AutoResearchClaw/config_test_run.yaml at main · aiming-lab/AutoResearchClaw · GitHub

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project:
  name: "cpu-optimization-test"
  mode: "full-auto"

research:
  topic: "Comparing gradient-free optimization algorithms (Nelder-Mead, Powell, CMA-ES) for non-convex benchmark functions using only CPU computation with NumPy"
  domains:
    - "optimization"
    - "numerical-methods"
  daily_paper_count: 5
  quality_threshold: 3.0

runtime:
  timezone: "Asia/Shanghai"
  max_parallel_tasks: 2
  approval_timeout_hours: 1
  retry_limit: 2

notifications:
  channel: "console"
  target: ""
  on_stage_start: true
  on_stage_fail: true
  on_gate_required: true

knowledge_base:
  backend: "markdown"
  root: "docs/kb"

openclaw_bridge:
  use_cron: false
  use_message: false
  use_memory: false
  use_sessions_spawn: false
  use_web_fetch: false
  use_browser: false

llm:
  provider: "openai-compatible"
  base_url: "https://openai-api.shenmishajing.workers.dev/v1"
  api_key: "r685RxDQ3lYYWC8nOH5SUDlLZEkutddM"
  api_key_env: "RESEARCHCLAW_API_KEY"
  primary_model: "gpt-4o"
  fallback_models:
    - "gpt-4.1"

security:
  hitl_required_stages: []
  allow_publish_without_approval: true
  redact_sensitive_logs: false

experiment:
  mode: "sandbox"
  time_budget_sec: 120
  max_iterations: 5
  metric_key: "primary_metric"
  metric_direction: "minimize"
  sandbox:
    python_path: "/opt/anaconda3/bin/python3"
    gpu_required: false
    max_memory_mb: 4096
    allowed_imports:
      - "numpy"
      - "scipy"
      - "matplotlib"
      - "json"
      - "time"
      - "os"
      - "sys"
      - "math"
      - "random"
      - "collections"
      - "itertools"
      - "functools"
      - "typing"
      - "dataclasses"
      - "pathlib"
      - "csv"

prompts:
  custom_file: ""