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Update notebook contrib guidance, update a few notebooks for site (#1651)

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* update some notebooks

* Update contributing.md

* remove os

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
This commit is contained in:
Jack Gerrits
2024-02-14 12:00:55 -05:00
committed by GitHub
parent a8cf7e3cf8
commit a62b5c3b2d
7 changed files with 123 additions and 223 deletions
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18
notebook/agentchat_auto_feedback_from_code_execution.ipynb
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@@ -21,16 +21,16 @@
"\n",
"In this notebook, we demonstrate how to use `AssistantAgent` and `UserProxyAgent` to write code and execute the code. Here `AssistantAgent` is an LLM-based agent that can write Python code (in a Python coding block) for a user to execute for a given task. `UserProxyAgent` is an agent which serves as a proxy for the human user to execute the code written by `AssistantAgent`, or automatically execute the code. Depending on the setting of `human_input_mode` and `max_consecutive_auto_reply`, the `UserProxyAgent` either solicits feedback from the human user or returns auto-feedback based on the result of code execution (success or failure and corresponding outputs) to `AssistantAgent`. `AssistantAgent` will debug the code and suggest new code if the result contains error. The two agents keep communicating to each other until the task is done.\n",
"\n",
"\\:\\:\\:info Requirements\n",
"\n",
"````{=mdx}\n",
":::info Requirements\n",
"Install `pyautogen`:\n",
"```bash\n",
"pip install pyautogen\n",
"```\n",
"\n",
"For more information, please refer to the [installation guide](/docs/installation/).\n",
"\n",
"\\:\\:\\:"
":::\n",
"````"
]
},
{
@@ -59,11 +59,11 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"\\:\\:\\:tip\n",
"\n",
"Learn more about the various ways to configure LLM endpoints [here](/docs/llm_configuration).\n",
"\n",
"\\:\\:\\:"
"````{=mdx}\n",
":::tip\n",
"Learn more about configuring LLMs for agents [here](/docs/llm_configuration).\n",
":::\n",
"````"
]
},
{