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Change references from agenext to autogen (#610)

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Jack Gerrits
2024-09-23 10:46:05 -04:00
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23 changed files with 49 additions and 54 deletions
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2
python/packages/autogen-core/docs/src/conf.py
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@@ -63,7 +63,7 @@ myst_enable_extensions = [
# -- Options for HTML output -------------------------------------------------
# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
html_title = "AGNext"
html_title = "AutoGen"
html_theme = "pydata_sphinx_theme"
html_static_path = ["_static"]

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python/packages/autogen-core/docs/src/index.md
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@@ -2,16 +2,16 @@
myst:
html_meta:
"description lang=en": |
Top-level documentation for AGNext, a framework for building multi-agent applications with AI agents.
Top-level documentation for AutoGen, a framework for building multi-agent applications with AI agents.
html_theme.sidebar_secondary.remove: false
---
# AGNext
# AutoGen
AGNext is a OSS framework for developing intelligent applications using AI Agents patterns.
AutoGen is an OSS framework for developing intelligent applications using AI Agents patterns.
It offers an easy way to quickly build event-driven, distributed, scalable, resilient AI agent systems. Agents are developed by using the [Actor model](https://en.wikipedia.org/wiki/Actor_model). You can build and run your agent system locally and easily move to a distributed system in the cloud when you are ready.
Key features of AGNext are summarized below.
Key features of AutoGen are summarized below.
```{gallery-grid}
:grid-columns: 1 2 2 3
@@ -31,7 +31,7 @@ Key features of AGNext are summarized below.
```
<!--
Key features of AGNext include:
Key features of AutoGen include:
- Asynchronous messaging: Agents communicate with each other through asynchronous messages, enabling event-driven and request/response communication models.
- Scalable & Distributed: Enable complex scenarios with networks of agents across org boundaries
@@ -40,7 +40,7 @@ Key features of AGNext include:
- Observable, traceable & debuggable -->
```{seealso}
To start quickly, read the [Quick Start](user-guide/guides/quickstart) guide and follow the tutorial sections. To learn about the core concepts of AGNext, begin with [Agent and Multi-Agent Application](user-guide/core-concepts/agent-and-multi-agent-application).
To start quickly, read the [Quick Start](user-guide/guides/quickstart) guide and follow the tutorial sections. To learn about the core concepts of AutoGen, begin with [Agent and Multi-Agent Application](user-guide/core-concepts/agent-and-multi-agent-application).
```
```{toctree}
@@ -52,7 +52,7 @@ user-guide/index
<!-- ## Community
Information about the community that leads, supports, and develops AGNext.
Information about the community that leads, supports, and develops AutoGen.
```{toctree}
:maxdepth: 2
@@ -72,8 +72,3 @@ packages/index
reference/index
```
<!-- ````{toctree}
:hidden:
Changelog <https://github.com/your-org/agnext/releases>
``` -->

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python/packages/autogen-core/docs/src/packages/index.md
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@@ -2,7 +2,7 @@
myst:
html_meta:
"description lang=en": |
AGNext packages provide a set of functionality for building multi-agent applications with AI agents.
AutoGen packages provide a set of functionality for building multi-agent applications with AI agents.
---
<style>
@@ -23,7 +23,7 @@ myst:
:::{card} {fas}`cube;pst-color-primary` AutoGen Core
:class-title: card-title
Implements the core functionality of the AGNext framework, providing basic building blocks for creating multi-agent systems.
Implements the core functionality of the AutoGen framework, providing basic building blocks for creating multi-agent systems.
```sh
pip install autogen-core

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python/packages/autogen-core/docs/src/reference/index.md
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@@ -2,7 +2,7 @@
myst:
html_meta:
"description lang=en": |
AGNext is a community-driven project. Learn how to get involved, contribute, and connect with the community.
AutoGen is a community-driven project. Learn how to get involved, contribute, and connect with the community.
---
<style>

2
python/packages/autogen-core/docs/src/user-guide/cookbook/openai-assistant-agent.ipynb
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@@ -10,7 +10,7 @@
"and [Azure OpenAI Assistant](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/assistant)\n",
"are server-side APIs for building\n",
"agents.\n",
"They can be used to build agents in AGNext. This cookbook demonstrates how to\n",
"They can be used to build agents in AutoGen. This cookbook demonstrates how to\n",
"to use OpenAI Assistant to create an agent that can run code and Q&A over document.\n",
"\n",
"## Message Protocol\n",

2
python/packages/autogen-core/docs/src/user-guide/core-concepts/application-stack.md
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@@ -1,6 +1,6 @@
# Application Stack
AGNext is designed to be an unopinionated framework that can be used to build
AutoGen core is designed to be an unopinionated framework that can be used to build
a wide variety of multi-agent applications. It is not tied to any specific
agent abstraction or multi-agent pattern.

6
python/packages/autogen-core/docs/src/user-guide/guides/agent-and-agent-runtime.ipynb
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@@ -6,7 +6,7 @@
"source": [
"# Agent and Agent Runtime\n",
"\n",
"In this and the following section, we focus on the core concepts of AGNext:\n",
"In this and the following section, we focus on the core concepts of AutoGen:\n",
"agents, agent runtime, messages, and communication.\n",
"You will not find any AI models or tools here, just the foundational\n",
"building blocks for building multi-agent applications."
@@ -16,12 +16,12 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"An agent in AGNext is an entity defined by the base class {py:class}`autogen_core.base.BaseAgent`.\n",
"An agent in AutoGen is an entity defined by the base class {py:class}`autogen_core.base.BaseAgent`.\n",
"It has a unique identifier of the type {py:class}`autogen_core.base.AgentId`,\n",
"a metadata dictionary of the type {py:class}`autogen_core.base.AgentMetadata`,\n",
"and method for handling messages {py:meth}`autogen_core.base.BaseAgent.on_message`.\n",
"\n",
"An agent runtime is the execution environment for agents in AGNext.\n",
"An agent runtime is the execution environment for agents in AutoGen.\n",
"Similar to the runtime environment of a programming language,\n",
"an agent runtime provides the necessary infrastructure to facilitate communication\n",
"between agents, manage agent lifecycles, enforce security boundaries, and support monitoring and\n",

2
python/packages/autogen-core/docs/src/user-guide/guides/logging.md
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@@ -1,6 +1,6 @@
# Logging
AGNext uses Python's built-in [`logging`](https://docs.python.org/3/library/logging.html) module.
AutoGen uses Python's built-in [`logging`](https://docs.python.org/3/library/logging.html) module.
There are two kinds of logging:

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python/packages/autogen-core/docs/src/user-guide/guides/message-and-communication.ipynb
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@@ -6,7 +6,7 @@
"source": [
"# Message and Communication\n",
"\n",
"An agent in AGNext can react to, send, and publish messages,\n",
"An agent in AutoGen core can react to, send, and publish messages,\n",
"and messages are the only means through which agents can communicate\n",
"with each other."
]
@@ -263,7 +263,7 @@
"source": [
"## Direct Messaging\n",
"\n",
"There are two types of communication in AGNext:\n",
"There are two types of communication in AutoGen core:\n",
"\n",
"- **Direct Messaging**: sends a direct message to another agent.\n",
"- **Broadcast**: publishes a message to a topic.\n",

2
python/packages/autogen-core/docs/src/user-guide/guides/model-clients.ipynb
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@@ -6,7 +6,7 @@
"source": [
"# Model Clients\n",
"\n",
"AGNext provides the {py:mod}`autogen_core.components.models` module with a suite of built-in\n",
"AutoGen provides the {py:mod}`autogen_core.components.models` module with a suite of built-in\n",
"model clients for using ChatCompletion API.\n",
"All model clients implement the {py:class}`~autogen_core.components.models.ChatCompletionClient` protocol class."
]

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python/packages/autogen-core/docs/src/user-guide/guides/multi-agent-design-patterns.md
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@@ -13,6 +13,6 @@ For example, the [tool-equiped agent](./tools.ipynb#tool-equipped-agent) in
the previous section employs a design pattern called ReAct,
which involves an agent interacting with tools.
You can implement any multi-agent design pattern using AGNext agents.
You can implement any multi-agent design pattern using AutoGen agents.
In the next two sections, we will discuss two common design patterns:
group chat for task decomposition, and reflection for robustness.

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python/packages/autogen-core/docs/src/user-guide/guides/quickstart.ipynb
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@@ -381,7 +381,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"AGNext also supports distributed agent runtime, which can host agents running on\n",
"AutoGen also supports a distributed agent runtime, which can host agents running on\n",
"different processes or machines, with different identities, languages and dependencies.\n",
"\n",
"To learn how to use agent runtime, communication, message handling, and subscription, please continue\n",

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python/packages/autogen-core/docs/src/user-guide/guides/reflection.ipynb
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@@ -11,7 +11,7 @@
"For example, given a task to write code, the first LLM can generate a code snippet,\n",
"and the second LLM can generate a critique of the code snippet.\n",
"\n",
"In the context of AGNext and agents, reflection can be implemented as a pair\n",
"In the context of AutoGen and agents, reflection can be implemented as a pair\n",
"of agents, where the first agent generates a message and the second agent\n",
"generates a response to the message. The two agents continue to interact\n",
"until they reach a stopping condition, such as a maximum number of iterations\n",
@@ -22,7 +22,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's implement a simple reflection design pattern using AGNext agents.\n",
"Let's implement a simple reflection design pattern using AutoGen agents.\n",
"There will be two agents: a coder agent and a reviewer agent, the coder agent\n",
"will generate a code snippet, and the reviewer agent will generate a critique\n",
"of the code snippet.\n",
@@ -259,7 +259,7 @@
"- It stores message histories for different `CodeWritingTask` in a dictionary,\n",
"so each task has its own history.\n",
"- When making an LLM inference request using its model client, it transforms\n",
"the message history into a list of {py:class}`agnext.components.models.LLMMessage` objects\n",
"the message history into a list of {py:class}`autogen_core.components.models.LLMMessage` objects\n",
"to pass to the model client.\n",
"\n",
"The reviewer agent subscribes to the `CodeReviewTask` message and publishes the `CodeReviewResult` message."

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python/packages/autogen-core/docs/src/user-guide/guides/telemetry.md
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@@ -1,6 +1,6 @@
# Open Telemetry
AGNext has native support for [open telemetry](https://opentelemetry.io/). This allows you to collect telemetry data from your application and send it to a telemetry backend of your choosing.
AutoGen has native support for [open telemetry](https://opentelemetry.io/). This allows you to collect telemetry data from your application and send it to a telemetry backend of your choosing.
These are the components that are currently instrumented:
- Runtime (Single Threaded Agent Runtime, Worker Agent Runtime)
@@ -12,7 +12,7 @@ To instrument your application, you will need an sdk and an exporter. You may al
pip install opentelemetry-sdk
```
Depending on your open telemetry collector, you can use grpc or http to export your telemetry.
Depending on your open telemetry collector, you can use grpc or http to export your telemetry.
```bash
# Pick one of the following
@@ -35,7 +35,7 @@ def configure_oltp_tracing(endpoint: str = None) -> trace.TracerProvider:
processor = BatchSpanProcessor(OTLPSpanExporter())
tracer_provider.add_span_processor(processor)
trace.set_tracer_provider(tracer_provider)
return tracer_provider
```

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python/packages/autogen-core/docs/src/user-guide/guides/tools.ipynb
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@@ -12,7 +12,7 @@
"In the context of AI agents, tools are designed to be executed by agents in\n",
"response to model-generated function calls.\n",
"\n",
"AGNext provides the {py:mod}`autogen_core.components.tools` module with a suite of built-in\n",
"AutoGen provides the {py:mod}`autogen_core.components.tools` module with a suite of built-in\n",
"tools and utilities for creating and running custom tools."
]
},

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python/packages/autogen-core/docs/src/user-guide/index.md
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@@ -2,12 +2,12 @@
myst:
html_meta:
"description lang=en": |
User Guide for AGNext, a framework for building multi-agent applications with AI agents.
User Guide for AutoGen, a framework for building multi-agent applications with AI agents.
---
# User Guide
AGNext is a flexible framework for building multi-agent systems. Begin with the [installation](guides/installation.md) guide to set up the framework on your machine. Then, follow the [quickstart](guides/quickstart) guide to get started with building your first multi-agent application.
AutoGen is a flexible framework for building multi-agent systems. Begin with the [installation](guides/installation.md) guide to set up the framework on your machine. Then, follow the [quickstart](guides/quickstart) guide to get started with building your first multi-agent application.
```{danger}
This project and documentation is a work in progress. If you have any questions or need help, please reach out to us on GitHub.