buster-dev / buster /examples /gradio_app.py
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PR: retriever interface (#77)
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import cfg
import gradio as gr
from buster.busterbot import Buster
from buster.retriever import Retriever
from buster.utils import get_retriever_from_extension
# initialize buster with the config in config.py (adapt to your needs) ...
retriever: Retriever = get_retriever_from_extension(cfg.documents_filepath)(cfg.documents_filepath)
buster: Buster = Buster(cfg=cfg.buster_cfg, retriever=retriever)
def chat(question, history):
history = history or []
answer = buster.process_input(question)
# formatting hack for code blocks to render properly every time
answer = answer.replace("```", "\n```\n")
history.append((question, answer))
return history, history
block = gr.Blocks(css="#chatbot .overflow-y-auto{height:500px}")
with block:
with gr.Row():
gr.Markdown("<h3><center>Buster 🤖: A Question-Answering Bot for your documentation</center></h3>")
chatbot = gr.Chatbot()
with gr.Row():
message = gr.Textbox(
label="What's your question?",
placeholder="Ask a question to AI stackoverflow here...",
lines=1,
)
submit = gr.Button(value="Send", variant="secondary").style(full_width=False)
examples = gr.Examples(
examples=[
"How can I perform backpropagation?",
"How do I deal with noisy data?",
],
inputs=message,
)
gr.Markdown("This application uses GPT to search the docs for relevant info and answer questions.")
gr.HTML("️<center> Created with ❤️ by @jerpint and @hadrienbertrand")
state = gr.State()
agent_state = gr.State()
submit.click(chat, inputs=[message, state], outputs=[chatbot, state])
message.submit(chat, inputs=[message, state], outputs=[chatbot, state])
block.launch(debug=True, share=False)