diff --git a/docs/docs/integrations/llms/azure_openai.ipynb b/docs/docs/integrations/llms/azure_openai.ipynb index 91abdcf3fe..98c8ac1835 100644 --- a/docs/docs/integrations/llms/azure_openai.ipynb +++ b/docs/docs/integrations/llms/azure_openai.ipynb @@ -15,21 +15,19 @@ "You can configure the `openai` package to use Azure OpenAI using environment variables. The following is for `bash`:\n", "\n", "```bash\n", - "# Set this to `azure`\n", - "export OPENAI_API_TYPE=azure\n", - "# The API version you want to use: set this to `2023-05-15` for the released version.\n", - "export OPENAI_API_VERSION=2023-05-15\n", + "# The API version you want to use: set this to `2023-12-01-preview` for the released version.\n", + "export OPENAI_API_VERSION=2023-12-01-preview\n", "# The base URL for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource.\n", - "export OPENAI_API_BASE=https://your-resource-name.openai.azure.com\n", + "export AZURE_OPENAI_ENDPOINT=https://your-resource-name.openai.azure.com\n", "# The API key for your Azure OpenAI resource. You can find this in the Azure portal under your Azure OpenAI resource.\n", - "export OPENAI_API_KEY=\n", + "export AZURE_OPENAI_API_KEY=\n", "```\n", "\n", "Alternatively, you can configure the API right within your running Python environment:\n", "\n", "```python\n", "import os\n", - "os.environ[\"OPENAI_API_TYPE\"] = \"azure\"\n", + "os.environ[\"OPENAI_API_VERSION\"] = \"2023-12-01-preview\"\n", "```\n", "\n", "## Azure Active Directory Authentication\n", @@ -76,15 +74,18 @@ "\n", "_**Note**: These docs are for the Azure text completion models. Models like GPT-4 are chat models. They have a slightly different interface, and can be accessed via the `AzureChatOpenAI` class. For docs on Azure chat see [Azure Chat OpenAI documentation](/docs/integrations/chat/azure_chat_openai)._\n", "\n", - "Let's say your deployment name is `text-davinci-002-prod`. In the `openai` Python API, you can specify this deployment with the `engine` parameter. For example:\n", + "Let's say your deployment name is `gpt-35-turbo-instruct-prod`. In the `openai` Python API, you can specify this deployment with the `engine` parameter. For example:\n", "\n", "```python\n", "import openai\n", "\n", - "response = openai.Completion.create(\n", - " engine=\"text-davinci-002-prod\",\n", - " prompt=\"This is a test\",\n", - " max_tokens=5\n", + "client = AzureOpenAI(\n", + " api_version=\"2023-12-01-preview\",\n", + ")\n", + "\n", + "response = client.completions.create(\n", + " model=\"gpt-35-turbo-instruct-prod\",\n", + " prompt=\"Test prompt\"\n", ")\n", "```\n" ] @@ -103,22 +104,21 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "id": "faacfa54", "metadata": {}, "outputs": [], "source": [ "import os\n", "\n", - "os.environ[\"OPENAI_API_TYPE\"] = \"azure\"\n", - "os.environ[\"OPENAI_API_VERSION\"] = \"2023-05-15\"\n", - "os.environ[\"OPENAI_API_BASE\"] = \"...\"\n", - "os.environ[\"OPENAI_API_KEY\"] = \"...\"" + "os.environ[\"OPENAI_API_VERSION\"] = \"2023-12-01-preview\"\n", + "os.environ[\"AZURE_OPENAI_ENDPOINT\"] = \"...\"\n", + "os.environ[\"AZURE_OPENAI_API_KEY\"] = \"...\"" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "id": "8fad2a6e", "metadata": {}, "outputs": [], @@ -129,7 +129,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "id": "8c80213a", "metadata": {}, "outputs": [], @@ -137,31 +137,28 @@ "# Create an instance of Azure OpenAI\n", "# Replace the deployment name with your own\n", "llm = AzureOpenAI(\n", - " deployment_name=\"td2\",\n", - " model_name=\"gpt-3.5-turbo-instruct\",\n", + " deployment_name=\"gpt-35-turbo-instruct-0914\",\n", ")" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "592dc404", "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "\"\\n\\nWhy couldn't the bicycle stand up by itself? Because it was...two tired!\"" - ] + "text/plain": "\" Why couldn't the bicycle stand up by itself?\\n\\nBecause it was two-tired!\"" }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Run the LLM\n", - "llm(\"Tell me a joke\")" + "llm.invoke(\"Tell me a joke\")" ] }, { @@ -174,7 +171,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "9c33fa19", "metadata": {}, "outputs": [ @@ -182,8 +179,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[1mAzureOpenAI\u001b[0m\n", - "Params: {'deployment_name': 'text-davinci-002', 'model_name': 'text-davinci-002', 'temperature': 0.7, 'max_tokens': 256, 'top_p': 1, 'frequency_penalty': 0, 'presence_penalty': 0, 'n': 1, 'best_of': 1}\n" + "\u001B[1mAzureOpenAI\u001B[0m\n", + "Params: {'deployment_name': 'gpt-35-turbo-instruct-0914', 'model_name': 'gpt-3.5-turbo-instruct', 'temperature': 0.7, 'top_p': 1, 'frequency_penalty': 0, 'presence_penalty': 0, 'n': 1, 'logit_bias': {}, 'max_tokens': 256}\n" ] } ],