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autogen/website/docs/topics/non-openai-models/cloud-anthropic.ipynb
HRUSHIKESH DOKALA 32fa709e13
Anthropic Client (#2931) 
* intial setup for the anthropic client with cost config

* update: other methods added

* fix: formatting

* fix: config unused

* update: changes made in the client

* update: test added to the workflow

* update: added tests to the anthropic client

* fix: errors in workflows and client

* fix

* fix: anthropic tools type

* update: notebook anthropic

* Nonetype fixed

* fix-tests config

* update: tests and client issues

* logger support

* remove sys path

* updated the functioning of the client

* update: type hints and stream

* skip tests- importerror

* fix: anthropic client and tests

* none fix

* Alternating roles, parameter keywords, cost on response,

* update: anthropic notebook

* update: notebook with more details

* devcontainer

* update: added validate_params from the client_utils

* fix: formatting

* fix: minor comment

---------

Co-authored-by: Mark Sze <mark@sze.family>
2024-06-19 06:15:12 +00:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"# Anthropic Claude\n",
"\n",
"In the v0.2.30 release of AutoGen we support Anthropic Client.\n",
"\n",
"Claude is a family of large language models developed by Anthropic and designed to revolutionize the way you interact with AI. Claude excels at a wide variety of tasks involving language, reasoning, analysis, coding, and more. The models are highly capable, easy to use, and can be customized to suit your needs.\n",
"\n",
"In this notebook, we demonstrate how to use Anthropic Claude model for AgentChat in AutoGen.\n",
"\n",
"## Features\n",
"\n",
"Additionally, this client class provides support for function/tool calling and will track token usage and cost correctly as per Anthropic's API costs (as of June 2024).\n",
"\n",
"## Requirements\n",
"To use Anthropic Claude with AutoGen, first you need to install the `pyautogen[\"anthropic]` package.\n",
"\n",
"To try out the function call feature of Claude model, you need to install `anthropic>=0.23.1`.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# !pip install pyautogen\n",
"!pip install pyautogen[\"anthropic\"]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set the config for the Anthropic API\n",
"\n",
"You can add any parameters that are needed for the custom model loading in the same configuration list.\n",
"\n",
"It is important to add the `api_type` field and set it to a string that corresponds to the client type used: `anthropic`.\n",
"\n",
"Example:\n",
"```\n",
"[\n",
" {\n",
" \"model\": \"claude-3-sonnet-20240229\",\n",
" \"api_key\": \"your Anthropic API Key goes here\",\n",
" \"api_type\": \"anthropic\",\n",
" \"temperature\": 0.5,\n",
" \"top_p\": 0.2, # Note: It is recommended to set temperature or top_p but not both.\n",
" \"max_tokens\": 10000,\n",
" },\n",
" {\n",
" \"model\":\"claude-3-opus-20240229\",\n",
" \"api_key\":\"your api key\",\n",
" \"api_type\":\"anthropic\",\n",
" },\n",
" {\n",
" \"model\":\"claude-2.0\",\n",
" \"api_key\":\"your api key\",\n",
" \"api_type\":\"anthropic\",\n",
" },\n",
" {\n",
" \"model\":\"claude-2.1\",\n",
" \"api_key\":\"your api key\",\n",
" \"api_type\":\"anthropic\",\n",
" },\n",
" {\n",
" \"model\":\"claude-3.0-haiku\",\n",
" \"api_key\":\"your api key\",\n",
" \"api_type\":\"anthropic\",\n",
" },\n",
"]\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Alternative\n",
"\n",
"As an alternative to the api_key key and value in the config, you can set the environment variable `ANTHROPIC_API_KEY` to your Anthropic API key.\n",
"\n",
"Linux/Mac:\n",
"```\n",
"export ANTHROPIC_API_KEY=\"your Anthropic API key here\"\n",
"```\n",
"Windows:\n",
"```\n",
"set ANTHROPIC_API_KEY=your_anthropic_api_key_here\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"from typing_extensions import Annotated\n",
"\n",
"import autogen\n",
"\n",
"config_list_claude = [\n",
" {\n",
" # Choose your model name.\n",
" \"model\": \"claude-3-sonnet-20240229\",\n",
" # You need to provide your API key here.\n",
" \"api_key\": os.getenv(\"ANTHROPIC_API_KEY\"),\n",
" \"api_type\": \"anthropic\",\n",
" }\n",
"]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Coding Example with Two Agent"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Construct Agents\n",
"\n",
"Construct a simple conversation between a User proxy and an ConversableAgent based on Claude-3 model.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"assistant = autogen.AssistantAgent(\n",
" \"assistant\",\n",
" llm_config={\n",
" \"config_list\": config_list_claude,\n",
" },\n",
")\n",
"\n",
"user_proxy = autogen.UserProxyAgent(\n",
" \"user_proxy\",\n",
" human_input_mode=\"NEVER\",\n",
" code_execution_config={\n",
" \"work_dir\": \"coding\",\n",
" \"use_docker\": False,\n",
" },\n",
" is_termination_msg=lambda x: x.get(\"content\", \"\") and x.get(\"content\", \"\").rstrip().endswith(\"TERMINATE\"),\n",
" max_consecutive_auto_reply=1,\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Initiate Chat"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"user_proxy.initiate_chat(\n",
" assistant, message=\"Write a python program to print the first 10 numbers of the Fibonacci sequence.\"\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Function Call in Latest Anthropic API \n",
"Anthropic just announced that tool use is now supported in the Anthropic API. To use this feature, please install `anthropic>=0.23.1`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Register the function"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"@user_proxy.register_for_execution() # Decorator factory for registering a function to be executed by an agent\n",
"@assistant.register_for_llm(\n",
" name=\"get_weather\", description=\"Get the current weather in a given location.\"\n",
") # Decorator factory for registering a function to be used by an agent\n",
"def preprocess(location: Annotated[str, \"The city and state, e.g. Toronto, ON.\"]) -> str:\n",
" return \"Absolutely cloudy and rainy\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"user_proxy.initiate_chat(\n",
" assistant,\n",
" message=\"What's the weather in Toronto?\",\n",
")"
]
}
],
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"description": "Define and load a custom model",
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