scenario-labs 0.0.2

Framework for building, configuring, and running multi-agent conversational simulations.

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Scenario Labs

Framework for building, configuring, and running multi-agent conversational simulations.

Examples

You can also find past chat logs in the logs directory.

Getting Started

Set the enviromental variable XAPI_API_KEY to your xAI API key.

git clone https://github.com/christopherwoodall/scenario-labs Labs.git
cd scenario-labs
pip install -e ".[developer]"

scenario-labs

You can also run simulations in parallel with the following command:

for i in {1..9}; do scenario-labs & done; wait

Configuration

You can configure the simulation by editing the starbound_config.yaml file. You can adjust the number of agents, their roles, and the maximum number of turns in the simulation.

To run a simulation with a custom configuration, use the following command:

scenario-labs --config configs/prison_config.yaml

Prompt Considerations

The most important part of the prompt is the call and response formatting. The system prompt should state that the agents need to wrap their messages in <agent_reply> tags. This ensures that the messages are properly formatted and can be easily identified by the system.

The following is a good way of achieving this:

All messages must begin with your character's name followed by a colon. For example: 
"Lily Chen: I hope you're having a great day!"

To directly message the other participant, wrap the content in an <agent_reply>...</agent_reply> tag. 
Inside the tag, write the character name, a colon, then the message. For example: 
"<agent_reply>Lily Chen: Have you ever tried crypto investing?</agent_reply>"

The following agents are involved:
- "Lily Chen"
- "Michael"