If I jump in and, say, manually 'tweak' one of those JSON strategies because I think I have a better idea, what happens next? Does the LLM just roll with my brilliant human intervention, or could it eventually 'learn' that my tweak was actually counterproductive and refine it back (or away from my edit)?
You can run in two modes, by default you run in the inference mode without learning. So, the changes you made will be used. If you switch to learning mode then the strategies are updated/refined and merged based on a config that you can control.
# How often to perform maintenance operations (merge, prune)
MAINTENANCE_INTERVAL = 40
# Strategy selection thresholds
STRATEGY_CREATION_THRESHOLD = 0.7 # Higher threshold to avoid creating similar strategies
STRATEGY_MERGING_THRESHOLD = 0.6 # Lower threshold to merge more similar strategies
MIN_SUCCESS_RATE_FOR_INFERENCE = 0.4 # Minimum success rate for a strategy to be used during inference
Comments
If I jump in and, say, manually 'tweak' one of those JSON strategies because I think I have a better idea, what happens next? Does the LLM just roll with my brilliant human intervention, or could it eventually 'learn' that my tweak was actually counterproductive and refine it back (or away from my edit)?
You can run in two modes, by default you run in the inference mode without learning. So, the changes you made will be used. If you switch to learning mode then the strategies are updated/refined and merged based on a config that you can control.
# How often to perform maintenance operations (merge, prune)
MAINTENANCE_INTERVAL = 40
# Strategy selection thresholds
STRATEGY_CREATION_THRESHOLD = 0.7 # Higher threshold to avoid creating similar strategies
STRATEGY_MERGING_THRESHOLD = 0.6 # Lower threshold to merge more similar strategies
MIN_SUCCESS_RATE_FOR_INFERENCE = 0.4 # Minimum success rate for a strategy to be used during inference
The configs are all defined here - https://github.com/codelion/optillm/blob/main/optillm/plugin...