Update app.py

app.py

@@ -89,6 +89,7 @@ from langchain.vectorstores import Chroma
 import gradio as gr
 from transformers import pipeline
 from sentence_transformers import SentenceTransformer
+from langchain.embeddings.openai import OpenAIEmbeddings
 
 __import__('pysqlite3')
 sys.modules['sqlite3'] = sys.modules.pop('pysqlite3')
@@ -118,7 +119,7 @@ texts = [doc.page_content for doc in docs]
 embeddings = embedding_model.encode(texts).tolist()  # Convert numpy arrays to lists
 
 # Create a Chroma vector store and add documents and their embeddings
-vectorstore = Chroma(persist_directory="./db")
+vectorstore = Chroma(persist_directory="./db",embedding_function=OpenAIEmbeddings())
 vectorstore.add_texts(texts=texts, metadatas=[{"id": i} for i in range(len(texts))], embeddings=embeddings)
 vectorstore.persist()