initial commit

app.py

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+import gradio as gr
+import logging
+import sys
+import os
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    handlers=[logging.StreamHandler(sys.stdout)]
+)
+logger = logging.getLogger(__name__)
+
+# Log startup information
+logger.info("Starting StudAI Summarization Service with Gradio")
+logger.info(f"Python version: {sys.version}")
+
+# Import model
+try:
+    from transformers import pipeline
+    logger.info("Loading summarization model (t5-small)...")
+    
+    summarizer = pipeline(
+        "summarization", 
+        model="t5-small",
+        device=-1  # Use CPU for more reliable execution
+    )
+    logger.info("Model loaded successfully!")
+    model_available = True
+except Exception as e:
+    logger.error(f"Failed to load model: {str(e)}")
+    model_available = False
+    
+def summarize_text(text, max_length=150, min_length=30):
+    """Summarize the provided text using the loaded model"""
+    try:
+        if not text or len(text) < 50:
+            return text
+            
+        if not model_available:
+            return "Error: Summarization model is not available"
+        
+        logger.info(f"Summarizing text of length {len(text)}")
+        result = summarizer(
+            text, 
+            max_length=max_length, 
+            min_length=min_length,
+            truncation=True
+        )
+        summary = result[0]["summary_text"]
+        logger.info(f"Generated summary of length {len(summary)}")
+        return summary
+    except Exception as e:
+        logger.error(f"Error during summarization: {str(e)}")
+        return f"Error: {str(e)}"
+
+def api_summarize(text, max_length=150, min_length=30):
+    """API function for summarization"""
+    summary = summarize_text(text, max_length, min_length)
+    return {"summary": summary}
+
+# Create Gradio interface
+with gr.Blocks(title="StudAI Summarization") as demo:
+    gr.Markdown("# StudAI Text Summarization")
+    gr.Markdown("This service provides text summarization for the StudAI Android app.")
+    
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                label="Input Text", 
+                placeholder="Enter text to summarize (at least 50 characters)",
+                lines=10
+            )
+            with gr.Row():
+                max_length = gr.Slider(
+                    label="Max Length", 
+                    minimum=50, 
+                    maximum=500, 
+                    value=150, 
+                    step=10
+                )
+                min_length = gr.Slider(
+                    label="Min Length", 
+                    minimum=10, 
+                    maximum=200, 
+                    value=30, 
+                    step=5
+                )
+            submit_btn = gr.Button("Summarize")
+        
+        with gr.Column():
+            output_text = gr.Textbox(label="Summary", lines=10)
+    
+    submit_btn.click(
+        fn=summarize_text, 
+        inputs=[input_text, max_length, min_length], 
+        outputs=output_text
+    )
+    
+    # Add API endpoints for Android app
+    gr.Interface(
+        fn=api_summarize,
+        inputs=[
+            gr.Textbox(label="text"),
+            gr.Number(label="max_length", default=150),
+            gr.Number(label="min_length", default=30)
+        ],
+        outputs=gr.JSON(),
+        title="Summarization API",
+        description="API for StudAI Android app"
+    ).launch(show_api=True)
+
+# Launch the app
+demo.launch() 

requirements.txt

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+gradio==4.13.0
+transformers==4.35.2
+torch==2.0.1
+numpy<2.0.0
+pydantic==2.4.2
+requests==2.31.0