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import os |
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import json |
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import gradio as gr |
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import streamlit as st |
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from huggingface_hub import HfApi, login |
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from dotenv import load_dotenv |
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from llm import get_groq_llm |
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from vectorstore import get_chroma_vectorstore |
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from embeddings import get_SFR_Code_embedding_model |
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from kadiApy_ragchain import KadiApyRagchain |
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load_dotenv() |
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vectorstore_path = "data/vectorstore" |
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GROQ_API_KEY = os.environ["GROQ_API_KEY"] |
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HF_TOKEN = os.environ["HF_Token"] |
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with open("config.json", "r") as file: |
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config = json.load(file) |
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login(HF_TOKEN) |
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hf_api = HfApi() |
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LLM_MODEL_NAME = config["llm_model_name"] |
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LLM_MODEL_TEMPERATURE = float(config["llm_model_temperature"]) |
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def initialize(): |
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global kadiAPY_ragchain |
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vectorstore = get_chroma_vectorstore(get_SFR_Code_embedding_model(), vectorstore_path) |
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llm = get_groq_llm(LLM_MODEL_NAME, LLM_MODEL_TEMPERATURE, GROQ_API_KEY) |
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kadiAPY_ragchain = KadiApyRagchain(llm, vectorstore) |
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initialize() |
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def bot_kadi(history): |
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user_query = history[-1][0] |
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response = kadiAPY_ragchain.process_query(user_query) |
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history[-1] = (user_query, response) |
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yield history |
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def check_input_text(text): |
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if not text: |
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gr.Warning("Please input a question.") |
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raise TypeError |
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return True |
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def add_text(history, text): |
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history = history + [(text, None)] |
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yield history, "" |
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import gradio as gr |
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def main(): |
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with gr.Blocks() as demo: |
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gr.Markdown("## KadiAPY - AI Coding-Assistant") |
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gr.Markdown("AI assistant for KadiAPY based on RAG architecture powered by LLM") |
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with gr.Tab("KadiAPY - AI Assistant"): |
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with gr.Row(): |
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with gr.Column(scale=10): |
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chatbot = gr.Chatbot([], elem_id="chatbot", label="Kadi Bot", bubble_full_width=False, show_copy_button=True, height=600) |
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user_txt = gr.Textbox(label="Question", placeholder="Type in your question and press Enter or click Submit") |
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with gr.Row(): |
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with gr.Column(scale=1): |
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submit_btn = gr.Button("Submit", variant="primary") |
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with gr.Column(scale=1): |
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clear_btn = gr.Button("Clear", variant="stop") |
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gr.Examples( |
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examples=[ |
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"Write me a python script with which can convert plain JSON to a Kadi4Mat-compatible extra metadata structure", |
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"I need a method to upload a file to a record. The id of the record is 3", |
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], |
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inputs=user_txt, |
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outputs=chatbot, |
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fn=add_text, |
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label="Try asking...", |
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cache_examples=False, |
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examples_per_page=3, |
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) |
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user_txt.submit(check_input_text, user_txt, None).success(add_text, [chatbot, user_txt], [chatbot, user_txt]).then(bot_kadi, [chatbot], [chatbot]) |
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submit_btn.click(check_input_text, user_txt, None).success(add_text, [chatbot, user_txt], [chatbot, user_txt]).then(bot_kadi, [chatbot], [chatbot]) |
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clear_btn.click(lambda: None, None, chatbot, queue=False) |
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demo.launch() |
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if __name__ == "__main__": |
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main() |
