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Update pages/management.py
Browse files- pages/management.py +54 -54
pages/management.py
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import os
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import streamlit as st
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from langchain.document_loaders import DirectoryLoader, TextLoader, PyPDFLoader
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from langchain.text_splitter import CharacterTextSplitter
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from app import vectorstore
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st.title("Document Management")
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# File uploader
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uploaded_file = st.file_uploader("Choose a file", type=['txt', 'pdf', 'docx'])
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if uploaded_file is not None:
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# Display current documents in the knowledge base
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# st.subheader("Current Documents in Knowledge Base")
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# # This is a placeholder. You'll need to implement a method to retrieve and display
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# # the list of documents currently in your Chroma database.
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# st.write("Placeholder for document list")
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# # Option to clear the entire knowledge base
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# if st.button("Clear Knowledge Base"):
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# if st.sidebar.checkbox("Are you sure you want to clear the entire knowledge base? This action cannot be undone."):
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# try:
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# # Clear the Chroma database
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# vectorstore.delete()
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# st.success("Knowledge base cleared!")
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# except Exception as e:
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# st.error(f"An error occurred: {e}")
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# import os
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# import streamlit as st
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# from langchain.document_loaders import DirectoryLoader, TextLoader, PyPDFLoader
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# from langchain.text_splitter import CharacterTextSplitter
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# from app import vectorstore
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# st.title("Document Management")
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# # File uploader
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# uploaded_file = st.file_uploader("Choose a file", type=['txt', 'pdf', 'docx'])
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# if uploaded_file is not None:
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# # Create a temporary directory to store the uploaded file
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# temp_dir = "temp_uploads"
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# os.makedirs(temp_dir, exist_ok=True)
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# file_path = os.path.join(temp_dir, uploaded_file.name)
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# # Save the uploaded file temporarily
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# with open(file_path, "wb") as f:
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# f.write(uploaded_file.getbuffer())
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# st.success(f"File {uploaded_file.name} successfully uploaded!")
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# # Process the uploaded file
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# if st.button("Process Document"):
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# with st.spinner("Processing document..."):
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# try:
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# # Load the document based on file type
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# if uploaded_file.type == "application/pdf":
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# loader = PyPDFLoader(file_path)
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# elif uploaded_file.type == "text/plain":
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# loader = TextLoader(file_path)
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# else:
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# st.error("Unsupported file type.")
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# st.stop()
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# documents = loader.load()
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# # Split the document into chunks
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# text_splitter = CharacterTextSplitter(chunk_size=800, chunk_overlap=150)
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# texts = text_splitter.split_documents(documents)
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# # Add the chunks to the vectorstore
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# vectorstore.add_documents(texts)
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# st.success(f"Document processed and added to the knowledge base!")
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# except Exception as e:
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# st.error(f"An error occurred: {e}")
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# # Clean up: remove the temporary file
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# os.remove(file_path)
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# # Display current documents in the knowledge base
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# # st.subheader("Current Documents in Knowledge Base")
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# # # This is a placeholder. You'll need to implement a method to retrieve and display
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# # # the list of documents currently in your Chroma database.
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# # st.write("Placeholder for document list")
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# # # Option to clear the entire knowledge base
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# # if st.button("Clear Knowledge Base"):
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# # if st.sidebar.checkbox("Are you sure you want to clear the entire knowledge base? This action cannot be undone."):
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# # try:
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# # # Clear the Chroma database
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# # vectorstore.delete()
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# # st.success("Knowledge base cleared!")
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# # except Exception as e:
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# # st.error(f"An error occurred: {e}")
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