Technocoloredgeek commited on
Commit
ae89ac0
1 Parent(s): 929b4ed

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +13 -3
app.py CHANGED
@@ -1,9 +1,13 @@
1
  import streamlit as st
2
  import os
 
 
 
 
3
  from langchain_community.document_loaders import PyMuPDFLoader
4
  from langchain.text_splitter import RecursiveCharacterTextSplitter
5
  from langchain_openai import ChatOpenAI
6
- from langchain_qdrant import QdrantVectorStore
7
  from langchain.prompts import ChatPromptTemplate
8
  from langchain_core.output_parsers import StrOutputParser
9
  from langchain_core.runnables import RunnablePassthrough
@@ -12,6 +16,12 @@ from qdrant_client.http.models import Distance, VectorParams
12
  from operator import itemgetter
13
  from langchain_community.embeddings import HuggingFaceEmbeddings
14
 
 
 
 
 
 
 
15
  # Set up API keys
16
  os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
17
 
@@ -57,10 +67,10 @@ def setup_vectorstore():
57
  )
58
 
59
  # Create the vector store
60
- qdrant_vector_store = QdrantVectorStore(
61
  client=qdrant_client,
62
  collection_name=COLLECTION_NAME,
63
- embeddings=embeddings # Changed this line
64
  )
65
 
66
  # Load and add documents
 
1
  import streamlit as st
2
  import os
3
+ import langchain
4
+ import langchain_community
5
+ import langchain_openai
6
+ import qdrant_client
7
  from langchain_community.document_loaders import PyMuPDFLoader
8
  from langchain.text_splitter import RecursiveCharacterTextSplitter
9
  from langchain_openai import ChatOpenAI
10
+ from langchain_community.vectorstores import Qdrant
11
  from langchain.prompts import ChatPromptTemplate
12
  from langchain_core.output_parsers import StrOutputParser
13
  from langchain_core.runnables import RunnablePassthrough
 
16
  from operator import itemgetter
17
  from langchain_community.embeddings import HuggingFaceEmbeddings
18
 
19
+ # Print version information
20
+ print(f"langchain version: {langchain.__version__}")
21
+ print(f"langchain_community version: {langchain_community.__version__}")
22
+ print(f"langchain_openai version: {langchain_openai.__version__}")
23
+ print(f"qdrant_client version: {qdrant_client.__version__}")
24
+
25
  # Set up API keys
26
  os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
27
 
 
67
  )
68
 
69
  # Create the vector store
70
+ qdrant_vector_store = Qdrant(
71
  client=qdrant_client,
72
  collection_name=COLLECTION_NAME,
73
+ embedding_function=embeddings
74
  )
75
 
76
  # Load and add documents