chore: track claude skills, tools, templates, reference code and research-wiki

- Add all claude skills (brainstorming, commit, debugging, TDD, etc.) - Add claude hooks (pre-commit-guard, post-edit-quality) - Add research templates (experiment plan, research brief, etc.) - Add claude tools (arxiv/semantic_scholar/openalex fetch, wiki, exa) - Add TRM4 reference implementation as algorithm fidelity baseline - Add research-wiki content (plans, index, graph, query_pack) - Update .gitignore to exclude .graphify_version runtime state
2026-07-06 20:59:03 -04:00
parent 0616d16956
commit 6bdb802f01
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+tree:
+  max_paragraphs_per_l2: 5
+  l1_segment_duration: 600.0           # L1: 每段 10 分钟（长视频适配）
+  l2_clip_duration: 60.0               # L2: 每 clip 60 秒
+  l3_fps: 0.5                          # L3: 0.5 帧/秒（每 2 秒一帧）
+  l2_representative_frames: 6          # L2 VLM 描述用的代表帧数（从10降到6以提速）
+  cache_dir: "data/videomme/trees"     # 树索引缓存目录（相对项目根目录）
+  concurrency: 16                      # asyncio Semaphore 上限：每视频最多 16 路同时在途 VLM 请求
+
+embed:
+  backend: "local"                     # CPU 本地运行，无需远程嵌入服务
+  model_name: "BAAI/bge-base-zh-v1.5"
+  embed_dim: 768                       # bge-base-zh-v1.5 输出维度
+  device: "cpu"                        # 本地 CPU 推理
+  api_key: ""
+  api_url: ""
+
+llm:
+  backend: "openai"                    # GPUStack 兼容 OpenAI API
+  model: "gemma-4-31B"
+  api_url: "http://100.83.164.94:11904/v1"
+  max_tokens: 256
+  temperature: 0.1
+  # api_key: 从 .env 加载
+
+vlm:
+  backend: "openai"                    # GPUStack 兼容 OpenAI API
+  model: "gemma-4-31B"
+  api_url: "http://100.83.164.94:11904/v1"
+  max_tokens: 512                      # 5帧描述 ~300 tokens，256 会截断 JSON 触发 fallback
+  temperature: 0.1
+  # api_key: 从 .env 加载
+
+retriever:
+  embed_dim: 768                       # 与 bge-base-zh-v1.5 维度一致
+  num_heads: 4
+  L_layers: 2
+  L_cycles: 4
+  max_rounds: 5
+  ffn_expansion: 2.0
+  checkpoint: null
+  k_l1: 1
+  k_l2: 1
+  k_l3: 1
+  max_paths: 5
+
+train:
+  lr: 1.0e-4
+  weight_decay: 1.0e-5
+  batch_size: 1
+  max_epochs_phase1: 30
+  max_epochs_phase2: 20
+  nav_loss_weight: 1.0
+  act_loss_weight: 0.1
+  margin_loss_weight: 0.5
+  act_lambda_step: 0.1
+  act_gamma: 0.9
+  eval_interval: 5
+  save_dir: "data/videomme/checkpoints"
+  dataset: "videomme"
+  dataset_path: "data/videomme/splits/train.jsonl"