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docs: update Azure OpenAI to v1 and langchain API to 0.1 (#18005)

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**Description:** Updated Azure OpenAI docs to OpenAI API v1 and LLM
invocation to langchain 0.1
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Massimiliano Pronesti 2024-03-01 22:47:00 +01:00 committed by GitHub
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57
docs/docs/integrations/llms/azure_openai.ipynb
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@ -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=<your Azure OpenAI API key>\n",
"export AZURE_OPENAI_API_KEY=<your 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"
]
}
],