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| import os | |
| import gradio as gr | |
| from transformers import pipeline | |
| from PyPDF2 import PdfReader | |
| # Load free Hugging Face models | |
| summarizer = pipeline("summarization", model="facebook/bart-large-cnn") | |
| qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad") | |
| # Global variable to store PDF text | |
| pdf_text_store = "" | |
| def extract_text_from_pdf(pdf_file): | |
| reader = PdfReader(pdf_file) | |
| text = "" | |
| for page in reader.pages: | |
| page_text = page.extract_text() | |
| if page_text: | |
| text += page_text + "\n" | |
| return text | |
| def upload_pdf(file, history): | |
| global pdf_text_store | |
| pdf_text_store = extract_text_from_pdf(file) | |
| if not pdf_text_store.strip(): | |
| history.append(("System", "❌ No text could be extracted from the PDF. Please try another PDF.")) | |
| return history | |
| summary = summarizer(pdf_text_store[:1000], max_length=200, min_length=50, do_sample=False)[0]['summary_text'] | |
| history.append(("System", f"✅ PDF processed!\n\n**Summary:**\n{summary}")) | |
| return history | |
| def chatbot(user_message, history): | |
| if not pdf_text_store: | |
| history.append((user_message, "❌ Please upload a PDF first.")) | |
| return "", history | |
| result = qa_pipeline({ | |
| 'context': pdf_text_store, | |
| 'question': user_message | |
| }) | |
| answer = result["answer"] | |
| history.append((user_message, answer)) | |
| return "", history | |
| with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple", secondary_hue="blue")) as demo: | |
| gr.HTML(""" | |
| <style> | |
| body { | |
| background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%); | |
| font-family: 'Helvetica Neue', sans-serif; | |
| } | |
| .title { | |
| text-align: center; | |
| font-size: 2.5rem; | |
| font-weight: 700; | |
| margin-bottom: 0.2em; | |
| color: #4f46e5; | |
| } | |
| .subtitle { | |
| text-align: center; | |
| font-size: 1.1rem; | |
| color: #4b5563; | |
| margin-bottom: 2em; | |
| } | |
| .custom-btn { | |
| background: #4f46e5; | |
| color: white; | |
| border-radius: 0.5em; | |
| padding: 0.5em 1.2em; | |
| transition: background 0.3s; | |
| } | |
| .custom-btn:hover { | |
| background: #4338ca; | |
| } | |
| .upload-box { | |
| background: white; | |
| padding: 1em; | |
| border-radius: 0.75em; | |
| box-shadow: 0 2px 10px rgba(0,0,0,0.1); | |
| margin-bottom: 1em; | |
| } | |
| .chat-area { | |
| background: white; | |
| border-radius: 0.75em; | |
| box-shadow: 0 2px 10px rgba(0,0,0,0.1); | |
| overflow: hidden; | |
| } | |
| </style> | |
| """) | |
| gr.HTML('<div class="title">📚 Chat with Your PDF</div>') | |
| gr.HTML('<div class="subtitle">Upload a PDF, get a summary, and chat with it!</div>') | |
| with gr.Row(): | |
| with gr.Column(scale=1, min_width=250): | |
| with gr.Group(elem_classes="upload-box"): | |
| gr.Markdown("### 📂 Upload Your PDF") | |
| pdf_upload = gr.File(label="Upload PDF", file_types=[".pdf"]) | |
| upload_btn = gr.Button("🚀 Process PDF", elem_classes="custom-btn") | |
| with gr.Column(scale=2): | |
| chatbot_ui = gr.Chatbot( | |
| label="💬 Chat with your PDF", | |
| height=500, | |
| show_copy_button=True, | |
| elem_classes="chat-area" | |
| ) | |
| user_input = gr.Textbox( | |
| placeholder="Ask something about your PDF...", | |
| show_label=False | |
| ) | |
| upload_btn.click(upload_pdf, inputs=[pdf_upload, chatbot_ui], outputs=chatbot_ui) | |
| user_input.submit(chatbot, [user_input, chatbot_ui], [user_input, chatbot_ui]) | |
| gr.HTML(""" | |
| <div style="text-align:center; font-size:0.9rem; color:#6b7280; margin-top:2em;"> | |
| Made with ❤️ – No API keys needed! | |
| </div> | |
| """) | |
| if __name__ == "__main__": | |
| demo.launch() | |