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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
)
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