mirror of
https://github.com/openai/openai-cookbook
synced 2024-11-11 13:11:02 +00:00
[azure] add functions notebook sample (#595)
* add azure functions notebook sample * update api key to use env var + note use of env vars over config in code across azure samples
This commit is contained in:
Krista Pratico
GitHub
parent
b5ea5f3b0e
commit
5e050080ab
@ -41,6 +41,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"import openai"
|
||||
]
|
||||
},
|
||||
@ -105,7 +106,22 @@
|
||||
"source": [
|
||||
"if not use_azure_active_directory:\n",
|
||||
" openai.api_type = 'azure'\n",
|
||||
" openai.api_key = '' # Add your api key here"
|
||||
" openai.api_key = os.environ[\"OPENAI_API_KEY\"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"> Note: In this example, we configured the library to use the Azure API by setting the variables in code. For development, consider setting the environment variables instead:\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
"OPENAI_API_BASE\n",
|
||||
"OPENAI_API_KEY\n",
|
||||
"OPENAI_API_TYPE\n",
|
||||
"OPENAI_API_VERSION\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -16,6 +16,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"import openai"
|
||||
]
|
||||
},
|
||||
@ -62,7 +63,22 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"openai.api_type = 'azure'\n",
|
||||
"openai.api_key = '' # Please add your api key here\n"
|
||||
"openai.api_key = os.environ[\"OPENAI_API_KEY\"]\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"> Note: In this example, we configured the library to use the Azure API by setting the variables in code. For development, consider setting the environment variables instead:\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
"OPENAI_API_BASE\n",
|
||||
"OPENAI_API_KEY\n",
|
||||
"OPENAI_API_TYPE\n",
|
||||
"OPENAI_API_VERSION\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -16,6 +16,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"import openai"
|
||||
]
|
||||
},
|
||||
@ -62,7 +63,22 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"openai.api_type = 'azure'\n",
|
||||
"openai.api_key = '' # Please add your api key here"
|
||||
"openai.api_key = os.environ[\"OPENAI_API_KEY\"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"> Note: In this example, we configured the library to use the Azure API by setting the variables in code. For development, consider setting the environment variables instead:\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
"OPENAI_API_BASE\n",
|
||||
"OPENAI_API_KEY\n",
|
||||
"OPENAI_API_TYPE\n",
|
||||
"OPENAI_API_VERSION\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -16,6 +16,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"import openai"
|
||||
]
|
||||
},
|
||||
@ -62,7 +63,22 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"openai.api_type = 'azure'\n",
|
||||
"openai.api_key = '' # Please add your api key here"
|
||||
"openai.api_key = os.environ[\"OPENAI_API_KEY\"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"> Note: In this example, we configured the library to use the Azure API by setting the variables in code. For development, consider setting the environment variables instead:\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
"OPENAI_API_BASE\n",
|
||||
"OPENAI_API_KEY\n",
|
||||
"OPENAI_API_TYPE\n",
|
||||
"OPENAI_API_VERSION\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
447
examples/azure/functions.ipynb
Normal file
447
examples/azure/functions.ipynb
Normal file
@ -0,0 +1,447 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Azure functions example\n",
|
||||
"\n",
|
||||
"This notebook shows how to use the function calling capability with the Azure OpenAI service. Functions allow a caller of chat completions to define capabilities that the model can use to extend its\n",
|
||||
"functionality into external tools and data sources.\n",
|
||||
"\n",
|
||||
"You can read more about chat functions on OpenAI's blog: https://openai.com/blog/function-calling-and-other-api-updates\n",
|
||||
"\n",
|
||||
"**NOTE**: Chat functions require model versions beginning with gpt-4 and gpt-35-turbo's `-0613` labels. They are not supported by older versions of the models."
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Setup\n",
|
||||
"\n",
|
||||
"First, we install the necessary dependencies."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"! pip install openai\n",
|
||||
"# (Optional) If you want to use Microsoft Active Directory\n",
|
||||
"! pip install azure-identity"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"import openai"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"\n",
|
||||
"Additionally, to properly access the Azure OpenAI Service, we need to create the proper resources at the [Azure Portal](https://portal.azure.com) (you can check a detailed guide on how to do this in the [Microsoft Docs](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/how-to/create-resource?pivots=web-portal))\n",
|
||||
"\n",
|
||||
"Once the resource is created, the first thing we need to use is its endpoint. You can get the endpoint by looking at the *\"Keys and Endpoints\"* section under the *\"Resource Management\"* section. Having this, we will set up the SDK using this information:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 27,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"openai.api_base = \"\" # Add your endpoint here\n",
|
||||
"\n",
|
||||
"# functions is only supported by the 2023-07-01-preview API version\n",
|
||||
"openai.api_version = \"2023-07-01-preview\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Authentication\n",
|
||||
"\n",
|
||||
"The Azure OpenAI service supports multiple authentication mechanisms that include API keys and Azure credentials."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"use_azure_active_directory = False"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"\n",
|
||||
"#### Authentication using API key\n",
|
||||
"\n",
|
||||
"To set up the OpenAI SDK to use an *Azure API Key*, we need to set up the `api_type` to `azure` and set `api_key` to a key associated with your endpoint (you can find this key in *\"Keys and Endpoints\"* under *\"Resource Management\"* in the [Azure Portal](https://portal.azure.com))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if not use_azure_active_directory:\n",
|
||||
" openai.api_type = \"azure\"\n",
|
||||
" openai.api_key = os.environ[\"OPENAI_API_KEY\"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"> Note: In this example, we configured the library to use the Azure API by setting the variables in code. For development, consider setting the environment variables instead:\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
"OPENAI_API_BASE\n",
|
||||
"OPENAI_API_KEY\n",
|
||||
"OPENAI_API_TYPE\n",
|
||||
"OPENAI_API_VERSION\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### Authentication using Microsoft Active Directory\n",
|
||||
"Let's now see how we can get a key via Microsoft Active Directory Authentication."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from azure.identity import DefaultAzureCredential\n",
|
||||
"\n",
|
||||
"if use_azure_active_directory:\n",
|
||||
" default_credential = DefaultAzureCredential()\n",
|
||||
" token = default_credential.get_token(\"https://cognitiveservices.azure.com/.default\")\n",
|
||||
"\n",
|
||||
" openai.api_type = \"azure_ad\"\n",
|
||||
" openai.api_key = token.token"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"A token is valid for a period of time, after which it will expire. To ensure a valid token is sent with every request, you can refresh an expiring token by hooking into requests.auth:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import typing\n",
|
||||
"import time\n",
|
||||
"import requests\n",
|
||||
"\n",
|
||||
"if typing.TYPE_CHECKING:\n",
|
||||
" from azure.core.credentials import TokenCredential\n",
|
||||
"\n",
|
||||
"class TokenRefresh(requests.auth.AuthBase):\n",
|
||||
"\n",
|
||||
" def __init__(self, credential: \"TokenCredential\", scopes: typing.List[str]) -> None:\n",
|
||||
" self.credential = credential\n",
|
||||
" self.scopes = scopes\n",
|
||||
" self.cached_token: typing.Optional[str] = None\n",
|
||||
"\n",
|
||||
" def __call__(self, req):\n",
|
||||
" if not self.cached_token or self.cached_token.expires_on - time.time() < 300:\n",
|
||||
" self.cached_token = self.credential.get_token(*self.scopes)\n",
|
||||
" req.headers[\"Authorization\"] = f\"Bearer {self.cached_token.token}\"\n",
|
||||
" return req\n",
|
||||
"\n",
|
||||
"if use_azure_active_directory:\n",
|
||||
" session = requests.Session()\n",
|
||||
" session.auth = TokenRefresh(default_credential, [\"https://cognitiveservices.azure.com/.default\"])\n",
|
||||
"\n",
|
||||
" openai.requestssession = session"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Functions\n",
|
||||
"\n",
|
||||
"With setup and authentication complete, you can now use functions with the Azure OpenAI service. This will be split into a few steps:\n",
|
||||
"\n",
|
||||
"1. Define the function(s)\n",
|
||||
"2. Pass function definition(s) into chat completions API\n",
|
||||
"3. Call function with arguments from the response\n",
|
||||
"4. Feed function response back into chat completions API"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 1. Define the function(s)\n",
|
||||
"\n",
|
||||
"A list of functions can be defined, each containing the name of the function, an optional description, and the parameters the function accepts (described as a JSON schema)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 21,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"functions = [\n",
|
||||
" {\n",
|
||||
" \"name\": \"get_current_weather\",\n",
|
||||
" \"description\": \"Get the current weather\",\n",
|
||||
" \"parameters\": {\n",
|
||||
" \"type\": \"object\",\n",
|
||||
" \"properties\": {\n",
|
||||
" \"location\": {\n",
|
||||
" \"type\": \"string\",\n",
|
||||
" \"description\": \"The city and state, e.g. San Francisco, CA\",\n",
|
||||
" },\n",
|
||||
" \"format\": {\n",
|
||||
" \"type\": \"string\",\n",
|
||||
" \"enum\": [\"celsius\", \"fahrenheit\"],\n",
|
||||
" \"description\": \"The temperature unit to use. Infer this from the users location.\",\n",
|
||||
" },\n",
|
||||
" },\n",
|
||||
" \"required\": [\"location\"],\n",
|
||||
" },\n",
|
||||
" }\n",
|
||||
"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 2. Pass function definition(s) into chat completions API\n",
|
||||
"\n",
|
||||
"Now we can pass the function into the chat completions API. If the model determines it should call the function, a `finish_reason` of \"function_call\" will be populated on the choice and the details of which function to call and its arguments will be present in the `message`. Optionally, you can set the `function_call` keyword argument to force the model to call a particular function (e.g. `function_call={\"name\": get_current_weather}`). By default, this is set to `auto`, allowing the model to choose whether to call the function or not. "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 22,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{\n",
|
||||
" \"choices\": [\n",
|
||||
" {\n",
|
||||
" \"content_filter_results\": {},\n",
|
||||
" \"finish_reason\": \"function_call\",\n",
|
||||
" \"index\": 0,\n",
|
||||
" \"message\": {\n",
|
||||
" \"function_call\": {\n",
|
||||
" \"arguments\": \"{\\n \\\"location\\\": \\\"Seattle, WA\\\"\\n}\",\n",
|
||||
" \"name\": \"get_current_weather\"\n",
|
||||
" },\n",
|
||||
" \"role\": \"assistant\"\n",
|
||||
" }\n",
|
||||
" }\n",
|
||||
" ],\n",
|
||||
" \"created\": 1689702512,\n",
|
||||
" \"id\": \"chatcmpl-7dj6GkYdM7Vw9eGn02bc2qqjN70Ps\",\n",
|
||||
" \"model\": \"gpt-4\",\n",
|
||||
" \"object\": \"chat.completion\",\n",
|
||||
" \"prompt_annotations\": [\n",
|
||||
" {\n",
|
||||
" \"content_filter_results\": {\n",
|
||||
" \"hate\": {\n",
|
||||
" \"filtered\": false,\n",
|
||||
" \"severity\": \"safe\"\n",
|
||||
" },\n",
|
||||
" \"self_harm\": {\n",
|
||||
" \"filtered\": false,\n",
|
||||
" \"severity\": \"safe\"\n",
|
||||
" },\n",
|
||||
" \"sexual\": {\n",
|
||||
" \"filtered\": false,\n",
|
||||
" \"severity\": \"safe\"\n",
|
||||
" },\n",
|
||||
" \"violence\": {\n",
|
||||
" \"filtered\": false,\n",
|
||||
" \"severity\": \"safe\"\n",
|
||||
" }\n",
|
||||
" },\n",
|
||||
" \"prompt_index\": 0\n",
|
||||
" }\n",
|
||||
" ],\n",
|
||||
" \"usage\": {\n",
|
||||
" \"completion_tokens\": 18,\n",
|
||||
" \"prompt_tokens\": 115,\n",
|
||||
" \"total_tokens\": 133\n",
|
||||
" }\n",
|
||||
"}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"messages = [\n",
|
||||
" {\"role\": \"system\", \"content\": \"Don't make assumptions about what values to plug into functions. Ask for clarification if a user request is ambiguous.\"},\n",
|
||||
" {\"role\": \"user\", \"content\": \"What's the weather like today in Seattle?\"}\n",
|
||||
"]\n",
|
||||
"\n",
|
||||
"chat_completion = openai.ChatCompletion.create(\n",
|
||||
" deployment_id=\"gpt-35-turbo-0613\",\n",
|
||||
" messages=messages,\n",
|
||||
" functions=functions,\n",
|
||||
")\n",
|
||||
"print(chat_completion)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 3. Call function with arguments from the response\n",
|
||||
"\n",
|
||||
"The name of the function call will be one that was provided initially and the arguments will include JSON matching the schema included in the function definition."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 23,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"get_current_weather\n",
|
||||
"{\n",
|
||||
" \"location\": \"Seattle, WA\"\n",
|
||||
"}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import json\n",
|
||||
"\n",
|
||||
"def get_current_weather(request):\n",
|
||||
" \"\"\"\n",
|
||||
" This function is for illustrative purposes.\n",
|
||||
" The location and unit should be used to determine weather\n",
|
||||
" instead of returning a hardcoded response.\n",
|
||||
" \"\"\"\n",
|
||||
" location = request.get(\"location\")\n",
|
||||
" unit = request.get(\"unit\")\n",
|
||||
" return {\"temperature\": \"22\", \"unit\": \"celsius\", \"description\": \"Sunny\"}\n",
|
||||
"\n",
|
||||
"function_call = chat_completion.choices[0].message.function_call\n",
|
||||
"print(function_call.name)\n",
|
||||
"print(function_call.arguments)\n",
|
||||
"\n",
|
||||
"if function_call.name == \"get_current_weather\":\n",
|
||||
" response = get_current_weather(json.loads(function_call.arguments))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 4. Feed function response back into chat completions API\n",
|
||||
"\n",
|
||||
"The response from the function should be serialized into a new message with the role set to \"function\". Now the model will use the response data to formulate its answer."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 24,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Today in Seattle, the weather is sunny with a temperature of 22 degrees celsius.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"messages.append(\n",
|
||||
" {\n",
|
||||
" \"role\": \"function\",\n",
|
||||
" \"name\": \"get_current_weather\",\n",
|
||||
" \"content\": json.dumps(response)\n",
|
||||
" }\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"function_completion = openai.ChatCompletion.create(\n",
|
||||
" deployment_id=\"gpt-35-turbo-0613\",\n",
|
||||
" messages=messages,\n",
|
||||
" functions=functions,\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"print(function_completion.choices[0].message.content.strip())"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"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": "3.10.0"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "3a5103089ab7e7c666b279eeded403fcec76de49a40685dbdfe9f9c78ad97c17"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user