Question 1

None of the devcontainers are building due to "Hash sum mismatch", what should I do?

Accepted Answer

This is an intermittent issue that appears to be caused by some combination of mirror and proxy issues. If it arises, try to replace the apt-get update step with the following: RUN echo "Acquire::http::Pipeline-Depth 0;" > /etc/apt/apt.conf.d/99custom && \ echo "Acquire::http::No-Cache true;" >> /etc/apt/apt.conf.d/99custom && \ echo "Acquire::BrokenProxy true;" >> /etc/apt/apt.conf.d/99customRUN apt-get clean && \ rm -r /var/lib/apt/lists/* && \ apt-get update -o Acquire::CompressionTypes::Order::=gz && \ apt-get -y update && \ apt-get install sudo git npm # and whatever packages need to be installed in this specific version of the devcontainer This is a combination of StackOverflow suggestions here and here.

Question 2

What should I do if I get the error "TypeError: Assistants.create() got an unexpected keyword argument 'file_ids'"?

Accepted Answer

This error typically occurs when using Autogen version earlier than 0.2.27 in combination with OpenAI library version 1.21 or later. The issue arises because the older version of Autogen does not support the file_ids parameter used by newer versions of the OpenAI API. To resolve this issue, you need to upgrade your Autogen library to version 0.2.27 or higher that ensures compatibility between Autogen and the OpenAI library. pip install --upgrade autogen

Question 3

Agents are throwing due to docker not running, how can I resolve this?

Accepted Answer

If running AutoGen locally the default for agents who execute code is for them to try and perform code execution within a docker container. If docker is not running, this will cause the agent to throw an error. To resolve this you have some options.

Question 4

When using autogen docker, is it always necessary to reinstall modules?

Accepted Answer

The "use_docker" arg in an agent's code_execution_config will be set to the name of the image containing the change after execution, when the conversation finishes. You can save that image name. For a new conversation, you can set "use_docker" to the saved name of the image to start execution there.

Question 5

How to get each agent message?

Accepted Answer

Please refer to https://microsoft.github.io/autogen/docs/reference/agentchat/conversable_agent#chat_messages

Question 6

How to get last message?

Accepted Answer

Refer to https://microsoft.github.io/autogen/docs/reference/agentchat/conversable_agent/#last_message

Question 7

Why is code not saved as file?

Accepted Answer

If you are using a custom system message for the coding agent, please include something like: If you want the user to save the code in a file before executing it, put # filename: <filename> inside the code block as the first line. in the system message. This line is in the default system message of the AssistantAgent. If the # filename doesn't appear in the suggested code still, consider adding explicit instructions such as "save the code to disk" in the initial user message in initiate_chat. The AssistantAgent doesn't save all the code by default, because there are cases in which one would just like to finish a task without saving the code.

Question 8

How do we decide what LLM is used for each agent? How many agents can be used? How do we decide how many agents in the group?

Accepted Answer

Each agent can be customized. You can use LLMs, tools, or humans behind each agent. If you use an LLM for an agent, use the one best suited for its role. There is no limit of the number of agents, but start from a small number like 2, 3. The more capable is the LLM and the fewer roles you need, the fewer agents you need. The default user proxy agent doesn't use LLM. If you'd like to use an LLM in UserProxyAgent, the use case could be to simulate user's behavior. The default assistant agent is instructed to use both coding and language skills. It doesn't have to do coding, depending on the tasks. And you can customize the system message. So if you want to use it for coding, use a model that's good at coding.

Question 9

Can I use non-OpenAI models?

Accepted Answer

Yes. You currently have two options: Autogen can work with any API endpoint which complies with OpenAI-compatible RESTful APIs - e.g. serving local LLM via FastChat or LM Studio. Please check https://microsoft.github.io/autogen/blog/2023/07/14/Local-LLMs for an example. You can supply your own custom model implementation and use it with Autogen. Please check https://microsoft.github.io/autogen/blog/2024/01/26/Custom-Models for more information.

AutoGenAtvērt-source Python rīks, lai arī kārtītu dažu agentu LLM raksturdarbu pildījuma uzdevumus kopīgi.

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