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()