Update notebook metadata for docs (#264)

* update model and add metadate

* move metadata to code cell

* update codeowners

* chore: Run nb-clean

---------

Co-authored-by: kdestin <[email protected]>

Author: sdgilley

.github/CODEOWNERS

@@ -5,4 +5,19 @@
 # Default owner for everything, unless overridden by a more specific rule.
 * @Azure-Samples/azure-ai-samples-maintainers
 
-scenarios/docs @Azure-Samples/azure-ai-samples-maintainers @Azure-Samples/AI-Platform-Docs
+
+#### files referenced in docs (DO NOT EDIT, except for Docs team!!!) ###################
+/scenarios/projects/basic/chat-simple.py @azure-samples/AI-Platform-Docs
+/scenarios/projects/basic/chat-template.py @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/assets/chat_eval_data.jsonl @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/assets/grounded_chat.prompty @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/assets/intent_mapping.prompty @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/assets/products.csv @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/chat_with_products.py @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/config.py @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/create_search_index.py @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/evaluate.py @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/get_product_documents.py @azure-samples/AI-Platform-Docs
+/scenarios/rag/custom-rag-app/requirements.txt @azure-samples/AI-Platform-Docs
+/scenarios/langchain/getting-started-with-langchain-chat-models.ipynb @azure-samples/AI-Platform-Docs
+/scenarios/langchain/getting-started-with-langchain-embeddings.ipynb @azure-samples/AI-Platform-Docs

scenarios/langchain/getting-started-with-langchain-chat-models.ipynb

@@ -26,7 +26,7 @@
     "\n",
     "    1. Create an [Azure subscription](https://azure.microsoft.com).\n",
     "    2. Create an Azure AI hub resource as explained at [How to create and manage an Azure AI Studio hub](https://learn.microsoft.com/en-us/azure/ai-studio/how-to/create-azure-ai-resource).\n",
-    "    3. Deploy one model supporting the [Azure AI model inference API](https://aka.ms/azureai/modelinference). In this example we use a `Mistral-Large-2407` and a `Mistral-Small` deployment. \n",
+    "    3. Deploy one model supporting the [Azure AI model inference API](https://aka.ms/azureai/modelinference). In this example we use a `mistral-medium-2505` and a `Mistral-Small` deployment. \n",
     "\n",
     "        * You can follow the instructions at [Add and configure models to Azure AI model inference service](https://learn.microsoft.com/azure/ai-studio/ai-services/how-to/create-model-deployments)."
    ]
@@ -54,7 +54,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_client"
+   },
    "outputs": [],
    "source": [
     "import os\n",
@@ -63,7 +65,7 @@
     "model = AzureAIChatCompletionsModel(\n",
     "    endpoint=os.environ[\"AZURE_INFERENCE_ENDPOINT\"],\n",
     "    credential=os.environ[\"AZURE_INFERENCE_CREDENTIAL\"],\n",
-    "    model=\"mistral-large-2407\",\n",
+    "    model=\"mistral-medium-2505\",\n",
     ")"
    ]
   },
@@ -84,7 +86,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "human_message"
+   },
    "outputs": [],
    "source": [
     "from langchain_core.messages import HumanMessage, SystemMessage\n",
@@ -181,15 +185,17 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_producer_verifier"
+   },
    "outputs": [],
    "source": [
     "from langchain_azure_ai.chat_models import AzureAIChatCompletionsModel\n",
     "\n",
     "producer = AzureAIChatCompletionsModel(\n",
     "    endpoint=os.environ[\"AZURE_INFERENCE_ENDPOINT\"],\n",
     "    credential=os.environ[\"AZURE_INFERENCE_CREDENTIAL\"],\n",
-    "    model=\"mistral-large-2407\",\n",
+    "    model=\"mistral-medium-2505\",\n",
     ")\n",
     "\n",
     "verifier = AzureAIChatCompletionsModel(\n",
@@ -209,7 +215,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "generate_poem"
+   },
    "outputs": [],
    "source": [
     "from langchain_core.prompts import PromptTemplate\n",
@@ -242,7 +250,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_output_parser"
+   },
    "outputs": [],
    "source": [
     "from langchain_core.output_parsers import StrOutputParser\n",
@@ -260,7 +270,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_chain"
+   },
    "outputs": [],
    "source": [
     "chain = producer_template | producer | parser | verifier_template | verifier | parser"
@@ -276,7 +288,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_multiple_outputs_chain"
+   },
    "outputs": [],
    "source": [
     "generate_poem = producer_template | producer | parser\n",
@@ -286,7 +300,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_chain_with_passthrough"
+   },
    "outputs": [],
    "source": [
     "from langchain_core.runnables import RunnablePassthrough, RunnableParallel\n",
@@ -304,7 +320,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "invoke_chain"
+   },
    "outputs": [],
    "source": [
     "chain.invoke({\"topic\": \"living in a foreign country\"})"
@@ -329,7 +347,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "configure_logging"
+   },
    "outputs": [],
    "source": [
     "import sys\n",
@@ -363,7 +383,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_client_with_logging"
+   },
    "outputs": [],
    "source": [
     "import os\n",
@@ -372,7 +394,7 @@
     "model = AzureAIChatCompletionsModel(\n",
     "    endpoint=os.environ[\"AZURE_INFERENCE_ENDPOINT\"],\n",
     "    credential=os.environ[\"AZURE_INFERENCE_CREDENTIAL\"],\n",
-    "    model=\"mistral-large-2407\",\n",
+    "    model=\"mistral-medium-2505\",\n",
     "    client_kwargs={\"logging_enable\": True},\n",
     ")"
    ]

scenarios/langchain/getting-started-with-langchain-embeddings.ipynb

@@ -54,7 +54,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_embed_model_client"
+   },
    "outputs": [],
    "source": [
     "import os\n",
@@ -84,7 +86,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "create_vector_store"
+   },
    "outputs": [],
    "source": [
     "from langchain_core.vectorstores import InMemoryVectorStore\n",
@@ -102,7 +106,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "add_documents"
+   },
    "outputs": [],
    "source": [
     "from langchain_core.documents import Document\n",
@@ -124,7 +130,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "name": "search_similarity"
+   },
    "outputs": [],
    "source": [
     "results = vector_store.similarity_search(query=\"thud\", k=1)\n",