Update app.py

app.py

@@ -22,12 +22,12 @@ hf = HuggingFaceEmbeddings(model_name=emb)
 # Load the document, split it into chunks, embed each chunk and load it into the vector store.
 #raw_documents = TextLoader('state_of_the_union.txt').load()
 def embed_fn(inp):
-    db=Chroma(persist_directory=f"{cwd}/chroma_langchain_db")
+    db=Chroma()
     text_splitter = CharacterTextSplitter(chunk_size=200, chunk_overlap=10)
     documents = text_splitter.split_text(inp)
     out_emb= hf.embed_documents(documents)
     string_representation = dumps(out_emb, pretty=True)
-    db.from_texts(documents,embedding_function=HuggingFaceEmbeddings(model_name=emb))
+    db.from_texts(documents,embedding_function=HuggingFaceEmbeddings(model_name=emb),persist_directory=f"{cwd}/chroma_langchain_db")
     
 def proc_doc(doc_in):
     for doc in doc_in: