
+    label = result["label"]
+    score = result["score"]
+
+    # Return a cleanly formatted string
+    return f"Prediction: {label} | Confidence: {score:.2%}"
+
+
+# 3. Create the Gradio Interface
+demo = ui.Interface(
+    fn=analyze_sentiment,
+    inputs=ui.Textbox(
+        lines=3, placeholder="Enter text here...", label="Input Text"
+    ),
+    outputs=ui.Textbox(label="Sentiment Analysis Result"),
+    title="Multilingual Sentiment Analysis",
+    description="Enter text in various languages to detect the underlying sentiment using the `tabularisai/multilingual-sentiment-analysis` model.",
+    examples=[
+        ["I love this product! It's amazing and works perfectly."],
+        ["Ce produit est terrible, je déteste ça."],
+        ["Este producto es increíble y funciona a la perfección."],
+    ],
+)
+
+# 4. Launch the app
+if __name__ == "__main__":
+    demo.launch()