ResvuChatbox / app.py
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import subprocess
import sys
import gradio as gr
from utils import initialize_database
from model import llm_chain_response, get_response_value
from process_documents import create_db_from_files
def run_setup():
subprocess.check_call([sys.executable, "setup.py"])
# Run the setup script
run_setup()
llm_chain = llm_chain_response()
def chat_with_mistral(user_input):
if not user_input:
return "The message is not be empty."
response = llm_chain.invoke({"query": user_input})
print(response)
print("---------------Response--------------")
print(get_response_value(response["result"]))
return get_response_value(response["result"])
def main():
# Initialize the database
create_db_from_files()
# Set up and launch the Gradio interface
iface = gr.Interface(
fn=chat_with_mistral,
inputs=gr.components.Textbox(label="Enter Your Message"),
outputs=gr.components.Markdown(label="ChatbotResponse"),
title="Resvu AI Chatbot",
description="Interact with the Resvu API via this chatbot. Enter a message and get a response.",
examples=["Hi, how are you", "Who are you?", "What services do you offer?", "How can I find out about upcoming community events?"],
allow_flagging="never"
)
iface.launch()
if __name__ == "__main__":
main()