Update app.py

app.py

@@ -1,26 +1,15 @@
 import streamlit as st
 import os
-import langchain
-import langchain_community
-import langchain_openai
-import qdrant_client
 from langchain_community.document_loaders import PyMuPDFLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain_openai import ChatOpenAI
-from langchain_community.vectorstores import Qdrant
+from langchain_openai import OpenAIEmbeddings, ChatOpenAI
+from langchain_qdrant import QdrantVectorStore
 from langchain.prompts import ChatPromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnablePassthrough
 from qdrant_client import QdrantClient
 from qdrant_client.http.models import Distance, VectorParams
 from operator import itemgetter
-from langchain_community.embeddings import HuggingFaceEmbeddings
-
-# Print version information
-print(f"langchain version: {langchain.__version__}")
-print(f"langchain_community version: {langchain_community.__version__}")
-print(f"langchain_openai version: {langchain_openai.__version__}")
-print(f"qdrant_client version: {qdrant_client.__version__}")
 
 # Set up API keys
 os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
@@ -51,14 +40,9 @@ def load_and_process_pdfs(pdf_links):
 def setup_vectorstore():
     LOCATION = ":memory:"
     COLLECTION_NAME = "AI_Ethics_Framework"
-    
-    qdrant_client = QdrantClient(location=LOCATION)
+    VECTOR_SIZE = 1536
 
-    # Create the embeddings
-    embeddings = HuggingFaceEmbeddings(model_name="Technocoloredgeek/midterm-finetuned-embedding")
-    
-    # Get the vector size from the embeddings
-    VECTOR_SIZE = len(embeddings.embed_query("test"))
+    qdrant_client = QdrantClient(location=LOCATION)
 
     # Create the collection
     qdrant_client.create_collection(
@@ -67,10 +51,10 @@ def setup_vectorstore():
     )
 
     # Create the vector store
-    qdrant_vector_store = Qdrant(
+    qdrant_vector_store = QdrantVectorStore(
         client=qdrant_client,
         collection_name=COLLECTION_NAME,
-        embedding_function=embeddings
+        embedding=OpenAIEmbeddings()
     )
 
     # Load and add documents