Spaces:
Sleeping
Sleeping
Handle epub loader
Browse files- app.py +16 -9
- requirements.txt +2 -1
app.py
CHANGED
@@ -2,18 +2,22 @@ import os
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import tempfile
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import streamlit as st
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from langchain.callbacks.base import BaseCallbackHandler
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from langchain.chains import ConversationalRetrievalChain
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from langchain.chat_models import ChatOpenAI
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from langchain.embeddings import HuggingFaceEmbeddings
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from langchain.memory import ConversationBufferMemory
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from langchain.memory.chat_message_histories import StreamlitChatMessageHistory
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_community.document_loaders import
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from langchain_community.vectorstores import DocArrayInMemorySearch
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from chat_profile import ChatProfileRoleEnum
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from calback_handler import StreamHandler, PrintRetrievalHandler
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# configs
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LLM_MODEL_NAME = "gpt-3.5-turbo"
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@@ -42,11 +46,11 @@ msgs = StreamlitChatMessageHistory()
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@st.cache_resource(ttl="1h")
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def configure_retriever(
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# Read documents
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docs = []
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temp_dir = tempfile.TemporaryDirectory()
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for file in
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temp_filepath = os.path.join(temp_dir.name, file.name)
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with open(temp_filepath, "wb") as f:
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f.write(file.getvalue())
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@@ -60,6 +64,8 @@ def configure_retriever(uploaded_files):
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loader = Docx2txtLoader(temp_filepath)
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elif extension == ".txt":
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loader = TextLoader(temp_filepath)
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else:
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st.write("This document format is not supported!")
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return None
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@@ -86,10 +92,11 @@ def configure_retriever(uploaded_files):
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with st.sidebar.expander("Documents"):
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st.subheader("Files")
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uploaded_files = st.file_uploader(
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label="Select files",
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)
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with st.sidebar.expander("Setup"):
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st.subheader("API Key")
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openai_api_key = st.text_input("OpenAI API Key", type="password")
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@@ -104,7 +111,7 @@ if not openai_api_key:
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st.stop()
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if uploaded_files:
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memory = ConversationBufferMemory(
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memory_key="chat_history", chat_memory=msgs, return_messages=True
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@@ -119,7 +126,7 @@ if uploaded_files:
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)
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chain = ConversationalRetrievalChain.from_llm(
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llm, retriever=
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)
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avatars = {
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import tempfile
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import streamlit as st
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from langchain.chains import ConversationalRetrievalChain
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from langchain.chat_models import ChatOpenAI
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from langchain.embeddings import HuggingFaceEmbeddings
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from langchain.memory import ConversationBufferMemory
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from langchain.memory.chat_message_histories import StreamlitChatMessageHistory
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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+
from langchain_community.document_loaders import (
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Docx2txtLoader,
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PyPDFLoader,
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TextLoader,
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UnstructuredEPubLoader,
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)
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from langchain_community.vectorstores import DocArrayInMemorySearch
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from calback_handler import PrintRetrievalHandler, StreamHandler
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from chat_profile import ChatProfileRoleEnum
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# configs
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LLM_MODEL_NAME = "gpt-3.5-turbo"
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@st.cache_resource(ttl="1h")
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def configure_retriever(files):
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# Read documents
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docs = []
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temp_dir = tempfile.TemporaryDirectory()
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for file in files:
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temp_filepath = os.path.join(temp_dir.name, file.name)
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with open(temp_filepath, "wb") as f:
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f.write(file.getvalue())
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loader = Docx2txtLoader(temp_filepath)
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elif extension == ".txt":
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loader = TextLoader(temp_filepath)
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elif extension == ".epub":
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loader = UnstructuredEPubLoader(temp_filepath)
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else:
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st.write("This document format is not supported!")
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return None
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with st.sidebar.expander("Documents"):
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st.subheader("Files")
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uploaded_files = st.file_uploader(
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label="Select files",
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type=["pdf", "txt", "docx", "epub"],
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accept_multiple_files=True,
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)
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with st.sidebar.expander("Setup"):
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st.subheader("API Key")
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openai_api_key = st.text_input("OpenAI API Key", type="password")
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st.stop()
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if uploaded_files:
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result_retriever = configure_retriever(uploaded_files)
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memory = ConversationBufferMemory(
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memory_key="chat_history", chat_memory=msgs, return_messages=True
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)
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chain = ConversationalRetrievalChain.from_llm(
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llm, retriever=result_retriever, memory=memory, verbose=False
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)
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avatars = {
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requirements.txt
CHANGED
@@ -6,4 +6,5 @@ streamlit
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streamlit_chat
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streamlit-extras
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pypdf
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docx2txt
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streamlit_chat
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streamlit-extras
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pypdf
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docx2txt
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unstructured
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