Update app.py

app.py

@@ -14,8 +14,9 @@ with open("brookline_data.txt", "r") as f:
 text_splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20)
 splitted_data = text_splitter.split_text(data)
 embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-mpnet-base-v2')
-retriever = Qdrant.as_retriever(self)
-
+#retriever = Qdrant.as_retriever()
+qdrant_vectorstore = Qdrant(client, embeddings.embed_query, collection_name="my_documents")
+retriever = qdrant_vectorstore.as_retriever() 
 llm = HuggingFaceHub(repo_id="ahmadmac/Trained-T5-large", model_kwargs={"temperature": 0.5, "max_length": 512},huggingfacehub_api_token=hf_token)
 qna = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever)
 prompt_template = """ you are a highly knowledgeable AI assistant. Engage in a conversation with the user. Your main goal is to provide clear and informative answers to the user's questions.