{"repo": "1692775560/paperclaw", "files": {"config.paperclaw.yaml": {"fb0ff81587c97c8b3366dde9f0a6f94218aa3207": {"t": 1785745201.2840576, "n": 4678, "h": "83f563e85b64d05b", "c": "# ============================================================================\n# PaperClaw 配置文件\n# 面向学术科研工作者的高能动性AI自动化辅助系统\n# 三层协同架构: 大脑(LLM决策引擎) + 手脚(Skill插件执行层) + 记忆(Memory知识管理)\n# ============================================================================\n\nproject:\n  name: \"my-research\"\n  mode: \"full-auto\"  # docs-first | semi-auto | full-auto\n\nresearch:\n  topic: \"你的研究主题\"\n  domains:\n    - \"machine-learning\"\n    - \"nlp\"\n  daily_paper_count: 10\n  quality_threshold: 4.0\n\nruntime:\n  timezone: \"Asia/Shanghai\"\n  max_parallel_tasks: 3\n  approval_timeout_hours: 12\n  retry_limit: 2\n\nnotifications:\n  channel: \"console\"\n  target: \"\"\n  on_stage_start: true\n  on_stage_fail: true\n  on_gate_required: true\n\nknowledge_base:\n  backend: \"markdown\"  # markdown | obsidian\n  root: \"docs/kb\"\n\n# ============================================================================\n# 大脑层配置 — LLM决策引擎\n# ============================================================================\n\nllm:\n  provider: \"openai-compatible\"\n  base_url: \"https://api.deepseek.com/v1\"\n  api_key_env: \"DEEPSEEK_API_KEY\"\n  api_key: \"sk-f31e2e0f6c064c4f86a08b0a4df5cf6a\"\n  primary_model: \"deepseek-chat\"\n  fallback_models:\n    - \"deepseek-chat\"\n  s2_api_key: \"\"  # Semantic Scholar API key (可选，提高文献检索速率限制)\n\nsecurity:\n  hitl_required_stages: [5, 9, 20]  # 需要人工审批的门控阶段\n  allow_publish_without_approval: false\n  redact_sensitive_logs: true\n\n# ============================================================================\n# 手脚层配置 — Skill插件执行层\n# ============================================================================\n\nexperiment:\n  # 实验执行模式\n  #   \"sandbox\"   — 本地沙盒执行，产出真实实验数据\n  #   \"docker\"    — Docker容器执行，支持GPU、依赖自动安装、内存隔离\n  #   \"ssh_remote\"— SSH远程服务器执行（适合GPU集群）\n  #   \"simulated\" — 模拟模式（仅用于开发调试）\n  mode: \"simulated\"\n  time_budget_sec: 300\n  max_iterations: 10\n  metric_key: \"primary_metric\"\n  metric_direction: \"minimize\"\n  \n  # Sandbox配置\n  sandbox:\n    python_path: \".venv/bin/python3\"\n    gpu_required: false\n    max_memory_mb: 4096\n  \n  # Docker配置（需先构建镜像: docker build -t paperclaw/experiment:latest）\n  docker:\n    image: \"paperclaw/experiment:latest\"\n    gpu_enabled: true\n    memory_limit_mb: 8192\n    network_policy: \"setup_only\"  # none | setup_only | pip_only | full\n    auto_install_deps: true\n    shm_size_mb: 2048\n    keep_containers: false\n  \n  # SSH远程执行配置\n  ssh_remote:\n    host: \"\"\n    user: \"\"\n    port: 22\n    key_path: \"\"\n    gpu_ids: []\n    remote_workdir: \"/tmp/paperclaw_experiments\"\n    remote_python: \"python3\"\n    setup_commands: []\n    use_docker: false\n    docker_image: \"paperclaw/experiment:latest\"\n    docker_network_policy: \"none\"\n    docker_memory_limit_mb: 8192\n    docker_shm_size_mb: 2048\n  \n  # OpenCode Beast Mode — 复杂实验自动路由到外部AI编码Agent\n  opencode:\n    enabled: true\n    auto: true\n    complexity_threshold: 0.2  # 0.0-1.0，越高越只在复杂实验时触发\n    model: \"\"  # 留空则使用 llm.primary_model\n    timeout_sec: 600\n    max_retries: 1\n    workspace_cleanup: true\n  \n  # Colab Drive模式（无需SSH，通过Google Drive同步）\n  colab_drive:\n    drive_root: \"\"\n    poll_interval_sec: 30\n    timeout_sec: 3600\n    setup_script: \"\"\n  \n  # 科学可视化Agent（代码生成图表 + Nano Banana图像生成）\n  figure_agent:\n    enabled: true\n    min_figures: 3\n    max_figures: 10\n    max_iterations: 3\n    render_timeout_sec: 30\n    docker_image: \"paperclaw/experiment:latest\"\n    output_format: \"python\"  # python | latex\n    nano_banana_enabled: true\n    gemini_model: \"gemini-2.5-flash-image\"\n    strict_mode: false\n    dpi: 300\n\n# ============================================================================\n# 记忆层配置 — Memory知识管理\n# ============================================================================\n\n# MetaClaw集成 — 跨运行学习与自我进化\nmetaclaw_bridge:\n  enabled: false\n  proxy_url: \"http://localhost:30000\"\n  skills_dir: \"~/.metaclaw/skills\"\n  fallback_url: \"\"\n  fallback_api_key: \"\"\n  \n  # PRM质量门控（LLM-as-judge评分）\n  prm:\n    enabled: false\n    api_base: \"\"\n    api_key_env: \"PRM_API_KEY\"\n    api_key: \"\"\n    model: \"gpt-4o\"\n    votes: 3\n    gate_stages: [5, 9, 15, 20]\n  \n  # Lesson转Skill（从失败中自动学习）\n  lesson_to_skill:\n    enabled: true\n    min_severity: \"warning\"  # info | warning | error\n    max_skills_per_run: 3\n\n# OpenClaw桥接（可选 — 与OpenClaw生态集成）\nopenclaw_bridge:\n  use_cron: false\n  use_message: false\n  use_memory: false\n  use_sessions_spawn: false\n  use_web_fetch: false\n  use_browser: false\n\n# ============================================================================\n# 输出配置\n# ============================================================================\n\nexport:\n  target_conference: \"neurips_2025\"  # neurips_2025 | iclr_2026 | icml_2026\n  authors: \"Anonymous\"\n  bib_file: \"references\"\n\n# 自定义提示词（可选）\nprompts:\n  custom_file: \"\"  # 留空则使用内置默认提示词\n"}}}}