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Update app.py
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app.py
CHANGED
@@ -1,9 +1,13 @@
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import streamlit as st
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import os
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from langchain_community.document_loaders import PyMuPDFLoader
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_openai import ChatOpenAI
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from
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from langchain.prompts import ChatPromptTemplate
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from langchain_core.output_parsers import StrOutputParser
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from langchain_core.runnables import RunnablePassthrough
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@@ -12,6 +16,12 @@ from qdrant_client.http.models import Distance, VectorParams
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from operator import itemgetter
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from langchain_community.embeddings import HuggingFaceEmbeddings
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# Set up API keys
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os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
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@@ -57,10 +67,10 @@ def setup_vectorstore():
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)
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# Create the vector store
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qdrant_vector_store =
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client=qdrant_client,
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collection_name=COLLECTION_NAME,
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)
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# Load and add documents
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import streamlit as st
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import os
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import langchain
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import langchain_community
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import langchain_openai
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import qdrant_client
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from langchain_community.document_loaders import PyMuPDFLoader
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_openai import ChatOpenAI
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from langchain_community.vectorstores import Qdrant
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from langchain.prompts import ChatPromptTemplate
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from langchain_core.output_parsers import StrOutputParser
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from langchain_core.runnables import RunnablePassthrough
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from operator import itemgetter
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from langchain_community.embeddings import HuggingFaceEmbeddings
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# Print version information
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print(f"langchain version: {langchain.__version__}")
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print(f"langchain_community version: {langchain_community.__version__}")
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print(f"langchain_openai version: {langchain_openai.__version__}")
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print(f"qdrant_client version: {qdrant_client.__version__}")
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# Set up API keys
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os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
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)
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# Create the vector store
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qdrant_vector_store = Qdrant(
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client=qdrant_client,
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collection_name=COLLECTION_NAME,
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embedding_function=embeddings
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)
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# Load and add documents
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