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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() |