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import os | |
import gradio as gr | |
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, SummaryIndex, ServiceContext | |
from llama_index.readers.web import SimpleWebPageReader | |
from llama_index.llms.mistralai import MistralAI | |
from llama_index.embeddings.mistralai import MistralAIEmbedding | |
from llama_index.core.query_engine import RetrieverQueryEngine | |
title = "Gaia Mistral 8x7b Chat RAG URL Demo" | |
description = "Example of an assistant with Gradio, RAG from url and Mistral AI via its API" | |
placeholder = "Vous pouvez me posez une question sur ce contexte, appuyer sur Entrée pour valider" | |
placeholder_url = "Extract text from this url" | |
llm_model = 'open-mixtral-8x7b' | |
# choose api_key from .env or from input field | |
# placeholder_api_key = "API key" | |
env_api_key = os.environ.get("MISTRAL_API_KEY") | |
query_engine = None | |
with gr.Blocks() as demo: | |
gr.Markdown(""" ### Welcome to Gaia Level 2 Demo | |
Add an URL at the bottom of the interface before interacting with the Chat. | |
This demo allows you to interact with a webpage and then ask questions to Mistral APIs. | |
Mistral will answer with the context extracted from the webpage. | |
""") | |
# with gr.Row(): | |
# api_key_text_box = gr.Textbox(placeholder=placeholder_api_key, container=False, scale=7) | |
def setup_with_url(url): | |
global query_engine | |
# Set-up clients | |
llm = MistralAI(api_key=env_api_key,model=llm_model) | |
embed_model = MistralAIEmbedding(model_name='mistral-embed', api_key=env_api_key) | |
service_context = ServiceContext.from_defaults(chunk_size=1024, llm=llm, embed_model=embed_model) | |
# Set-up db | |
documents = SimpleWebPageReader(html_to_text=True).load_data([url]) | |
index = VectorStoreIndex.from_documents(documents, service_context=service_context) | |
query_engine = index.as_query_engine(similarity_top_k=15) | |
return placeholder | |
gr.Markdown(""" ### 1 / Extract data from URL """) | |
with gr.Row(): | |
url_msg = gr.Textbox(placeholder=placeholder_url, container=False, scale=7) | |
url_btn = gr.Button(value="Process url ✅", interactive=True) | |
url_btn.click(setup_with_url, [url_msg], url_msg, show_progress= "full") | |
gr.Markdown(""" ### 2 / Ask a question about this context """) | |
chatbot = gr.Chatbot() | |
msg = gr.Textbox(placeholder=placeholder) | |
clear = gr.ClearButton([msg, chatbot]) | |
def respond(message, chat_history): | |
response = query_engine.query(message) | |
chat_history.append((message, str(response))) | |
return chat_history | |
msg.submit(respond, [msg, chatbot], [chatbot]) | |
demo.title = title | |
demo.launch() |