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import gradio as gr
import sys
import os
# Add parent directory to path to handle both local and Docker execution
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
try:
from DocumentQA import DocumentQA
except ImportError:
from src.DocumentQA import DocumentQA
# Initialize the DocumentQA system
qa_system = DocumentQA()
def process_document(file):
"""
Process the uploaded document.
"""
if file is not None:
qa_system.process_document(file.name)
return "Thank you for providing your document. I have analyzed it, so now you can ask me any questions regarding it!"
return "No document uploaded."
def chat(message, history):
"""
Chat function to interact with the DocumentQA system.
"""
if message.strip():
response = qa_system.query(message)
history.append([message, response])
return history, ""
def clear_chat():
"""
Clear the chat history.
"""
qa_system.chat_history.clear()
return []
# Create the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# LLM AI Assistant")
with gr.Row():
with gr.Column():
file_upload = gr.File(label="Upload Document")
upload_button = gr.Button("Process Document")
upload_status = gr.Textbox(label="Status")
with gr.Column():
chatbot = gr.Chatbot(type="tuples")
msg = gr.Textbox(label="Ask a question")
clear = gr.Button("Clear")
upload_button.click(process_document, inputs=file_upload, outputs=upload_status)
msg.submit(chat, [msg, chatbot], [chatbot, msg])
clear.click(clear_chat, None, chatbot, queue=False)
if __name__ == "__main__":
demo.launch(debug=True, server_name="0.0.0.0", server_port=7862, share=False)
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