Update app.py

app.py

@@ -1,29 +1,25 @@
-from flask import Flask, request, jsonify
+import gradio as gr
 from transformers import pipeline
 
-app = Flask(__name__)
-
-# Load the summarization pipeline
+# Load the summarization model
 pipe = pipeline("summarization", model="Falconsai/text_summarization")
 
-@app.route('/')
-def home():
-    return "Text Summarization API is running!"
-
-@app.route('/summarize', methods=['POST'])
-def summarize():
-    try:
-        data = request.json
-        text = data.get("text", "")
-
-        if not text:
-            return jsonify({"error": "No text provided"}), 400
-
-        summary = pipe(text, max_length=150, min_length=30, do_sample=False)
-        return jsonify({"summary": summary[0]['summary_text']})
-
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-if __name__ == '__main__':
-    app.run(debug=True)
+# Define the function to summarize text
+def summarize_text(text):
+    if not text.strip():
+        return "Please enter some text to summarize."
+    summary = pipe(text, max_length=150, min_length=30, do_sample=False)
+    return summary[0]['summary_text']
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=summarize_text,
+    inputs=gr.Textbox(lines=5, placeholder="Enter text to summarize..."),
+    outputs="text",
+    title="Text Summarization App",
+    description="Enter text, and the AI will generate a concise summary.",
+)
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    iface.launch()