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# app.py
import gradio as gr
from modules.summarizer import summarize_text
from modules.classifier import classify_text
from modules.event_detector import detect_events
# Main function that processes input
def process_text(input_text):
summary = summarize_text(input_text)
classification = classify_text(input_text)
events = detect_events(input_text)
# Display events in a comma-separated format
events_formatted = ', '.join(events) if isinstance(events, list) else events
return summary, classification, events_formatted
# Create the Gradio UI
with gr.Blocks() as demo:
gr.Markdown(
"""
# 🧠 NLP Assistant
Enter your text below and get:
- 📚 **Summarization**
- 🏷️ **Text Classification**
- 🗂️ **Event Detection**
"""
)
with gr.Row():
input_text = gr.Textbox(
label="Input Text",
placeholder="Paste your article, document, or paragraph here...",
lines=10
)
with gr.Row():
submit_btn = gr.Button("Process")
with gr.Row():
summary_output = gr.Textbox(label="Summary", lines=5)
classification_output = gr.Textbox(label="Classification", lines=2)
events_output = gr.Textbox(label="Detected Events", lines=5)
submit_btn.click(
fn=process_text,
inputs=[input_text],
outputs=[summary_output, classification_output, events_output]
)
# Launch Gradio app
if __name__ == "__main__":
demo.launch()
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