project: "AgentScope" # Project name
name: "Email_search" # Experiment name
checkpoint_root_dir: ${oc.env:TRINITY_CHECKPOINT_ROOT_DIR,./checkpoints}  # Directory to save model checkpoints
algorithm:
  algorithm_type: multi_step_grpo  # GRPO series for multi-step scenario
  repeat_times: 8  # Number of rollouts per prompt for advantage estimation
  optimizer:
    lr: 1e-6  # Learning rate
  policy_loss_fn: "rec"  # Policy loss function
  policy_loss_fn_args: # Policy loss function arguments
    epsilon_low: 0.2
    epsilon_high: 0.2
    clip_mode: "one-side"
    weight: "none"
    temp: 1.0
    regularizer: "none"
    regularizer_coef: 0.0
  kl_loss_fn: 'k2' # KL divergence loss function
  kl_loss_fn_args:
    kl_coef: 0.0 # KL divergence coefficient
  advantage_fn_args:
    std_cal_level: 'batch' # Advantage normalization level
model:
  model_path: ${oc.env:TRINITY_MODEL_PATH,Qwen/Qwen3-4B-Instruct-2507}  # Base model path
  max_response_tokens: 4096  # Max tokens per response
  max_model_len: 20480  # Max context length
buffer:
  total_epochs: 10  # Total training epochs
  batch_size: 64  # Batch size per explore step
  train_batch_size: 2560  # 64*8*5, total experiences per training step
  trainer_input:
    experience_buffer:
      name: experience_buffer
      storage_type: queue
      replay_buffer:
        enable: true  # Enable experience replay
        priority_fn: 'decay_limit_randomization'
        priority_fn_args:
          decay: 2.0
          use_count_limit: 3
          sigma: 2.0
explorer:
  eval_interval: 10
  max_repeat_times_per_runner: 1 # Max repeat times per runner
  max_timeout: 3600 # Max timeout for each rollout (seconds)
  rollout_model:
    enable_history: true # Enable conversation history
    enable_openai_api: true # Enable OpenAI-compatible API
    enable_auto_tool_choice: true # Enable automatic tool selection
    tool_call_parser: hermes # Parser for tool calls
    engine_num: 4   # Number of vLLM engines for rollout model
    tensor_parallel_size: 1  # TP size per engine for rollout model
    enable_prefix_caching: false # Disable prefix caching
  auxiliary_models:
    - name: judge
      model_path: Qwen/Qwen3-30B-A3B-Instruct-2507 # Judge model path
      engine_num: 1  # Number of vLLM engines for judge model
      tensor_parallel_size: 2  # TP size per engine for judge model
      enable_thinking: false # Disable thinking/reasoning mode
      max_prompt_tokens: 2048 # Max tokens for prompt
      max_response_tokens: 128 # Max tokens for response
      max_model_len: 2500 # Max model context length
synchronizer:
  sync_style: dynamic_by_explorer # Sync triggered dynamically by explorer
  sync_interval: 5 # Sync every N steps
  sync_timeout: 3600 # Timeout for synchronization (seconds)
trainer:
  save_interval: 100 # Save checkpoint every N steps
  grad_clip: 1.0 # Gradient clipping value
  use_dynamic_bsz: true # Use dynamic batch size
  max_token_len_per_gpu: 16384 # Max token length per GPU
  ulysses_sequence_parallel_size: 1 # Sequence parallel size for Ulysses