Add Gradio app and model files

app.py

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+
+import gradio as gr
+import joblib
+
+# Load your trained model from the model file
+model = joblib.load("model.pkl")
+
+# Define a function to use with the Gradio interface
+def predict_sentiment(text):
+    prediction = model.predict([text])[0]
+    probabilities = model.predict_proba([text])[0]
+    return {
+        "Prediction": prediction,
+        "Probabilities": dict(zip(model.classes_, probabilities))
+    }
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=predict_sentiment,
+    inputs=gr.Textbox(lines=2, placeholder="Enter your text here..."),
+    outputs=gr.JSON(label="Prediction and Probabilities"),
+    title="Sentiment Analysis App",
+    description="This app predicts sentiment responses using a trained logistic regression model."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    interface.launch()

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5c0f66e2084a15e883d8ee26675d93e88f70ba07689ebe512c24ab1e3e151db8
+size 2397780

requirements.txt

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+gradio
+scikit-learn
+joblib