Configuration Reference
Complete reference for all SkillOpt configuration parameters.
Model
| Parameter |
Type |
Default |
Description |
model.backend |
str |
azure_openai |
Backend: azure_openai / openai_chat / claude_code_exec / qwen |
model.optimizer |
str |
gpt-5.5 |
Optimizer model (for reflection & slow update) |
model.target |
str |
gpt-5.5 |
Target model (for rollout execution) |
model.reasoning_effort |
str |
medium |
Reasoning effort level |
model.optimizer_backend |
str |
openai_chat |
Optimizer backend: openai_chat / claude_chat / qwen_chat / minimax_chat |
model.target_backend |
str |
openai_chat |
Target backend: chat backends plus execution harnesses |
model.qwen_chat_base_url |
str |
http://localhost:8000/v1 |
Shared Qwen/vLLM OpenAI-compatible endpoint |
model.qwen_chat_enable_thinking |
bool |
false |
Shared Qwen thinking flag |
model.optimizer_qwen_chat_base_url |
str |
— |
Optimizer-specific Qwen/vLLM endpoint; overrides shared qwen_chat_base_url |
model.target_qwen_chat_base_url |
str |
— |
Target-specific Qwen/vLLM endpoint; overrides shared qwen_chat_base_url |
Training (train)
| Parameter |
Type |
Default |
DL Analogy |
Description |
train.num_epochs |
int |
4 |
Epochs |
Number of training epochs |
train.batch_size |
int |
40 |
Batch size |
Tasks sampled per step |
train.accumulation |
int |
1 |
Gradient accumulation |
Accumulation rounds per step |
train.seed |
int |
42 |
Random seed |
Reproducibility seed |
Gradient / Reflection (gradient)
| Parameter |
Type |
Default |
Description |
gradient.minibatch_size |
int |
8 |
Reflect minibatch size |
gradient.merge_batch_size |
int |
8 |
Patch merge batch size |
gradient.analyst_workers |
int |
16 |
Parallel reflection workers |
gradient.max_analyst_rounds |
int |
3 |
Max rounds of analyst reflection |
gradient.failure_only |
bool |
false |
Only reflect on failures |
Optimizer (optimizer)
| Parameter |
Type |
Default |
DL Analogy |
Description |
optimizer.learning_rate |
int |
4 |
Learning rate |
Max edit patches per step (edit budget) |
optimizer.min_learning_rate |
int |
2 |
Min LR |
Min edits for decay schedulers |
optimizer.lr_scheduler |
str |
cosine |
LR schedule |
constant / linear / cosine / autonomous |
optimizer.skill_update_mode |
str |
patch |
— |
patch / rewrite_from_suggestions / full_rewrite_minibatch |
optimizer.use_slow_update |
bool |
true |
Momentum |
Epoch-boundary longitudinal comparison & guidance |
optimizer.slow_update_samples |
int |
20 |
— |
Samples for slow update evaluation |
optimizer.use_meta_skill |
bool |
true |
Meta-learning |
Cross-epoch optimizer-side strategy memory |
optimizer.longitudinal_pair_policy |
str |
mixed |
— |
mixed / changed / unchanged |
Evaluation (evaluation)
| Parameter |
Type |
Default |
Description |
evaluation.use_gate |
bool |
true |
Enable validation gating (accept/reject updates) |
evaluation.eval_test |
bool |
true |
Run test evaluation after training |
Environment (env)
| Parameter |
Type |
Default |
Description |
env.name |
str |
— |
Benchmark name (e.g., searchqa, docvqa) |
env.data_path |
str |
— |
Path to dataset |
env.skill_init |
str |
— |
Path to initial seed skill (optional) |
env.split_mode |
str |
ratio |
ratio or split_dir |
env.split_ratio |
str |
2:1:7 |
Train:val:test ratio |
env.exec_timeout |
int |
120 |
Per-task timeout in seconds |
env.out_root |
str |
— |
Output directory |
Azure OpenAI Credentials
| Variable |
Description |
AZURE_OPENAI_ENDPOINT / model.azure_openai_endpoint |
Azure resource endpoint |
AZURE_OPENAI_API_KEY / model.azure_openai_api_key |
Azure API key |
OPENAI_API_KEY |
OpenAI API key (for openai_chat backend) |
ANTHROPIC_API_KEY |
Anthropic API key (for claude_code_exec backend) |
QWEN_CHAT_BASE_URL |
Shared local vLLM endpoint for qwen_chat |
QWEN_CHAT_MODEL |
Shared served model name for qwen_chat |
QWEN_CHAT_API_KEY |
Optional API key for the shared Qwen endpoint |
OPTIMIZER_QWEN_CHAT_BASE_URL |
Optimizer-specific local vLLM endpoint |
OPTIMIZER_QWEN_CHAT_MODEL |
Optimizer-specific served model name |
TARGET_QWEN_CHAT_BASE_URL |
Target-specific local vLLM endpoint |
TARGET_QWEN_CHAT_MODEL |
Target-specific served model name |