Swicthed to use all_products as the sample vector store for the streamlit app

config/architectures.json

@@ -15,7 +15,7 @@
       "description": "An architecture which uses a raw baseline LLM for its core, but augments requests from the user with information which has been retrieved from a knowledge store where the organisational knowledge has previously been stored for this purpose.",
       "steps": [
         {"class":  "InputRequestScreener"},
-        {"class":  "RetrievalAugmentor", "params": {"vector_store": "products_tvs"}},
+        {"class":  "RetrievalAugmentor", "params": {"vector_store": "01_all_products"}},
         {"class":  "HFLlamaHttpRequestor", "params":  {"model":  "meta-llama/Llama-2-7b-chat-hf", "system_prompt": "You are a helpful domestic appliance advisor. Please answer the following customer question, answering only from the facts provided. Do not make things up, and say if you cannot answer.", "max_tokens": 2000}},
         {"class":  "OutputResponseScreener"}
       ],