app.py

import spaces
import os
import gradio as gr

from ui import upload_document, chat, clear_chat

custom_css = """
.gradio-container {
    max-width: 100% !important;
    padding: 1.5rem 2rem !important;
    margin: 0 !important;
}
.header-box {
    text-align: center;
    padding: 1rem;
    margin-bottom: 1rem;
    width: 100%;
}
.header-box h1 {
    margin-bottom: 0.5rem;
}
.header-box p {
    margin: 0.3rem 0;
}
.example-btn {
    border-radius: 8px !important;
    font-size: 0.88rem !important;
    flex: 1 !important;
}
.send-btn {
    background: linear-gradient(135deg, #2563eb 0%, #1d4ed8 100%) !important;
    color: white !important;
    border: none !important;
    font-weight: 600 !important;
    border-radius: 8px !important;
    box-shadow: 0 4px 12px rgba(37, 99, 235, 0.3) !important;
}
.send-btn:hover {
    background: linear-gradient(135deg, #1d4ed8 0%, #1e40af 100%) !important;
    box-shadow: 0 6px 16px rgba(37, 99, 235, 0.45) !important;
}
"""


def user_submit(user_message, history):
    if not user_message or not user_message.strip():
        return "", history
    updated_history = chat(user_message, history)
    return "", updated_history


with gr.Blocks(title="Enterprise AI Document Intelligence Platform") as demo:

    gr.Markdown(
        """
        <div style="text-align: center;">

        # 🤖 Enterprise AI Document Intelligence Platform

        Upload a PDF and chat with your documents using<br>AI-powered Retrieval-Augmented Generation (RAG)

        *Powered by*<br>**Groq • Sentence Transformers • FAISS**

        </div>
        """
    )

    gr.Markdown("---")

    with gr.Row():
        # Sidebar for PDF Ingestion (responsive 1/4 screen width)
        with gr.Column(scale=1, min_width=320):
            gr.Markdown("### 📄 Document Ingestion")

            upload = gr.File(
                label="Upload Enterprise PDF",
                file_types=[".pdf"],
                file_count="single"
            )

            status = gr.Markdown("*No document indexed yet. Upload a PDF above.*")

            active_doc = gr.Markdown("ℹ️ **Active Index:** Empty")

            clear_btn = gr.Button("🗑️ Clear Chat History", variant="secondary")

            gr.Markdown(
                """
                ---
                **System Stack:**
                - 📄 PyMuPDF PDF Text Extraction
                - 🧠 `all-MiniLM-L6-v2` Vector Embeddings
                - ⚡ FAISS Vector Similarity Index
                - 🤖 Groq `llama-3.3-70b-versatile` Engine
                """
            )

        # Main Chat Panel (expanding to fill remaining full width)
        with gr.Column(scale=3):
            gr.Markdown("### 💬 Enterprise Knowledge Chat")

            chatbot = gr.Chatbot(
                height=560,
                placeholder="💡 Upload a PDF document on the left, then ask questions here."
            )

            gr.Markdown("#### 💡 Try Asking")
            with gr.Row():
                ex1 = gr.Button("📄 Summarize this document", variant="secondary", size="sm", elem_classes=["example-btn"])
                ex2 = gr.Button("🛠️ List technical skills", variant="secondary", size="sm", elem_classes=["example-btn"])
                ex3 = gr.Button("🚀 What projects are mentioned?", variant="secondary", size="sm", elem_classes=["example-btn"])
                ex4 = gr.Button("📋 Give me a short overview", variant="secondary", size="sm", elem_classes=["example-btn"])

            with gr.Row():
                question = gr.Textbox(
                    placeholder="Ask anything about the uploaded document...",
                    show_label=False,
                    scale=5,
                    container=False
                )
                ask = gr.Button("Send 🚀", variant="primary", scale=1, elem_classes=["send-btn"])

    # Event Connections
    upload.upload(
        upload_document,
        inputs=upload,
        outputs=[status, active_doc]
    )

    ask.click(
        user_submit,
        inputs=[question, chatbot],
        outputs=[question, chatbot]
    )

    question.submit(
        user_submit,
        inputs=[question, chatbot],
        outputs=[question, chatbot]
    )

    ex1.click(
        lambda h: user_submit("Summarize this document", h),
        inputs=[chatbot],
        outputs=[question, chatbot]
    )

    ex2.click(
        lambda h: user_submit("List technical skills", h),
        inputs=[chatbot],
        outputs=[question, chatbot]
    )

    ex3.click(
        lambda h: user_submit("What projects are mentioned?", h),
        inputs=[chatbot],
        outputs=[question, chatbot]
    )

    ex4.click(
        lambda h: user_submit("Give me a short overview", h),
        inputs=[chatbot],
        outputs=[question, chatbot]
    )

    clear_btn.click(
        clear_chat,
        inputs=[],
        outputs=[chatbot]
    )

if __name__ == "__main__":
    demo.launch(
        css=custom_css,
        theme=gr.themes.Soft(),
        ssr_mode=False
    )