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Update app.py
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app.py
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@@ -2,14 +2,14 @@ import streamlit as st
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from dotenv import load_dotenv
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from PyPDF2 import PdfReader
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.embeddings import
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from langchain.vectorstores import FAISS
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from langchain.chat_models import ChatOpenAI
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from langchain.memory import ConversationBufferMemory
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from langchain.chains import ConversationalRetrievalChain
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from htmlTemplates import css, bot_template, user_template
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from langchain.llms import HuggingFaceHub
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from langchain.callbacks import get_openai_callback
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def get_pdf_text(pdf_docs):
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text = ""
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@@ -33,7 +33,8 @@ def get_text_chunks(text):
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def get_vectorstore(text_chunks):
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# embeddings = OpenAIEmbeddings()
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embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
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vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
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return vectorstore
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from dotenv import load_dotenv
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from PyPDF2 import PdfReader
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.embeddings import HuggingFaceEmbeddings
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from langchain.vectorstores import FAISS
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# from langchain.chat_models import ChatOpenAI
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from langchain.memory import ConversationBufferMemory
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from langchain.chains import ConversationalRetrievalChain
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from htmlTemplates import css, bot_template, user_template
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from langchain.llms import HuggingFaceHub
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# from langchain.callbacks import get_openai_callback
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def get_pdf_text(pdf_docs):
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text = ""
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def get_vectorstore(text_chunks):
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# embeddings = OpenAIEmbeddings()
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# embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
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embeddings = HuggingFaceEmbeddings()
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vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
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return vectorstore
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