python/samples/getting_started/01-basic-loading-the-kernel.ipynb

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 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic Loading of the Kernel\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To run the notebooks we recommend using Poetry and starting a shell with a virtual environment\n",
    "prepared to use SK.\n",
    "\n",
    "See [DEV_SETUP.md](../../python/DEV_SETUP.md) for more information.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Note: if using a Poetry virtual environment, do not run this cell\n",
    "%pip install semantic-kernel==1.0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from semantic_kernel import Kernel\n",
    "\n",
    "kernel = Kernel()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Configuring API Keys and Endpoints\n",
    "\n",
    "#### Option 1: using OpenAI\n",
    "\n",
    "Add your [OpenAI Key](https://openai.com/product/) key to either your environment variables or to the `.env` file in the same folder (org Id only if you have multiple orgs):\n",
    "\n",
    "```\n",
    "OPENAI_API_KEY=\"sk-...\"\n",
    "OPENAI_ORG_ID=\"\"\n",
    "```\n",
    "The environment variables names should match the names used in the `.env` file, as shown above.\n",
    "\n",
    "If using the `.env` file, please configure the `env_file_path` parameter with a valid path when creating the ChatCompletion class:\n",
    "\n",
    "```\n",
    "chat_completion = OpenAIChatCompletion(service_id=\"test\", env_file_path=<path_to_file>)\n",
    "```\n",
    "\n",
    "Use \"keyword arguments\" to instantiate an OpenAI Chat Completion service and add it to the kernel:\n",
    "\n",
    "#### Option 2: using Azure OpenAI\n",
    "\n",
    "Add your [Azure Open AI Service key](https://learn.microsoft.com/azure/cognitive-services/openai/quickstart?pivots=programming-language-studio) settings to either your system's environment variables or to the `.env` file in the same folder:\n",
    "\n",
    "```\n",
    "AZURE_OPENAI_API_KEY=\"...\"\n",
    "AZURE_OPENAI_ENDPOINT=\"https://...\"\n",
    "AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=\"...\"\n",
    "AZURE_OPENAI_TEXT_DEPLOYMENT_NAME=\"...\"\n",
    "AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME=\"...\"\n",
    "```\n",
    "The environment variables names should match the names used in the `.env` file, as shown above.\n",
    "\n",
    "If using the `.env` file, please configure the `env_file_path` parameter with a valid path when creating the ChatCompletion class:\n",
    "\n",
    "```\n",
    "chat_completion = AzureChatCompletion(service_id=\"test\", env_file_path=<path_to_file>)\n",
    "```\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When using the kernel for AI requests, the kernel needs some settings like URL and credentials to the AI models.\n",
    "\n",
    "The SDK currently supports OpenAI and Azure OpenAI, among other connectors.\n",
    "\n",
    "If you need an Azure OpenAI key, go [here](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/quickstart?pivots=rest-api).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make sure paths are correct for the imports\n",
    "\n",
    "import sys\n",
    "import os\n",
    "\n",
    "notebook_dir = os.path.abspath('')\n",
    "parent_dir = os.path.dirname(notebook_dir)\n",
    "grandparent_dir = os.path.dirname(parent_dir)\n",
    "\n",
    "\n",
    "sys.path.append(grandparent_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from services import Service\n",
    "\n",
    "from samples.service_settings import ServiceSettings\n",
    "\n",
    "service_settings = ServiceSettings()\n",
    "\n",
    "# Select a service to use for this notebook (available services: OpenAI, AzureOpenAI, HuggingFace)\n",
    "selectedService = (\n",
    "    Service.AzureOpenAI\n",
    "    if service_settings.global_llm_service is None\n",
    "    else Service(service_settings.global_llm_service.lower())\n",
    ")\n",
    "print(f\"Using service type: {selectedService}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove all services so that this cell can be re-run without restarting the kernel\n",
    "kernel.remove_all_services()\n",
    "\n",
    "service_id = None\n",
    "if selectedService == Service.OpenAI:\n",
    "    from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion\n",
    "\n",
    "    service_id = \"oai_chat_gpt\"\n",
    "    kernel.add_service(\n",
    "        OpenAIChatCompletion(service_id=service_id, ai_model_id=\"gpt-3.5-turbo\"),\n",
    "    )\n",
    "elif selectedService == Service.AzureOpenAI:\n",
    "    from semantic_kernel.connectors.ai.open_ai import AzureChatCompletion\n",
    "\n",
    "    service_id = \"aoai_chat_completion\"\n",
    "    kernel.add_service(\n",
    "        AzureChatCompletion(service_id=service_id),\n",
    "    )"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great, now that you're familiar with setting up the Semantic Kernel, let's see [how we can use it to run prompts](02-running-prompts-from-file.ipynb).\n"
   ]
  }
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