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bfts_config.yaml
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# path to the task data directory
data_dir: "data"
preprocess_data: False
goal: null
eval: null
log_dir: logs
workspace_dir: workspaces
# whether to copy the data to the workspace directory (otherwise it will be symlinked)
# copying is recommended to prevent the agent from accidentally modifying the original data
copy_data: True
exp_name: run # a random experiment name will be generated if not provided
# settings for code execution
exec:
timeout: 3600
agent_file_name: runfile.py
format_tb_ipython: False
generate_report: True
# LLM settings for final report from journal
report:
model: gpt-4o-2024-11-20
temp: 1.0
experiment:
num_syn_datasets: 1
debug:
stage4: False
# agent hyperparams
agent:
type: parallel
num_workers: 4
stages:
stage1_max_iters: 20
stage2_max_iters: 12
stage3_max_iters: 12
stage4_max_iters: 18
# how many improvement iterations to run
steps: 5 # if stage-specific max_iters are not provided, the agent will use this value for all stages
# whether to instruct the agent to use CV (set to 1 to disable)
k_fold_validation: 1
multi_seed_eval:
num_seeds: 3 # should be the same as num_workers if num_workers < 3. Otherwise, set it to be 3.
# whether to instruct the agent to generate a prediction function
expose_prediction: False
# whether to provide the agent with a preview of the data
data_preview: False
# LLM settings for coding
code:
model: anthropic.claude-3-5-sonnet-20241022-v2:0
temp: 1.0
max_tokens: 12000
# LLM settings for evaluating program output / tracebacks
feedback:
model: gpt-4o-2024-11-20
# gpt-4o
temp: 0.5
max_tokens: 8192
vlm_feedback:
model: gpt-4o-2024-11-20
temp: 0.5
max_tokens: null
search:
max_debug_depth: 3
debug_prob: 0.5
num_drafts: 3
# Options for summarizing findings and selecting the best node
# If not specified, the default behavior will be used.
# summary:
# model: gpt-4o
# temp: 0.3
# select_node:
# model: gpt-4o
# temp: 0.3