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Update readme for anthropic
48 lines
2.1 KiB
Python
48 lines
2.1 KiB
Python
import anthropic
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import streamlit as st
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from streamlit.logger import get_logger
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from langchain.chains import ConversationalRetrievalChain
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from langchain.memory import ConversationBufferMemory
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from langchain.llms import OpenAI
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from langchain.chat_models import ChatAnthropic
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from langchain.vectorstores import SupabaseVectorStore
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memory = ConversationBufferMemory(
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memory_key="chat_history", return_messages=True)
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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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logger = get_logger(__name__)
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def count_tokens(question, model):
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count = f'Words: {len(question.split())}'
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if model.startswith("claude"):
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count += f' | Tokens: {anthropic.count_tokens(question)}'
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return count
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def chat_with_doc(model, vector_store: SupabaseVectorStore):
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question = st.text_area("## Ask a question")
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button = st.button("Ask")
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count_button = st.button("Count Tokens", type='secondary')
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if button:
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if model.startswith("gpt"):
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logger.info('Using OpenAI model %s', model)
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qa = ConversationalRetrievalChain.from_llm(
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OpenAI(
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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)
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result = qa({"question": question})
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logger.info('Result: %s', result)
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st.write(result["answer"])
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elif anthropic_api_key and model.startswith("claude"):
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logger.info('Using Anthropics model %s', model)
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qa = ConversationalRetrievalChain.from_llm(
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ChatAnthropic(
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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)
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result = qa({"question": question})
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logger.info('Result: %s', result)
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st.write(result["answer"])
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if count_button:
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st.write(count_tokens(question, model))
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