Merge pull request #15 from Shaunwei/support-anthropic-100k

Support for Anthropics Models
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Stan Girard 2023-05-14 12:40:53 +02:00 committed by GitHub
commit 218d684cd8
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5 changed files with 67 additions and 25 deletions

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@ -1,3 +1,4 @@
supabase_url = "https://lalalala.supabase.co"
supabase_service_key = "lalalala"
openai_api_key = "sk-lalalala"
anthropic_api_key = ""

6
.vscode/settings.json vendored Normal file
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@ -0,0 +1,6 @@
{
"[python]": {
"editor.defaultFormatter": "ms-python.autopep8"
},
"python.formatting.provider": "none"
}

40
main.py
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@ -10,23 +10,28 @@ 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="Quiver",
layout="wide",
initial_sidebar_state="expanded",
)
st.title("🧠 Quiver - Your second brain 🧠")
st.markdown("Store your knowledge in a vector store and query it with OpenAI's GPT-3/4.")
st.markdown("---\n\n")
@ -40,28 +45,37 @@ 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.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.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")

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@ -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)
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"])

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@ -8,4 +8,4 @@ StrEnum==0.4.10
supabase==1.0.3
tiktoken==0.4.0
unstructured==0.6.5
anthropic==0.2.8