Commit graph

5 commits

Author SHA1 Message Date
Teknium
7ff7155cbd fix(skills/llama-cpp): concise description, restore python bindings, fix curl
- Description truncated to 60 chars in system prompt (extract_skill_description),
  so the 500-char HF workflow description never reached the agent; shortened to
  'llama.cpp local GGUF inference + HF Hub model discovery.' (56 chars).
- Restore llama-cpp-python section (basic, chat+stream, embeddings,
  Llama.from_pretrained) and frontmatter dependencies entry.
- Fix broken 'Authorization: Bearer ***' curl line (missing closing quote;
  llama-server doesn't require auth by default).
2026-04-21 13:30:10 -07:00
burtenshaw
d6cf2cc058 improve llama.cpp skill 2026-04-21 13:30:10 -07:00
Teknium
73bccc94c7
skills: consolidate mlops redundancies (gguf+llama-cpp, grpo+trl, guidance→optional) (#11965)
Three tightly-scoped built-in skill consolidations to reduce redundancy in
the available_skills listing injected into every system prompt:

1. gguf-quantization → llama-cpp (merged)
   GGUF is llama.cpp's format; two skills covered the same toolchain. The
   merged llama-cpp skill keeps the full K-quant table + imatrix workflow
   from gguf and the ROCm/benchmarks/supported-models sections from the
   original llama-cpp. All 5 reference files preserved.

2. grpo-rl-training → fine-tuning-with-trl (folded in)
   GRPO isn't a framework, it's a trainer inside TRL. Moved the 17KB
   deep-dive SKILL.md to references/grpo-training.md and the working
   template to templates/basic_grpo_training.py. TRL's GRPO workflow
   section now points to both. Atropos skill's related_skills updated.

3. guidance → optional-skills/mlops/
   Dropped from built-in. Outlines (still built-in) covers the same
   structured-generation ground with wider adoption. Listed in the
   optional catalog for users who specifically want Guidance.

Net: 3 fewer built-in skill lines in every system prompt, zero content
loss. Contributor authorship preserved via git rename detection.
2026-04-17 21:36:40 -07:00
Teknium
5ceed021dc
feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap (#3934)
* feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap

Map active skills to Telegram's slash command menu so users can
discover and invoke skills directly. Three changes:

1. Telegram menu now includes active skill commands alongside built-in
   commands, capped at 100 entries (Telegram Bot API limit). Overflow
   commands remain callable but hidden from the picker. Logged at
   startup when cap is hit.

2. New /commands [page] gateway command for paginated browsing of all
   commands + skills. /help now shows first 10 skill commands and
   points to /commands for the full list.

3. When a user types a slash command that matches a disabled or
   uninstalled skill, they get actionable guidance:
   - Disabled: 'Enable it with: hermes skills config'
   - Optional (not installed): 'Install with: hermes skills install official/<path>'

Built on ideas from PR #3921 by @kshitijk4poor.

* chore: move 21 niche skills to optional-skills

Move specialized/niche skills from built-in (skills/) to optional
(optional-skills/) to reduce the default skill count. Users can
install them with: hermes skills install official/<category>/<name>

Moved skills (21):
- mlops: accelerate, chroma, faiss, flash-attention,
  hermes-atropos-environments, huggingface-tokenizers, instructor,
  lambda-labs, llava, nemo-curator, pinecone, pytorch-lightning,
  qdrant, saelens, simpo, slime, tensorrt-llm, torchtitan
- research: domain-intel, duckduckgo-search
- devops: inference-sh cli

Built-in skills: 96 → 75
Optional skills: 22 → 43

* fix: only include repo built-in skills in Telegram menu, not user-installed

User-installed skills (from hub or manually added) stay accessible via
/skills and by typing the command directly, but don't get registered
in the Telegram slash command picker. Only skills whose SKILL.md is
under the repo's skills/ directory are included in the menu.

This keeps the Telegram menu focused on the curated built-in set while
user-installed skills remain discoverable through /skills and /commands.
2026-03-30 10:57:30 -07:00
teknium1
732c66b0f3 refactor: reorganize skills into sub-categories
The skills directory was getting disorganized — mlops alone had 40
skills in a flat list, and 12 categories were singletons with just
one skill each.

Code change:
- prompt_builder.py: Support sub-categories in skill scanner.
  skills/mlops/training/axolotl/SKILL.md now shows as category
  'mlops/training' instead of just 'mlops'. Backwards-compatible
  with existing flat structure.

Split mlops (40 skills) into 7 sub-categories:
- mlops/training (12): accelerate, axolotl, flash-attention,
  grpo-rl-training, peft, pytorch-fsdp, pytorch-lightning,
  simpo, slime, torchtitan, trl-fine-tuning, unsloth
- mlops/inference (8): gguf, guidance, instructor, llama-cpp,
  obliteratus, outlines, tensorrt-llm, vllm
- mlops/models (6): audiocraft, clip, llava, segment-anything,
  stable-diffusion, whisper
- mlops/vector-databases (4): chroma, faiss, pinecone, qdrant
- mlops/evaluation (5): huggingface-tokenizers,
  lm-evaluation-harness, nemo-curator, saelens, weights-and-biases
- mlops/cloud (2): lambda-labs, modal
- mlops/research (1): dspy

Merged singleton categories:
- gifs → media (gif-search joins youtube-content)
- music-creation → media (heartmula, songsee)
- diagramming → creative (excalidraw joins ascii-art)
- ocr-and-documents → productivity
- domain → research (domain-intel)
- feeds → research (blogwatcher)
- market-data → research (polymarket)

Fixed misplaced skills:
- mlops/code-review → software-development (not ML-specific)
- mlops/ml-paper-writing → research (academic writing)

Added DESCRIPTION.md files for all new/updated categories.
2026-03-09 03:35:53 -07:00