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TinyTroupe, a new LLM-powered multiagent persona simulation Python library

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Re: TinyTroupe, a new LLM-powered multiagent persona simulation Python library

#13

Post by highcountess »

xrd wrote: post #3

I love jupyter notebooks. And, I'm amazed that a company like Microsoft would put a notebook front and center that starts off with a bunch of errors. Not a good look. I really think you can improve your AI marketing by a lot by creating compelling jupyter notebooks. Unsloth is a great example of the right way. https://github.com/microsoft/TinyTroupe/blob/main/examples/a...

I am glad I was not the only one that was taken aback a bit by that. I am not one to be too critical about loose ends or roughness in things that are provided for free and my ability to contribute a change, but it is a bit surprising that Microsoft would now have QA on this considering it ties into the current image they are trying to build.

Re: TinyTroupe, a new LLM-powered multiagent persona simulation Python library

#14

Post by simonw »

Here's a quick way to start this running if you're using uv:

    cd /tmp
    git clone https://github.com/microsoft/tinytroupe
    cd tinytroupe
    OPENAI_API_KEY='your-key-here' uv run jupyter notebook
I used this pattern because my OpenAI key is stashed in a LLM-managed JSON file:

    OPENAI_API_KEY="$(jq -r '.openai' "$(dirname "$(llm logs path)")/keys.json")" \
      uv run jupyter notebook
(Which inspired me to add a new LLM feature: llm keys get openai - https://github.com/simonw/llm/issues/623)

Re: TinyTroupe, a new LLM-powered multiagent persona simulation Python library

#15

Post by ttul »

simonw wrote: post #9

It looks like this defaults to GPT-4o: https://github.com/microsoft/TinyTroupe/blob/7ae16568ad1c4de... If you're going to try this out I would strongly recommend running it against GPT-4o mini instead. Mini is 16x cheaper and I'm confident the results you'll get out of it won't be 1/16th as good for this kind of experiment.

I suppose the Microsoft researchers default to 4o because the models are free in their environment…

Re: TinyTroupe, a new LLM-powered multiagent persona simulation Python library

#17

Post by dragonwriter »

This seems fundamentally unsuitable for its stated purpose, which is “understanding human behavior”.

While it may, as it says, produce “convincing interactions”, there is no basis at all peesented for believing it produces an accurate model of human behavior, so using it to “understand human behavior” is at best willful self-deception, and probably, with a little effort at tweaking inputs to produce the desired results, most often when used by someone who presents it as “enlightening productivity and business scenarios” it will be an engine for simply manufacturing support for a pre-selected option.

It is certainly easier and cheaper than exploring actual human interactions to understand human behavior, but then so is just using a magic 8-ball, which may be less convincing, but for all the evidence supporting this is just as accurate.

Re: TinyTroupe, a new LLM-powered multiagent persona simulation Python library

#18

Post by potatoman22 »

dragonwriter wrote: post #17

This seems fundamentally unsuitable for its stated purpose, which is “understanding human behavior”. While it may, as it says, produce “convincing interactions”, there is no basis at all peesented for believing it produces an accurate model of human behavior, so using it to “understand human behavior” is at best willful self-deception, and probably, with a little effort at tweaking inputs to produce the desired resul…

I wonder how one could measure the how human-like the agents' opinions and interactions are? There's a ton of value in simulating preferences, but you're right that it's hard to know if the simulation is accurate.

I have a hunch that, through sampling many AI "opinions," you can arrive at something like the wisdom of the crowd, but again, it's hard to validate.

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