app.py

import gradio as gr
from transformers import pipeline

summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")

def analyze_text(text):
    summary = summarizer(text, max_length=150, min_length=40, do_sample=False)[0]["summary_text"]
    follow_ups = [
        "What assumptions are made?",
        "What are potential counterarguments?",
        "What are possible next research questions?"
    ]
    return summary, "\n".join(follow_ups)

with gr.Blocks() as demo:
    gr.Markdown("### 🧠 Clarity Agent\nPaste text or upload a file to get a summary and follow-up ideas.")

    with gr.Row():
        input_text = gr.Textbox(label="Paste text", lines=12)
        file_upload = gr.File(label="...or upload .txt/.md", file_types=[".txt", ".md"])

    submit = gr.Button("Analyze")
    output_summary = gr.Textbox(label="Summary")
    output_questions = gr.Textbox(label="Follow-up Questions")

    def load_and_analyze(paste, file):
        content = paste or (file.read().decode() if file else "")
        return analyze_text(content) if content.strip() else ("No input provided", "")

    submit.click(load_and_analyze, inputs=[input_text, file_upload], outputs=[output_summary, output_questions])

demo.launch()