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import os
import json
import gradio as gr
import streamlit as st
from huggingface_hub import HfApi, login
from dotenv import load_dotenv
from llm import get_groq_llm
from vectorstore import get_chroma_vectorstore
from embeddings import get_SFR_Code_embedding_model
from kadiApy_ragchain import KadiApyRagchain
# Load environment variables from .env file
load_dotenv()
vectorstore_path = "data/vectorstore"
GROQ_API_KEY = os.environ["GROQ_API_KEY"]
HF_TOKEN = os.environ["HF_Token"]
with open("config.json", "r") as file:
config = json.load(file)
login(HF_TOKEN)
hf_api = HfApi()
# Access the values
LLM_MODEL_NAME = config["llm_model_name"]
LLM_MODEL_TEMPERATURE = float(config["llm_model_temperature"])
def initialize():
global kadiAPY_ragchain
vectorstore = get_chroma_vectorstore(get_SFR_Code_embedding_model(), vectorstore_path)
llm = get_groq_llm(LLM_MODEL_NAME, LLM_MODEL_TEMPERATURE, GROQ_API_KEY)
kadiAPY_ragchain = KadiApyRagchain(llm, vectorstore)
initialize()
def bot_kadi(history):
user_query = history[-1][0]
response = kadiAPY_ragchain.process_query(user_query)
history[-1] = (user_query, response)
yield history
import gradio as gr
def add_text_to_chatbot(chat_history, user_input):
if user_input:
chat_history.append((user_input, None))
response = "This is a placeholder response. Replace this with your AI logic."
chat_history.append((None, response))
return chat_history, ""
def main():
with gr.Blocks() as demo:
gr.Markdown("## KadiAPY - AI Coding-Assistant")
gr.Markdown("AI assistant for KadiAPY based on RAG architecture powered by LLM")
with gr.Tab("KadiAPY - AI Assistant"):
with gr.Row():
with gr.Column(scale=10):
chatbot = gr.Chatbot([], elem_id="chatbot", label="Kadi Bot", bubble_full_width=False, show_copy_button=True, height=600)
user_txt = gr.Textbox(label="Question", placeholder="Type in your question and press Enter or click Submit")
with gr.Row():
with gr.Column(scale=1):
submit_btn = gr.Button("Submit", variant="primary")
with gr.Column(scale=1):
clear_btn = gr.Button("Clear", variant="stop")
gr.Examples(
examples=[
"Write me a python script with which can convert plain JSON to a Kadi4Mat-compatible extra metadata structure",
"I need a method to upload a file to a record. The id of the record is 3",
],
inputs=user_txt,
outputs=chatbot,
fn=add_text_to_chatbot,
label="Try asking...",
cache_examples=False,
examples_per_page=3,
)
submit_btn.click(add_text_to_chatbot, [chatbot, user_txt], [chatbot, user_txt])
clear_btn.click(lambda: ([], ""), None, [chatbot, user_txt])
demo.launch()
if __name__ == "__main__":
main() |