python/notebooks/00-getting-started.ipynb

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  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Setup\n",
    "\n",
    "**Step 1**: Import Semantic Kernel SDK from pypi.org"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!python -m pip install semantic-kernel==0.5.1.dev0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import semantic_kernel as sk\n",
    "\n",
    "kernel = sk.Kernel()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Configure the service you'd like to use via the `Service` Enum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from services import Service\n",
    "\n",
    "# Select a service to use for this notebook (available services: OpenAI, AzureOpenAI, HuggingFace)\n",
    "selectedService = Service.OpenAI"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Option 1: using OpenAI\n",
    "\n",
    "**Step 2**: Add your [OpenAI Key](https://openai.com/product/) key to a `.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",
    "\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",
    "**Step 2**: Add your [Azure Open AI Service key](https://learn.microsoft.com/azure/cognitive-services/openai/quickstart?pivots=programming-language-studio) settings to a `.env` file in the same folder:\n",
    "\n",
    "```\n",
    "AZURE_OPENAI_API_KEY=\"...\"\n",
    "AZURE_OPENAI_ENDPOINT=\"https://...\"\n",
    "AZURE_OPENAI_DEPLOYMENT_NAME=\"...\"\n",
    "```\n",
    "\n",
    "Use \"keyword arguments\" to instantiate an Azure OpenAI Chat Completion service and add it to the kernel:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "service_id = None\n",
    "if selectedService == Service.OpenAI:\n",
    "    from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion\n",
    "\n",
    "    api_key, org_id = sk.openai_settings_from_dot_env()\n",
    "    service_id = \"chat-gpt\"\n",
    "    kernel.add_service(\n",
    "        OpenAIChatCompletion(service_id=service_id, ai_model_id=\"gpt-3.5-turbo-1106\", api_key=api_key, org_id=org_id),\n",
    "    )\n",
    "elif selectedService == Service.AzureOpenAI:\n",
    "    from semantic_kernel.connectors.ai.open_ai import AzureChatCompletion\n",
    "\n",
    "    deployment, api_key, endpoint = sk.azure_openai_settings_from_dot_env()\n",
    "    service_id = \"chat_completion\"\n",
    "    kernel.add_service(\n",
    "        AzureChatCompletion(service_id=service_id, deployment_name=deployment, endpoint=endpoint, api_key=api_key),\n",
    "    )"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run a Semantic Function\n",
    "\n",
    "**Step 3**: Load a Plugin and run a semantic function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    plugin = kernel.import_plugin_from_prompt_directory(service_id, \"../../samples/plugins\", \"FunPlugin\")\n",
    "except ValueError as e:\n",
    "    # Don't fail if we try to add the plug in again\n",
    "    # This is just for the sake of the example\n",
    "    # Once the plugin has been added to the kernel it will fail\n",
    "    # to add it again, if this cell is run multiple times without\n",
    "    # restarting the kernel\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "joke_function = plugin[\"Joke\"]\n",
    "\n",
    "joke = await kernel.invoke(joke_function, sk.KernelArguments(input=\"time travel to dinosaur age\", style=\"super silly\"))\n",
    "print(joke)"
   ]
  }
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