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# import for typing | |
from langchain.chains import RetrievalQAWithSourcesChain | |
# gradio | |
import gradio as gr | |
global qa | |
from qa import qa | |
##### | |
# | |
# Gradio fns | |
#### | |
def create_gradio_interface(qa:RetrievalQAWithSourcesChain): | |
""" | |
Create a gradio interface for the QA model | |
""" | |
def add_text(history, text): | |
history = history + [(text, None)] | |
return history, "" | |
def bot(history): | |
response = infer(history[-1][0], history) | |
sources = [doc.metadata.get("source") for doc in response['source_documents']] | |
src_list = '\n'.join(sources) | |
print_this = response['answer'] + "\n\n\n Sources: \n\n\n" + src_list | |
history[-1][1] = print_this #response['answer'] | |
return history | |
def infer(question, history): | |
query = question | |
result = qa({"query": query, "history": history, "question": question}) | |
return result | |
css=""" | |
#col-container {max-width: 700px; margin-left: auto; margin-right: auto;} | |
""" | |
title = """ | |
<div style="text-align: center;max-width: 1920px;"> | |
<h1>Chat with your Documentation</h1> | |
<p style="text-align: center;">This is a privately hosten Docs AI Buddy, <br /> | |
It will help you with any question regarding the documentation of Ray ;)</p> | |
</div> | |
""" | |
with gr.Blocks(css=css) as demo: | |
with gr.Column(min_width=900, elem_id="col-container"): | |
gr.HTML(title) | |
chatbot = gr.Chatbot([], elem_id="chatbot") | |
#with gr.Row(): | |
# clear = gr.Button("Clear") | |
with gr.Row(): | |
question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter ") | |
with gr.Row(): | |
clear = gr.ClearButton([chatbot, question]) | |
question.submit(add_text, [chatbot, question], [chatbot, question], queue=False).then( | |
bot, chatbot, chatbot | |
) | |
#clear.click(lambda: None, None, chatbot, queue=False) | |
return demo | |
if __name__ == "__main__": | |
demo = create_gradio_interface(qa) | |
demo.queue().launch() | |