Update app.py

app.py

@@ -119,8 +119,14 @@ embeddings = embedding_model.encode(texts).tolist()  # Convert numpy arrays to l
 
 # Create a Chroma vector store and add documents and their embeddings
 vectorstore = Chroma(persist_directory="./data")
-for i, (text, embedding) in enumerate(zip(texts, embeddings)):
-    vectorstore.add_texts([text], metadatas=[{"id": i}], embeddings=[embedding])
+vectorstore.add_texts(texts)
+for i, embedding in enumerate(embeddings):
+    vectorstore._collection.upsert(
+        ids=[str(i)],
+        embeddings=[embedding],
+        metadatas=[{"id": i}],
+        documents=[texts[i]]
+    )
 vectorstore.persist()
 
 # Load the Hugging Face model for text generation
@@ -180,3 +186,4 @@ demo.launch(debug=True)
 
 
 
+