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import gradio as gr
from src.rag import RAG
def upload_files(files, filepaths):
verbose = False
filepaths_new = [file.name for file in files]
if verbose:
print(f'previous files: {filepaths}')
print(f'new files: {filepaths_new}')
filepaths = filepaths + filepaths_new
return filepaths, filepaths
def initialize_rag(pdfs):
print(f'Initializing RAG-Chatbot with:\npdfs:\n{pdfs}')
# Initialize RAG instance
try:
rag = RAG(
urls=[],
pdfs=pdfs,
k=2
)
message = "RAG-Chatbot initialized successfully!"
except Exception as e:
rag = None
message = f"Error initializing RAG-Chatbot:\n{e}"
return message, rag
def get_rag_response(message, history, rag):
if rag is None:
return "Error: RAG-Chatbot is not initialized yet!"
print(f"Question: {message}")
response = rag.ask_QAbot(message)
answer_str = response['answer']
sources = [f"{i+1}. {source.split('/')[-1]}" for i, source in enumerate(response['sources'])]
sources_str = ';'.join(sources)
print(sources_str)
response_str = f"""
{answer_str}
Sources:
{sources_str}
"""
return response_str
with gr.Blocks() as demo:
gr.Markdown("# RAG-Chatbot")
gr.Markdown("## Instructions")
gr.Markdown("""
Upload PDF's that will form the basis of the database for our RAG-Chatbot.
Once done adding documents (multiple uploads allowed), click `Initialize` to start the building process.
Note that building time depends on the number and length of uploaded documents.
When the building is done,
as will be indicated by `RAG-Chatbot initialized successfully!` in the Initialization Status box,
you can start chatting!
""")
# PDFs
gr.Markdown("## 1. Build the bot")
pdfpaths = gr.State([])
file_output = gr.File()
upload_button = gr.UploadButton("Upload PDF(s)", file_count="multiple")
upload_button.upload(
fn=upload_files,
inputs=[upload_button, pdfpaths],
outputs=[file_output, pdfpaths])
# State to store the RAG instance
rag_instance = gr.State(None) # Initially None
init_button = gr.Button("Initialize")
init_status = gr.Textbox(label="Initialization Status", interactive=False)
# Event handlers
init_button.click(
initialize_rag,
inputs=[pdfpaths],
outputs=[init_status, rag_instance] # Output: status message and the RAG instance
)
gr.Markdown('## 2. Chat')
# Chat Interface for RAG-Chatbot
gr.ChatInterface(
fn=get_rag_response,
additional_inputs=[rag_instance],
type="messages"
)
if __name__ == "__main__":
demo.launch()
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