From b8fc2694468601754f4383d6c6c80956459bf4b8 Mon Sep 17 00:00:00 2001 From: shaun Date: Sun, 14 May 2023 01:28:55 -0700 Subject: [PATCH] Delete diff.txt --- diff.txt | 163 ------------------------------------------------------- 1 file changed, 163 deletions(-) delete mode 100644 diff.txt diff --git a/diff.txt b/diff.txt deleted file mode 100644 index b1edd2c65..000000000 --- a/diff.txt +++ /dev/null @@ -1,163 +0,0 @@ -diff --git a/.streamlit/secrets.toml.example b/.streamlit/secrets.toml.example -index 093c5bf..4c405dc 100644 ---- a/.streamlit/secrets.toml.example -+++ b/.streamlit/secrets.toml.example -@@ -1,3 +1,4 @@ - supabase_url = "https://lalalala.supabase.co" - supabase_service_key = "lalalala" --openai_api_key = "sk-lalalala" -\ No newline at end of file -+openai_api_key = "sk-lalalala" -+anthropic_api_key = "" -diff --git a/main.py b/main.py -index 6ed2560..88af1c5 100644 ---- a/main.py -+++ b/main.py -@@ -10,25 +10,30 @@ from langchain.embeddings.openai import OpenAIEmbeddings - from langchain.vectorstores import SupabaseVectorStore - from supabase import Client, create_client - --# supabase_url = "https://fqgpcifsfmamprzldyiv.supabase.co" - supabase_url = st.secrets.supabase_url - supabase_key = st.secrets.supabase_service_key - openai_api_key = st.secrets.openai_api_key -+anthropic_api_key = st.secrets.anthropic_api_key - supabase: Client = create_client(supabase_url, supabase_key) - - embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key) --vector_store = SupabaseVectorStore(supabase, embeddings, table_name="documents") -+vector_store = SupabaseVectorStore( -+ supabase, embeddings, table_name="documents") -+models = ["gpt-3.5-turbo", "gpt-4"] -+if anthropic_api_key: -+ models += ["claude-v1", "claude-v1.3", -+ "claude-instant-v1-100k", "claude-instant-v1.1-100k"] - - # Set the theme - st.set_page_config( - page_title="Second Brain", - layout="wide", - initial_sidebar_state="expanded", -- - ) - - st.title("🧠 Second Brain 🧠") --st.markdown("Store your knowledge in a vector store and query it with OpenAI's GPT-3/4.") -+st.markdown( -+ "Store your knowledge in a vector store and query it with OpenAI's GPT-3/4.") - st.markdown("---\n\n") - - # Initialize session state variables -@@ -40,31 +45,40 @@ if 'chunk_size' not in st.session_state: - st.session_state['chunk_size'] = 500 - if 'chunk_overlap' not in st.session_state: - st.session_state['chunk_overlap'] = 0 -+if 'max_tokens' not in st.session_state: -+ st.session_state['max_tokens'] = 256 - - # Create a radio button for user to choose between adding knowledge or asking a question --user_choice = st.radio("Choose an action", ('Add Knowledge', 'Chat with your Brain','Forget' )) -+user_choice = st.radio( -+ "Choose an action", ('Add Knowledge', 'Chat with your Brain', 'Forget')) - - st.markdown("---\n\n") - -- -- - if user_choice == 'Add Knowledge': - # Display chunk size and overlap selection only when adding knowledge -- st.sidebar.title("Configuration") -- st.sidebar.markdown("Choose your chunk size and overlap for adding knowledge.") -- st.session_state['chunk_size'] = st.sidebar.slider("Select Chunk Size", 100, 1000, st.session_state['chunk_size'], 50) -- st.session_state['chunk_overlap'] = st.sidebar.slider("Select Chunk Overlap", 0, 100, st.session_state['chunk_overlap'], 10) -+ st.sidebar.title("Configuration") -+ st.sidebar.markdown( -+ "Choose your chunk size and overlap for adding knowledge.") -+ st.session_state['chunk_size'] = st.sidebar.slider( -+ "Select Chunk Size", 100, 1000, st.session_state['chunk_size'], 50) -+ st.session_state['chunk_overlap'] = st.sidebar.slider( -+ "Select Chunk Overlap", 0, 100, st.session_state['chunk_overlap'], 10) - file_uploader(supabase, openai_api_key, vector_store) - elif user_choice == 'Chat with your Brain': - # Display model and temperature selection only when asking questions -- st.sidebar.title("Configuration") -- st.sidebar.markdown("Choose your model and temperature for asking questions.") -- st.session_state['model'] = st.sidebar.selectbox("Select Model", ["gpt-3.5-turbo", "gpt-4"], index=("gpt-3.5-turbo", "gpt-4").index(st.session_state['model'])) -- st.session_state['temperature'] = st.sidebar.slider("Select Temperature", 0.0, 1.0, st.session_state['temperature'], 0.1) -- chat_with_doc(openai_api_key, vector_store) -+ st.sidebar.title("Configuration") -+ st.sidebar.markdown( -+ "Choose your model and temperature for asking questions.") -+ st.session_state['model'] = st.sidebar.selectbox( -+ "Select Model", models, index=(models).index(st.session_state['model'])) -+ st.session_state['temperature'] = st.sidebar.slider( -+ "Select Temperature", 0.0, 1.0, st.session_state['temperature'], 0.1) -+ st.session_state['max_tokens'] = st.sidebar.slider( -+ "Select Max Tokens", 256, 2048, st.session_state['max_tokens'], 2048) -+ chat_with_doc(st.session_state['model'], vector_store) - elif user_choice == 'Forget': - st.sidebar.title("Configuration") -- -+ - brain(supabase) - --st.markdown("---\n\n") -\ No newline at end of file -+st.markdown("---\n\n") -diff --git a/question.py b/question.py -index 8e875f6..6f8e9d3 100644 ---- a/question.py -+++ b/question.py -@@ -1,14 +1,35 @@ - import streamlit as st -+from streamlit.logger import get_logger - from langchain.chains import ConversationalRetrievalChain - from langchain.memory import ConversationBufferMemory - from langchain.llms import OpenAI -+from langchain.chat_models import ChatAnthropic -+from langchain.vectorstores import SupabaseVectorStore - --memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True) -+memory = ConversationBufferMemory( -+ memory_key="chat_history", return_messages=True) -+openai_api_key = st.secrets.openai_api_key -+anthropic_api_key = st.secrets.anthropic_api_key -+logger = get_logger(__name__) - --def chat_with_doc(openai_api_key, vector_store): -- question = st.text_input("## Ask a question") -+ -+def chat_with_doc(model, vector_store: SupabaseVectorStore): -+ question = st.text_area("## Ask a question") - button = st.button("Ask") - if button: -- qa = ConversationalRetrievalChain.from_llm(OpenAI(model_name=st.session_state['model'], openai_api_key=openai_api_key, temperature=st.session_state['temperature']), vector_store.as_retriever(), memory=memory) -- result = qa({"question": question}) -- st.write(result["answer"]) -\ No newline at end of file -+ if model.startswith("gpt"): -+ logger.info('Using OpenAI model %s', model) -+ qa = ConversationalRetrievalChain.from_llm( -+ OpenAI( -+ model_name=st.session_state['model'], openai_api_key=openai_api_key, temperature=st.session_state['temperature'], max_tokens=st.session_state['max_tokens']), vector_store.as_retriever(), memory=memory, verbose=True) -+ result = qa({"question": question}) -+ logger.info('Result: %s', result) -+ st.write(result["answer"]) -+ elif anthropic_api_key and model.startswith("claude"): -+ logger.info('Using Anthropics model %s', model) -+ qa = ConversationalRetrievalChain.from_llm( -+ ChatAnthropic( -+ model=st.session_state['model'], anthropic_api_key=anthropic_api_key, temperature=st.session_state['temperature'], max_tokens_to_sample=st.session_state['max_tokens']), vector_store.as_retriever(), memory=memory, verbose=True, max_tokens_limit=102400) -+ result = qa({"question": question}) -+ logger.info('Result: %s', result) -+ st.write(result["answer"]) -diff --git a/requirements.txt b/requirements.txt -index 981d00b..ea8f1f6 100644 ---- a/requirements.txt -+++ b/requirements.txt -@@ -8,4 +8,4 @@ StrEnum==0.4.10 - supabase==1.0.3 - tiktoken==0.4.0 - unstructured==0.6.5 -- -+anthropic=0.2.8