mirror of
https://github.com/QuivrHQ/quivr.git
synced 2024-09-11 14:36:35 +03:00
92 lines
3.3 KiB
Python
92 lines
3.3 KiB
Python
# main.py
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import os
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import tempfile
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import streamlit as st
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from files import file_uploader, url_uploader
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from question import chat_with_doc
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from brain import brain
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from langchain.embeddings.openai import OpenAIEmbeddings
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from langchain.vectorstores import SupabaseVectorStore
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from supabase import Client, create_client
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supabase_url = st.secrets.supabase_url
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supabase_key = st.secrets.supabase_service_key
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openai_api_key = st.secrets.openai_api_key
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anthropic_api_key = st.secrets.anthropic_api_key
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supabase: Client = create_client(supabase_url, supabase_key)
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embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
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vector_store = SupabaseVectorStore(
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supabase, embeddings, table_name="documents")
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models = ["gpt-3.5-turbo", "gpt-4"]
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if anthropic_api_key:
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models += ["claude-v1", "claude-v1.3",
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"claude-instant-v1-100k", "claude-instant-v1.1-100k"]
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# Set the theme
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st.set_page_config(
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page_title="Quivr",
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layout="wide",
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initial_sidebar_state="expanded",
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)
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st.title("🧠 Quivr - Your second brain 🧠")
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st.markdown("Store your knowledge in a vector store and query it with OpenAI's GPT-3/4.")
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st.markdown("---\n\n")
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# Initialize session state variables
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if 'model' not in st.session_state:
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st.session_state['model'] = "gpt-3.5-turbo"
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if 'temperature' not in st.session_state:
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st.session_state['temperature'] = 0.0
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if 'chunk_size' not in st.session_state:
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st.session_state['chunk_size'] = 500
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if 'chunk_overlap' not in st.session_state:
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st.session_state['chunk_overlap'] = 0
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if 'max_tokens' not in st.session_state:
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st.session_state['max_tokens'] = 256
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# Create a radio button for user to choose between adding knowledge or asking a question
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user_choice = st.radio(
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"Choose an action", ('Add Knowledge', 'Chat with your Brain', 'Forget'))
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st.markdown("---\n\n")
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if user_choice == 'Add Knowledge':
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# Display chunk size and overlap selection only when adding knowledge
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st.sidebar.title("Configuration")
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st.sidebar.markdown(
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"Choose your chunk size and overlap for adding knowledge.")
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st.session_state['chunk_size'] = st.sidebar.slider(
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"Select Chunk Size", 100, 1000, st.session_state['chunk_size'], 50)
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st.session_state['chunk_overlap'] = st.sidebar.slider(
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"Select Chunk Overlap", 0, 100, st.session_state['chunk_overlap'], 10)
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# Create two columns for the file uploader and URL uploader
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col1, col2 = st.columns(2)
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with col1:
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file_uploader(supabase, openai_api_key, vector_store)
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with col2:
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url_uploader(supabase, openai_api_key, vector_store)
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elif user_choice == 'Chat with your Brain':
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# Display model and temperature selection only when asking questions
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st.sidebar.title("Configuration")
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st.sidebar.markdown(
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"Choose your model and temperature for asking questions.")
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st.session_state['model'] = st.sidebar.selectbox(
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"Select Model", models, index=(models).index(st.session_state['model']))
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st.session_state['temperature'] = st.sidebar.slider(
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"Select Temperature", 0.0, 1.0, st.session_state['temperature'], 0.1)
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st.session_state['max_tokens'] = st.sidebar.slider(
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"Select Max Tokens", 256, 2048, st.session_state['max_tokens'], 2048)
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chat_with_doc(st.session_state['model'], vector_store)
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elif user_choice == 'Forget':
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st.sidebar.title("Configuration")
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brain(supabase)
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st.markdown("---\n\n")
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