chatbot-g-rag / app.py
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Update llama index lib
6999c1b
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()