Update app.py

app.py

@@ -9,6 +9,10 @@ from langchain.vectorstores import Chroma
 from langchain.llms import HuggingFacePipeline
 from langchain.chains import RetrievalQA
 from constants import CHROMA_SETTINGS
+import chromadb
+from chromadb.utils import embedding_functions
+
+
 
 #model and tokenizer loading
 checkpoint = "LaMini-T5-738M"
@@ -32,8 +36,10 @@ def llm_pipeline():
 @st.cache_resource
 def qa_llm():
     llm = llm_pipeline()
-    embeddings = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")
-    db = Chroma(persist_directory="db", embedding_function=embeddings, client_settings=CHROMA_SETTINGS)
+    embeddings = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="all-MiniLM-L6-v2")
+    client = chromadb.PersistentClient(path="/db")
+    clientsetting = chromadb.Client(CHROMA_SETTINGS)
+    db = Chroma(persist_directory=client, embedding_function=embeddings, client_settings=clientsetting)
     retriever = db.as_retriever()
     qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=True)
     return qa