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simplify getting-started; update news (#2175)
* simplify getting-started; update news * bug fix
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Chi Wang
GitHub
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README.md
12
README.md
@ -12,23 +12,25 @@
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<img src="https://github.com/microsoft/autogen/blob/main/website/static/img/flaml.svg" width=200>
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<br>
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</p> -->
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:fire: Mar 26: Andrew Ng gave a shoutout to AutoGen in [What's next for AI agentic workflows](https://youtu.be/sal78ACtGTc?si=JduUzN_1kDnMq0vF) at Sequoia Capital's AI Ascent.
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:fire: Mar 3: What's new in AutoGen? 📰[Blog](https://microsoft.github.io/autogen/blog/2024/03/03/AutoGen-Update); 📺[Youtube](https://www.youtube.com/watch?v=j_mtwQiaLGU).
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:fire: Mar 1: the first AutoGen multi-agent experiment on the challenging [GAIA](https://huggingface.co/spaces/gaia-benchmark/leaderboard) benchmark achieved the No. 1 accuracy in all the three levels.
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:fire: Jan 30: AutoGen is highlighted by Peter Lee in Microsoft Research Forum [Keynote](https://t.co/nUBSjPDjqD).
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:tada: Jan 30: AutoGen is highlighted by Peter Lee in Microsoft Research Forum [Keynote](https://t.co/nUBSjPDjqD).
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:fire: Dec 31: [AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework](https://arxiv.org/abs/2308.08155) is selected by [TheSequence: My Five Favorite AI Papers of 2023](https://thesequence.substack.com/p/my-five-favorite-ai-papers-of-2023).
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:tada: Dec 31: [AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework](https://arxiv.org/abs/2308.08155) is selected by [TheSequence: My Five Favorite AI Papers of 2023](https://thesequence.substack.com/p/my-five-favorite-ai-papers-of-2023).
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<!-- :fire: Nov 24: pyautogen [v0.2](https://github.com/microsoft/autogen/releases/tag/v0.2.0) is released with many updates and new features compared to v0.1.1. It switches to using openai-python v1. Please read the [migration guide](https://microsoft.github.io/autogen/docs/Installation#python). -->
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<!-- :fire: Nov 11: OpenAI's Assistants are available in AutoGen and interoperatable with other AutoGen agents! Checkout our [blogpost](https://microsoft.github.io/autogen/blog/2023/11/13/OAI-assistants) for details and examples. -->
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:fire: Nov 8: AutoGen is selected into [Open100: Top 100 Open Source achievements](https://www.benchcouncil.org/evaluation/opencs/annual.html) 35 days after spinoff.
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:tada: Nov 8: AutoGen is selected into [Open100: Top 100 Open Source achievements](https://www.benchcouncil.org/evaluation/opencs/annual.html) 35 days after spinoff.
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:fire: Nov 6: AutoGen is mentioned by Satya Nadella in a [fireside chat](https://youtu.be/0pLBvgYtv6U).
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:tada: Nov 6: AutoGen is mentioned by Satya Nadella in a [fireside chat](https://youtu.be/0pLBvgYtv6U).
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:fire: Nov 1: AutoGen is the top trending repo on GitHub in October 2023.
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:tada: Nov 1: AutoGen is the top trending repo on GitHub in October 2023.
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:tada: Oct 03: AutoGen spins off from FLAML on GitHub and has a major paper update (first version on Aug 16).
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@ -83,8 +83,7 @@ class DockerCommandLineCodeExecutor(CodeExecutor):
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if isinstance(work_dir, str):
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work_dir = Path(work_dir)
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if not work_dir.exists():
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raise ValueError(f"Working directory {work_dir} does not exist.")
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work_dir.mkdir(exist_ok=True)
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client = docker.from_env()
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@ -71,8 +71,7 @@ $functions"""
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if isinstance(work_dir, str):
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work_dir = Path(work_dir)
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if not work_dir.exists():
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raise ValueError(f"Working directory {work_dir} does not exist.")
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work_dir.mkdir(exist_ok=True)
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self._timeout = timeout
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self._work_dir: Path = work_dir
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@ -1 +1 @@
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__version__ = "0.2.20"
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__version__ = "0.2.21"
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@ -1,5 +1,6 @@
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from pathlib import Path
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import sys
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import os
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import tempfile
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import uuid
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import pytest
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@ -10,7 +11,8 @@ from autogen.coding.factory import CodeExecutorFactory
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from autogen.coding.docker_commandline_code_executor import DockerCommandLineCodeExecutor
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from autogen.coding.local_commandline_code_executor import LocalCommandLineCodeExecutor
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from conftest import MOCK_OPEN_AI_API_KEY, skip_docker
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sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
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from conftest import MOCK_OPEN_AI_API_KEY, skip_docker # noqa: E402
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if skip_docker or not is_docker_running():
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classes_to_test = [LocalCommandLineCodeExecutor]
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@ -52,7 +54,7 @@ def test_commandline_executor_init(cls) -> None:
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assert executor.timeout == 10 and str(executor.work_dir) == "."
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# Try invalid working directory.
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with pytest.raises(ValueError, match="Working directory .* does not exist."):
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with pytest.raises(FileNotFoundError):
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executor = cls(timeout=111, work_dir="/invalid/directory")
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@ -38,30 +38,37 @@ pip install pyautogen
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```
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<Tabs>
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<TabItem value="nocode" label="No code execution" default>
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```python
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from autogen import AssistantAgent, UserProxyAgent
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llm_config = {"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY"]}
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assistant = AssistantAgent("assistant", llm_config=llm_config)
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user_proxy = UserProxyAgent("user_proxy", code_execution_config=False)
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# Start the chat
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user_proxy.initiate_chat(
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assistant,
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message="Tell me a joke about NVDA and TESLA stock prices.",
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)
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```
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</TabItem>
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<TabItem value="local" label="Local execution" default>
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:::warning
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When asked, be sure to check the generated code before continuing to ensure it is safe to run.
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:::
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```python
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import autogen
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from autogen import AssistantAgent, UserProxyAgent
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from autogen.coding import LocalCommandLineCodeExecutor
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import os
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from pathlib import Path
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llm_config = {
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"config_list": [{"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY"]}],
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}
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work_dir = Path("coding")
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work_dir.mkdir(exist_ok=True)
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llm_config = {"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY"]}
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assistant = AssistantAgent("assistant", llm_config=llm_config)
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code_executor = LocalCommandLineCodeExecutor(work_dir=work_dir)
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user_proxy = UserProxyAgent(
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"user_proxy", code_execution_config={"executor": code_executor}
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"user_proxy", code_execution_config={"executor": autogen.coding.LocalCommandLineCodeExecutor(work_dir="coding")}
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)
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# Start the chat
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@ -75,20 +82,12 @@ user_proxy.initiate_chat(
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<TabItem value="docker" label="Docker execution" default>
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```python
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import autogen
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from autogen import AssistantAgent, UserProxyAgent
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from autogen.coding import DockerCommandLineCodeExecutor
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import os
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from pathlib import Path
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llm_config = {"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY"]}
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llm_config = {
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"config_list": [{"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY"]}],
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}
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work_dir = Path("coding")
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work_dir.mkdir(exist_ok=True)
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with DockerCommandLineCodeExecutor(work_dir=work_dir) as code_executor:
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with autogen.coding.DockerCommandLineCodeExecutor(work_dir="coding") as code_executor:
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assistant = AssistantAgent("assistant", llm_config=llm_config)
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user_proxy = UserProxyAgent(
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"user_proxy", code_execution_config={"executor": code_executor}
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@ -103,7 +102,7 @@ with DockerCommandLineCodeExecutor(work_dir=work_dir) as code_executor:
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Open `coding/plot.png` to see the generated plot.
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</TabItem>
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</TabItem>
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</Tabs>
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:::tip
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