Refreshed notebooks, particularly with new Week 1

week5/day4.ipynb

@@ -313,7 +313,7 @@
     "# the retriever is an abstraction over the VectorStore that will be used during RAG\n",
     "retriever = vectorstore.as_retriever()\n",
     "\n",
-    "# putting it together: set up the conversation chain with the GPT 3.5 LLM, the vector store and memory\n",
+    "# putting it together: set up the conversation chain with the GPT 4o-mini LLM, the vector store and memory\n",
     "conversation_chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=retriever, memory=memory)"
    ]
   },
@@ -329,6 +329,20 @@
     "print(result[\"answer\"])"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e6eb99fb-33ec-4025-ab92-b634ede03647",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# set up a new conversation memory for the chat\n",
+    "memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)\n",
+    "\n",
+    "# putting it together: set up the conversation chain with the GPT 4o-mini LLM, the vector store and memory\n",
+    "conversation_chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=retriever, memory=memory)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "bbbcb659-13ce-47ab-8a5e-01b930494964",
@@ -346,7 +360,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Wrapping that in a function\n",
+    "# Wrapping in a function - note that history isn't used, as the memory is in the conversation_chain\n",
     "\n",
     "def chat(message, history):\n",
     "    result = conversation_chain.invoke({\"question\": message})\n",
@@ -362,7 +376,7 @@
    "source": [
     "# And in Gradio:\n",
     "\n",
-    "view = gr.ChatInterface(chat).launch()"
+    "view = gr.ChatInterface(chat, type=\"messages\").launch(inbrowser=True)"
    ]
   },
   {