From 4f673192cb8ba45d4c636d93c797edad8cb5bd88 Mon Sep 17 00:00:00 2001 From: Eric Zhu Date: Thu, 26 Dec 2024 09:12:02 -0800 Subject: [PATCH 01/20] "model" to "chat completion" (#4804) Co-authored-by: Jack Gerrits --- .../framework/component-config.ipynb | 270 +++++++++--------- .../src/autogen_core/_component_config.py | 4 +- python/packages/autogen-ext/test.py | 4 +- 3 files changed, 139 insertions(+), 139 deletions(-) diff --git a/python/packages/autogen-core/docs/src/user-guide/core-user-guide/framework/component-config.ipynb b/python/packages/autogen-core/docs/src/user-guide/core-user-guide/framework/component-config.ipynb index e69869e2087..6d21c33d2a8 100644 --- a/python/packages/autogen-core/docs/src/user-guide/core-user-guide/framework/component-config.ipynb +++ b/python/packages/autogen-core/docs/src/user-guide/core-user-guide/framework/component-config.ipynb @@ -1,137 +1,137 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Component config\n", - "\n", - "AutoGen components are able to be declaratively configured in a generic fashion. This is to support configuration based experiences, such as AutoGen studio, but it is also useful for many other scenarios.\n", - "\n", - "The system that provides this is called \"component configuration\". In AutoGen, a component is simply something that can be created from a config object and itself can be dumped to a config object. In this way, you can define a component in code and then get the config object from it.\n", - "\n", - "This system is generic and allows for components defined outside of AutoGen itself (such as extensions) to be configured in the same way.\n", - "\n", - "## How does this differ from state?\n", - "\n", - "This is a very important point to clarify. When we talk about serializing an object, we must include *all* data that makes that object itself. Including things like message history etc. When deserializing from serialized state, you must get back the *exact* same object. This is not the case with component configuration.\n", - "\n", - "Component configuration should be thought of as the blueprint for an object, and can be stamped out many times to create many instances of the same configured object.\n", - "\n", - "## Usage\n", - "\n", - "If you have a component in Python and want to get the config for it, simply call {py:meth}`~autogen_core.ComponentConfig.dump_component` on it. The resulting object can be passed back into {py:meth}`~autogen_core.ComponentLoader.load_component` to get the component back.\n", - "\n", - "### Loading a component from a config\n", - "\n", - "To load a component from a config object, you can use the {py:meth}`~autogen_core.ComponentLoader.load_component` method. This method will take a config object and return a component object. It is best to call this method on the interface you want. For example to load a model client:\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from autogen_core.models import ChatCompletionClient\n", - "\n", - "config = {\n", - " \"provider\": \"openai_model_client\",\n", - " \"config\": {\"model\": \"gpt-4o\"},\n", - "}\n", - "\n", - "client = ChatCompletionClient.load_component(config)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Creating a component class\n", - "\n", - "To add component functionality to a given class:\n", - "\n", - "1. Add a call to {py:meth}`~autogen_core.Component` in the class inheritance list.\n", - "2. Implment the {py:meth}`~autogen_core.ComponentConfigImpl._to_config` and {py:meth}`~autogen_core.ComponentConfigImpl._from_config` methods\n", - "\n", - "For example:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from autogen_core import Component\n", - "from pydantic import BaseModel\n", - "\n", - "\n", - "class Config(BaseModel):\n", - " value: str\n", - "\n", - "\n", - "class MyComponent(Component[Config]):\n", - " component_type = \"custom\"\n", - " component_config_schema = Config\n", - "\n", - " def __init__(self, value: str):\n", - " self.value = value\n", - "\n", - " def _to_config(self) -> Config:\n", - " return Config(value=self.value)\n", - "\n", - " @classmethod\n", - " def _from_config(cls, config: Config) -> \"MyComponent\":\n", - " return cls(value=config.value)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "## Secrets\n", - "\n", - "If a field of a config object is a secret value, it should be marked using [`SecretStr`](https://docs.pydantic.dev/latest/api/types/#pydantic.types.SecretStr), this will ensure that the value will not be dumped to the config object.\n", - "\n", - "For example:\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from pydantic import BaseModel, SecretStr\n", - "\n", - "\n", - "class ClientConfig(BaseModel):\n", - " endpoint: str\n", - " api_key: SecretStr" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "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": "3.12.7" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Component config\n", + "\n", + "AutoGen components are able to be declaratively configured in a generic fashion. This is to support configuration based experiences, such as AutoGen studio, but it is also useful for many other scenarios.\n", + "\n", + "The system that provides this is called \"component configuration\". In AutoGen, a component is simply something that can be created from a config object and itself can be dumped to a config object. In this way, you can define a component in code and then get the config object from it.\n", + "\n", + "This system is generic and allows for components defined outside of AutoGen itself (such as extensions) to be configured in the same way.\n", + "\n", + "## How does this differ from state?\n", + "\n", + "This is a very important point to clarify. When we talk about serializing an object, we must include *all* data that makes that object itself. Including things like message history etc. When deserializing from serialized state, you must get back the *exact* same object. This is not the case with component configuration.\n", + "\n", + "Component configuration should be thought of as the blueprint for an object, and can be stamped out many times to create many instances of the same configured object.\n", + "\n", + "## Usage\n", + "\n", + "If you have a component in Python and want to get the config for it, simply call {py:meth}`~autogen_core.ComponentConfig.dump_component` on it. The resulting object can be passed back into {py:meth}`~autogen_core.ComponentLoader.load_component` to get the component back.\n", + "\n", + "### Loading a component from a config\n", + "\n", + "To load a component from a config object, you can use the {py:meth}`~autogen_core.ComponentLoader.load_component` method. This method will take a config object and return a component object. It is best to call this method on the interface you want. For example to load a model client:\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from autogen_core.models import ChatCompletionClient\n", + "\n", + "config = {\n", + " \"provider\": \"openai_chat_completion_client\",\n", + " \"config\": {\"model\": \"gpt-4o\"},\n", + "}\n", + "\n", + "client = ChatCompletionClient.load_component(config)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating a component class\n", + "\n", + "To add component functionality to a given class:\n", + "\n", + "1. Add a call to {py:meth}`~autogen_core.Component` in the class inheritance list.\n", + "2. Implment the {py:meth}`~autogen_core.ComponentConfigImpl._to_config` and {py:meth}`~autogen_core.ComponentConfigImpl._from_config` methods\n", + "\n", + "For example:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from autogen_core import Component\n", + "from pydantic import BaseModel\n", + "\n", + "\n", + "class Config(BaseModel):\n", + " value: str\n", + "\n", + "\n", + "class MyComponent(Component[Config]):\n", + " component_type = \"custom\"\n", + " component_config_schema = Config\n", + "\n", + " def __init__(self, value: str):\n", + " self.value = value\n", + "\n", + " def _to_config(self) -> Config:\n", + " return Config(value=self.value)\n", + "\n", + " @classmethod\n", + " def _from_config(cls, config: Config) -> \"MyComponent\":\n", + " return cls(value=config.value)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## Secrets\n", + "\n", + "If a field of a config object is a secret value, it should be marked using [`SecretStr`](https://docs.pydantic.dev/latest/api/types/#pydantic.types.SecretStr), this will ensure that the value will not be dumped to the config object.\n", + "\n", + "For example:\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pydantic import BaseModel, SecretStr\n", + "\n", + "\n", + "class ClientConfig(BaseModel):\n", + " endpoint: str\n", + " api_key: SecretStr" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.12.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 } diff --git a/python/packages/autogen-core/src/autogen_core/_component_config.py b/python/packages/autogen-core/src/autogen_core/_component_config.py index 521d6a58180..f5426428c90 100644 --- a/python/packages/autogen-core/src/autogen_core/_component_config.py +++ b/python/packages/autogen-core/src/autogen_core/_component_config.py @@ -40,9 +40,9 @@ def _type_to_provider_str(t: type) -> str: WELL_KNOWN_PROVIDERS = { - "azure_openai_model_client": "autogen_ext.models.openai.AzureOpenAIChatCompletionClient", + "azure_openai_chat_completion_client": "autogen_ext.models.openai.AzureOpenAIChatCompletionClient", "AzureOpenAIChatCompletionClient": "autogen_ext.models.openai.AzureOpenAIChatCompletionClient", - "openai_model_client": "autogen_ext.models.openai.OpenAIChatCompletionClient", + "openai_chat_completion_client": "autogen_ext.models.openai.OpenAIChatCompletionClient", "OpenAIChatCompletionClient": "autogen_ext.models.openai.OpenAIChatCompletionClient", } diff --git a/python/packages/autogen-ext/test.py b/python/packages/autogen-ext/test.py index b0e027b4f12..4bd65eca2c5 100644 --- a/python/packages/autogen-ext/test.py +++ b/python/packages/autogen-ext/test.py @@ -4,7 +4,7 @@ client = ChatCompletionClient.load_component( { - "provider": "openai_model_client", + "provider": "openai_chat_completion_client", "config": { "model": "gpt-4o" } @@ -18,4 +18,4 @@ # asyncio.run(main()) -print(client.dump_component().model_dump_json()) \ No newline at end of file +print(client.dump_component().model_dump_json()) From f774eaa1051e49add4b0e0758fb540e035a4dda6 Mon Sep 17 00:00:00 2001 From: Eric Zhu Date: Thu, 26 Dec 2024 09:40:32 -0800 Subject: [PATCH 02/20] Add minimum dep versions (#4803) --- python/packages/autogen-core/pyproject.toml | 13 +- python/packages/autogen-ext/pyproject.toml | 2 +- python/uv.lock | 405 ++++++++++++++++++-- 3 files changed, 381 insertions(+), 39 deletions(-) diff --git a/python/packages/autogen-core/pyproject.toml b/python/packages/autogen-core/pyproject.toml index 191d4c7bada..b61f6efb0eb 100644 --- a/python/packages/autogen-core/pyproject.toml +++ b/python/packages/autogen-core/pyproject.toml @@ -16,23 +16,18 @@ classifiers = [ ] dependencies = [ "openai>=1.3", - "pillow", - "aioconsole", - "aiohttp", + "pillow>=11.0.0", + "aioconsole>=0.8.1", + "aiohttp>=3.10.10", "typing-extensions", "pydantic<3.0.0,>=2.0.0", "protobuf~=4.25.1", - "tiktoken", + "tiktoken>=0.8.0", "opentelemetry-api~=1.27.0", "asyncio_atexit", "jsonref~=1.1.0", ] -[project.optional-dependencies] -grpc = [ - "grpcio~=1.62.0", -] - [tool.uv] dev-dependencies = [ "autogen_test_utils", diff --git a/python/packages/autogen-ext/pyproject.toml b/python/packages/autogen-ext/pyproject.toml index d99bfdce5af..0d04e747ea2 100644 --- a/python/packages/autogen-ext/pyproject.toml +++ b/python/packages/autogen-ext/pyproject.toml @@ -25,7 +25,7 @@ m1 = "autogen_ext.teams.magentic_one_cli:main" langchain = ["langchain_core~= 0.3.3"] azure = ["azure-core", "azure-identity"] docker = ["docker~=7.0"] -openai = ["openai>=1.3", "aiofiles"] +openai = ["openai>=1.52.2", "aiofiles"] file-surfer = [ "autogen-agentchat==0.4.0.dev11", "markitdown>=0.0.1a2", diff --git a/python/uv.lock b/python/uv.lock index c4824f5bdf9..94aa848bf97 100644 --- a/python/uv.lock +++ b/python/uv.lock @@ -29,17 +29,20 @@ resolution-markers = [ "python_full_version < '3.11' and platform_system == 'Darwin'", "python_full_version == '3.11.*' and platform_system == 'Darwin'", "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system == 'Darwin'", - "python_full_version >= '3.12.4' and platform_system == 'Darwin'", + "python_full_version < '3.13' and platform_system == 'Darwin'", + "python_full_version >= '3.13' and platform_system == 'Darwin'", "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux'", "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux'", "python_full_version == '3.11.*' and 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<175728472+Copilot@users.noreply.github.com> * Remove unused import NoneType from test_tools.py --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- .../src/autogen_core/_function_utils.py | 28 +++--------- .../src/autogen_core/_pydantic_compat.py | 17 +------ .../packages/autogen-core/tests/test_tools.py | 44 ++++++++++++++++++- 3 files changed, 51 insertions(+), 38 deletions(-) diff --git a/python/packages/autogen-core/src/autogen_core/_function_utils.py b/python/packages/autogen-core/src/autogen_core/_function_utils.py index d541411d417..a6803d085e4 100644 --- a/python/packages/autogen-core/src/autogen_core/_function_utils.py +++ b/python/packages/autogen-core/src/autogen_core/_function_utils.py @@ -2,13 +2,13 @@ # Credit to original authors import inspect +import typing from logging import getLogger from typing import ( Annotated, Any, Callable, Dict, - ForwardRef, List, Optional, Set, @@ -25,29 +25,13 @@ from pydantic_core import PydanticUndefined from typing_extensions import Literal -from ._pydantic_compat import evaluate_forwardref, model_dump, type2schema +from ._pydantic_compat import model_dump, type2schema logger = getLogger(__name__) T = TypeVar("T") -def get_typed_annotation(annotation: Any, globalns: Dict[str, Any]) -> Any: - """Get the type annotation of a parameter. - - Args: - annotation: The annotation of the parameter - globalns: The global namespace of the function - - Returns: - The type annotation of the parameter - """ - if isinstance(annotation, str): - annotation = ForwardRef(annotation) - annotation = evaluate_forwardref(annotation, globalns, globalns) - return annotation - - def get_typed_signature(call: Callable[..., Any]) -> inspect.Signature: """Get the signature of a function with type annotations. @@ -59,16 +43,17 @@ def get_typed_signature(call: Callable[..., Any]) -> inspect.Signature: """ signature = inspect.signature(call) globalns = getattr(call, "__globals__", {}) + type_hints = typing.get_type_hints(call, globalns, include_extras=True) typed_params = [ inspect.Parameter( name=param.name, kind=param.kind, default=param.default, - annotation=get_typed_annotation(param.annotation, globalns), + annotation=type_hints[param.name], ) for param in signature.parameters.values() ] - return_annotation = get_typed_annotation(signature.return_annotation, globalns) + return_annotation = type_hints.get("return", inspect.Signature.empty) typed_signature = inspect.Signature(typed_params, return_annotation=return_annotation) return typed_signature @@ -89,7 +74,8 @@ def get_typed_return_annotation(call: Callable[..., Any]) -> Any: return None globalns = getattr(call, "__globals__", {}) - return get_typed_annotation(annotation, globalns) + type_hints = typing.get_type_hints(call, globalns, include_extras=True) + return type_hints.get("return", inspect.Signature.empty) def get_param_annotations( diff --git a/python/packages/autogen-core/src/autogen_core/_pydantic_compat.py b/python/packages/autogen-core/src/autogen_core/_pydantic_compat.py index 66135061663..c29ccb70c06 100644 --- a/python/packages/autogen-core/src/autogen_core/_pydantic_compat.py +++ b/python/packages/autogen-core/src/autogen_core/_pydantic_compat.py @@ -8,26 +8,11 @@ from pydantic.version import VERSION as PYDANTIC_VERSION from typing_extensions import get_origin -__all__ = ("model_dump", "type2schema", "evaluate_forwardref") +__all__ = ("model_dump", "type2schema") PYDANTIC_V1 = PYDANTIC_VERSION.startswith("1.") -def evaluate_forwardref( - value: Any, - globalns: dict[str, Any] | None = None, - localns: dict[str, Any] | None = None, -) -> Any: - if PYDANTIC_V1: - from pydantic.typing import evaluate_forwardref as evaluate_forwardref_internal - - return evaluate_forwardref_internal(value, globalns, localns) - else: - from pydantic._internal._typing_extra import eval_type_lenient - - return eval_type_lenient(value, globalns, localns) - - def type2schema(t: Type[Any] | None) -> Dict[str, Any]: if PYDANTIC_V1: from pydantic import schema_of # type: ignore diff --git a/python/packages/autogen-core/tests/test_tools.py b/python/packages/autogen-core/tests/test_tools.py index 64d97e11519..f6910b50781 100644 --- a/python/packages/autogen-core/tests/test_tools.py +++ b/python/packages/autogen-core/tests/test_tools.py @@ -164,6 +164,48 @@ def my_function() -> "str": assert sig.return_annotation is str +def test_get_typed_signature_params() -> None: + def my_function(arg: str) -> None: + return None + + sig = get_typed_signature(my_function) + assert isinstance(sig, inspect.Signature) + assert sig.return_annotation is type(None) + assert len(sig.parameters) == 1 + assert sig.parameters["arg"].annotation is str + + +def test_get_typed_signature_two_params() -> None: + def my_function(arg: str, arg2: int) -> None: + return None + + sig = get_typed_signature(my_function) + assert isinstance(sig, inspect.Signature) + assert len(sig.parameters) == 2 + assert sig.parameters["arg"].annotation is str + assert sig.parameters["arg2"].annotation is int + + +def test_get_typed_signature_param_str() -> None: + def my_function(arg: "str") -> None: + return None + + sig = get_typed_signature(my_function) + assert isinstance(sig, inspect.Signature) + assert len(sig.parameters) == 1 + assert sig.parameters["arg"].annotation is str + + +def test_get_typed_signature_param_annotated() -> None: + def my_function(arg: Annotated[str, "An arg"]) -> None: + return None + + sig = get_typed_signature(my_function) + assert isinstance(sig, inspect.Signature) + assert len(sig.parameters) == 1 + assert sig.parameters["arg"].annotation == Annotated[str, "An arg"] + + def test_func_tool() -> None: def my_function() -> str: return "result" @@ -227,7 +269,7 @@ def my_function() -> None: assert tool.name == "my_function" assert tool.description == "Function tool." assert issubclass(tool.args_type(), BaseModel) - assert tool.return_type() is None + assert tool.return_type() is type(None) assert tool.state_type() is None From 501d8bb8f32900ef836f5f92bf16d10ed71f4121 Mon Sep 17 00:00:00 2001 From: Eric Zhu Date: Thu, 26 Dec 2024 15:28:35 -0800 Subject: [PATCH 04/20] Update uv actiona and pin uv version to 0.5.11 (#4820) --- .github/workflows/checks.yml | 24 ++++++++++++++------- .github/workflows/codeql.yml | 3 ++- .github/workflows/docs.yml | 6 ++++-- .github/workflows/dotnet-build.yml | 9 +++++--- .github/workflows/single-python-package.yml | 3 ++- 5 files changed, 30 insertions(+), 15 deletions(-) diff --git a/.github/workflows/checks.yml b/.github/workflows/checks.yml index 703c0749425..c01b3bfd444 100644 --- a/.github/workflows/checks.yml +++ b/.github/workflows/checks.yml @@ -15,9 +15,10 @@ jobs: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -33,9 +34,10 @@ jobs: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -61,9 +63,10 @@ jobs: ] steps: - uses: actions/checkout@v4 - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -89,9 +92,10 @@ jobs: ] steps: - uses: actions/checkout@v4 - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -115,9 +119,10 @@ jobs: ] steps: - uses: actions/checkout@v4 - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -139,9 +144,10 @@ jobs: package: ["./packages/autogen-core"] steps: - uses: actions/checkout@v4 - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -160,9 +166,10 @@ jobs: package: ["./packages/autogen-core"] steps: - uses: actions/checkout@v4 - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -178,9 +185,10 @@ jobs: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml index 76457b6d815..c7776791b58 100644 --- a/.github/workflows/codeql.yml +++ b/.github/workflows/codeql.yml @@ -73,9 +73,10 @@ jobs: - name: list available kernels run: | python -m jupyter kernelspec list - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - run: uv sync --locked --all-extras working-directory: ./python - name: Prepare python venv diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 6908ef929f4..cf205af09f1 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -51,9 +51,10 @@ jobs: with: lfs: "true" ref: ${{ matrix.version.ref }} - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -99,9 +100,10 @@ jobs: with: lfs: "true" ref: ${{ matrix.version.ref }} - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" diff --git a/.github/workflows/dotnet-build.yml b/.github/workflows/dotnet-build.yml index e70a943ccd7..e1fa05095d9 100644 --- a/.github/workflows/dotnet-build.yml +++ b/.github/workflows/dotnet-build.yml @@ -76,9 +76,10 @@ jobs: - name: list available kernels run: | python -m jupyter kernelspec list - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - run: uv sync --locked --all-extras working-directory: ./python - name: Prepare python venv @@ -119,9 +120,10 @@ jobs: - uses: actions/checkout@v4 with: lfs: true - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -203,9 +205,10 @@ jobs: - name: list available kernels run: | python -m jupyter kernelspec list - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" diff --git a/.github/workflows/single-python-package.yml b/.github/workflows/single-python-package.yml index db761e2c256..d8d2c66a131 100644 --- a/.github/workflows/single-python-package.yml +++ b/.github/workflows/single-python-package.yml @@ -32,9 +32,10 @@ jobs: ref: ${{ github.event.inputs.ref }} # Require ref to be a tag - run: git show-ref --verify refs/tags/${{ github.event.inputs.ref }} - - uses: astral-sh/setup-uv@v3 + - uses: astral-sh/setup-uv@v5 with: enable-cache: true + version: "0.5.11" - run: uv build --package ${{ github.event.inputs.package }} --out-dir dist/ working-directory: python - name: Publish package to PyPI From edad1b606505c1b72d167841c6b15845f1d8b7e2 Mon Sep 17 00:00:00 2001 From: Eric Zhu Date: Fri, 27 Dec 2024 05:34:21 -0800 Subject: [PATCH 05/20] Emphasis on_messages is for new messages only; remove unused file. (#4819) * Emphasis on_messages is for new messages only * update * update uv * update uv action * try pin uv version * pin all uv versions to 0.5.11 * revert uv lock file and remove unwanted file. --- .../agents/_assistant_agent.py | 8 +++++++ .../agents/_base_chat_agent.py | 21 ++++++++++++++++++- .../tutorial/agents.ipynb | 14 +++++++++---- python/packages/autogen-ext/test.py | 21 ------------------- 4 files changed, 38 insertions(+), 26 deletions(-) delete mode 100644 python/packages/autogen-ext/test.py diff --git a/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_assistant_agent.py b/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_assistant_agent.py index 0fad2d670fb..9be3adcdc99 100644 --- a/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_assistant_agent.py +++ b/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_assistant_agent.py @@ -72,6 +72,14 @@ class AssistantAgent(BaseChatAgent): the inner messages as they are created, and the :class:`~autogen_agentchat.base.Response` object as the last item before closing the generator. + + .. note:: + + The caller must only pass the new messages to the agent on each call + to the :meth:`on_messages` or :meth:`on_messages_stream` method. + The agent maintains its state between calls to these methods. + Do not pass the entire conversation history to the agent on each call. + Tool call behavior: * If the model returns no tool call, then the response is immediately returned as a :class:`~autogen_agentchat.messages.TextMessage` in :attr:`~autogen_agentchat.base.Response.chat_message`. diff --git a/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_base_chat_agent.py b/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_base_chat_agent.py index 5b41d7bea33..c78c9adb90e 100644 --- a/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_base_chat_agent.py +++ b/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_base_chat_agent.py @@ -14,7 +14,26 @@ class BaseChatAgent(ChatAgent, ABC): - """Base class for a chat agent.""" + """Base class for a chat agent. + + This abstract class provides a base implementation for a :class:`ChatAgent`. + To create a new chat agent, subclass this class and implement the + :meth:`on_messages`, :meth:`on_reset`, and :attr:`produced_message_types`. + If streaming is required, also implement the :meth:`on_messages_stream` method. + + An agent is considered stateful and maintains its state between calls to + the :meth:`on_messages` or :meth:`on_messages_stream` methods. + The agent should store its state in the + agent instance. The agent should also implement the :meth:`on_reset` method + to reset the agent to its initialization state. + + .. note:: + + The caller should only pass the new messages to the agent on each call + to the :meth:`on_messages` or :meth:`on_messages_stream` method. + Do not pass the entire conversation history to the agent on each call. + This design principle must be followed when creating a new agent. + """ def __init__(self, name: str, description: str) -> None: self._name = name diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb index 7f5edd8e4d0..70811b062bf 100644 --- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb @@ -11,7 +11,7 @@ "\n", "- {py:attr}`~autogen_agentchat.agents.BaseChatAgent.name`: The unique name of the agent.\n", "- {py:attr}`~autogen_agentchat.agents.BaseChatAgent.description`: The description of the agent in text.\n", - "- {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_messages`: Send the agent a sequence of {py:class}`~autogen_agentchat.messages.ChatMessage` get a {py:class}`~autogen_agentchat.base.Response`.\n", + "- {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_messages`: Send the agent a sequence of {py:class}`~autogen_agentchat.messages.ChatMessage` get a {py:class}`~autogen_agentchat.base.Response`. **It is important to note that agents are expected to be stateful and this method is expected to be called with new messages, not the complete history**.\n", "- {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_messages_stream`: Same as {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_messages` but returns an iterator of {py:class}`~autogen_agentchat.messages.AgentEvent` or {py:class}`~autogen_agentchat.messages.ChatMessage` followed by a {py:class}`~autogen_agentchat.base.Response` as the last item.\n", "- {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_reset`: Reset the agent to its initial state.\n", "\n", @@ -106,8 +106,13 @@ "```{note}\n", "It is important to note that {py:meth}`~autogen_agentchat.agents.AssistantAgent.on_messages`\n", "will update the internal state of the agent -- it will add the messages to the agent's\n", - "history. So you should not repeatedly call this method with the same messages if you want to\n", - "carry on a conversation with the agent.\n", + "history. So you should call this method with new messages.\n", + "**You should not repeatedly call this method with the same messages or the complete history.**\n", + "```\n", + "\n", + "```{note}\n", + "Unlike in v0.2 AgentChat, the tools are executed by the same agent directly within\n", + "the same call to {py:meth}`~autogen_agentchat.agents.AssistantAgent.on_messages`.\n", "```\n", "\n", "## User Proxy Agent\n", @@ -141,7 +146,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The User Proxy agent is ideally used for on-demand human-in-the-loop interactions for scenarios such as Just In Time approvals, human feedback, alerts, etc. For slower user interactions, consider terminating the session using a termination condition and start another one from run or run_stream with another message.\n", + "The User Proxy agent is ideally used for on-demand human-in-the-loop interactions for scenarios such as Just In Time approvals, human feedback, alerts, etc. For slower user interactions, consider terminating a team using a termination condition and start another one from\n", + "{py:meth}`~autogen_agentchat.base.TaskRunner.run` or {py:meth}`~autogen_agentchat.base.TaskRunner.run_stream` with another message.\n", "\n", "## Streaming Messages\n", "\n", diff --git a/python/packages/autogen-ext/test.py b/python/packages/autogen-ext/test.py deleted file mode 100644 index 4bd65eca2c5..00000000000 --- a/python/packages/autogen-ext/test.py +++ /dev/null @@ -1,21 +0,0 @@ -from autogen_core.components.models import LLMMessage -from autogen_core.models import ChatCompletionClient -from autogen_core.models import UserMessage - -client = ChatCompletionClient.load_component( - { - "provider": "openai_chat_completion_client", - "config": { - "model": "gpt-4o" - } - } -) - -# async def main(): -# print(await client.create([UserMessage(source="user", content="Hello")])) - -# import asyncio - -# asyncio.run(main()) - -print(client.dump_component().model_dump_json()) From 9a2dbb4fba545c46e41014a22a2b68ca5828214a Mon Sep 17 00:00:00 2001 From: Leonardo Pinheiro Date: Fri, 27 Dec 2024 23:41:16 +1000 Subject: [PATCH 06/20] Add * before keyword args for ChatCompletionClient (#4822) add * before keyword args Co-authored-by: Leonardo Pinheiro Co-authored-by: Jack Gerrits --- .../src/autogen_core/models/_model_client.py | 6 ++++-- .../packages/autogen-core/tests/test_tool_agent.py | 6 ++++-- .../autogen_ext/models/openai/_openai_client.py | 14 ++++++++------ .../replay/_replay_chat_completion_client.py | 6 ++++-- 4 files changed, 20 insertions(+), 12 deletions(-) diff --git a/python/packages/autogen-core/src/autogen_core/models/_model_client.py b/python/packages/autogen-core/src/autogen_core/models/_model_client.py index 0cba5b07904..7a0762a46e9 100644 --- a/python/packages/autogen-core/src/autogen_core/models/_model_client.py +++ b/python/packages/autogen-core/src/autogen_core/models/_model_client.py @@ -29,6 +29,7 @@ class ChatCompletionClient(ABC, ComponentLoader): async def create( self, messages: Sequence[LLMMessage], + *, tools: Sequence[Tool | ToolSchema] = [], # None means do not override the default # A value means to override the client default - often specified in the constructor @@ -41,6 +42,7 @@ async def create( def create_stream( self, messages: Sequence[LLMMessage], + *, tools: Sequence[Tool | ToolSchema] = [], # None means do not override the default # A value means to override the client default - often specified in the constructor @@ -56,10 +58,10 @@ def actual_usage(self) -> RequestUsage: ... def total_usage(self) -> RequestUsage: ... @abstractmethod - def count_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | ToolSchema] = []) -> int: ... + def count_tokens(self, messages: Sequence[LLMMessage], *, tools: Sequence[Tool | ToolSchema] = []) -> int: ... @abstractmethod - def remaining_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | ToolSchema] = []) -> int: ... + def remaining_tokens(self, messages: Sequence[LLMMessage], *, tools: Sequence[Tool | ToolSchema] = []) -> int: ... @property @abstractmethod diff --git a/python/packages/autogen-core/tests/test_tool_agent.py b/python/packages/autogen-core/tests/test_tool_agent.py index d0d6dec8915..c93815d5dfd 100644 --- a/python/packages/autogen-core/tests/test_tool_agent.py +++ b/python/packages/autogen-core/tests/test_tool_agent.py @@ -92,6 +92,7 @@ class MockChatCompletionClient(ChatCompletionClient): async def create( self, messages: Sequence[LLMMessage], + *, tools: Sequence[Tool | ToolSchema] = [], json_output: Optional[bool] = None, extra_create_args: Mapping[str, Any] = {}, @@ -116,6 +117,7 @@ async def create( def create_stream( self, messages: Sequence[LLMMessage], + *, tools: Sequence[Tool | ToolSchema] = [], json_output: Optional[bool] = None, extra_create_args: Mapping[str, Any] = {}, @@ -129,10 +131,10 @@ def actual_usage(self) -> RequestUsage: def total_usage(self) -> RequestUsage: return RequestUsage(prompt_tokens=0, completion_tokens=0) - def count_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | ToolSchema] = []) -> int: + def count_tokens(self, messages: Sequence[LLMMessage], *, tools: Sequence[Tool | ToolSchema] = []) -> int: return 0 - def remaining_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | ToolSchema] = []) -> int: + def remaining_tokens(self, messages: Sequence[LLMMessage], *, tools: Sequence[Tool | ToolSchema] = []) -> int: return 0 @property diff --git a/python/packages/autogen-ext/src/autogen_ext/models/openai/_openai_client.py b/python/packages/autogen-ext/src/autogen_ext/models/openai/_openai_client.py index a70ee087aa9..2128378d98e 100644 --- a/python/packages/autogen-ext/src/autogen_ext/models/openai/_openai_client.py +++ b/python/packages/autogen-ext/src/autogen_ext/models/openai/_openai_client.py @@ -355,6 +355,7 @@ class BaseOpenAIChatCompletionClient(ChatCompletionClient): def __init__( self, client: Union[AsyncOpenAI, AsyncAzureOpenAI], + *, create_args: Dict[str, Any], model_capabilities: Optional[ModelCapabilities] = None, ): @@ -389,6 +390,7 @@ def create_from_config(cls, config: Dict[str, Any]) -> ChatCompletionClient: async def create( self, messages: Sequence[LLMMessage], + *, tools: Sequence[Tool | ToolSchema] = [], json_output: Optional[bool] = None, extra_create_args: Mapping[str, Any] = {}, @@ -581,11 +583,11 @@ async def create( async def create_stream( self, messages: Sequence[LLMMessage], + *, tools: Sequence[Tool | ToolSchema] = [], json_output: Optional[bool] = None, extra_create_args: Mapping[str, Any] = {}, cancellation_token: Optional[CancellationToken] = None, - *, max_consecutive_empty_chunk_tolerance: int = 0, ) -> AsyncGenerator[Union[str, CreateResult], None]: """ @@ -800,7 +802,7 @@ def actual_usage(self) -> RequestUsage: def total_usage(self) -> RequestUsage: return self._total_usage - def count_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | ToolSchema] = []) -> int: + def count_tokens(self, messages: Sequence[LLMMessage], *, tools: Sequence[Tool | ToolSchema] = []) -> int: model = self._create_args["model"] try: encoding = tiktoken.encoding_for_model(model) @@ -889,9 +891,9 @@ def count_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | To num_tokens += 12 return num_tokens - def remaining_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | ToolSchema] = []) -> int: + def remaining_tokens(self, messages: Sequence[LLMMessage], *, tools: Sequence[Tool | ToolSchema] = []) -> int: token_limit = _model_info.get_token_limit(self._create_args["model"]) - return token_limit - self.count_tokens(messages, tools) + return token_limit - self.count_tokens(messages, tools=tools) @property def capabilities(self) -> ModelCapabilities: @@ -974,7 +976,7 @@ def __init__(self, **kwargs: Unpack[OpenAIClientConfiguration]): client = _openai_client_from_config(copied_args) create_args = _create_args_from_config(copied_args) self._raw_config: Dict[str, Any] = copied_args - super().__init__(client, create_args, model_capabilities) + super().__init__(client=client, create_args=create_args, model_capabilities=model_capabilities) def __getstate__(self) -> Dict[str, Any]: state = self.__dict__.copy() @@ -1059,7 +1061,7 @@ def __init__(self, **kwargs: Unpack[AzureOpenAIClientConfiguration]): client = _azure_openai_client_from_config(copied_args) create_args = _create_args_from_config(copied_args) self._raw_config: Dict[str, Any] = copied_args - super().__init__(client, create_args, model_capabilities) + super().__init__(client=client, create_args=create_args, model_capabilities=model_capabilities) def __getstate__(self) -> Dict[str, Any]: state = self.__dict__.copy() diff --git a/python/packages/autogen-ext/src/autogen_ext/models/replay/_replay_chat_completion_client.py b/python/packages/autogen-ext/src/autogen_ext/models/replay/_replay_chat_completion_client.py index 5b7ac7095c2..1167be59b8a 100644 --- a/python/packages/autogen-ext/src/autogen_ext/models/replay/_replay_chat_completion_client.py +++ b/python/packages/autogen-ext/src/autogen_ext/models/replay/_replay_chat_completion_client.py @@ -128,6 +128,7 @@ def __init__( async def create( self, messages: Sequence[LLMMessage], + *, tools: Sequence[Tool | ToolSchema] = [], json_output: Optional[bool] = None, extra_create_args: Mapping[str, Any] = {}, @@ -155,6 +156,7 @@ async def create( async def create_stream( self, messages: Sequence[LLMMessage], + *, tools: Sequence[Tool | ToolSchema] = [], json_output: Optional[bool] = None, extra_create_args: Mapping[str, Any] = {}, @@ -191,11 +193,11 @@ def actual_usage(self) -> RequestUsage: def total_usage(self) -> RequestUsage: return self._total_usage - def count_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | ToolSchema] = []) -> int: + def count_tokens(self, messages: Sequence[LLMMessage], *, tools: Sequence[Tool | ToolSchema] = []) -> int: _, token_count = self._tokenize(messages) return token_count - def remaining_tokens(self, messages: Sequence[LLMMessage], tools: Sequence[Tool | ToolSchema] = []) -> int: + def remaining_tokens(self, messages: Sequence[LLMMessage], *, tools: Sequence[Tool | ToolSchema] = []) -> int: return max( 0, self._total_available_tokens - self._total_usage.prompt_tokens - self._total_usage.completion_tokens ) From d1dff316bce02f841400a713eb5ee406f9a163e0 Mon Sep 17 00:00:00 2001 From: Sachin Joglekar Date: Fri, 27 Dec 2024 05:53:52 -0800 Subject: [PATCH 07/20] Update pydantic version & fix mypy errors (#4811) * Update pydantic version & fix mypy errors * uv lock changes * Update lock * update lockfile --------- Co-authored-by: Jack Gerrits Co-authored-by: Jack Gerrits --- python/packages/autogen-core/pyproject.toml | 2 +- .../models/openai/config/__init__.py | 5 +- .../src/component_schema_gen/__main__.py | 4 +- python/uv.lock | 589 ++++-------------- 4 files changed, 112 insertions(+), 488 deletions(-) diff --git a/python/packages/autogen-core/pyproject.toml b/python/packages/autogen-core/pyproject.toml index b61f6efb0eb..9602e0f8d80 100644 --- a/python/packages/autogen-core/pyproject.toml +++ b/python/packages/autogen-core/pyproject.toml @@ -20,7 +20,7 @@ dependencies = [ "aioconsole>=0.8.1", "aiohttp>=3.10.10", "typing-extensions", - "pydantic<3.0.0,>=2.0.0", + "pydantic<3.0.0,>=2.10.0", "protobuf~=4.25.1", "tiktoken>=0.8.0", "opentelemetry-api~=1.27.0", diff --git a/python/packages/autogen-ext/src/autogen_ext/models/openai/config/__init__.py b/python/packages/autogen-ext/src/autogen_ext/models/openai/config/__init__.py index 4f83466f531..c2938cb7c85 100644 --- a/python/packages/autogen-ext/src/autogen_ext/models/openai/config/__init__.py +++ b/python/packages/autogen-ext/src/autogen_ext/models/openai/config/__init__.py @@ -2,7 +2,7 @@ from autogen_core import ComponentModel from autogen_core.models import ModelCapabilities -from pydantic import BaseModel, ConfigDict +from pydantic import BaseModel from typing_extensions import Required, TypedDict from .._azure_token_provider import AzureTokenProvider @@ -79,9 +79,6 @@ class CreateArgumentsConfigModel(BaseModel): class BaseOpenAIClientConfigurationConfigModel(CreateArgumentsConfigModel): - # To allow `model_capabilities` field without triggering pydantic warnings. - model_config = ConfigDict(protected_namespaces=()) - model: str api_key: str | None = None timeout: float | None = None diff --git a/python/packages/component-schema-gen/src/component_schema_gen/__main__.py b/python/packages/component-schema-gen/src/component_schema_gen/__main__.py index 300227bff26..a61e7f38635 100644 --- a/python/packages/component-schema-gen/src/component_schema_gen/__main__.py +++ b/python/packages/component-schema-gen/src/component_schema_gen/__main__.py @@ -53,7 +53,7 @@ def build_specific_component_schema(component: type[ComponentConfigImpl[T]], pro return component_model_schema -def main(): +def main() -> None: outer_model_schema: Dict[str, Any] = { "type": "object", "$ref": "#/$defs/ComponentModel", @@ -69,7 +69,7 @@ def main(): for key, value in WELL_KNOWN_PROVIDERS.items(): reverse_provider_lookup_table[value].append(key) - def add_type(type: type[ComponentConfigImpl[T]]): + def add_type(type: type[ComponentConfigImpl[T]]) -> None: canonical = type.component_provider_override or _type_to_provider_str(type) reverse_provider_lookup_table[canonical].append(canonical) for provider_str in reverse_provider_lookup_table[canonical]: diff --git a/python/uv.lock b/python/uv.lock index 94aa848bf97..afb0c232607 100644 --- a/python/uv.lock +++ b/python/uv.lock @@ -1,48 +1,19 @@ version = 1 requires-python = ">=3.10, <3.13" resolution-markers = [ - "python_full_version < '3.11' and platform_system == 'Darwin'", - "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux'", - "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux')", - "python_full_version == '3.11.*' and platform_system == 'Darwin'", - "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux'", - "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux')", - "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system == 'Darwin'", - "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux'", - "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system != 'Darwin' and platform_system != 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.../src/autogen_core/tools/__init__.py | 4 --- .../tools/code_execution/__init__.py | 3 ++ .../tools/code_execution}/_code_execution.py | 7 ++-- 6 files changed, 11 insertions(+), 45 deletions(-) create mode 100644 python/packages/autogen-ext/src/autogen_ext/tools/code_execution/__init__.py rename python/packages/{autogen-core/src/autogen_core/tools => autogen-ext/src/autogen_ext/tools/code_execution}/_code_execution.py (87%) diff --git a/python/packages/autogen-core/docs/src/user-guide/core-user-guide/cookbook/tool-use-with-intervention.ipynb b/python/packages/autogen-core/docs/src/user-guide/core-user-guide/cookbook/tool-use-with-intervention.ipynb index 27f9bfc6a1e..46b7595090a 100644 --- a/python/packages/autogen-core/docs/src/user-guide/core-user-guide/cookbook/tool-use-with-intervention.ipynb +++ b/python/packages/autogen-core/docs/src/user-guide/core-user-guide/cookbook/tool-use-with-intervention.ipynb @@ -36,9 +36,10 @@ " UserMessage,\n", ")\n", "from autogen_core.tool_agent import ToolAgent, ToolException, tool_agent_caller_loop\n", - "from autogen_core.tools import PythonCodeExecutionTool, ToolSchema\n", + "from autogen_core.tools import ToolSchema\n", "from autogen_ext.code_executors.docker import DockerCommandLineCodeExecutor\n", - "from autogen_ext.models.openai import OpenAIChatCompletionClient" + "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", + "from autogen_ext.tools.code_execution import PythonCodeExecutionTool" ] }, { diff --git a/python/packages/autogen-core/docs/src/user-guide/core-user-guide/framework/tools.ipynb b/python/packages/autogen-core/docs/src/user-guide/core-user-guide/framework/tools.ipynb index 7e7ea0ef99f..f2bf29425c2 100644 --- a/python/packages/autogen-core/docs/src/user-guide/core-user-guide/framework/tools.ipynb +++ b/python/packages/autogen-core/docs/src/user-guide/core-user-guide/framework/tools.ipynb @@ -22,7 +22,7 @@ "source": [ "## Built-in Tools\n", "\n", - "One of the built-in tools is the {py:class}`~autogen_core.tools.PythonCodeExecutionTool`,\n", + "One of the built-in tools is the {py:class}`~autogen_ext.tools.code_execution.PythonCodeExecutionTool`,\n", "which allows agents to execute Python code snippets.\n", "\n", "Here is how you create the tool and use it." @@ -44,8 +44,8 @@ ], "source": [ "from autogen_core import CancellationToken\n", - "from autogen_core.tools import PythonCodeExecutionTool\n", "from autogen_ext.code_executors.docker import DockerCommandLineCodeExecutor\n", + "from autogen_ext.tools.code_execution import PythonCodeExecutionTool\n", "\n", "# Create the tool.\n", "code_executor = DockerCommandLineCodeExecutor()\n", diff --git a/python/packages/autogen-core/src/autogen_core/components/tools/__init__.py b/python/packages/autogen-core/src/autogen_core/components/tools/__init__.py index e3c480fee30..f9b5906943f 100644 --- a/python/packages/autogen-core/src/autogen_core/components/tools/__init__.py +++ b/python/packages/autogen-core/src/autogen_core/components/tools/__init__.py @@ -9,19 +9,10 @@ from ...tools import ( BaseToolWithState as BaseToolWithStateAlias, ) -from ...tools import ( - CodeExecutionInput as CodeExecutionInputAlias, -) -from ...tools import ( - CodeExecutionResult as CodeExecutionResultAlias, -) from ...tools import FunctionTool as FunctionToolAlias from ...tools import ( ParametersSchema as ParametersSchemaAlias, ) -from ...tools import ( - PythonCodeExecutionTool as PythonCodeExecutionToolAlias, -) from ...tools import ( Tool as ToolAlias, ) @@ -35,9 +26,6 @@ "ParametersSchema", "BaseTool", "BaseToolWithState", - "PythonCodeExecutionTool", - "CodeExecutionInput", - "CodeExecutionResult", "FunctionTool", ] @@ -80,27 +68,6 @@ class BaseToolWithState(BaseToolWithStateAlias[ArgsT, ReturnT, StateT]): pass -@deprecated( - "autogen_core.tools.PythonCodeExecutionToolAlias moved to autogen_core.tools.PythonCodeExecutionToolAlias. This alias will be removed in 0.4.0." -) -class PythonCodeExecutionTool(PythonCodeExecutionToolAlias): - pass - - -@deprecated( - "autogen_core.tools.CodeExecutionInputAlias moved to autogen_core.tools.CodeExecutionInputAlias. This alias will be removed in 0.4.0." -) -class CodeExecutionInput(CodeExecutionInputAlias): - pass - - -@deprecated( - "autogen_core.tools.CodeExecutionResultAlias moved to autogen_core.tools.CodeExecutionResultAlias. This alias will be removed in 0.4.0." -) -class CodeExecutionResult(CodeExecutionResultAlias): - pass - - @deprecated( "autogen_core.tools.FunctionToolAlias moved to autogen_core.tools.FunctionToolAlias. This alias will be removed in 0.4.0." ) diff --git a/python/packages/autogen-core/src/autogen_core/tools/__init__.py b/python/packages/autogen-core/src/autogen_core/tools/__init__.py index dcfb1759a91..52a9d725f7d 100644 --- a/python/packages/autogen-core/src/autogen_core/tools/__init__.py +++ b/python/packages/autogen-core/src/autogen_core/tools/__init__.py @@ -1,5 +1,4 @@ from ._base import BaseTool, BaseToolWithState, ParametersSchema, Tool, ToolSchema -from ._code_execution import CodeExecutionInput, CodeExecutionResult, PythonCodeExecutionTool from ._function_tool import FunctionTool __all__ = [ @@ -8,8 +7,5 @@ "ParametersSchema", "BaseTool", "BaseToolWithState", - "PythonCodeExecutionTool", - "CodeExecutionInput", - "CodeExecutionResult", "FunctionTool", ] diff --git a/python/packages/autogen-ext/src/autogen_ext/tools/code_execution/__init__.py b/python/packages/autogen-ext/src/autogen_ext/tools/code_execution/__init__.py new file mode 100644 index 00000000000..f58ea00df66 --- /dev/null +++ b/python/packages/autogen-ext/src/autogen_ext/tools/code_execution/__init__.py @@ -0,0 +1,3 @@ +from ._code_execution import CodeExecutionInput, CodeExecutionResult, PythonCodeExecutionTool + +__all__ = ["CodeExecutionInput", "CodeExecutionResult", "PythonCodeExecutionTool"] diff --git a/python/packages/autogen-core/src/autogen_core/tools/_code_execution.py b/python/packages/autogen-ext/src/autogen_ext/tools/code_execution/_code_execution.py similarity index 87% rename from python/packages/autogen-core/src/autogen_core/tools/_code_execution.py rename to python/packages/autogen-ext/src/autogen_ext/tools/code_execution/_code_execution.py index f3f2b072e6f..95e8fa34aac 100644 --- a/python/packages/autogen-core/src/autogen_core/tools/_code_execution.py +++ b/python/packages/autogen-ext/src/autogen_ext/tools/code_execution/_code_execution.py @@ -1,9 +1,8 @@ +from autogen_core import CancellationToken +from autogen_core.code_executor import CodeBlock, CodeExecutor +from autogen_core.tools import BaseTool from pydantic import BaseModel, Field, model_serializer -from .. import CancellationToken -from ..code_executor import CodeBlock, CodeExecutor -from ._base import BaseTool - class CodeExecutionInput(BaseModel): code: str = Field(description="The contents of the Python code block that should be executed") From e710f9d04fc7531ff5b36153defa6be23db46de2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Rich=C3=A1rd=20Gyik=C3=B3?= Date: Fri, 27 Dec 2024 15:58:28 +0100 Subject: [PATCH 09/20] Update discover.md with autogen-ext-mcp community package (#4826) Co-authored-by: Jack Gerrits --- .../docs/src/user-guide/extensions-user-guide/discover.md | 1 + 1 file changed, 1 insertion(+) diff --git a/python/packages/autogen-core/docs/src/user-guide/extensions-user-guide/discover.md b/python/packages/autogen-core/docs/src/user-guide/extensions-user-guide/discover.md index f0cb99529c7..1a43d176c1f 100644 --- a/python/packages/autogen-core/docs/src/user-guide/extensions-user-guide/discover.md +++ b/python/packages/autogen-core/docs/src/user-guide/extensions-user-guide/discover.md @@ -38,6 +38,7 @@ Find community samples and examples of how to use AutoGen |---|---|---| | [autogen-watsonx-client](https://github.com/tsinggggg/autogen-watsonx-client) | [PyPi](https://pypi.org/project/autogen-watsonx-client/) | Model client for [IBM watsonx.ai](https://www.ibm.com/products/watsonx-ai) | | [autogen-openaiext-client](https://github.com/vballoli/autogen-openaiext-client) | [PyPi](https://pypi.org/project/autogen-openaiext-client/) | Model client for other LLMs like Gemini, etc. through the OpenAI API | +| [autogen-ext-mcp](https://github.com/richard-gyiko/autogen-ext-mcp) | [PyPi](https://pypi.org/project/autogen-ext-mcp/) | Tool adapter for Model Context Protocol server tools | From 90a44b5b7dac7765c050477c74c36caa0a334984 Mon Sep 17 00:00:00 2001 From: Kimi <86585011+kimmywork@users.noreply.github.com> Date: Sat, 28 Dec 2024 00:12:44 +0800 Subject: [PATCH 10/20] fix: update LMStudio API Endpoint and added model name support (#4732) * fix: update LMStudio API Endpoint and added model name support * fix: ensure modelName non-null * fix: add braces around if branch --------- Co-authored-by: Ryan Sweet Co-authored-by: Xiaoyun Zhang --- dotnet/src/AutoGen/LMStudioConfig.cs | 22 ++++++++++++++++------ 1 file changed, 16 insertions(+), 6 deletions(-) diff --git a/dotnet/src/AutoGen/LMStudioConfig.cs b/dotnet/src/AutoGen/LMStudioConfig.cs index 4605b051142..29c60ff13f3 100644 --- a/dotnet/src/AutoGen/LMStudioConfig.cs +++ b/dotnet/src/AutoGen/LMStudioConfig.cs @@ -13,18 +13,28 @@ namespace AutoGen; /// public class LMStudioConfig : ILLMConfig { - public LMStudioConfig(string host, int port) + public LMStudioConfig(string host, int port, string modelName) { this.Host = host; this.Port = port; - this.Uri = new Uri($"http://{host}:{port}"); + this.Uri = new Uri($"http://{host}:{port}/v1"); + if (modelName == null) + { + throw new ArgumentNullException("modelName is a required property for LMStudioConfig and cannot be null"); + } + this.ModelName = modelName; } - public LMStudioConfig(Uri uri) + public LMStudioConfig(Uri uri, string modelName) { this.Uri = uri; this.Host = uri.Host; this.Port = uri.Port; + if (modelName == null) + { + throw new ArgumentNullException("modelName is a required property for LMStudioConfig and cannot be null"); + } + this.ModelName = modelName; } public string Host { get; } @@ -33,6 +43,8 @@ public LMStudioConfig(Uri uri) public Uri Uri { get; } + public string ModelName { get; } + internal ChatClient CreateChatClient() { var client = new OpenAIClient(new ApiKeyCredential("api-key"), new OpenAIClientOptions @@ -40,8 +52,6 @@ internal ChatClient CreateChatClient() Endpoint = this.Uri, }); - // model name doesn't matter for LM Studio - - return client.GetChatClient("model-name"); + return client.GetChatClient(this.ModelName); } } From 5bd91fb15ee94b3d60c65d7981084f38ecca12aa Mon Sep 17 00:00:00 2001 From: Jack Gerrits Date: Fri, 27 Dec 2024 12:21:39 -0500 Subject: [PATCH 11/20] Accept agent type in more places (#4829) * Accept agenttype in more places * remove type hint --- .../src/autogen_core/_default_subscription.py | 3 ++- .../src/autogen_core/_type_prefix_subscription.py | 8 ++++++-- .../autogen-core/src/autogen_core/_type_subscription.py | 8 ++++++-- 3 files changed, 14 insertions(+), 5 deletions(-) diff --git a/python/packages/autogen-core/src/autogen_core/_default_subscription.py b/python/packages/autogen-core/src/autogen_core/_default_subscription.py index d47c621094f..4c5251c8530 100644 --- a/python/packages/autogen-core/src/autogen_core/_default_subscription.py +++ b/python/packages/autogen-core/src/autogen_core/_default_subscription.py @@ -1,5 +1,6 @@ from typing import Callable, Type, TypeVar, overload +from ._agent_type import AgentType from ._base_agent import BaseAgent, subscription_factory from ._subscription_context import SubscriptionInstantiationContext from ._type_subscription import TypeSubscription @@ -16,7 +17,7 @@ class DefaultSubscription(TypeSubscription): agent_type (str, optional): The agent type to use for the subscription. Defaults to None, in which case it will attempt to detect the agent type based on the instantiation context. """ - def __init__(self, topic_type: str = "default", agent_type: str | None = None): + def __init__(self, topic_type: str = "default", agent_type: str | AgentType | None = None): if agent_type is None: try: agent_type = SubscriptionInstantiationContext.agent_type().type diff --git a/python/packages/autogen-core/src/autogen_core/_type_prefix_subscription.py b/python/packages/autogen-core/src/autogen_core/_type_prefix_subscription.py index 4c88f12a419..9e0d5268398 100644 --- a/python/packages/autogen-core/src/autogen_core/_type_prefix_subscription.py +++ b/python/packages/autogen-core/src/autogen_core/_type_prefix_subscription.py @@ -1,6 +1,7 @@ import uuid from ._agent_id import AgentId +from ._agent_type import AgentType from ._subscription import Subscription from ._topic import TopicId from .exceptions import CantHandleException @@ -30,9 +31,12 @@ class TypePrefixSubscription(Subscription): agent_type (str): Agent type to handle this subscription """ - def __init__(self, topic_type_prefix: str, agent_type: str): + def __init__(self, topic_type_prefix: str, agent_type: str | AgentType): self._topic_type_prefix = topic_type_prefix - self._agent_type = agent_type + if isinstance(agent_type, AgentType): + self._agent_type = agent_type.type + else: + self._agent_type = agent_type self._id = str(uuid.uuid4()) @property diff --git a/python/packages/autogen-core/src/autogen_core/_type_subscription.py b/python/packages/autogen-core/src/autogen_core/_type_subscription.py index 4ad815418fc..14d599b5630 100644 --- a/python/packages/autogen-core/src/autogen_core/_type_subscription.py +++ b/python/packages/autogen-core/src/autogen_core/_type_subscription.py @@ -1,6 +1,7 @@ import uuid from ._agent_id import AgentId +from ._agent_type import AgentType from ._subscription import Subscription from ._topic import TopicId from .exceptions import CantHandleException @@ -29,9 +30,12 @@ class TypeSubscription(Subscription): agent_type (str): Agent type to handle this subscription """ - def __init__(self, topic_type: str, agent_type: str): + def __init__(self, topic_type: str, agent_type: str | AgentType): self._topic_type = topic_type - self._agent_type = agent_type + if isinstance(agent_type, AgentType): + self._agent_type = agent_type.type + else: + self._agent_type = agent_type self._id = str(uuid.uuid4()) @property From 461605869c8164317da4ecf89f3984b3b4006f79 Mon Sep 17 00:00:00 2001 From: Jack Gerrits Date: Fri, 27 Dec 2024 12:52:36 -0500 Subject: [PATCH 12/20] Update links in extension page to fix 404 (#4827) Update links in extension page --- .../docs/src/user-guide/extensions-user-guide/index.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/python/packages/autogen-core/docs/src/user-guide/extensions-user-guide/index.md b/python/packages/autogen-core/docs/src/user-guide/extensions-user-guide/index.md index a60b9447ad1..291138af07b 100644 --- a/python/packages/autogen-core/docs/src/user-guide/extensions-user-guide/index.md +++ b/python/packages/autogen-core/docs/src/user-guide/extensions-user-guide/index.md @@ -31,14 +31,14 @@ AutoGen is designed to be extensible. The `autogen-ext` package contains many di :gutter: 3 :::{grid-item-card} {fas}`magnifying-glass;pst-color-primary` Discover -:link: ./installation.html +:link: ./discover.html -How to install AgentChat +Discover community extensions and samples ::: :::{grid-item-card} {fas}`code;pst-color-primary` Create your own -:link: ./quickstart.html +:link: ./create-your-own.html -Build your first agent +Create your own extension ::: :::: From fadff4aece7541ad65c1b4406b0639a235031b1c Mon Sep 17 00:00:00 2001 From: Jack Gerrits Date: Fri, 27 Dec 2024 13:11:42 -0500 Subject: [PATCH 13/20] Fix definition of workspace package, remove uv pin (#4830) * Fix definition of workspace package, remove uv pin * add --all-packages * pin docs uv versions for older project structure * try old version to verify CI * Use workflow target * change syntax * change check * try with var in matrix * add all packages to workspace * remove project table --- .github/workflows/checks.yml | 8 ----- .github/workflows/codeql.yml | 3 +- .github/workflows/docs.yml | 30 +++++++++---------- .github/workflows/dotnet-build.yml | 9 ++---- .github/workflows/single-python-package.yml | 1 - python/packages/agbench/pyproject.toml | 4 +-- .../packages/autogen-agentchat/pyproject.toml | 4 --- python/packages/autogen-core/pyproject.toml | 5 ++-- python/packages/autogen-ext/pyproject.toml | 4 +-- .../packages/autogen-magentic-one/README.md | 24 +++++++-------- .../autogen-magentic-one/pyproject.toml | 4 +-- .../autogen-test-utils/pyproject.toml | 4 --- .../component-schema-gen/pyproject.toml | 4 --- python/pyproject.toml | 17 +++++++---- .../new-package/hooks/post_gen_project.py | 17 +++++++++++ .../new-package/hooks/pre_gen_project.py | 6 ++-- .../pyproject.toml | 4 +-- python/uv.lock | 23 +++++++------- 18 files changed, 86 insertions(+), 85 deletions(-) diff --git a/.github/workflows/checks.yml b/.github/workflows/checks.yml index c01b3bfd444..6d99af595cf 100644 --- a/.github/workflows/checks.yml +++ b/.github/workflows/checks.yml @@ -18,7 +18,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -37,7 +36,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -66,7 +64,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -95,7 +92,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -122,7 +118,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -147,7 +142,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -169,7 +163,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -188,7 +181,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml index c7776791b58..6c2ca98cced 100644 --- a/.github/workflows/codeql.yml +++ b/.github/workflows/codeql.yml @@ -61,7 +61,7 @@ jobs: - name: Checkout repository uses: actions/checkout@v4 - - name: Set up Python + - name: Set up Python uses: actions/setup-python@v5 with: python-version: 3.11 @@ -76,7 +76,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - run: uv sync --locked --all-extras working-directory: ./python - name: Prepare python venv diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index cf205af09f1..35cc7c1378b 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -31,19 +31,20 @@ jobs: matrix: version: [ - { ref: main, dest-dir: dev }, - { ref: "v0.4.0.dev0", dest-dir: "0.4.0.dev0" }, - { ref: "v0.4.0.dev1", dest-dir: "0.4.0.dev1" }, - { ref: "v0.4.0.dev2", dest-dir: "0.4.0.dev2" }, - { ref: "v0.4.0.dev3", dest-dir: "0.4.0.dev3" }, - { ref: "v0.4.0.dev4", dest-dir: "0.4.0.dev4" }, - { ref: "v0.4.0.dev5", dest-dir: "0.4.0.dev5" }, - { ref: "v0.4.0.dev6", dest-dir: "0.4.0.dev6" }, - { ref: "v0.4.0.dev7", dest-dir: "0.4.0.dev7" }, - { ref: "v0.4.0.dev8", dest-dir: "0.4.0.dev8" }, - { ref: "v0.4.0.dev9", dest-dir: "0.4.0.dev9" }, - { ref: "v0.4.0.dev10", dest-dir: "0.4.0.dev10" }, - { ref: "v0.4.0.dev11", dest-dir: "0.4.0.dev11" }, + # For main use the workflow target + { ref: "${{github.ref}}", dest-dir: dev, uv-version: "0.5.13" }, + { ref: "v0.4.0.dev0", dest-dir: "0.4.0.dev0", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev1", dest-dir: "0.4.0.dev1", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev2", dest-dir: "0.4.0.dev2", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev3", dest-dir: "0.4.0.dev3", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev4", dest-dir: "0.4.0.dev4", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev5", dest-dir: "0.4.0.dev5", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev6", dest-dir: "0.4.0.dev6", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev7", dest-dir: "0.4.0.dev7", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev8", dest-dir: "0.4.0.dev8", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev9", dest-dir: "0.4.0.dev9", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev10", dest-dir: "0.4.0.dev10", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev11", dest-dir: "0.4.0.dev11", uv-version: "0.5.11" }, ] steps: - name: Checkout @@ -54,7 +55,7 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" + version: ${{ matrix.version.uv-version }} - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -103,7 +104,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" diff --git a/.github/workflows/dotnet-build.yml b/.github/workflows/dotnet-build.yml index e1fa05095d9..06a9713dfcc 100644 --- a/.github/workflows/dotnet-build.yml +++ b/.github/workflows/dotnet-build.yml @@ -79,7 +79,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - run: uv sync --locked --all-extras working-directory: ./python - name: Prepare python venv @@ -104,10 +103,10 @@ jobs: dotnet build --no-restore --configuration Release -bl /p:SignAssembly=true - name: Unit Test run: dotnet test --no-build -bl --configuration Release --filter type=!integration - + integration-test: strategy: - fail-fast: true + fail-fast: true matrix: os: [ ubuntu-latest] version: [ net8.0 ] @@ -123,7 +122,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -208,7 +206,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - uses: actions/setup-python@v5 with: python-version: "3.11" @@ -302,4 +299,4 @@ jobs: env: MYGET_TOKEN: ${{ secrets.MYGET_TOKEN }} continue-on-error: true - + diff --git a/.github/workflows/single-python-package.yml b/.github/workflows/single-python-package.yml index d8d2c66a131..b4657a5f516 100644 --- a/.github/workflows/single-python-package.yml +++ b/.github/workflows/single-python-package.yml @@ -35,7 +35,6 @@ jobs: - uses: astral-sh/setup-uv@v5 with: enable-cache: true - version: "0.5.11" - run: uv build --package ${{ github.event.inputs.package }} --out-dir dist/ working-directory: python - name: Publish package to PyPI diff --git a/python/packages/agbench/pyproject.toml b/python/packages/agbench/pyproject.toml index 7cdfc89c0ec..de5f9df22af 100644 --- a/python/packages/agbench/pyproject.toml +++ b/python/packages/agbench/pyproject.toml @@ -28,8 +28,8 @@ dependencies = [ "scipy" ] -[tool.uv] -dev-dependencies = [ +[dependency-groups] +dev = [ "types-tabulate", "types-docker" ] diff --git a/python/packages/autogen-agentchat/pyproject.toml b/python/packages/autogen-agentchat/pyproject.toml index 5f11afc0775..0e586ea44c5 100644 --- a/python/packages/autogen-agentchat/pyproject.toml +++ b/python/packages/autogen-agentchat/pyproject.toml @@ -18,10 +18,6 @@ dependencies = [ "autogen-core==0.4.0.dev11", ] -[tool.uv] -dev-dependencies = [] - - [tool.ruff] extend = "../../pyproject.toml" include = ["src/**", "tests/*.py"] diff --git a/python/packages/autogen-core/pyproject.toml b/python/packages/autogen-core/pyproject.toml index 9602e0f8d80..116b2ced851 100644 --- a/python/packages/autogen-core/pyproject.toml +++ b/python/packages/autogen-core/pyproject.toml @@ -28,8 +28,9 @@ dependencies = [ "jsonref~=1.1.0", ] -[tool.uv] -dev-dependencies = [ + +[dependency-groups] +dev = [ "autogen_test_utils", "aiofiles", "azure-identity", diff --git a/python/packages/autogen-ext/pyproject.toml b/python/packages/autogen-ext/pyproject.toml index 0d04e747ea2..522de50e7dc 100644 --- a/python/packages/autogen-ext/pyproject.toml +++ b/python/packages/autogen-ext/pyproject.toml @@ -56,8 +56,8 @@ grpc = [ [tool.hatch.build.targets.wheel] packages = ["src/autogen_ext"] -[tool.uv] -dev-dependencies = [ +[dependency-groups] +dev = [ "autogen_test_utils" ] diff --git a/python/packages/autogen-magentic-one/README.md b/python/packages/autogen-magentic-one/README.md index 5b95154e871..8d81ad7ceb1 100644 --- a/python/packages/autogen-magentic-one/README.md +++ b/python/packages/autogen-magentic-one/README.md @@ -35,15 +35,15 @@ Find additional information about Magentic-one in our [blog post](https://aka.ms Magentic-One work is based on a multi-agent architecture where a lead Orchestrator agent is responsible for high-level planning, directing other agents and tracking task progress. The Orchestrator begins by creating a plan to tackle the task, gathering needed facts and educated guesses in a Task Ledger that is maintained. At each step of its plan, the Orchestrator creates a Progress Ledger where it self-reflects on task progress and checks whether the task is completed. If the task is not yet completed, it assigns one of Magentic-One other agents a subtask to complete. After the assigned agent completes its subtask, the Orchestrator updates the Progress Ledger and continues in this way until the task is complete. If the Orchestrator finds that progress is not being made for enough steps, it can update the Task Ledger and create a new plan. This is illustrated in the figure above; the Orchestrator work is thus divided into an outer loop where it updates the Task Ledger and an inner loop to update the Progress Ledger. Overall, Magentic-One consists of the following agents: -- Orchestrator: the lead agent responsible for task decomposition and planning, directing other agents in executing subtasks, tracking overall progress, and taking corrective actions as needed +- Orchestrator: the lead agent responsible for task decomposition and planning, directing other agents in executing subtasks, tracking overall progress, and taking corrective actions as needed - WebSurfer: This is an LLM-based agent that is proficient in commanding and managing the state of a Chromium-based web browser. With each incoming request, the WebSurfer performs an action on the browser then reports on the new state of the web page The action space of the WebSurfer includes navigation (e.g. visiting a URL, performing a web search); web page actions (e.g., clicking and typing); and reading actions (e.g., summarizing or answering questions). The WebSurfer relies on the accessibility tree of the browser and on set-of-marks prompting to perform its actions. - FileSurfer: This is an LLM-based agent that commands a markdown-based file preview application to read local files of most types. The FileSurfer can also perform common navigation tasks such as listing the contents of directories and navigating a folder structure. - Coder: This is an LLM-based agent specialized through its system prompt for writing code, analyzing information collected from the other agents, or creating new artifacts. - ComputerTerminal: Finally, ComputerTerminal provides the team with access to a console shell where the Coder’s programs can be executed, and where new programming libraries can be installed. -Together, Magentic-One’s agents provide the Orchestrator with the tools and capabilities that it needs to solve a broad variety of open-ended problems, as well as the ability to autonomously adapt to, and act in, dynamic and ever-changing web and file-system environments. +Together, Magentic-One’s agents provide the Orchestrator with the tools and capabilities that it needs to solve a broad variety of open-ended problems, as well as the ability to autonomously adapt to, and act in, dynamic and ever-changing web and file-system environments. -While the default multimodal LLM we use for all agents is GPT-4o, Magentic-One is model agnostic and can incorporate heterogonous models to support different capabilities or meet different cost requirements when getting tasks done. For example, it can use different LLMs and SLMs and their specialized versions to power different agents. We recommend a strong reasoning model for the Orchestrator agent such as GPT-4o. In a different configuration of Magentic-One, we also experiment with using OpenAI o1-preview for the outer loop of the Orchestrator and for the Coder, while other agents continue to use GPT-4o. +While the default multimodal LLM we use for all agents is GPT-4o, Magentic-One is model agnostic and can incorporate heterogonous models to support different capabilities or meet different cost requirements when getting tasks done. For example, it can use different LLMs and SLMs and their specialized versions to power different agents. We recommend a strong reasoning model for the Orchestrator agent such as GPT-4o. In a different configuration of Magentic-One, we also experiment with using OpenAI o1-preview for the outer loop of the Orchestrator and for the Coder, while other agents continue to use GPT-4o. ### Logging in Team One Agents @@ -71,13 +71,13 @@ You can install the Magentic-One package and then run the example code to see ho source .venv/bin/activate ``` For Windows, run `.venv\Scripts\activate` to activate the environment. - + 2. Install magentic-one from source: ```bash cd packages/autogen-magentic-one pip install -e . ``` - + The following instructions are for running the example code: 3. Configure the environment variables for the chat completion client. See instructions below [Environment Configuration for Chat Completion Client](#environment-configuration-for-chat-completion-client). @@ -89,11 +89,11 @@ playwright install --with-deps chromium ``` 6. Now you can run the example code to see how the agents work together to accomplish a task. -> [!CAUTION] -> The example code may download files from the internet, execute code, and interact with web pages. Ensure you are in a safe environment before running the example code. +> [!CAUTION] +> The example code may download files from the internet, execute code, and interact with web pages. Ensure you are in a safe environment before running the example code. > [!NOTE] -> You will need to ensure Docker is running prior to running the example. +> You will need to ensure Docker is running prior to running the example. ```bash @@ -113,7 +113,7 @@ playwright install --with-deps chromium - hil_mode: (Optional) Enable human-in-the-loop mode (default: disabled) - save_screenshots: (Optional) Save screenshots of browser (default: disabled) -7. [Preview] We have a preview API for Magentic-One. +7. [Preview] We have a preview API for Magentic-One. You can use the `MagenticOneHelper` class to interact with the system and stream logs. See the [interface README](interface/README.md) for more details. @@ -146,7 +146,7 @@ To configure for Azure OpenAI service, set the following environment variables: This project uses Azure OpenAI service with [Entra ID authentcation by default](https://learn.microsoft.com/azure/ai-services/openai/how-to/managed-identity). If you run the examples on a local device, you can use the Azure CLI cached credentials for testing: -Log in to Azure using `az login`, and then run the examples. The account used must have [RBAC permissions](https://learn.microsoft.com/azure/ai-services/openai/how-to/role-based-access-control) like `Azure Cognitive Services OpenAI User` for the OpenAI service; otherwise, you will receive the error: Principal does not have access to API/Operation. +Log in to Azure using `az login`, and then run the examples. The account used must have [RBAC permissions](https://learn.microsoft.com/azure/ai-services/openai/how-to/role-based-access-control) like `Azure Cognitive Services OpenAI User` for the OpenAI service; otherwise, you will receive the error: Principal does not have access to API/Operation. Note that even if you are the owner of the subscription, you still need to grant the necessary Azure Cognitive Services OpenAI permissions to call the API. @@ -178,12 +178,12 @@ export BING_API_KEY=xxxxxxx ``` @misc{fourney2024magenticonegeneralistmultiagentsolving, - title={Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks}, + title={Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks}, author={Adam Fourney and Gagan Bansal and Hussein Mozannar and Cheng Tan and Eduardo Salinas and Erkang and Zhu and Friederike Niedtner and Grace Proebsting and Griffin Bassman and Jack Gerrits and Jacob Alber and Peter Chang and Ricky Loynd and Robert West and Victor Dibia and Ahmed Awadallah and Ece Kamar and Rafah Hosn and Saleema Amershi}, year={2024}, eprint={2411.04468}, archivePrefix={arXiv}, primaryClass={cs.AI}, - url={https://arxiv.org/abs/2411.04468}, + url={https://arxiv.org/abs/2411.04468}, } ``` diff --git a/python/packages/autogen-magentic-one/pyproject.toml b/python/packages/autogen-magentic-one/pyproject.toml index 65e71dd8496..df1b0f2d150 100644 --- a/python/packages/autogen-magentic-one/pyproject.toml +++ b/python/packages/autogen-magentic-one/pyproject.toml @@ -38,8 +38,8 @@ dependencies = [ "pydantic<3.0.0,>=2.0.0", ] -[tool.uv] -dev-dependencies = [ +[dependency-groups] +dev = [ "aiofiles", "types-aiofiles", "types-requests", diff --git a/python/packages/autogen-test-utils/pyproject.toml b/python/packages/autogen-test-utils/pyproject.toml index 6e2f2de52b9..22b0ba073ff 100644 --- a/python/packages/autogen-test-utils/pyproject.toml +++ b/python/packages/autogen-test-utils/pyproject.toml @@ -11,10 +11,6 @@ dependencies = ["autogen-core", ] -[tool.uv] -dev-dependencies = [] - - [tool.ruff] extend = "../../pyproject.toml" include = ["src/**"] diff --git a/python/packages/component-schema-gen/pyproject.toml b/python/packages/component-schema-gen/pyproject.toml index 8a45d6e5410..272142601ee 100644 --- a/python/packages/component-schema-gen/pyproject.toml +++ b/python/packages/component-schema-gen/pyproject.toml @@ -22,10 +22,6 @@ dependencies = [ [project.scripts] gen-component-schema = "component_schema_gen.__main__:main" -[tool.uv] -dev-dependencies = [] - - [tool.ruff] extend = "../../pyproject.toml" include = ["src/**"] diff --git a/python/pyproject.toml b/python/pyproject.toml index 5829a09ab03..ba5f987a419 100644 --- a/python/pyproject.toml +++ b/python/pyproject.toml @@ -1,8 +1,5 @@ -[tool.uv.workspace] -members = ["packages/*"] - -[tool.uv] -dev-dependencies = [ +[dependency-groups] +dev = [ "pyright==1.1.389", "mypy==1.13.0", "ruff==0.4.8", @@ -20,13 +17,21 @@ dev-dependencies = [ "cookiecutter", "poethepoet", "tomli", + "tomli-w" ] +[tool.uv.workspace] +members = ["packages/*"] + [tool.uv.sources] +agbench = { workspace = true } +autogen-agentchat = { workspace = true } autogen-core = { workspace = true } autogen-ext = { workspace = true } -autogen-agentchat = { workspace = true } +autogen-magentic-one = { workspace = true } +autogenstudio = { workspace = true } autogen-test-utils = { workspace = true } +component-schema-gen = { workspace = true } [tool.ruff] line-length = 120 diff --git a/python/templates/new-package/hooks/post_gen_project.py b/python/templates/new-package/hooks/post_gen_project.py index 491d1284c78..6fc5d446ff0 100644 --- a/python/templates/new-package/hooks/post_gen_project.py +++ b/python/templates/new-package/hooks/post_gen_project.py @@ -1,7 +1,24 @@ import os import shutil +from pathlib import Path +import tomli_w +import tomllib source_dir = os.getcwd() target_dir = "{{ cookiecutter.__final_destination }}" shutil.move(source_dir, target_dir) + +THIS_FILE_DIR = Path(__file__).parent + +# Add the package to the workspace def + +workspace_def_path = THIS_FILE_DIR / ".." / ".." / ".." / "pyproject.toml" + +with workspace_def_path.open("rb") as f: + config = tomllib.load(f) + +config["tool"]["uv"]["sources"]["{{ cookiecutter.package_name }}"] = {"workspace": True} + +with workspace_def_path.open("wb") as f: + tomli_w.dump(config, f) diff --git a/python/templates/new-package/hooks/pre_gen_project.py b/python/templates/new-package/hooks/pre_gen_project.py index 3e1b246e61e..1a85fb8595e 100644 --- a/python/templates/new-package/hooks/pre_gen_project.py +++ b/python/templates/new-package/hooks/pre_gen_project.py @@ -2,16 +2,16 @@ import sys from packaging import version -MODULE_REGEX = r'^[a-zA-Z][\-a-zA-Z0-9]+$' +MODULE_REGEX = r"^[a-zA-Z][\-a-zA-Z0-9]+$" -package_name = '{{ cookiecutter.package_name }}' +package_name = "{{ cookiecutter.package_name }}" at_least_one_error = False if not re.match(MODULE_REGEX, package_name): print(f'ERROR: "{package_name}" must use kebab case') at_least_one_error = True -packaging_version = '{{ cookiecutter.version }}' +packaging_version = "{{ cookiecutter.version }}" # Check version format using version.VERSION_PATTERN if not re.match(version.VERSION_PATTERN, packaging_version, re.VERBOSE | re.IGNORECASE): diff --git a/python/templates/new-package/{{cookiecutter.package_name}}/pyproject.toml b/python/templates/new-package/{{cookiecutter.package_name}}/pyproject.toml index 4a62c585402..a313e6c2861 100644 --- a/python/templates/new-package/{{cookiecutter.package_name}}/pyproject.toml +++ b/python/templates/new-package/{{cookiecutter.package_name}}/pyproject.toml @@ -20,8 +20,8 @@ dependencies = [ {% endif %} ] -[tool.uv] -dev-dependencies = [] +[dependency-groups] +dev = [] [tool.ruff] diff --git a/python/uv.lock b/python/uv.lock index afb0c232607..151634a4faa 100644 --- a/python/uv.lock +++ b/python/uv.lock @@ -27,7 +27,9 @@ members = [ "autogenstudio", "component-schema-gen", ] -requirements = [ + +[manifest.dependency-groups] +dev = [ { name = "cookiecutter" }, { name = "grpcio-tools", specifier = "~=1.62.0" }, { name = "mypy", specifier = "==1.13.0" }, @@ -43,6 +45,7 @@ requirements = [ { name = "rich" }, { name = "ruff", specifier = "==0.4.8" }, { name = "tomli" }, + { name = "tomli-w" }, { name = "typer" }, ] @@ -341,9 +344,6 @@ dependencies = [ [package.metadata] requires-dist = [{ name = "autogen-core", editable = "packages/autogen-core" }] -[package.metadata.requires-dev] -dev = [] - [[package]] name = "autogen-core" version = "0.4.0.dev11" @@ -628,9 +628,6 @@ dependencies = [ [package.metadata] requires-dist = [{ name = "autogen-core", editable = "packages/autogen-core" }] -[package.metadata.requires-dev] -dev = [] - [[package]] name = "autogenstudio" version = "0.4.0.dev41" @@ -957,9 +954,6 @@ requires-dist = [ { name = "autogen-ext", editable = "packages/autogen-ext" }, ] -[package.metadata.requires-dev] -dev = [] - [[package]] name = "cookiecutter" version = "2.6.0" @@ -4658,6 +4652,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/cf/db/ce8eda256fa131af12e0a76d481711abe4681b6923c27efb9a255c9e4594/tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38", size = 13237 }, ] +[[package]] +name = "tomli-w" +version = "1.1.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/d4/19/b65f1a088ee23e37cdea415b357843eca8b1422a7b11a9eee6e35d4ec273/tomli_w-1.1.0.tar.gz", hash = "sha256:49e847a3a304d516a169a601184932ef0f6b61623fe680f836a2aa7128ed0d33", size = 6929 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c4/ac/ce90573ba446a9bbe65838ded066a805234d159b4446ae9f8ec5bbd36cbd/tomli_w-1.1.0-py3-none-any.whl", hash = "sha256:1403179c78193e3184bfaade390ddbd071cba48a32a2e62ba11aae47490c63f7", size = 6440 }, +] + [[package]] name = "torch" version = "2.5.1" From b9bd8b0c64dbd6c7ebeff47e5818c64e5a7c2cf4 Mon Sep 17 00:00:00 2001 From: Eric Zhu Date: Fri, 27 Dec 2024 10:20:52 -0800 Subject: [PATCH 14/20] human-in-the-loop section for agentchat tutorial (#4832) * human-in-the-loop section for agentchat tutorial --- .../agents/_user_proxy_agent.py | 2 +- .../human-in-the-loop-termination.drawio | 64 +++ .../human-in-the-loop-user-proxy.drawio | 92 ++++ .../user-guide/agentchat-user-guide/index.md | 2 +- .../human-in-the-loop-termination.svg | 3 + .../tutorial/human-in-the-loop-user-proxy.svg | 3 + .../tutorial/human-in-the-loop.ipynb | 439 ++++++++++++++++++ 7 files changed, 603 insertions(+), 2 deletions(-) create mode 100644 python/packages/autogen-core/docs/drawio/human-in-the-loop-termination.drawio create mode 100644 python/packages/autogen-core/docs/drawio/human-in-the-loop-user-proxy.drawio create mode 100644 python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-termination.svg create mode 100644 python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-user-proxy.svg create mode 100644 python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.ipynb diff --git a/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py b/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py index 6b8ab305579..1695be4267c 100644 --- a/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py +++ b/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py @@ -48,7 +48,7 @@ class UserProxyAgent(BaseChatAgent): You can run the team again with the user input. This way, the state of the team can be saved and restored when the user responds. - See `Pause for User Input `_ for more information. + See `Human-in-the-loop `_ for more information. Example: Simple usage case:: diff --git a/python/packages/autogen-core/docs/drawio/human-in-the-loop-termination.drawio b/python/packages/autogen-core/docs/drawio/human-in-the-loop-termination.drawio new file mode 100644 index 00000000000..1c4b1564b4c --- /dev/null +++ b/python/packages/autogen-core/docs/drawio/human-in-the-loop-termination.drawio @@ -0,0 +1,64 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/python/packages/autogen-core/docs/drawio/human-in-the-loop-user-proxy.drawio b/python/packages/autogen-core/docs/drawio/human-in-the-loop-user-proxy.drawio new file mode 100644 index 00000000000..6b392341ea5 --- /dev/null +++ b/python/packages/autogen-core/docs/drawio/human-in-the-loop-user-proxy.drawio @@ -0,0 +1,92 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md index d5df491a69a..bfc6e8859b1 100644 --- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md @@ -61,6 +61,7 @@ tutorial/models tutorial/messages tutorial/agents tutorial/teams +tutorial/human-in-the-loop tutorial/selector-group-chat tutorial/swarm tutorial/termination @@ -75,4 +76,3 @@ tutorial/state examples/index ``` - diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-termination.svg b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-termination.svg new file mode 100644 index 00000000000..6bfda4dd094 --- /dev/null +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-termination.svg @@ -0,0 +1,3 @@ + + +
Agent 2
Agent 2
Agent 1
Agent 1
Agent 3
Agent 3
RoundRobinGroupChat
RoundRobinGroupChat
Application/User
Application/User
Task/Feedback
Task/Feedback
TaskResult
TaskResult
Termination
Condition
Termination...
Orchestrator
Orchestrator
Starts / Resumes the Team
Starts / Resumes the Team
Saves the Team's State
Saves the Team's State \ No newline at end of file diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-user-proxy.svg b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-user-proxy.svg new file mode 100644 index 00000000000..77d9a2372c5 --- /dev/null +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-user-proxy.svg @@ -0,0 +1,3 @@ + + +
UserProxyAgent
UserProxyAgent
Agent 1
Agent 1
Agent 3
Agent 3
RoundRobinGroupChat
RoundRobinGroupChat
Application/User
Application/User
Task
Task
TaskResult
TaskResult
Termination
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Orchestrator
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User Input Response
User Input Response
Request for User Input
Request for User Input \ No newline at end of file diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.ipynb new file mode 100644 index 00000000000..7862feceae6 --- /dev/null +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.ipynb @@ -0,0 +1,439 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Human-in-the-Loop\n", + "\n", + "In the previous section [Teams](./teams.ipynb), we have seen how to create, observe,\n", + "and control a team of agents.\n", + "This section will focus on how to interact with the team from your application,\n", + "and provide human feedback to the team.\n", + "\n", + "There are two main ways to interact with the team from your application:\n", + "\n", + "1. During a team's run -- execution of {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` or {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream`, provide feedback through a {py:class}`~autogen_agentchat.agents.UserProxyAgent`.\n", + "2. Once the run terminates, provide feedback through input to the next call to {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` or {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream`.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Providing Feedback During a Run\n", + "\n", + "The {py:class}`~autogen_agentchat.agents.UserProxyAgent` is a special built-in agent\n", + "that acts as a proxy for a user to provide feedback to the team.\n", + "\n", + "To use the {py:class}`~autogen_agentchat.agents.UserProxyAgent`, you can create an instance of it\n", + "and include it in the team before running the team.\n", + "The team will decide when to call the {py:class}`~autogen_agentchat.agents.UserProxyAgent`\n", + "to ask for feedback from the user.\n", + "\n", + "The following diagram illustrates how you can use \n", + "{py:class}`~autogen_agentchat.agents.UserProxyAgent`\n", + "to get feedback from the user during a team's run:\n", + "\n", + "![human-in-the-loop-user-proxy](./human-in-the-loop-user-proxy.svg)\n", + "\n", + "The bold arrows indicates the flow of control during a team's run:\n", + "when the team calls the {py:class}`~autogen_agentchat.agents.UserProxyAgent`,\n", + "it transfers the control to the application/user, and waits for the feedback;\n", + "once the feedback is provided, the control is transferred back to the team\n", + "and the team continues its execution.\n", + "\n", + "```{note}\n", + "When {py:class}`~autogen_agentchat.agents.UserProxyAgent` is called during a run,\n", + "it blocks the execution of the team until the user provides feedback or errors out.\n", + "This will hold up the team's progress and put the team in an unstable state\n", + "that cannot be saved or resumed.\n", + "```\n", + "\n", + "Due to the blocking nature of this approach, it is recommended to use it only for short interactions\n", + "that require immediate feedback from the user, such as asking for approval or disapproval\n", + "with a button click, or an alert requiring immediate attention otherwise failing the task.\n", + "\n", + "Here is an example of how to use the {py:class}`~autogen_agentchat.agents.UserProxyAgent`\n", + "in a {py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` for a poetry generation task:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "Write a 4-line poem about the ocean.\n", + "---------- assistant ----------\n", + "Waves whisper secrets to the shore’s embrace, \n", + "A dance of blue under the sun's warm grace. \n", + "Endless horizons where dreams take flight, \n", + "The ocean's heart glimmers, a canvas of light. \n", + "TERMINATE\n", + "[Prompt tokens: 46, Completion tokens: 49]\n", + "---------- user_proxy ----------\n", + "APPROVE\n", + "---------- Summary ----------\n", + "Number of messages: 3\n", + "Finish reason: Text 'APPROVE' mentioned\n", + "Total prompt tokens: 46\n", + "Total completion tokens: 49\n", + "Duration: 6.64 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='Write a 4-line poem about the ocean.', type='TextMessage'), TextMessage(source='assistant', models_usage=RequestUsage(prompt_tokens=46, completion_tokens=49), content=\"Waves whisper secrets to the shore’s embrace, \\nA dance of blue under the sun's warm grace. \\nEndless horizons where dreams take flight, \\nThe ocean's heart glimmers, a canvas of light. \\nTERMINATE\", type='TextMessage'), TextMessage(source='user_proxy', models_usage=None, content='APPROVE', type='TextMessage')], stop_reason=\"Text 'APPROVE' mentioned\")" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from autogen_agentchat.agents import AssistantAgent, UserProxyAgent\n", + "from autogen_agentchat.conditions import TextMentionTermination\n", + "from autogen_agentchat.teams import RoundRobinGroupChat\n", + "from autogen_agentchat.ui import Console\n", + "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", + "\n", + "# Create the agents.\n", + "model_client = OpenAIChatCompletionClient(model=\"gpt-4o-mini\")\n", + "assistant = AssistantAgent(\"assistant\", model_client=model_client)\n", + "user_proxy = UserProxyAgent(\"user_proxy\", input_func=input) # Use input() to get user input from console.\n", + "\n", + "# Create the termination condition which will end the conversation when the user says \"APPROVE\".\n", + "termination = TextMentionTermination(\"APPROVE\")\n", + "\n", + "# Create the team.\n", + "team = RoundRobinGroupChat([assistant, user_proxy], termination_condition=termination)\n", + "\n", + "# Run the conversation and stream to the console.\n", + "stream = team.run_stream(task=\"Write a 4-line poem about the ocean.\")\n", + "# Use asyncio.run(...) when running in a script.\n", + "await Console(stream)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the console output, you can see the team solicited feedback from the user\n", + "through `user_proxy` to approve the generated poem.\n", + "\n", + "You can provide your own input function to the {py:class}`~autogen_agentchat.agents.UserProxyAgent`\n", + "to customize the feedback process." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Providing Feedback to the Next Run\n", + "\n", + "Often times, an application or a user interacts with the team of agents in an interactive loop:\n", + "the team runs until termination, \n", + "the application or user provides feedback, and the team runs again with the feedback.\n", + "\n", + "This approach is useful in a persisted session\n", + "with asynchronous communication between the team and the application/user:\n", + "Once a team finishes a run, the application saves the state of the team,\n", + "puts it in a persistent storage, and resumes the team when the feedback arrives.\n", + "\n", + "```{note}\n", + "For how to save and load the state of a team, please refer to [Managing State](./state.ipynb).\n", + "This section will focus on the feedback mechanisms.\n", + "```\n", + "\n", + "The following diagram illustrates the flow of control in this approach:\n", + "\n", + "![human-in-the-loop-termination](./human-in-the-loop-termination.svg)\n", + "\n", + "There are two ways to implement this approach:\n", + "\n", + "- Set the maximum number of turns so that the team always stops after the specified number of turns.\n", + "- Use termination conditions such as {py:class}`~autogen_agentchat.conditions.TextMentionTermination` and {py:class}`~autogen_agentchat.conditions.HandoffTermination` to allow the team to decide when to stop and give control back, given the team's internal state.\n", + "\n", + "You can use both methods together to achieve your desired behavior." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Max Turns\n", + "\n", + "This method allows you to pause the team for user input by setting a maximum number of turns. For instance, you can configure the team to stop after the first agent responds by setting `max_turns` to 1. This is particularly useful in scenarios where continuous user engagement is required, such as in a chatbot.\n", + "\n", + "To implement this, set the `max_turns` parameter in the {py:meth}`~autogen_agentchat.teams.RoundRobinGroupChat` constructor.\n", + "\n", + "```python\n", + "team = RoundRobinGroupChat([...], max_turns=1)\n", + "```\n", + "\n", + "Once the team stops, the turn count will be reset. When you resume the team,\n", + "it will start from 0 again. However, the team's internal state will be preserved,\n", + "for example, the {py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` will\n", + "resume from the next agent in the list with the same conversation history.\n", + "\n", + "```{note}\n", + "`max_turn` is specific to the team class and is currently only supported by\n", + "{py:class}`~autogen_agentchat.teams.RoundRobinGroupChat`, {py:class}`~autogen_agentchat.teams.SelectorGroupChat`, and {py:class}`~autogen_agentchat.teams.Swarm`.\n", + "When used with termination conditions, the team will stop when either condition is met.\n", + "```\n", + "\n", + "Here is an example of how to use `max_turns` in a {py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` for a poetry generation task\n", + "with a maximum of 1 turn:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "Write a 4-line poem about the ocean.\n", + "---------- assistant ----------\n", + "Endless waves in a dance with the shore, \n", + "Whispers of secrets in tales from the roar, \n", + "Beneath the vast sky, where horizons blend, \n", + "The ocean’s embrace is a timeless friend. \n", + "TERMINATE\n", + "[Prompt tokens: 46, Completion tokens: 48]\n", + "---------- Summary ----------\n", + "Number of messages: 2\n", + "Finish reason: Maximum number of turns 1 reached.\n", + "Total prompt tokens: 46\n", + "Total completion tokens: 48\n", + "Duration: 1.63 seconds\n", + "---------- user ----------\n", + "Can you make it about a person and its relationship with the ocean\n", + "---------- assistant ----------\n", + "She walks along the tide, where dreams intertwine, \n", + "With every crashing wave, her heart feels aligned, \n", + "In the ocean's embrace, her worries dissolve, \n", + "A symphony of solace, where her spirit evolves. \n", + "TERMINATE\n", + "[Prompt tokens: 117, Completion tokens: 49]\n", + "---------- Summary ----------\n", + "Number of messages: 2\n", + "Finish reason: Maximum number of turns 1 reached.\n", + "Total prompt tokens: 117\n", + "Total completion tokens: 49\n", + "Duration: 1.21 seconds\n" + ] + } + ], + "source": [ + "from autogen_agentchat.agents import AssistantAgent\n", + "from autogen_agentchat.teams import RoundRobinGroupChat\n", + "from autogen_agentchat.ui import Console\n", + "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", + "\n", + "# Create the agents.\n", + "model_client = OpenAIChatCompletionClient(model=\"gpt-4o-mini\")\n", + "assistant = AssistantAgent(\"assistant\", model_client=model_client)\n", + "\n", + "# Create the team setting a maximum number of turns to 1.\n", + "team = RoundRobinGroupChat([assistant], max_turns=1)\n", + "\n", + "task = \"Write a 4-line poem about the ocean.\"\n", + "while True:\n", + " # Run the conversation and stream to the console.\n", + " stream = team.run_stream(task=task)\n", + " # Use asyncio.run(...) when running in a script.\n", + " await Console(stream)\n", + " # Get the user response.\n", + " task = input(\"Enter your feedback (type 'exit' to leave): \")\n", + " if task.lower().strip() == \"exit\":\n", + " break" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can see that the team stopped immediately after one agent responded." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Termination Conditions\n", + "\n", + "We have already seen several examples of termination conditions in the previous sections.\n", + "In this section, we focus on {py:class}`~autogen_agentchat.conditions.HandoffTermination`\n", + "which stops the team when an agent sends a {py:class}`~autogen_agentchat.messages.HandoffMessage` message.\n", + "\n", + "Let's create a team with a single {py:class}`~autogen_agentchat.agents.AssistantAgent` agent\n", + "with a handoff setting, and run the team with a task that requires additional input from the user\n", + "because the agent doesn't have relevant tools to continue processing the task.\n", + "\n", + "```{note}\n", + "The model used with {py:class}`~autogen_agentchat.agents.AssistantAgent` must support tool call\n", + "to use the handoff feature.\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "What is the weather in New York?\n", + "---------- lazy_assistant ----------\n", + "[FunctionCall(id='call_nSjgvWCUYo5ccacBz7yzrPLN', arguments='{}', name='transfer_to_user')]\n", + "[Prompt tokens: 68, Completion tokens: 12]\n", + "---------- lazy_assistant ----------\n", + "[FunctionExecutionResult(content='Transfer to user.', call_id='call_nSjgvWCUYo5ccacBz7yzrPLN')]\n", + "---------- lazy_assistant ----------\n", + "Transfer to user.\n", + "---------- Summary ----------\n", + "Number of messages: 4\n", + "Finish reason: Handoff to user from lazy_assistant detected.\n", + "Total prompt tokens: 68\n", + "Total completion tokens: 12\n", + "Duration: 0.75 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='What is the weather in New York?', type='TextMessage'), ToolCallRequestEvent(source='lazy_assistant', models_usage=RequestUsage(prompt_tokens=68, completion_tokens=12), content=[FunctionCall(id='call_nSjgvWCUYo5ccacBz7yzrPLN', arguments='{}', name='transfer_to_user')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='lazy_assistant', models_usage=None, content=[FunctionExecutionResult(content='Transfer to user.', call_id='call_nSjgvWCUYo5ccacBz7yzrPLN')], type='ToolCallExecutionEvent'), HandoffMessage(source='lazy_assistant', models_usage=None, target='user', content='Transfer to user.', type='HandoffMessage')], stop_reason='Handoff to user from lazy_assistant detected.')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from autogen_agentchat.agents import AssistantAgent\n", + "from autogen_agentchat.base import Handoff\n", + "from autogen_agentchat.conditions import HandoffTermination, TextMentionTermination\n", + "from autogen_agentchat.teams import RoundRobinGroupChat\n", + "from autogen_agentchat.ui import Console\n", + "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", + "\n", + "# Create an OpenAI model client.\n", + "model_client = OpenAIChatCompletionClient(\n", + " model=\"gpt-4o-2024-08-06\",\n", + " # api_key=\"sk-...\", # Optional if you have an OPENAI_API_KEY env variable set.\n", + ")\n", + "\n", + "# Create a lazy assistant agent that always hands off to the user.\n", + "lazy_agent = AssistantAgent(\n", + " \"lazy_assistant\",\n", + " model_client=model_client,\n", + " handoffs=[Handoff(target=\"user\", message=\"Transfer to user.\")],\n", + " system_message=\"Always transfer to user when you don't know the answer. Respond 'TERMINATE' when task is complete.\",\n", + ")\n", + "\n", + "# Define a termination condition that checks for handoff message targetting helper and text \"TERMINATE\".\n", + "handoff_termination = HandoffTermination(target=\"user\")\n", + "text_termination = TextMentionTermination(\"TERMINATE\")\n", + "combined_termination = handoff_termination | text_termination\n", + "\n", + "# Create a single-agent team.\n", + "lazy_agent_team = RoundRobinGroupChat([lazy_agent], termination_condition=combined_termination)\n", + "\n", + "# Run the team and stream to the console.\n", + "task = \"What is the weather in New York?\"\n", + "await Console(lazy_agent_team.run_stream(task=task))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can see the team stopped due to the handoff message was detected.\n", + "Let's continue the team by providing the information the agent needs." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "The weather in New York is sunny.\n", + "---------- lazy_assistant ----------\n", + "Great to hear that it's sunny in New York! Is there anything else you'd like to know or discuss?\n", + "[Prompt tokens: 109, Completion tokens: 23]\n", + "---------- lazy_assistant ----------\n", + "TERMINATE\n", + "[Prompt tokens: 138, Completion tokens: 5]\n", + "---------- Summary ----------\n", + "Number of messages: 3\n", + "Finish reason: Text 'TERMINATE' mentioned\n", + "Total prompt tokens: 247\n", + "Total completion tokens: 28\n", + "Duration: 1.44 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='The weather in New York is sunny.', type='TextMessage'), TextMessage(source='lazy_assistant', models_usage=RequestUsage(prompt_tokens=109, completion_tokens=23), content=\"Great to hear that it's sunny in New York! Is there anything else you'd like to know or discuss?\", type='TextMessage'), TextMessage(source='lazy_assistant', models_usage=RequestUsage(prompt_tokens=138, completion_tokens=5), content='TERMINATE', type='TextMessage')], stop_reason=\"Text 'TERMINATE' mentioned\")" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "await Console(lazy_agent_team.run_stream(task=\"The weather in New York is sunny.\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can see the team continued after the user provided the information." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 2819515220b37b53e988cad406c426489b0272eb Mon Sep 17 00:00:00 2001 From: Eric Zhu Date: Fri, 27 Dec 2024 10:25:36 -0800 Subject: [PATCH 15/20] Improve agentchat tutorial Teams section (#4834) * update teams doc * Update * fmt --- .../user-guide/agentchat-user-guide/index.md | 2 +- .../agentchat-user-guide/tutorial/teams.ipynb | 1346 +++++++---------- 2 files changed, 586 insertions(+), 762 deletions(-) diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md index bfc6e8859b1..faadedc1611 100644 --- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md @@ -32,7 +32,7 @@ Build your first agent ::: :::{grid-item-card} {fas}`graduation-cap;pst-color-primary` Tutorial -:link: ./tutorial/index.html +:link: ./tutorial/models.html Step-by-step guide to using AgentChat ::: diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/teams.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/teams.ipynb index b62fbbe6ed2..c810c306908 100644 --- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/teams.ipynb +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/teams.ipynb @@ -1,764 +1,588 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Teams\n", - "\n", - "In this section you'll learn how to create a _multi-agent team_ (or simply team) using AutoGen. A team is a group of agents that work together to achieve a common goal.\n", - "\n", - "We'll first show you how to create and run a team. We'll then explain how to observe the team's behavior, which is crucial for debugging and understanding the team's performance, and common operations to control the team's behavior.\n", - "\n", - "We'll start by focusing on a simple team with consisting of a single agent (the baseline case) and use a round robin strategy to select the agent to act. We'll then show how to create a team with multiple agents and how to implement a more sophisticated strategy to select the agent to act." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Creating a Team\n", - "\n", - "{py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` is a simple yet effective team configuration where all agents share the same context and take turns responding in a round-robin fashion. Each agent, during its turn, broadcasts its response to all other agents, ensuring that the entire team maintains a consistent context.\n", - "\n", - "We will begin by creating a team with a single {py:class}`~autogen_agentchat.agents.AssistantAgent` and a {py:class}`~autogen_agentchat.conditions.TextMentionTermination` condition that stops the team when a specific word is detected in the agent's response.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from autogen_agentchat.agents import AssistantAgent\n", - "from autogen_agentchat.conditions import TextMentionTermination\n", - "from autogen_agentchat.teams import RoundRobinGroupChat\n", - "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", - "\n", - "# Create an OpenAI model client.\n", - "model_client = OpenAIChatCompletionClient(\n", - " model=\"gpt-4o-2024-08-06\",\n", - " # api_key=\"sk-...\", # Optional if you have an OPENAI_API_KEY env variable set.\n", - ")\n", - "\n", - "\n", - "# Define a tool that gets the weather for a city.\n", - "async def get_weather(city: str) -> str:\n", - " \"\"\"Get the weather for a city.\"\"\"\n", - " return f\"The weather in {city} is 72 degrees and Sunny.\"\n", - "\n", - "\n", - "# Create an assistant agent.\n", - "weather_agent = AssistantAgent(\n", - " \"assistant\",\n", - " model_client=model_client,\n", - " tools=[get_weather],\n", - " system_message=\"Respond 'TERMINATE' when task is complete.\",\n", - ")\n", - "\n", - "# Define a termination condition.\n", - "text_termination = TextMentionTermination(\"TERMINATE\")\n", - "\n", - "# Create a single-agent team.\n", - "single_agent_team = RoundRobinGroupChat([weather_agent], termination_condition=text_termination)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Running a Team\n", - "\n", - "Let's calls the {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` method\n", - "to start the team with a task." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='What is the weather in New York?'), ToolCallRequestEvent(source='assistant', models_usage=RequestUsage(prompt_tokens=70, completion_tokens=15), content=[FunctionCall(id='call_6qWxrK1VdEVSryXKyIVpwE0h', arguments='{\"city\":\"New York\"}', name='get_weather')]), ToolCallExecutionEvent(source='assistant', models_usage=None, content=[FunctionExecutionResult(content='The weather in New York is 72 degrees and Sunny.', call_id='call_6qWxrK1VdEVSryXKyIVpwE0h')]), TextMessage(source='assistant', models_usage=RequestUsage(prompt_tokens=96, completion_tokens=13), content='The weather in New York is 72 degrees and sunny.'), TextMessage(source='assistant', models_usage=RequestUsage(prompt_tokens=125, completion_tokens=4), content='TERMINATE')], stop_reason=\"Text 'TERMINATE' mentioned\")\n" - ] - } - ], - "source": [ - "async def run_team() -> None:\n", - " result = await single_agent_team.run(task=\"What is the weather in New York?\")\n", - " print(result)\n", - "\n", - "\n", - "# Use `asyncio.run(run_team())` when running in a script.\n", - "await run_team()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The team ran the same agent until the termination condition was met.\n", - "In this case, the termination condition was met when the word \"TERMINATE\" is detected in the\n", - "agent's response.\n", - "When the team stops, it returns a {py:class}`~autogen_agentchat.base.TaskResult` object with all the messages produced by the agents in the team." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Observability\n", - "\n", - "Similar to the agent's {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_messages_stream` method, you can stream the team's messages by calling the {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream` method. This method returns a generator that yields messages produced by the agents in the team as they are generated, with the final item being the task result.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "source='user' models_usage=None content='What is the weather in New York?'\n", - "source='assistant' models_usage=RequestUsage(prompt_tokens=70, completion_tokens=15) content=[FunctionCall(id='call_FcJlzgDmPUgGSKLjeGajFZ7V', arguments='{\"city\":\"New York\"}', name='get_weather')]\n", - "source='assistant' models_usage=None content=[FunctionExecutionResult(content='The weather in New York is 72 degrees and Sunny.', call_id='call_FcJlzgDmPUgGSKLjeGajFZ7V')]\n", - "source='assistant' models_usage=RequestUsage(prompt_tokens=96, completion_tokens=14) content='The weather in New York is currently 72 degrees and sunny.'\n", - "source='assistant' models_usage=RequestUsage(prompt_tokens=126, completion_tokens=4) content='TERMINATE'\n", - "Stop Reason: Text 'TERMINATE' mentioned\n" - ] - } - ], - "source": [ - "from autogen_agentchat.base import TaskResult\n", - "\n", - "\n", - "async def run_team_stream() -> None:\n", - " async for message in single_agent_team.run_stream(task=\"What is the weather in New York?\"):\n", - " if isinstance(message, TaskResult):\n", - " print(\"Stop Reason:\", message.stop_reason)\n", - " else:\n", - " print(message)\n", - "\n", - "\n", - "# Use `asyncio.run(run_team_stream())` when running in a script.\n", - "await run_team_stream()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As demonstrated in the example above, you can determine the reason why the team stopped by checking the {py:attr}`~autogen_agentchat.base.TaskResult.stop_reason` attribute.\n", - "\n", - "The {py:meth}`~autogen_agentchat.ui.Console` method provides a convenient way to print messages to the console with proper formatting.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------- user ----------\n", - "What is the weather in Seattle?\n", - "---------- assistant ----------\n", - "[FunctionCall(id='call_QBqpeKQlczRYIlCIzKh43Kha', arguments='{\"city\":\"Seattle\"}', name='get_weather')]\n", - "[Prompt tokens: 69, Completion tokens: 14]\n", - "---------- assistant ----------\n", - "[FunctionExecutionResult(content='The weather in Seattle is 72 degrees and Sunny.', call_id='call_QBqpeKQlczRYIlCIzKh43Kha')]\n", - "---------- assistant ----------\n", - "The weather in Seattle is currently 72 degrees and sunny.\n", - "[Prompt tokens: 93, Completion tokens: 13]\n", - "---------- assistant ----------\n", - "TERMINATE\n", - "[Prompt tokens: 122, Completion tokens: 4]\n", - "---------- Summary ----------\n", - "Number of messages: 5\n", - "Finish reason: Text 'TERMINATE' mentioned\n", - "Total prompt tokens: 284\n", - "Total completion tokens: 31\n", - "Duration: 1.82 seconds\n" - ] - } - ], - "source": [ - "from autogen_agentchat.ui import Console\n", - "\n", - "# Use `asyncio.run(single_agent_team.reset())` when running in a script.\n", - "await single_agent_team.reset() # Reset the team for the next run.\n", - "# Use `asyncio.run(single_agent_team.run_stream(task=\"What is the weather in Seattle?\"))` when running in a script.\n", - "await Console(\n", - " single_agent_team.run_stream(task=\"What is the weather in Seattle?\")\n", - ") # Stream the messages to the console." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Resetting a Team\n", - "\n", - "You can reset the team by calling the {py:meth}`~autogen_agentchat.teams.BaseGroupChat.reset` method. This method will clear the team's state, including all agents." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "await single_agent_team.reset() # Reset the team for the next run." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It is usually a good idea to reset the team if the next task is not related to the previous task.\n", - "However, if the next task is related to the previous task, you don't need to reset and you can instead resume. We will cover this in the next section." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "## Team Usage Guide\n", - "\n", - "We will now implement a slightly more complex team with multiple agents and learn how to resume the team after stopping it and even involve the user in the conversation.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Reflection Pattern\n", - "\n", - "We will now create a team with two agents that implement the _reflection_ pattern, a multi-agent design pattern where a critic agent evaluates the responses of a primary agent.\n", - "\n", - "Learn more about the reflection pattern using the [Core API](../../core-user-guide/design-patterns/reflection.ipynb).\n", - "\n", - "In this example, we will use the {py:class}`~autogen_agentchat.agents.AssistantAgent` class for both the primary and critic agents. We will combine the {py:class}`~autogen_agentchat.conditions.TextMentionTermination` and {py:class}`~autogen_agentchat.conditions.MaxMessageTermination` conditions to stop the team.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from autogen_agentchat.agents import AssistantAgent\n", - "from autogen_agentchat.conditions import MaxMessageTermination, TextMentionTermination\n", - "from autogen_agentchat.teams import RoundRobinGroupChat\n", - "from autogen_agentchat.ui import Console\n", - "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", - "\n", - "# Create an OpenAI model client.\n", - "model_client = OpenAIChatCompletionClient(\n", - " model=\"gpt-4o-2024-08-06\",\n", - " # api_key=\"sk-...\", # Optional if you have an OPENAI_API_KEY env variable set.\n", - ")\n", - "\n", - "# Create the primary agent.\n", - "primary_agent = AssistantAgent(\n", - " \"primary\",\n", - " model_client=model_client,\n", - " system_message=\"You are a helpful AI assistant.\",\n", - ")\n", - "\n", - "# Create the critic agent.\n", - "critic_agent = AssistantAgent(\n", - " \"critic\",\n", - " model_client=model_client,\n", - " system_message=\"Provide constructive feedback. Respond with 'APPROVE' to when your feedbacks are addressed.\",\n", - ")\n", - "\n", - "# Define a termination condition that stops the task if the critic approves.\n", - "text_termination = TextMentionTermination(\"APPROVE\")\n", - "# Define a termination condition that stops the task after 5 messages.\n", - "max_message_termination = MaxMessageTermination(5)\n", - "# Combine the termination conditions using the `|`` operator so that the\n", - "# task stops when either condition is met.\n", - "termination = text_termination | max_message_termination\n", - "\n", - "# Create a team with the primary and critic agents.\n", - "reflection_team = RoundRobinGroupChat([primary_agent, critic_agent], termination_condition=termination)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's give a poem-writing task to the team and see how the agents interact with each other." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------- user ----------\n", - "Write a short poem about fall season.\n", - "---------- primary ----------\n", - "Golden leaves dance on the breeze, \n", - "Whispering secrets through the trees. \n", - "Crisp air nips at cheeks so bright, \n", - "As daylight fades to early night. \n", - "\n", - "Pumpkins sit on porches grand, \n", - "In a painted, harvest land. \n", - "Sweaters hug us, warm and snug, \n", - "While cider fills each steamy mug. \n", - "\n", - "In this season's gentle sway, \n", - "Nature tells of time's ballet. \n", - "With each leaf's descent and flight, \n", - "Autumn sings its soft goodnight. \n", - "[Prompt tokens: 27, Completion tokens: 107]\n", - "---------- critic ----------\n", - "Your poem is beautiful and elegantly captures the essence of the fall season. The imagery you used creates vivid pictures of autumn landscapes and activities, making it easy for the reader to visualize the scene. The rhyming and rhythm contribute to the poem's musicality, enhancing its appeal. Each stanza highlights different aspects of fall, creating a well-rounded depiction of the season.\n", - "\n", - "To make the poem even more evocative, consider including a few additional sensory details or emotions tied to the season. For instance, you might evoke the sounds of rustling leaves or the feeling of warmth from a fireplace. Overall, it's a delightful and charming poem that effectively conveys the spirit of fall.\n", - "\n", - "If these suggestions are considered, please share the revised poem for additional feedback!\n", - "[Prompt tokens: 152, Completion tokens: 148]\n", - "---------- primary ----------\n", - "Thank you for the thoughtful feedback! Here's a revised version of the poem, incorporating more sensory details and emotions:\n", - "\n", - "---\n", - "\n", - "Golden leaves dance on the breeze, \n", - "Whispering secrets through the trees. \n", - "Crisp air kisses cheeks aglow, \n", - "As twilight casts a gentle show. \n", - "\n", - "Pumpkins guard each porch with pride, \n", - "In this painted, harvest tide. \n", - "Sweaters hug us, warm and snug, \n", - "While cider steams in every mug. \n", - "\n", - "Children laugh in rustling leaves, \n", - "As branches weave autumnal eaves. \n", - "Fireplaces crackle, whisper warmth, \n", - "Embracing hearts in homey charms. \n", - "\n", - "In this season's tender sway, \n", - "Nature turns in grand ballet. \n", - "With each leaf's descent and flight, \n", - "Autumn sings its soft goodnight. \n", - "\n", - "---\n", - "\n", - "I hope this version resonates even more deeply with the spirit of fall.\n", - "[Prompt tokens: 294, Completion tokens: 178]\n", - "---------- critic ----------\n", - "Your revised poem beautifully captures the essence of the fall season with delightful sensory details and emotions. The inclusion of words like \"twilight casts a gentle show,\" \"children laugh in rustling leaves,\" and \"fireplaces crackle\" adds depth and paints a vivid picture of autumn scenes. The addition of emotions, particularly the \"embracing hearts in homey charms,\" evokes a sense of warmth and comfort associated with this season.\n", - "\n", - "The poem flows smoothly with its rhythmic quality and maintains a harmonious balance in its description of autumn. Overall, it now provides an even richer and more immersive experience for the reader. Excellent work on enhancing the sensory experience—this version resonates wonderfully with the spirit of fall. \n", - "\n", - "APPROVE\n", - "[Prompt tokens: 490, Completion tokens: 142]\n", - "---------- Summary ----------\n", - "Number of messages: 5\n", - "Finish reason: Text 'APPROVE' mentioned, Maximum number of messages 5 reached, current message count: 5\n", - "Total prompt tokens: 963\n", - "Total completion tokens: 575\n", - "Duration: 8.10 seconds\n" - ] - } - ], - "source": [ - "# Use `asyncio.run(Console(reflection_team.run_stream(task=\"Write a short poem about fall season.\")))` when running in a script.\n", - "await Console(\n", - " reflection_team.run_stream(task=\"Write a short poem about fall season.\")\n", - ") # Stream the messages to the console." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Resuming a Team\n", - "\n", - "Let's run the team again with a new task while keeping the context about the previous task." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------- user ----------\n", - "将这首诗用中文唐诗风格写一遍。\n", - "---------- primary ----------\n", - "金叶飘舞随风起， \n", - "林间低语秋声细。 \n", - "凉风轻拂面颊红， \n", - "夕光渐隐天色丽。 \n", - "\n", - "南瓜门前静自笑， \n", - "丰收景色绘秋貌。 \n", - "暖衣贴身享温柔， \n", - "热饮氤氲杯中绕。 \n", - "\n", - "童声笑逐落叶中， \n", - "枝叶缀出秋帷浓。 \n", - "炉火轻鸣诉温情， \n", - "温馨满怀思乡容。 \n", - "\n", - "此时佳季自徘徊， \n", - "秋之舞步若梦来。 \n", - "片片叶落随风去， \n", - "秋声袅袅道安睡。 \n", - "[Prompt tokens: 664, Completion tokens: 155]\n", - "---------- critic ----------\n", - "这首诗成功地以唐诗的风格捕捉了秋天的精髓，以古雅的语言和流畅的节奏展示了秋日的美丽。你运用了优美的意象，如“金叶飘舞”和“夕光渐隐”，将秋季的景色描绘得栩栩如生。词句简炼而意境深远，充满了诗意。\n", - "\n", - "同时，诗中融入的情感，如“温馨满怀思乡容”以及“炉火轻鸣诉温情”，有效传达了秋天的暖意与思乡之情，令人感到温暖和亲切。\n", - "\n", - "整体而言，这是一首极具唐诗魅力的作品，成功地展现了秋天的许多层面，并引发读者的共鸣。恭喜你完成了这次优雅的改编！\n", - "\n", - "APPROVE\n", - "[Prompt tokens: 837, Completion tokens: 199]\n", - "---------- Summary ----------\n", - "Number of messages: 3\n", - "Finish reason: Text 'APPROVE' mentioned\n", - "Total prompt tokens: 1501\n", - "Total completion tokens: 354\n", - "Duration: 4.44 seconds\n" - ] - } - ], - "source": [ - "# Write the poem in Chinese Tang poetry style.\n", - "# Use `asyncio.run(Console(reflection_team.run_stream(task=\"将这首诗用中文唐诗风格写一遍。\")))` when running in a script.\n", - "await Console(reflection_team.run_stream(task=\"将这首诗用中文唐诗风格写一遍。\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Resume with another task." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------- user ----------\n", - "Write the poem in Spanish.\n", - "---------- primary ----------\n", - "Certainly! Here's a translation of the poem into Spanish:\n", - "\n", - "---\n", - "\n", - "Hojas doradas bailan en la brisa, \n", - "Susurran secretos en la arboleda. \n", - "El aire fresco besa las mejillas, \n", - "Mientras el crepúsculo se despide a su manera. \n", - "\n", - "Calabazas vigilan cada entrada, \n", - "En esta tierra de cosecha pintada. \n", - "Los suéteres nos abrazan calurosos, \n", - "Mientras el vapor sube de cada taza amorosa. \n", - "\n", - "Risas de niños suenan en hojas caídas, \n", - "Mientras ramas tejen toldos de caricias. \n", - "Las chimeneas crepitan, susurran calor, \n", - "Abrazando los corazones con su amor hogareño. \n", - "\n", - "En la danza de esta estación serena, \n", - "La naturaleza gira con su escena. \n", - "Con cada hoja que desciende en el viento, \n", - "El otoño canta su suave cuento. \n", - "\n", - "---\n", - "\n", - "Espero que esta traducción refleje el mismo espíritu y encantamiento del poema original.\n", - "[Prompt tokens: 1719, Completion tokens: 209]\n", - "---------- critic ----------\n", - "Your translation of the poem into Spanish beautifully captures the essence and lyrical quality of the original. The imagery and emotions are conveyed effectively, maintaining the warmth and serene atmosphere of fall that the poem embodies. Each stanza mirrors the themes presented in the English version, like the golden leaves, harvest, and cozy reflections of autumn.\n", - "\n", - "Overall, your translation is both poetic and faithful to the original content. If you have further adjustments or specific stylistic preferences, feel free to share. Great job on this translation!\n", - "\n", - "APPROVE\n", - "[Prompt tokens: 1946, Completion tokens: 102]\n", - "---------- Summary ----------\n", - "Number of messages: 3\n", - "Finish reason: Text 'APPROVE' mentioned\n", - "Total prompt tokens: 3665\n", - "Total completion tokens: 311\n", - "Duration: 4.22 seconds\n" - ] - } - ], - "source": [ - "# Write the poem in Spanish.\n", - "# Use `asyncio.run(Console(reflection_team.run_stream(task=\"Write the poem in Spanish.\")))` when running in a script.\n", - "await Console(reflection_team.run_stream(task=\"Write the poem in Spanish.\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Resuming a Previous Task\n", - "\n", - "We can call {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` or {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream` methods\n", - "without setting the `task` again to resume the previous task. The team will continue from where it left off." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------- primary ----------\n", - "Thank you for your kind words! I'm glad the translation captures the essence and lyrical quality of the original poem. If you have any more requests or need further assistance, please feel free to let me know. I'm here to help!\n", - "[Prompt tokens: 2042, Completion tokens: 46]\n", - "---------- critic ----------\n", - "You're very welcome! I'm glad to hear that you're satisfied with the translation. If you have any more requests, whether it's poetry, translation, or any other kind of assistance, don't hesitate to reach out. I'm here to help with whatever you need. Enjoy the rest of your creative journey!\n", - "[Prompt tokens: 2106, Completion tokens: 58]\n", - "---------- primary ----------\n", - "Thank you for your encouraging words! I'm here to assist you with any other requests you might have, whether related to creativity, translation, or any other topic. Feel free to reach out whenever you need help or inspiration. Enjoy your journey in creativity!\n", - "[Prompt tokens: 2158, Completion tokens: 50]\n", - "---------- critic ----------\n", - "You're welcome! It's always a pleasure to assist you. If you ever have more questions or need inspiration, don't hesitate to reach out. Happy creating, and enjoy every moment of your creative journey!\n", - "[Prompt tokens: 2226, Completion tokens: 39]\n", - "---------- primary ----------\n", - "Thank you so much! Your encouragement is greatly appreciated. Feel free to reach out at any time for assistance or inspiration. I wish you the best on your creative journey and hope you enjoy every step of the way!\n", - "[Prompt tokens: 2259, Completion tokens: 43]\n", - "---------- Summary ----------\n", - "Number of messages: 5\n", - "Finish reason: Maximum number of messages 5 reached, current message count: 5\n", - "Total prompt tokens: 10791\n", - "Total completion tokens: 236\n", - "Duration: 5.00 seconds\n" - ] - } - ], - "source": [ - "# Use the `asyncio.run(Console(reflection_team.run_stream()))` when running in a script.\n", - "await Console(reflection_team.run_stream())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Pausing for User Input\n", - "\n", - "Sometimes, teams may require additional input from the application (e.g., the user) to continue making meaningful progress on a task. Here are two ways to achieve this:\n", - "\n", - "- Set the maximum number of turns so that the team stops after the specified number of turns.\n", - "- Use the {py:class}`~autogen_agentchat.conditions.HandoffTermination` termination condition.\n", - "\n", - "You can also create custom termination conditions. For more details, see [Termination Conditions](./termination.ipynb).\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Via Max Turns\n", - "\n", - "This method allows you to pause the team for user input by setting a maximum number of turns. For instance, you can configure the team to stop after the first agent responds by setting `max_turns` to 1. This is particularly useful in scenarios where continuous user engagement is required, such as in a chatbot.\n", - "\n", - "To implement this, set the `max_turns` parameter in the {py:meth}`~autogen_agentchat.teams.RoundRobinGroupChat` constructor.\n", - "\n", - "```python\n", - "team = RoundRobinGroupChat([...], max_turns=1)\n", - "```\n", - "\n", - "Once the team stops, the turn count will be reset. When you resume the team,\n", - "it will start from 0 again.\n", - "\n", - "Note that `max_turn` is specific to the team class and is currently only supported by\n", - "{py:class}`~autogen_agentchat.teams.RoundRobinGroupChat`, {py:class}`~autogen_agentchat.teams.SelectorGroupChat`, and {py:class}`~autogen_agentchat.teams.Swarm`.\n", - "When used with termination conditions, the team will stop when either condition is met." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Via Handoff\n", - "\n", - "You can use the {py:class}`~autogen_agentchat.conditions.HandoffTermination` termination condition\n", - "to stop the team when an agent sends a {py:class}`~autogen_agentchat.messages.HandoffMessage` message.\n", - "\n", - "Let's create a team with a single {py:class}`~autogen_agentchat.agents.AssistantAgent` agent\n", - "with a handoff setting.\n", - "\n", - "```{note}\n", - "The model used with {py:class}`~autogen_agentchat.agents.AssistantAgent` must support tool call\n", - "to use the handoff feature.\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from autogen_agentchat.agents import AssistantAgent\n", - "from autogen_agentchat.base import Handoff\n", - "from autogen_agentchat.conditions import HandoffTermination, TextMentionTermination\n", - "from autogen_agentchat.teams import RoundRobinGroupChat\n", - "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", - "\n", - "# Create an OpenAI model client.\n", - "model_client = OpenAIChatCompletionClient(\n", - " model=\"gpt-4o-2024-08-06\",\n", - " # api_key=\"sk-...\", # Optional if you have an OPENAI_API_KEY env variable set.\n", - ")\n", - "\n", - "# Create a lazy assistant agent that always hands off to the user.\n", - "lazy_agent = AssistantAgent(\n", - " \"lazy_assistant\",\n", - " model_client=model_client,\n", - " handoffs=[Handoff(target=\"user\", message=\"Transfer to user.\")],\n", - " system_message=\"Always transfer to user when you don't know the answer. Respond 'TERMINATE' when task is complete.\",\n", - ")\n", - "\n", - "# Define a termination condition that checks for handoff message targetting helper and text \"TERMINATE\".\n", - "handoff_termination = HandoffTermination(target=\"user\")\n", - "text_termination = TextMentionTermination(\"TERMINATE\")\n", - "termination = handoff_termination | text_termination\n", - "\n", - "# Create a single-agent team.\n", - "lazy_agent_team = RoundRobinGroupChat([lazy_agent], termination_condition=termination)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's run the team with a task that requires additional input from the user\n", - "because the agent doesn't have relevant tools to continue processing the task." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------- user ----------\n", - "What is the weather in New York?\n", - "---------- lazy_assistant ----------\n", - "[FunctionCall(id='call_YHm4KPjFIWZE95YrJWlJwcv4', arguments='{}', name='transfer_to_user')]\n", - "[Prompt tokens: 68, Completion tokens: 11]\n", - "---------- lazy_assistant ----------\n", - "[FunctionExecutionResult(content='Transfer to user.', call_id='call_YHm4KPjFIWZE95YrJWlJwcv4')]\n", - "---------- lazy_assistant ----------\n", - "Transfer to user.\n", - "---------- Summary ----------\n", - "Number of messages: 4\n", - "Finish reason: Handoff to user from lazy_assistant detected.\n", - "Total prompt tokens: 68\n", - "Total completion tokens: 11\n", - "Duration: 0.73 seconds\n" - ] - } - ], - "source": [ - "from autogen_agentchat.ui import Console\n", - "\n", - "# Use `asyncio.run(Console(lazy_agent_team.run_stream(task=\"What is the weather in New York?\")))` when running in a script.\n", - "await Console(lazy_agent_team.run_stream(task=\"What is the weather in New York?\"))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can see the team stopped due to the handoff message was detected.\n", - "Let's continue the team by providing the information the agent needs." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------- user ----------\n", - "It is raining in New York.\n", - "---------- lazy_assistant ----------\n", - "I hope you stay dry! Is there anything else you would like to know or do?\n", - "[Prompt tokens: 108, Completion tokens: 19]\n", - "---------- lazy_assistant ----------\n", - "TERMINATE\n", - "[Prompt tokens: 134, Completion tokens: 4]\n", - "---------- Summary ----------\n", - "Number of messages: 3\n", - "Finish reason: Text 'TERMINATE' mentioned\n", - "Total prompt tokens: 242\n", - "Total completion tokens: 23\n", - "Duration: 6.77 seconds\n" - ] - } - ], - "source": [ - "# Use `asyncio.run(Console(lazy_agent_team.run_stream(task=\"It is raining in New York.\")))` when running in a script.\n", - "await Console(lazy_agent_team.run_stream(task=\"It is raining in New York.\"))" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "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": "3.11.5" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Teams\n", + "\n", + "In this section you'll learn how to create a _multi-agent team_ (or simply team) using AutoGen. A team is a group of agents that work together to achieve a common goal.\n", + "\n", + "We'll first show you how to create and run a team. We'll then explain how to observe the team's behavior, which is crucial for debugging and understanding the team's performance, and common operations to control the team's behavior." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating a Team\n", + "\n", + "{py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` is a simple yet effective team configuration where all agents share the same context and take turns responding in a round-robin fashion. Each agent, during its turn, broadcasts its response to all other agents, ensuring that the entire team maintains a consistent context.\n", + "\n", + "We will begin by creating a team with two {py:class}`~autogen_agentchat.agents.AssistantAgent` and a {py:class}`~autogen_agentchat.conditions.TextMentionTermination` condition that stops the team when a specific word is detected in the agent's response.\n", + "\n", + "The two-agent team implements the _reflection_ pattern, a multi-agent design pattern where a critic agent evaluates the responses of a primary agent. Learn more about the reflection pattern using the [Core API](../../core-user-guide/design-patterns/reflection.ipynb)." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "import asyncio\n", + "\n", + "from autogen_agentchat.agents import AssistantAgent\n", + "from autogen_agentchat.base import TaskResult\n", + "from autogen_agentchat.conditions import ExternalTermination, TextMentionTermination\n", + "from autogen_agentchat.teams import RoundRobinGroupChat\n", + "from autogen_agentchat.ui import Console\n", + "from autogen_core import CancellationToken\n", + "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", + "\n", + "# Create an OpenAI model client.\n", + "model_client = OpenAIChatCompletionClient(\n", + " model=\"gpt-4o-2024-08-06\",\n", + " # api_key=\"sk-...\", # Optional if you have an OPENAI_API_KEY env variable set.\n", + ")\n", + "\n", + "# Create the primary agent.\n", + "primary_agent = AssistantAgent(\n", + " \"primary\",\n", + " model_client=model_client,\n", + " system_message=\"You are a helpful AI assistant.\",\n", + ")\n", + "\n", + "# Create the critic agent.\n", + "critic_agent = AssistantAgent(\n", + " \"critic\",\n", + " model_client=model_client,\n", + " system_message=\"Provide constructive feedback. Respond with 'APPROVE' to when your feedbacks are addressed.\",\n", + ")\n", + "\n", + "# Define a termination condition that stops the task if the critic approves.\n", + "text_termination = TextMentionTermination(\"APPROVE\")\n", + "\n", + "# Create a team with the primary and critic agents.\n", + "team = RoundRobinGroupChat([primary_agent, critic_agent], termination_condition=text_termination)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Running a Team\n", + "\n", + "Let's calls the {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` method\n", + "to start the team with a task." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='Write a short poem about the fall season.', type='TextMessage'), TextMessage(source='primary', models_usage=RequestUsage(prompt_tokens=28, completion_tokens=109), content=\"Leaves of amber, gold, and rust, \\nDance upon the gentle gust. \\nCrisp air whispers tales of old, \\nAs daylight wanes, the night grows bold. \\n\\nPumpkin patch and apple treats, \\nLaughter in the street repeats. \\nSweaters warm and fires aglow, \\nIt's time for nature's vibrant show. \\n\\nThe harvest moon ascends the sky, \\nWhile geese in formation start to fly. \\nAutumn speaks in colors bright, \\nA fleeting grace, a pure delight. \", type='TextMessage'), TextMessage(source='critic', models_usage=RequestUsage(prompt_tokens=154, completion_tokens=200), content='Your poem beautifully captures the essence of the fall season with vivid imagery and a rhythmic flow. The use of descriptive language like \"amber, gold, and rust\" effectively paints a visual picture of the changing leaves. Phrases such as \"crisp air whispers tales of old\" and \"daylight wanes, the night grows bold\" add a poetic touch by incorporating seasonal characteristics.\\n\\nHowever, you might consider exploring other sensory details to deepen the reader\\'s immersion. For example, mentioning the sound of crunching leaves underfoot or the scent of cinnamon and spices in the air could enhance the sensory experience.\\n\\nAdditionally, while the mention of \"pumpkin patch and apple treats\" is evocative of fall, expanding on these elements or including more personal experiences or emotions associated with the season might make the poem more relatable and engaging.\\n\\nOverall, you\\'ve crafted a lovely poem that celebrates the beauty and traditions of autumn with grace and warmth. A few tweaks to include multisensory details could elevate it even further.', type='TextMessage'), TextMessage(source='primary', models_usage=RequestUsage(prompt_tokens=347, completion_tokens=178), content=\"Thank you for the thoughtful feedback. Here's a revised version of the poem with additional sensory details:\\n\\nLeaves of amber, gold, and rust, \\nDance upon the gentle gust. \\nCrisp air whispers tales of old, \\nAs daylight wanes, the night grows bold. \\n\\nCrunch beneath the wandering feet, \\nA melody of autumn's beat. \\nCinnamon and spices blend, \\nIn every breeze, nostalgia sends. \\n\\nPumpkin patch and apple treats, \\nLaughter in the street repeats. \\nSweaters warm and fires aglow, \\nIt's time for nature's vibrant show. \\n\\nThe harvest moon ascends the sky, \\nWhile geese in formation start to fly. \\nAutumn speaks in colors bright, \\nA fleeting grace, a pure delight. \\n\\nI hope this version resonates even more with the spirit of fall. Thank you again for your suggestions!\", type='TextMessage'), TextMessage(source='critic', models_usage=RequestUsage(prompt_tokens=542, completion_tokens=3), content='APPROVE', type='TextMessage')], stop_reason=\"Text 'APPROVE' mentioned\")\n" + ] + } + ], + "source": [ + "# Use `asyncio.run(...)` when running in a script.\n", + "result = await team.run(task=\"Write a short poem about the fall season.\")\n", + "print(result)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The team ran the same agent until the termination condition was met.\n", + "In this case, the termination condition was met when the word \"TERMINATE\" is detected in the\n", + "agent's response.\n", + "When the team stops, it returns a {py:class}`~autogen_agentchat.base.TaskResult` object with all the messages produced by the agents in the team." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Observing a Team\n", + "\n", + "Similar to the agent's {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_messages_stream` method, you can stream the team's messages while it is running by calling the {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream` method. This method returns a generator that yields messages produced by the agents in the team as they are generated, with the final item being the {py:class}`~autogen_agentchat.base.TaskResult` object." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "source='user' models_usage=None content='Write a short poem about the fall season.' type='TextMessage'\n", + "source='primary' models_usage=RequestUsage(prompt_tokens=28, completion_tokens=105) content=\"Leaves descend in golden dance, \\nWhispering secrets as they fall, \\nCrisp air brings a gentle trance, \\nHeralding Autumn's call. \\n\\nPumpkins glow with orange light, \\nFields wear a cloak of amber hue, \\nDays retreat to longer night, \\nSkies shift to deeper blue. \\n\\nWinds carry scents of earth and pine, \\nSweaters wrap us, warm and tight, \\nNature's canvas, bold design, \\nIn Fall's embrace, we find delight. \" type='TextMessage'\n", + "source='critic' models_usage=RequestUsage(prompt_tokens=150, completion_tokens=226) content='Your poem beautifully captures the essence of fall with vivid imagery and a soothing rhythm. The imagery of leaves descending, pumpkins glowing, and fields cloaked in amber hues effectively paints a picture of the autumn season. The use of contrasting elements like \"Days retreat to longer night\" and \"Sweaters wrap us, warm and tight\" provides a nice balance between the cold and warmth associated with the season. Additionally, the personification of autumn through phrases like \"Autumn\\'s call\" and \"Nature\\'s canvas, bold design\" adds depth to the depiction of fall.\\n\\nTo enhance the poem further, you might consider focusing on the soundscape of fall, such as the rustling of leaves or the distant call of migrating birds, to engage readers\\' auditory senses. Also, varying the line lengths slightly could add a dynamic flow to the reading experience.\\n\\nOverall, your poem is engaging and effectively encapsulates the beauty and transition of fall. With a few adjustments to explore other sensory details, it could become even more immersive. \\n\\nIf you incorporate some of these suggestions or find another way to expand the sensory experience, please share your update!' type='TextMessage'\n", + "source='primary' models_usage=RequestUsage(prompt_tokens=369, completion_tokens=143) content=\"Thank you for the thoughtful critique and suggestions. Here's a revised version of the poem with added attention to auditory senses and varied line lengths:\\n\\nLeaves descend in golden dance, \\nWhisper secrets in their fall, \\nBreezes hum a gentle trance, \\nHeralding Autumn's call. \\n\\nPumpkins glow with orange light, \\nAmber fields beneath wide skies, \\nDays retreat to longer night, \\nChill winds and distant cries. \\n\\nRustling whispers of the trees, \\nSweaters wrap us, snug and tight, \\nNature's canvas, bold and free, \\nIn Fall's embrace, pure delight. \\n\\nI appreciate your feedback and hope this version better captures the sensory richness of the season!\" type='TextMessage'\n", + "source='critic' models_usage=RequestUsage(prompt_tokens=529, completion_tokens=160) content='Your revised poem is a beautiful enhancement of the original. By incorporating auditory elements such as \"Breezes hum\" and \"Rustling whispers of the trees,\" you\\'ve added an engaging soundscape that draws the reader deeper into the experience of fall. The varied line lengths work well to create a more dynamic rhythm throughout the poem, adding interest and variety to each stanza.\\n\\nThe succinct, yet vivid, lines of \"Chill winds and distant cries\" wonderfully evoke the atmosphere of the season, adding a touch of mystery and depth. The final stanza wraps up the poem nicely, celebrating the complete sensory embrace of fall with lines like \"Nature\\'s canvas, bold and free.\"\\n\\nYou\\'ve successfully infused more sensory richness into the poem, enhancing its overall emotional and atmospheric impact. Great job on the revisions!\\n\\nAPPROVE' type='TextMessage'\n", + "Stop Reason: Text 'APPROVE' mentioned\n" + ] + } + ], + "source": [ + "# When running inside a script, use a async main function and call it from `asyncio.run(...)`.\n", + "await team.reset() # Reset the team for a new task.\n", + "async for message in team.run_stream(task=\"Write a short poem about the fall season.\"): # type: ignore\n", + " if isinstance(message, TaskResult):\n", + " print(\"Stop Reason:\", message.stop_reason)\n", + " else:\n", + " print(message)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As demonstrated in the example above, you can determine the reason why the team stopped by checking the {py:attr}`~autogen_agentchat.base.TaskResult.stop_reason` attribute.\n", + "\n", + "The {py:meth}`~autogen_agentchat.ui.Console` method provides a convenient way to print messages to the console with proper formatting.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "Write a short poem about the fall season.\n", + "---------- primary ----------\n", + "Golden leaves in crisp air dance, \n", + "Whispering tales as they prance. \n", + "Amber hues paint the ground, \n", + "Nature's symphony all around. \n", + "\n", + "Sweaters hug with tender grace, \n", + "While pumpkins smile, a warm embrace. \n", + "Chill winds hum through towering trees, \n", + "A vibrant tapestry in the breeze. \n", + "\n", + "Harvest moons in twilight glow, \n", + "Casting magic on fields below. \n", + "Fall's embrace, a gentle call, \n", + "To savor beauty before snowfalls. \n", + "[Prompt tokens: 28, Completion tokens: 99]\n", + "---------- critic ----------\n", + "Your poem beautifully captures the essence of the fall season, creating a vivid and cozy atmosphere. The imagery of golden leaves and amber hues paints a picturesque scene that many can easily relate to. I particularly appreciate the personification of pumpkins and the gentle embrace of sweaters, which adds warmth to your verses. \n", + "\n", + "To enhance the poem further, you might consider adding more sensory details to make the reader feel even more immersed in the experience. For example, including specific sounds, scents, or textures could deepen the connection to autumn's ambiance. Additionally, you could explore the emotional transitions as the season prepares for winter to provide a reflective element to the piece.\n", + "\n", + "Overall, it's a lovely and evocative depiction of fall, evoking feelings of comfort and appreciation for nature's changing beauty. Great work!\n", + "[Prompt tokens: 144, Completion tokens: 157]\n", + "---------- primary ----------\n", + "Thank you for your thoughtful feedback! I'm glad you enjoyed the imagery and warmth in the poem. To enhance the sensory experience and emotional depth, here's a revised version incorporating your suggestions:\n", + "\n", + "---\n", + "\n", + "Golden leaves in crisp air dance, \n", + "Whispering tales as they prance. \n", + "Amber hues paint the crunchy ground, \n", + "Nature's symphony all around. \n", + "\n", + "Sweaters hug with tender grace, \n", + "While pumpkins grin, a warm embrace. \n", + "Chill winds hum through towering trees, \n", + "Crackling fires warm the breeze. \n", + "\n", + "Apples in the orchard's glow, \n", + "Sweet cider scents that overflow. \n", + "Crunch of paths beneath our feet, \n", + "Cinnamon spice and toasty heat. \n", + "\n", + "Harvest moons in twilight's glow, \n", + "Casting magic on fields below. \n", + "Fall's embrace, a gentle call, \n", + "Reflects on life's inevitable thaw. \n", + "\n", + "--- \n", + "\n", + "I hope this version enhances the sensory and emotional elements of the season. Thank you again for your insights!\n", + "[Prompt tokens: 294, Completion tokens: 195]\n", + "---------- critic ----------\n", + "APPROVE\n", + "[Prompt tokens: 506, Completion tokens: 4]\n", + "---------- Summary ----------\n", + "Number of messages: 5\n", + "Finish reason: Text 'APPROVE' mentioned\n", + "Total prompt tokens: 972\n", + "Total completion tokens: 455\n", + "Duration: 11.78 seconds\n" + ] }, - "nbformat": 4, - "nbformat_minor": 2 + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='Write a short poem about the fall season.', type='TextMessage'), TextMessage(source='primary', models_usage=RequestUsage(prompt_tokens=28, completion_tokens=99), content=\"Golden leaves in crisp air dance, \\nWhispering tales as they prance. \\nAmber hues paint the ground, \\nNature's symphony all around. \\n\\nSweaters hug with tender grace, \\nWhile pumpkins smile, a warm embrace. \\nChill winds hum through towering trees, \\nA vibrant tapestry in the breeze. \\n\\nHarvest moons in twilight glow, \\nCasting magic on fields below. \\nFall's embrace, a gentle call, \\nTo savor beauty before snowfalls. \", type='TextMessage'), TextMessage(source='critic', models_usage=RequestUsage(prompt_tokens=144, completion_tokens=157), content=\"Your poem beautifully captures the essence of the fall season, creating a vivid and cozy atmosphere. The imagery of golden leaves and amber hues paints a picturesque scene that many can easily relate to. I particularly appreciate the personification of pumpkins and the gentle embrace of sweaters, which adds warmth to your verses. \\n\\nTo enhance the poem further, you might consider adding more sensory details to make the reader feel even more immersed in the experience. For example, including specific sounds, scents, or textures could deepen the connection to autumn's ambiance. Additionally, you could explore the emotional transitions as the season prepares for winter to provide a reflective element to the piece.\\n\\nOverall, it's a lovely and evocative depiction of fall, evoking feelings of comfort and appreciation for nature's changing beauty. Great work!\", type='TextMessage'), TextMessage(source='primary', models_usage=RequestUsage(prompt_tokens=294, completion_tokens=195), content=\"Thank you for your thoughtful feedback! I'm glad you enjoyed the imagery and warmth in the poem. To enhance the sensory experience and emotional depth, here's a revised version incorporating your suggestions:\\n\\n---\\n\\nGolden leaves in crisp air dance, \\nWhispering tales as they prance. \\nAmber hues paint the crunchy ground, \\nNature's symphony all around. \\n\\nSweaters hug with tender grace, \\nWhile pumpkins grin, a warm embrace. \\nChill winds hum through towering trees, \\nCrackling fires warm the breeze. \\n\\nApples in the orchard's glow, \\nSweet cider scents that overflow. \\nCrunch of paths beneath our feet, \\nCinnamon spice and toasty heat. \\n\\nHarvest moons in twilight's glow, \\nCasting magic on fields below. \\nFall's embrace, a gentle call, \\nReflects on life's inevitable thaw. \\n\\n--- \\n\\nI hope this version enhances the sensory and emotional elements of the season. Thank you again for your insights!\", type='TextMessage'), TextMessage(source='critic', models_usage=RequestUsage(prompt_tokens=506, completion_tokens=4), content='APPROVE', type='TextMessage')], stop_reason=\"Text 'APPROVE' mentioned\")" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "await team.reset() # Reset the team for a new task.\n", + "await Console(team.run_stream(task=\"Write a short poem about the fall season.\")) # Stream the messages to the console." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Resetting a Team\n", + "\n", + "You can reset the team by calling the {py:meth}`~autogen_agentchat.teams.BaseGroupChat.reset` method. This method will clear the team's state, including all agents.\n", + "It will call the each agent's {py:meth}`~autogen_agentchat.base.ChatAgent.on_reset` method to clear the agent's state." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "await team.reset() # Reset the team for the next run." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It is usually a good idea to reset the team if the next task is not related to the previous task.\n", + "However, if the next task is related to the previous task, you don't need to reset and you can instead\n", + "resume the team." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Stopping a Team\n", + "\n", + "Apart from automatic termination conditions such as {py:class}`~autogen_agentchat.conditions.TextMentionTermination`\n", + "that stops the team based on the internal state of the team, you can also stop the team\n", + "from outside by using the {py:class}`~autogen_agentchat.conditions.ExternalTermination`.\n", + "\n", + "Calling {py:meth}`~autogen_agentchat.conditions.ExternalTermination.set` \n", + "on {py:class}`~autogen_agentchat.conditions.ExternalTermination` will stop\n", + "the team when the current agent's turn is over.\n", + "Thus, the team may not stop immediately.\n", + "This allows the current agent to finish its turn and broadcast the final message to the team\n", + "before the team stops, keeping the team's state consistent." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "Write a short poem about the fall season.\n", + "---------- primary ----------\n", + "Leaves of amber, gold, and red, \n", + "Gently drifting from trees overhead. \n", + "Whispers of wind through the crisp, cool air, \n", + "Nature's canvas painted with care. \n", + "\n", + "Harvest moons and evenings that chill, \n", + "Fields of plenty on every hill. \n", + "Sweaters wrapped tight as twilight nears, \n", + "Fall's charming embrace, as warm as it appears. \n", + "\n", + "Pumpkins aglow with autumn's light, \n", + "Harvest feasts and stars so bright. \n", + "In every leaf and breeze that calls, \n", + "We find the magic of glorious fall. \n", + "[Prompt tokens: 28, Completion tokens: 114]\n", + "---------- Summary ----------\n", + "Number of messages: 2\n", + "Finish reason: External termination requested\n", + "Total prompt tokens: 28\n", + "Total completion tokens: 114\n", + "Duration: 1.71 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='Write a short poem about the fall season.', type='TextMessage'), TextMessage(source='primary', models_usage=RequestUsage(prompt_tokens=28, completion_tokens=114), content=\"Leaves of amber, gold, and red, \\nGently drifting from trees overhead. \\nWhispers of wind through the crisp, cool air, \\nNature's canvas painted with care. \\n\\nHarvest moons and evenings that chill, \\nFields of plenty on every hill. \\nSweaters wrapped tight as twilight nears, \\nFall's charming embrace, as warm as it appears. \\n\\nPumpkins aglow with autumn's light, \\nHarvest feasts and stars so bright. \\nIn every leaf and breeze that calls, \\nWe find the magic of glorious fall. \", type='TextMessage')], stop_reason='External termination requested')" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Create a new team with an external termination condition.\n", + "external_termination = ExternalTermination()\n", + "team = RoundRobinGroupChat(\n", + " [primary_agent, critic_agent],\n", + " termination_condition=external_termination | text_termination, # Use the bitwise OR operator to combine conditions.\n", + ")\n", + "\n", + "# Run the team in a background task.\n", + "run = asyncio.create_task(Console(team.run_stream(task=\"Write a short poem about the fall season.\")))\n", + "\n", + "# Wait for some time.\n", + "await asyncio.sleep(0.1)\n", + "\n", + "# Stop the team.\n", + "external_termination.set()\n", + "\n", + "# Wait for the team to finish.\n", + "await run" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the ouput above, you can see the team stopped because the external termination condition was met,\n", + "but the speaking agent was able to finish its turn before the team stopped." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Resuming a Team\n", + "\n", + "Teams are stateful and maintains the conversation history and context\n", + "after each run, unless you reset the team.\n", + "\n", + "You can resume a team to continue from where it left off by calling the {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` or {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream` method again\n", + "without a new task.\n", + "{py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` will continue from the next agent in the round-robin order." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- critic ----------\n", + "This poem beautifully captures the essence of the fall season with vivid imagery and a soothing rhythm. The descriptions of the changing leaves, cool air, and various autumn traditions make it easy for readers to envision and feel the charm of fall. Here are a few suggestions to enhance its impact:\n", + "\n", + "1. **Structure Variation**: Consider breaking some lines with a hyphen or ellipsis for dramatic effect or emphasis. For instance, “Sweaters wrapped tight as twilight nears— / Fall’s charming embrace, as warm as it appears.\"\n", + "\n", + "2. **Sensory Details**: While the poem already evokes visual and tactile senses, incorporating other senses such as sound or smell could deepen the immersion. For example, include the scent of wood smoke or the crunch of leaves underfoot.\n", + "\n", + "3. **Metaphorical Language**: Adding metaphors or similes can further enrich the imagery. For example, you might compare the leaves falling to a golden rain or the chill in the air to a gentle whisper.\n", + "\n", + "Overall, it’s a lovely depiction of fall. These suggestions are minor tweaks that might elevate the reader's experience even further. Nice work!\n", + "\n", + "Let me know if these feedbacks are addressed.\n", + "[Prompt tokens: 159, Completion tokens: 237]\n", + "---------- primary ----------\n", + "Thank you for the thoughtful feedback! Here’s a revised version, incorporating your suggestions: \n", + "\n", + "Leaves of amber, gold—drifting like dreams, \n", + "A golden rain from trees’ canopies. \n", + "Whispers of wind—a gentle breath, \n", + "Nature’s scented tapestry embracing earth. \n", + "\n", + "Harvest moons rise as evenings chill, \n", + "Fields of plenty paint every hill. \n", + "Sweaters wrapped tight as twilight nears— \n", + "Fall’s embrace, warm as whispered years. \n", + "\n", + "Pumpkins aglow with autumn’s light, \n", + "Crackling leaves underfoot in flight. \n", + "In every leaf and breeze that calls, \n", + "We find the magic of glorious fall. \n", + "\n", + "I hope these changes enhance the imagery and sensory experience. Thank you again for your feedback!\n", + "[Prompt tokens: 389, Completion tokens: 150]\n", + "---------- critic ----------\n", + "Your revisions have made the poem even more evocative and immersive. The use of sensory details, such as \"whispers of wind\" and \"crackling leaves,\" beautifully enriches the poem, engaging multiple senses. The metaphorical language, like \"a golden rain from trees’ canopies\" and \"Fall’s embrace, warm as whispered years,\" adds depth and enhances the emotional warmth of the poem. The structural variation with the inclusion of dashes effectively adds emphasis and flow. \n", + "\n", + "Overall, these changes bring greater vibrancy and life to the poem, allowing readers to truly experience the wonders of fall. Excellent work on the revisions!\n", + "\n", + "APPROVE\n", + "[Prompt tokens: 556, Completion tokens: 132]\n", + "---------- Summary ----------\n", + "Number of messages: 3\n", + "Finish reason: Text 'APPROVE' mentioned\n", + "Total prompt tokens: 1104\n", + "Total completion tokens: 519\n", + "Duration: 9.79 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='critic', models_usage=RequestUsage(prompt_tokens=159, completion_tokens=237), content='This poem beautifully captures the essence of the fall season with vivid imagery and a soothing rhythm. The descriptions of the changing leaves, cool air, and various autumn traditions make it easy for readers to envision and feel the charm of fall. Here are a few suggestions to enhance its impact:\\n\\n1. **Structure Variation**: Consider breaking some lines with a hyphen or ellipsis for dramatic effect or emphasis. For instance, “Sweaters wrapped tight as twilight nears— / Fall’s charming embrace, as warm as it appears.\"\\n\\n2. **Sensory Details**: While the poem already evokes visual and tactile senses, incorporating other senses such as sound or smell could deepen the immersion. For example, include the scent of wood smoke or the crunch of leaves underfoot.\\n\\n3. **Metaphorical Language**: Adding metaphors or similes can further enrich the imagery. For example, you might compare the leaves falling to a golden rain or the chill in the air to a gentle whisper.\\n\\nOverall, it’s a lovely depiction of fall. These suggestions are minor tweaks that might elevate the reader\\'s experience even further. Nice work!\\n\\nLet me know if these feedbacks are addressed.', type='TextMessage'), TextMessage(source='primary', models_usage=RequestUsage(prompt_tokens=389, completion_tokens=150), content='Thank you for the thoughtful feedback! Here’s a revised version, incorporating your suggestions: \\n\\nLeaves of amber, gold—drifting like dreams, \\nA golden rain from trees’ canopies. \\nWhispers of wind—a gentle breath, \\nNature’s scented tapestry embracing earth. \\n\\nHarvest moons rise as evenings chill, \\nFields of plenty paint every hill. \\nSweaters wrapped tight as twilight nears— \\nFall’s embrace, warm as whispered years. \\n\\nPumpkins aglow with autumn’s light, \\nCrackling leaves underfoot in flight. \\nIn every leaf and breeze that calls, \\nWe find the magic of glorious fall. \\n\\nI hope these changes enhance the imagery and sensory experience. Thank you again for your feedback!', type='TextMessage'), TextMessage(source='critic', models_usage=RequestUsage(prompt_tokens=556, completion_tokens=132), content='Your revisions have made the poem even more evocative and immersive. The use of sensory details, such as \"whispers of wind\" and \"crackling leaves,\" beautifully enriches the poem, engaging multiple senses. The metaphorical language, like \"a golden rain from trees’ canopies\" and \"Fall’s embrace, warm as whispered years,\" adds depth and enhances the emotional warmth of the poem. The structural variation with the inclusion of dashes effectively adds emphasis and flow. \\n\\nOverall, these changes bring greater vibrancy and life to the poem, allowing readers to truly experience the wonders of fall. Excellent work on the revisions!\\n\\nAPPROVE', type='TextMessage')], stop_reason=\"Text 'APPROVE' mentioned\")" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "await Console(team.run_stream()) # Resume the team to continue the last task." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can see the team resumed from where it left off in the output above,\n", + "and the first message is from the next agent after the last agent that spoke\n", + "before the team stopped.\n", + "\n", + "Let's resume the team again with a new task while keeping the context about the previous task." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "将这首诗用中文唐诗风格写一遍。\n", + "---------- primary ----------\n", + "朔风轻拂叶飘金， \n", + "枝上斜阳染秋林。 \n", + "满山丰收人欢喜， \n", + "月明归途衣渐紧。 \n", + "\n", + "南瓜影映灯火中， \n", + "落叶沙沙伴归程。 \n", + "片片秋意随风起， \n", + "秋韵悠悠心自明。 \n", + "[Prompt tokens: 700, Completion tokens: 77]\n", + "---------- critic ----------\n", + "这首改编的唐诗风格诗作成功地保留了原诗的意境与情感，体现出秋季特有的氛围和美感。通过“朔风轻拂叶飘金”、“枝上斜阳染秋林”等意象，生动地描绘出了秋天的景色，与唐诗中的自然意境相呼应。且“月明归途衣渐紧”、“落叶沙沙伴归程”让人感受到秋天的安宁与温暖。\n", + "\n", + "通过这些诗句，读者能够感受到秋天的惬意与宁静，勾起丰收与团圆的画面，是一次成功的翻译改编。\n", + "\n", + "APPROVE\n", + "[Prompt tokens: 794, Completion tokens: 161]\n", + "---------- Summary ----------\n", + "Number of messages: 3\n", + "Finish reason: Text 'APPROVE' mentioned\n", + "Total prompt tokens: 1494\n", + "Total completion tokens: 238\n", + "Duration: 3.89 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='将这首诗用中文唐诗风格写一遍。', type='TextMessage'), TextMessage(source='primary', models_usage=RequestUsage(prompt_tokens=700, completion_tokens=77), content='朔风轻拂叶飘金， \\n枝上斜阳染秋林。 \\n满山丰收人欢喜， \\n月明归途衣渐紧。 \\n\\n南瓜影映灯火中， \\n落叶沙沙伴归程。 \\n片片秋意随风起， \\n秋韵悠悠心自明。 ', type='TextMessage'), TextMessage(source='critic', models_usage=RequestUsage(prompt_tokens=794, completion_tokens=161), content='这首改编的唐诗风格诗作成功地保留了原诗的意境与情感，体现出秋季特有的氛围和美感。通过“朔风轻拂叶飘金”、“枝上斜阳染秋林”等意象，生动地描绘出了秋天的景色，与唐诗中的自然意境相呼应。且“月明归途衣渐紧”、“落叶沙沙伴归程”让人感受到秋天的安宁与温暖。\\n\\n通过这些诗句，读者能够感受到秋天的惬意与宁静，勾起丰收与团圆的画面，是一次成功的翻译改编。\\n\\nAPPROVE', type='TextMessage')], stop_reason=\"Text 'APPROVE' mentioned\")" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The new task is to translate the same poem to Chinese Tang-style poetry.\n", + "await Console(team.run_stream(task=\"将这首诗用中文唐诗风格写一遍。\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Aborting a Team\n", + "\n", + "You can abort a call to {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` or {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream`\n", + "during execution by setting a {py:class}`~autogen_core.CancellationToken` passed to the `cancellation_token` parameter.\n", + "\n", + "Different from stopping a team, aborting a team will immediately stop the team and raise a {py:class}`~asyncio.CancelledError` exception.\n", + "\n", + "```{note}\n", + "The caller will get a {py:class}`~asyncio.CancelledError` exception when the team is aborted.\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Task was cancelled.\n" + ] + } + ], + "source": [ + "# Create a cancellation token.\n", + "cancellation_token = CancellationToken()\n", + "\n", + "# Use another coroutine to run the team.\n", + "run = asyncio.create_task(\n", + " team.run(\n", + " task=\"Translate the poem to Spanish.\",\n", + " cancellation_token=cancellation_token,\n", + " )\n", + ")\n", + "\n", + "# Cancel the run.\n", + "cancellation_token.cancel()\n", + "\n", + "try:\n", + " result = await run # This will raise a CancelledError.\n", + "except asyncio.CancelledError:\n", + " print(\"Task was cancelled.\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 } From a5681d73c6c3a7dba89f28fced27da2cfa7b500f Mon Sep 17 00:00:00 2001 From: Jack Gerrits Date: Fri, 27 Dec 2024 13:37:55 -0500 Subject: [PATCH 16/20] Allow closure agent to ignore unknown messages, add docs (#4836) Allow closure agent to ignore unknown messages --- .../src/autogen_core/_closure_agent.py | 88 +++++++++++++++++-- 1 file changed, 80 insertions(+), 8 deletions(-) diff --git a/python/packages/autogen-core/src/autogen_core/_closure_agent.py b/python/packages/autogen-core/src/autogen_core/_closure_agent.py index 03206d18fef..8f93b4f2bc9 100644 --- a/python/packages/autogen-core/src/autogen_core/_closure_agent.py +++ b/python/packages/autogen-core/src/autogen_core/_closure_agent.py @@ -1,7 +1,8 @@ from __future__ import annotations import inspect -from typing import Any, Awaitable, Callable, List, Mapping, Protocol, Sequence, TypeVar, get_type_hints +import warnings +from typing import Any, Awaitable, Callable, List, Literal, Mapping, Protocol, Sequence, TypeVar, get_type_hints from ._agent_id import AgentId from ._agent_instantiation import AgentInstantiationContext @@ -73,7 +74,11 @@ async def publish_message( class ClosureAgent(BaseAgent, ClosureContext): def __init__( - self, description: str, closure: Callable[[ClosureContext, T, MessageContext], Awaitable[Any]] + self, + description: str, + closure: Callable[[ClosureContext, T, MessageContext], Awaitable[Any]], + *, + unknown_type_policy: Literal["error", "warn", "ignore"] = "warn", ) -> None: try: runtime = AgentInstantiationContext.current_runtime() @@ -89,6 +94,7 @@ def __init__( handled_types = get_handled_types_from_closure(closure) self._expected_types = handled_types self._closure = closure + self._unknown_type_policy = unknown_type_policy super().__init__(description) @property @@ -110,9 +116,17 @@ def runtime(self) -> AgentRuntime: async def on_message_impl(self, message: Any, ctx: MessageContext) -> Any: if type(message) not in self._expected_types: - raise CantHandleException( - f"Message type {type(message)} not in target types {self._expected_types} of {self.id}" - ) + if self._unknown_type_policy == "warn": + warnings.warn( + f"Message type {type(message)} not in target types {self._expected_types} of {self.id}. Set unknown_type_policy to 'error' to raise an exception, or 'ignore' to suppress this warning.", + stacklevel=1, + ) + return None + elif self._unknown_type_policy == "error": + raise CantHandleException( + f"Message type {type(message)} not in target types {self._expected_types} of {self.id}. Set unknown_type_policy to 'warn' to suppress this exception, or 'ignore' to suppress this warning." + ) + return await self._closure(self, message, ctx) async def save_state(self) -> Mapping[str, Any]: @@ -130,19 +144,77 @@ async def register_closure( type: str, closure: Callable[[ClosureContext, T, MessageContext], Awaitable[Any]], *, - skip_class_subscriptions: bool = False, + unknown_type_policy: Literal["error", "warn", "ignore"] = "warn", skip_direct_message_subscription: bool = False, description: str = "", subscriptions: Callable[[], list[Subscription] | Awaitable[list[Subscription]]] | None = None, ) -> AgentType: + """The closure agent allows you to define an agent using a closure, or function without needing to define a class. It allows values to be extracted out of the runtime. + + The closure can define the type of message which is expected, or `Any` can be used to accept any type of message. + + Example: + + .. code-block:: python + + import asyncio + from autogen_core import SingleThreadedAgentRuntime, MessageContext, ClosureAgent, ClosureContext + from dataclasses import dataclass + + from autogen_core._default_subscription import DefaultSubscription + from autogen_core._default_topic import DefaultTopicId + + + @dataclass + class MyMessage: + content: str + + + async def main(): + queue = asyncio.Queue[MyMessage]() + + async def output_result(_ctx: ClosureContext, message: MyMessage, ctx: MessageContext) -> None: + await queue.put(message) + + runtime = SingleThreadedAgentRuntime() + await ClosureAgent.register_closure( + runtime, "output_result", output_result, subscriptions=lambda: [DefaultSubscription()] + ) + + runtime.start() + await runtime.publish_message(MyMessage("Hello, world!"), DefaultTopicId()) + await runtime.stop_when_idle() + + result = await queue.get() + print(result) + + + asyncio.run(main()) + + + Args: + runtime (AgentRuntime): Runtime to register the agent to + type (str): Agent type of registered agent + closure (Callable[[ClosureContext, T, MessageContext], Awaitable[Any]]): Closure to handle messages + unknown_type_policy (Literal["error", "warn", "ignore"], optional): What to do if a type is encountered that does not match the closure type. Defaults to "warn". + skip_direct_message_subscription (bool, optional): Do not add direct message subscription for this agent. Defaults to False. + description (str, optional): Description of what agent does. Defaults to "". + subscriptions (Callable[[], list[Subscription] | Awaitable[list[Subscription]]] | None, optional): List of subscriptions for this closure agent. Defaults to None. + + Returns: + AgentType: Type of the agent that was registered + """ + def factory() -> ClosureAgent: - return ClosureAgent(description=description, closure=closure) + return ClosureAgent(description=description, closure=closure, unknown_type_policy=unknown_type_policy) + assert len(cls._unbound_subscriptions()) == 0, "Closure agents are expected to have no class subscriptions" agent_type = await cls.register( runtime=runtime, type=type, factory=factory, # type: ignore - skip_class_subscriptions=skip_class_subscriptions, + # There should be no need to process class subscriptions, as the closure agent does not have any subscriptions.s + skip_class_subscriptions=True, skip_direct_message_subscription=skip_direct_message_subscription, ) From ad7433e81764c4202d5de2c4169eb0120c0289ae Mon Sep 17 00:00:00 2001 From: Jack Gerrits Date: Fri, 27 Dec 2024 14:38:42 -0500 Subject: [PATCH 17/20] Remove pydantic v1 compat (#4838) Remove pydantic compat --- .../src/autogen_core/_function_utils.py | 8 ++- .../src/autogen_core/_pydantic_compat.py | 50 ------------------- 2 files changed, 3 insertions(+), 55 deletions(-) delete mode 100644 python/packages/autogen-core/src/autogen_core/_pydantic_compat.py diff --git a/python/packages/autogen-core/src/autogen_core/_function_utils.py b/python/packages/autogen-core/src/autogen_core/_function_utils.py index a6803d085e4..7f11e458a27 100644 --- a/python/packages/autogen-core/src/autogen_core/_function_utils.py +++ b/python/packages/autogen-core/src/autogen_core/_function_utils.py @@ -21,12 +21,10 @@ get_origin, ) -from pydantic import BaseModel, Field, create_model # type: ignore +from pydantic import BaseModel, Field, TypeAdapter, create_model # type: ignore from pydantic_core import PydanticUndefined from typing_extensions import Literal -from ._pydantic_compat import model_dump, type2schema - logger = getLogger(__name__) T = TypeVar("T") @@ -141,7 +139,7 @@ def get_parameter_json_schema(k: str, v: Any, default_values: Dict[str, Any]) -> A Pydanitc model for the parameter """ - schema = type2schema(v) + schema = TypeAdapter(v).json_schema() if k in default_values: dv = default_values[k] schema["default"] = dv @@ -293,7 +291,7 @@ def f( ) ) - return model_dump(function) + return function.model_dump() def normalize_annotated_type(type_hint: Type[Any]) -> Type[Any]: diff --git a/python/packages/autogen-core/src/autogen_core/_pydantic_compat.py b/python/packages/autogen-core/src/autogen_core/_pydantic_compat.py deleted file mode 100644 index c29ccb70c06..00000000000 --- a/python/packages/autogen-core/src/autogen_core/_pydantic_compat.py +++ /dev/null @@ -1,50 +0,0 @@ -# File based from: https://github.com/microsoft/autogen/blob/47f905267245e143562abfb41fcba503a9e1d56d/autogen/_pydantic.py -# Credit to original authors - - -from typing import Any, Dict, Tuple, Type, Union, get_args - -from pydantic import BaseModel -from pydantic.version import VERSION as PYDANTIC_VERSION -from typing_extensions import get_origin - -__all__ = ("model_dump", "type2schema") - -PYDANTIC_V1 = PYDANTIC_VERSION.startswith("1.") - - -def type2schema(t: Type[Any] | None) -> Dict[str, Any]: - if PYDANTIC_V1: - from pydantic import schema_of # type: ignore - - if t is None: - return {"type": "null"} - elif get_origin(t) is Union: - return {"anyOf": [type2schema(tt) for tt in get_args(t)]} - elif get_origin(t) in [Tuple, tuple]: - prefixItems = [type2schema(tt) for tt in get_args(t)] - return { - "maxItems": len(prefixItems), - "minItems": len(prefixItems), - "prefixItems": prefixItems, - "type": "array", - } - - d = schema_of(t) # type: ignore - if "title" in d: - d.pop("title") - if "description" in d: - d.pop("description") - - return d - else: - from pydantic import TypeAdapter - - return TypeAdapter(t).json_schema() - - -def model_dump(model: BaseModel) -> Dict[str, Any]: - if PYDANTIC_V1: - return model.dict() # type: ignore - else: - return model.model_dump() From d933b9ab5f36010fe63b796bbdd34c4ee7283d0b Mon Sep 17 00:00:00 2001 From: Eric Zhu Date: Fri, 27 Dec 2024 11:49:12 -0800 Subject: [PATCH 18/20] dev12 (#4839) * dev12 --- .github/workflows/docs.yml | 1 + CONTRIBUTING.md | 4 +- README.md | 7 +- docs/switcher.json | 7 +- python/README.md | 2 +- .../packages/autogen-agentchat/pyproject.toml | 4 +- .../_templates/sidebar-nav-bs-agentchat.html | 71 +++++++++--------- .../src/_templates/sidebar-nav-bs-core.html | 72 +++++++++--------- .../_templates/sidebar-nav-bs-extensions.html | 74 +++++++++---------- .../packages/autogen-core/docs/src/index.md | 9 +-- .../agentchat-user-guide/installation.md | 4 +- .../agentchat-user-guide/quickstart.ipynb | 2 +- .../tutorial/models.ipynb | 4 +- .../framework/distributed-agent-runtime.ipynb | 2 +- .../core-user-guide/installation.md | 2 +- .../extensions-user-guide/installation.md | 4 +- python/packages/autogen-core/pyproject.toml | 4 +- python/packages/autogen-ext/pyproject.toml | 12 +-- .../azure/_azure_container_code_executor.py | 2 +- .../docker/_docker_code_executor.py | 2 +- .../models/openai/_openai_client.py | 4 +- python/packages/autogen-studio/pyproject.toml | 6 +- .../agentchat_chainlit/requirements.txt | 2 +- python/uv.lock | 6 +- 24 files changed, 154 insertions(+), 153 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 35cc7c1378b..75f9b6fc3b6 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -45,6 +45,7 @@ jobs: { ref: "v0.4.0.dev9", dest-dir: "0.4.0.dev9", uv-version: "0.5.11" }, { ref: "v0.4.0.dev10", dest-dir: "0.4.0.dev10", uv-version: "0.5.11" }, { ref: "v0.4.0.dev11", dest-dir: "0.4.0.dev11", uv-version: "0.5.11" }, + { ref: "v0.4.0.dev12", dest-dir: "0.4.0.dev12", uv-version: "0.5.11" }, ] steps: - name: Checkout diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 3dcccbb1811..ab86f7ed118 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -49,8 +49,8 @@ We will update verion numbers according to the following rules: 1. Create a PR that updates the version numbers across the codebase ([example](https://github.com/microsoft/autogen/pull/4359)) 2. The docs CI will fail for the PR, but this is expected and will be resolved in the next step -2. After merging the PR, create and push a tag that corresponds to the new verion. For example, for `0.4.0.dev11`: - - `git tag 0.4.0.dev11 && git push origin 0.4.0.dev11` +2. After merging the PR, create and push a tag that corresponds to the new verion. For example, for `0.4.0.dev12`: + - `git tag 0.4.0.dev12 && git push origin 0.4.0.dev12` 3. Restart the docs CI by finding the failed [job corresponding to the `push` event](https://github.com/microsoft/autogen/actions/workflows/docs.yml) and restarting all jobs 4. Run [this](https://github.com/microsoft/autogen/actions/workflows/single-python-package.yml) workflow for each of the packages that need to be released and get an approval for the release for it to run diff --git a/README.md b/README.md index 0e6702f2a3d..6efb8051dad 100644 --- a/README.md +++ b/README.md @@ -5,14 +5,14 @@ [![Twitter](https://img.shields.io/twitter/url/https/twitter.com/cloudposse.svg?style=social&label=Follow%20%40pyautogen)](https://twitter.com/pyautogen) [![LinkedIn](https://img.shields.io/badge/LinkedIn-Company?style=flat&logo=linkedin&logoColor=white)](https://www.linkedin.com/company/105812540) [![Discord](https://img.shields.io/badge/discord-chat-green?logo=discord)](https://aka.ms/autogen-discord) [![GitHub Discussions](https://img.shields.io/badge/Discussions-Q%26A-green?logo=github)](https://github.com/microsoft/autogen/discussions) [![0.2 Docs](https://img.shields.io/badge/Docs-0.2-blue)](https://microsoft.github.io/autogen/0.2/) [![0.4 Docs](https://img.shields.io/badge/Docs-0.4-blue)](https://microsoft.github.io/autogen/dev/) -[![PyPi autogen-core](https://img.shields.io/badge/PyPi-autogen--core-blue?logo=pypi)](https://pypi.org/project/autogen-core/0.4.0.dev11/) [![PyPi autogen-agentchat](https://img.shields.io/badge/PyPi-autogen--agentchat-blue?logo=pypi)](https://pypi.org/project/autogen-agentchat/0.4.0.dev11/) [![PyPi autogen-ext](https://img.shields.io/badge/PyPi-autogen--ext-blue?logo=pypi)](https://pypi.org/project/autogen-ext/0.4.0.dev11/) +[![PyPi autogen-core](https://img.shields.io/badge/PyPi-autogen--core-blue?logo=pypi)](https://pypi.org/project/autogen-core/0.4.0.dev12/) [![PyPi autogen-agentchat](https://img.shields.io/badge/PyPi-autogen--agentchat-blue?logo=pypi)](https://pypi.org/project/autogen-agentchat/0.4.0.dev12/) [![PyPi autogen-ext](https://img.shields.io/badge/PyPi-autogen--ext-blue?logo=pypi)](https://pypi.org/project/autogen-ext/0.4.0.dev12/) # AutoGen > [!IMPORTANT] > -> - (12/19/24) Hello! +> - (12/19/24) Hello! The majority of the AutoGen Team members will be resting and recharging with family and friends over the holiday period. Activity/responses on the project may be delayed during the period of Dec 20-Jan 06. We will be excited to engage with you in the new year! > - (12/11/24) We have created a new Discord server for the AutoGen community. Join us at [aka.ms/autogen-discord](https://aka.ms/autogen-discord). > - (11/14/24) ⚠️ In response to a number of asks to clarify and distinguish between official AutoGen and its forks that created confusion, we issued a [clarification statement](https://github.com/microsoft/autogen/discussions/4217). @@ -20,7 +20,6 @@ The majority of the AutoGen Team members will be resting and recharging with fam > - (10/02/24) [AutoGen 0.4](https://microsoft.github.io/autogen/dev) is a from-the-ground-up rewrite of AutoGen. Learn more about the history, goals and future at [this blog post](https://microsoft.github.io/autogen/blog). We’re excited to work with the community to gather feedback, refine, and improve the project before we officially release 0.4. This is a big change, so AutoGen 0.2 is still available, maintained, and developed in the [0.2 branch](https://github.com/microsoft/autogen/tree/0.2). > - *[Join us for Community Office Hours](https://github.com/microsoft/autogen/discussions/4059)* We will host a weekly open discussion to answer questions, talk about Roadmap, etc. - AutoGen is an open-source framework for building AI agent systems. It simplifies the creation of event-driven, distributed, scalable, and resilient agentic applications. It allows you to quickly build systems where AI agents collaborate and perform tasks autonomously @@ -108,7 +107,7 @@ We look forward to your contributions! First install the packages: ```bash -pip install "autogen-agentchat==0.4.0.dev11" "autogen-ext[openai]==0.4.0.dev11" +pip install "autogen-agentchat==0.4.0.dev12" "autogen-ext[openai]==0.4.0.dev12" ``` The following code uses OpenAI's GPT-4o model and you need to provide your diff --git a/docs/switcher.json b/docs/switcher.json index 205f954c732..fa2c2745a23 100644 --- a/docs/switcher.json +++ b/docs/switcher.json @@ -66,7 +66,12 @@ { "name": "0.4.0.dev11", "version": "0.4.0.dev11", - "url": "/autogen/0.4.0.dev11/", + "url": "/autogen/0.4.0.dev11/" + }, + { + "name": "0.4.0.dev12", + "version": "0.4.0.dev12", + "url": "/autogen/0.4.0.dev12/", "preferred": true } ] diff --git a/python/README.md b/python/README.md index 24cb7e79633..0007d3ae70a 100644 --- a/python/README.md +++ b/python/README.md @@ -1,7 +1,7 @@ # AutoGen Python packages [![0.4 Docs](https://img.shields.io/badge/Docs-0.4-blue)](https://microsoft.github.io/autogen/dev/) -[![PyPi autogen-core](https://img.shields.io/badge/PyPi-autogen--core-blue?logo=pypi)](https://pypi.org/project/autogen-core/0.4.0.dev11/) [![PyPi autogen-agentchat](https://img.shields.io/badge/PyPi-autogen--agentchat-blue?logo=pypi)](https://pypi.org/project/autogen-agentchat/0.4.0.dev11/) [![PyPi autogen-ext](https://img.shields.io/badge/PyPi-autogen--ext-blue?logo=pypi)](https://pypi.org/project/autogen-ext/0.4.0.dev11/) +[![PyPi autogen-core](https://img.shields.io/badge/PyPi-autogen--core-blue?logo=pypi)](https://pypi.org/project/autogen-core/0.4.0.dev12/) [![PyPi autogen-agentchat](https://img.shields.io/badge/PyPi-autogen--agentchat-blue?logo=pypi)](https://pypi.org/project/autogen-agentchat/0.4.0.dev12/) [![PyPi autogen-ext](https://img.shields.io/badge/PyPi-autogen--ext-blue?logo=pypi)](https://pypi.org/project/autogen-ext/0.4.0.dev12/) This directory works as a single `uv` workspace containing all project packages. See [`packages`](./packages/) to discover all project packages. diff --git a/python/packages/autogen-agentchat/pyproject.toml b/python/packages/autogen-agentchat/pyproject.toml index 0e586ea44c5..273792d3358 100644 --- a/python/packages/autogen-agentchat/pyproject.toml +++ b/python/packages/autogen-agentchat/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "hatchling.build" [project] name = "autogen-agentchat" -version = "0.4.0.dev11" +version = "0.4.0.dev12" license = {file = "LICENSE-CODE"} description = "AutoGen agents and teams library" readme = "README.md" @@ -15,7 +15,7 @@ classifiers = [ "Operating System :: OS Independent", ] dependencies = [ - "autogen-core==0.4.0.dev11", + "autogen-core==0.4.0.dev12", ] [tool.ruff] diff --git a/python/packages/autogen-core/docs/src/_templates/sidebar-nav-bs-agentchat.html b/python/packages/autogen-core/docs/src/_templates/sidebar-nav-bs-agentchat.html index 684eb304ac7..cce87d18d1c 100644 --- a/python/packages/autogen-core/docs/src/_templates/sidebar-nav-bs-agentchat.html +++ b/python/packages/autogen-core/docs/src/_templates/sidebar-nav-bs-agentchat.html @@ -1,38 +1,39 @@ {# Displays the TOC-subtree for pages nested under the currently active top-level TOCtree element. #} -