# Import Libraries
import gradio as gr
import spaces
from dotenv import load_dotenv
from implementation.answer import answer_question
load_dotenv(override=True)
def format_context(context):
result = "
Relevant Context
\n\n"
for doc in context:
result += f"Source: {doc.metadata['source']}\n\n"
result += doc.page_content + "\n\n"
return result
@spaces.GPU
def chat(history):
last_message = (
"\n".join(map(str, history[-1]["content"]))
if isinstance(history[-1]["content"], list)
else history[-1]["content"]
)
prior = history[:-1]
answer, context = answer_question(last_message, prior, use_rewrite=True)
history.append({"role": "assistant", "content": answer})
return history, format_context(context)
def main():
def put_message_in_chatbot(message, history):
return "", history + [{"role": "user", "content": message}]
with gr.Blocks(title="PyComp: Simple Python Companion") as ui:
gr.Markdown(
"# 🏢 Meet PyComp: Simple Python Companion\nAsk me anything about Python!")
with gr.Row():
with gr.Column(scale=1):
chatbot = gr.Chatbot(
label="💬 Conversation",
height=600,
)
message = gr.Textbox(
label="Your Question",
placeholder="Ask anything about Python",
show_label=False,
)
with gr.Column(scale=1):
context_markdown = gr.Markdown(
label="📚 Retrieved Context",
value="*Retrieved context will appear here*",
container=True,
height=600,
)
message.submit(
put_message_in_chatbot, inputs=[
message, chatbot], outputs=[message, chatbot]
).then(chat, inputs=chatbot, outputs=[chatbot, context_markdown])
ui.launch()
if __name__ == "__main__":
main()