sdk/python/foundation-models/nvidia-nim-llama3-8b/aiinference.ipynb (89 lines of code) (raw):

{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Use AI Inference SDK with Meta Llama 3.1 - 8b Instruct NIM in Azure AI Foundry and Azure ML\n", "\n", "This demo notebook shows how to consume Meta-llama-3.1-8B NIM deployments in Azure AI Foundry and Azure AML using AI Inference SDK with Meta Llama 3 NIM " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Prerequisites\n", "\n", "Before we start, there are certain steps we need to take to deploy the models:\n", "\n", "* Register for a valid Azure account with subscription \n", "* Make sure you have access to [Azure AI Studio](https://learn.microsoft.com/en-us/azure/ai-studio/what-is-ai-studio?tabs=home)\n", "* Create a project and resource group\n", "* Select Nvidia NIM: Meta Llama 3.1 -8b Instruct NIM models from Model catalog\n", "\n", "![nim-models.png](nim-models.png)\n", "\n", "Once deployed successfully, you should be assigned for an API endpoint and a security key for inference. \n", "\n", "\n", "Install the package azure-ai-inference using your package manager, like pip:\n", "\n", "```\n", "pip install azure-ai-inference\n", "```" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import os\n", "from azure.ai.inference import ChatCompletionsClient\n", "from azure.core.credentials import AzureKeyCredential\n", "from azure.ai.inference.models import SystemMessage, UserMessage\n", "\n", "endpoint = \"https://<endpoint>.<region>.inference.ml.azure.com/v1\"\n", "key = os.getenv(\"AZURE_AI_CHAT_KEY\", \"keyhere\")\n", "\n", "client = ChatCompletionsClient(\n", " endpoint=endpoint,\n", " credential=AzureKeyCredential(key),\n", " # model=model\n", ")\n", "\n", "response = client.complete(\n", " messages=[\n", " SystemMessage(\"You are a helpful assistant.\"),\n", " UserMessage(\"Can you write me a song?\"),\n", " ],\n", ")\n", "\n", "print(response.choices[0].message.content)" ] } ], "metadata": { "kernelspec": { "display_name": "dev", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.16" } }, "nbformat": 4, "nbformat_minor": 2 }