Update app.py
Browse files
app.py
CHANGED
@@ -11,6 +11,18 @@ from langchain.memory import ConversationBufferMemory
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import streamlit as st
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import os
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import time
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if not os.path.exists('files'):
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os.mkdir('files')
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@@ -37,18 +49,13 @@ if 'memory' not in st.session_state:
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return_messages=True,
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input_key="question")
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if 'vectorstore' not in st.session_state:
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st.session_state.vectorstore = Chroma(persist_directory='jj',
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)
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if 'llm' not in st.session_state:
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st.session_state.llm = Ollama(base_url="http://localhost:11434",
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callback_manager=CallbackManager(
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[StreamingStdOutCallbackHandler()]),
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)
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# Initialize session state
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if 'chat_history' not in st.session_state:
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st.session_state.chat_history = []
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import streamlit as st
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import os
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import time
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from langchain_community.llms import HuggingFaceEndpoint
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from langchain_community.embeddings import HuggingFaceEmbeddings
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model_name = "sentence-transformers/all-mpnet-base-v2"
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model_kwargs = {'device': 'cpu'}
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encode_kwargs = {'normalize_embeddings': False}
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embeddings = HuggingFaceEmbeddings(
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model_name=model_name,
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model_kwargs=model_kwargs,
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encode_kwargs=encode_kwargs
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)
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if not os.path.exists('files'):
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os.mkdir('files')
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return_messages=True,
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input_key="question")
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if 'vectorstore' not in st.session_state:
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#st.session_state.vectorstore = Chroma(persist_directory='jj', embedding_function=OllamaEmbeddings(base_url='http://localhost:11434',model="mistral")
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st.session_state.vectorstore = Chroma(persist_directory='jj', embedding_function=embeddings)
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if 'llm' not in st.session_state:
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#st.session_state.llm = Ollama(base_url="http://localhost:11434",model="mistral",verbose=True,callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]),)
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st.session_state.llm = HuggingFaceEndpoint(repo_id="mistralai/Mistral-7B-Instruct-v0.2", Temperature=0.9)
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# Initialize session state
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if 'chat_history' not in st.session_state:
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st.session_state.chat_history = []
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