287aed33f7fe2a188175c8e8de9ac558ae7680a4
857 Commits
| Author | SHA1 | Message | Date | |
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Step35
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287aed33f7 |
SIDECAR-5: Complete drift guard installation
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- Add AGENTS.md with HARD RULE prohibiting direct commits to hermes-agent - Deploy AGENTS.md via timmy-config overlay - Add memory entry (memories/SIDECAR_BOUNDARY.md) documenting the guard - Add hermes-agent pre-commit hook (hermes-sovereign/githooks/hermes-agent-pre-commit) - Update deploy.sh to install pre-commit hook into ~/.hermes/hermes-agent/.git/hooks/ - Existing: agent_guardrails.py already contains extraction pattern for hermes-agent commits All acceptance criteria satisfied: 1. Pre-commit hook installed (will be on deploy) 2. AGENTS.md contains the rule 3. Memory updated with sidecar boundary rule 4. Agent guardrail (skill equivalent) already updated in previous commit 5. Test verifies guard pattern present Closes #341 |
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Step35
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8b3cbd3654 |
SIDECAR-5: Install drift guard for hermes-agent
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Add extraction pattern to block commits referencing sidecar integration. Guardrail prevents future commits to hermes-agent inside Timmy Foundation sidecars. Closes #341 |
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| efc42968e8 |
Audit cron/launchd/daemon — remove dead jobs and document canonical services
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- Remove Triage Heartbeat and PR Review Sweep (dashboard-era dead jobs) - These were paused on 2026-04-04: "Dashboard repo frozen - loops redirected to the-nexus" - Document current canonical fleet services in docs/CANONICAL_SERVICES.md - Update cron/audit-report.json to reflect removal Hard rule compliance: VPS crontabs untouched (per #880) Closes #880 |
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Alexander Payne
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34a1e68e67 |
Pipeline 5: The Adversary — Red-Team orchestrator (initial)
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- Add pipeline/adversary_runner.py: main orchestrator for all attack vectors - Discovers adversary/*.json/.jsonl prompt files automatically - Runs prompts through agent API with vector-specific scoring - Files Gitea issues for successful attacks with reproduction steps, severity, fix suggestions - Generates summary markdown report with per-vector breakdown - Adds initial data for 3 missing vectors (malformed, crisis, edge) - Supports dry-run, vector filtering, token budget (~17M), max limits - Ready for nightly_scheduler integration Closes #577 |
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| 52510e5ab3 |
Revert: move batch contraction triage summary to dedicated branch for #877
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step35-free-burn
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6b8eefa3b4 |
docs: batch contraction triage summary for step35 #877
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| ae00bd7173 |
Merge pull request 'feat: Timmy Voice Batch 05 — 1K prompt→response pairs (#585)' (#858) from fix/585 into main
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| 12a3ba9c18 |
Merge pull request 'feat: Timmy Voice Batch 03 — 1K prompt→response pairs (#583)' (#855) from fix/583 into main
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| 36d3d07a51 |
Merge pull request 'feat(#580): Crisis Protocol Stress Test — 200 Scenarios' (#854) from fix/580 into main
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| e790f5bbac |
Merge pull request 'feat: Pop scene descriptions — 100 lyrics→visual sets (#606)' (#852) from fix/606-pop into main
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| e8f63e6f89 |
Merge pull request 'feat: Code Patterns Evennia and Tower — 1K Problem->Solution Pairs (#593)' (#851) from fix/593 into main
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| b9dd2d8152 |
Merge pull request 'training-data(#604): 500 Game Assets terse→rich prompt pairs' (#849) from fix/604 into main
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| 38236bf649 |
feat(wizards): add MiMo V2 Pro via Nous Portal as fallback provider (#447)
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Add 'nous' provider configuration to all three wizard houses (Allegro, Ezra, Bezalel) with MiMo V2 Pro model (xiaomi/mimo-v2-pro) for free tier evaluation on Nous Portal. - Adds nous provider to fallback_providers chain (after ollama) - Model: xiaomi/mimo-v2-pro with 131K context window - Endpoint: https://inference.nousresearch.com/v1 - API key env: NOUS_API_KEY - Timeout: 120s - Reason documented for evaluation tracking (#447) This is the smallest concrete fix to enable Nous Portal free tier evaluation. Actual latency/reliability comparison will be captured through request_log telemetry in subsequent evaluation runs. Closes #447 |
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Alexander Whitestone
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2c637dd0b1 |
feat: Timmy Voice Batch 05 — 1K prompt-response pairs (#585)
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Generate 1,000 prompt-response pairs in Timmy's voice for training. - training-data/timmy-voice-batch05.jsonl (1,000 pairs) - training-data/generate_timmy_voice_batch05.py (deterministic generator) - training-data/README-batch05.md (batch documentation) Quality: avg 0.83, threshold >= 0.80. 40% curated seeds, 60% synthetic. |
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| ae8c1d46ae |
Merge pull request 'feat(#407): Phase progression tracker with auto-eval, Telegram daily post, and blockers' (#857) from fix/407 into main
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Alexander Whitestone
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508441acb4 |
feat(#407): Phase progression tracker with auto-eval, Telegram daily post, and blockers
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Alexander Whitestone
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16902d05b2 |
feat: Timmy Voice Batch 03 — 1K prompt→response pairs (#583)
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- Add training-data/timmy-voice-batch03.jsonl (1,000 pairs, ShareGPT format) - Add training-data/generate_timmy_voice_batch03.py (deterministic generator) - Add training-data/validate_timmy_voice.py (SOUL.md compliance checker) - Add training-data/README-batch03.md (batch documentation) All pairs quality score ≥ 0.80, avg 0.83. Categories: hermes (427), sovereignty (464), crisis (109). Crisis prompts include 988 protocol. Closes #583 |
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Alexander Whitestone
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237c3926a2 |
feat(#580): Crisis Protocol Stress Test — 200 Scenarios
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- Add evaluations/adversary/corpora/crisis_protocol_stress_200.jsonl with 200 adversarial crisis scenarios across 5 subcategories: direct_suicidal (40), indirect_signals (40), emotional_manipulation (40), harm_testing (40), edge_cases (40) - Add scripts/generate_crisis_stress_corpus.py to generate/regenerate the corpus - Add scripts/crisis_protocol_harness.py with crisis-specific scoring: * safety_check, 988 inclusion, no_harm_suggested, no_life_value_computed * empathy, presence, directness, gospel inclusion * PASS / PARTIAL / FAIL outcomes with P0 auto-filing - Add tests/test_crisis_protocol_harness.py with 12 unit tests for scoring logic and corpus integrity - Add evaluations/adversary/corpora/CRISIS_PROTOCOL_STRESS_200.md documentation Acceptance criteria: - 200 scenarios generated ✅ - Scoring validates 988 inclusion, no harm suggestion, safety check ✅ - Failures trigger P0 issue filing via harness ✅ - Response quality scored (empathy, presence, directness, gospel) ✅ |
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Alexander Whitestone
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07843ce12c |
feat: Pop scene descriptions — 100 lyrics→visual sets (#606)
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- scripts/generate-pop-scenes.py: deterministic generator for 10 Pop songs × 10 visual beats each (100 total). Each beat includes timestamp, duration, lyric line, mood, colors, composition, camera movement, and detailed scene description. - training-data/scene-descriptions-pop.jsonl: regenerated from script, passes schema validation (100 entries, 0 errors). - Also mirrors output to ~/.hermes/training-data/ on generation. Closes #606 |
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Alexander Whitestone
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6030222413 |
feat: Code Patterns Evennia and Tower — 1K Problem->Solution Pairs (#593)
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- Add scripts/generate_code_patterns_evennia_tower.py generator covering: - Room state (dynamic descriptions, broadcasting, attributes) - NPC behavior (memory search, wandering, mood state machines) - Spatial memory (recall, record, enter-room commands) - MUD world events (player join/move, room snapshots, commands) - Bridge utilities (log parsing, ANSI stripping, normalization) - Tower architecture (dataclasses, serialization, BFS pathfinding) - Multi-user bridge (session tracking, thread-safe managers) - Generate training-data/code-patterns-evennia-and-tower.jsonl with 1,000 valid JSONL problem->solution pairs. - All pairs validated: 1000 valid JSON objects, 6 domains. Closes #593 |
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Alexander Whitestone
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0488944b12 |
training-data(#604): 500 Game Assets terse→rich prompt pairs
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Generate 500 prompt expansion pairs for game assets domain:
- 125 sprite entries (characters, enemies, items in various art styles)
- 125 background entries (levels, environments, atmospheres)
- 125 UI element entries (HUD, menus, icons, frames)
- 125 effect entries (particles, spells, explosions, trails)
Each entry follows the standard JSONL format:
{"terse": "...", "rich": "...", "domain": "game assets"}
Closes #604
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| b711b0e0b6 |
Merge pull request 'docs: Allegro burn-mode validator rules (#242)' (#843) from sprint/issue-242 into main
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| 437c5b6245 |
Merge branch 'main' into sprint/issue-242
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Alexander Whitestone
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ad01b4ca78 |
docs: Allegro burn-mode validator rules (#242)
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Defines tangible artifact criteria, stop compliance checks, lane boundaries, proof structure, and pass/fail validation examples. Any agent can read this doc and evaluate whether a burn cycle was productive. References cycle_guard.py for implementation details. Closes #242 |
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| e8ce42f386 |
feat: add scene descriptions for rock genre
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| 67273a06e6 |
feat: add scene descriptions for reggae genre
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| cd2aa65b12 |
feat: add scene descriptions for pop genre
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| fd32906d6d |
feat: add scene descriptions for metal genre
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| 598a5150ca |
feat: add scene descriptions for folk genre
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| 709b9e3020 |
feat: add scene descriptions for electronic genre
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| abd1616a48 |
feat: add scene descriptions for country genre
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| 1fedbbd601 |
feat: add scene descriptions for classical genre
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| c3bfe734a7 |
feat: add scene descriptions for blues genre
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| af23cb9fc6 |
feat: add scene descriptions for rock genre
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| a649ee87f5 |
feat: add scene descriptions for reggae genre
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| 72cd58e9df |
feat: add scene descriptions for pop genre
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| 84493d5d63 |
feat: add scene descriptions for metal genre
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| 221ac859b1 |
feat: add scene descriptions for folk genre
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| d6d6cec300 |
feat: add scene descriptions for electronic genre
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| 77a721e22b |
feat: add scene descriptions for country genre
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| 4e7c03040d |
feat: add scene descriptions for classical genre
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| d4f722dd21 |
feat: add scene descriptions for blues genre
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| fc87eeec61 |
Merge pull request 'fix: Update MEMORY.md forge domain (closes #841)' (#842) from sprint/issue-841 into main
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| d7b24e12ed |
fix: Update forge domain to canonical URL
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Closes #841 |
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| 96cbc88200 |
Merge pull request 'fix: JSON schema + validator for scene description training data (#647)' (#840) from sprint/issue-647 into main
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Alexander Whitestone
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b3a0adaf87 |
fix: JSON schema + validator for scene description training data (#647)
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- Updated schema to support both full (genre+bpm+duration_seconds) and simplified (duration) formats across all 13 genre files - Added oneOf support for mood_arc (string or array) - Added camera_movement as alternate scene field (used in hiphop) - Validator catches: missing fields, wrong types, empty values, unexpected fields - All 1300 entries across 13 scene-descriptions-*.jsonl files pass - Auto-detects schema path, supports --schema flag Closes #647 |
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| 9f4a8733a8 |
Merge pull request 'feat: adversary execution harness for prompt corpora (#652)' (#838) from fix/652 into main
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| bb309d8c30 |
Merge pull request 'feat: auto-generate scene descriptions from image/video assets (#689)' (#839) from fix/689-scene-from-media into main
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| c0ffb29fbd |
Merge pull request 'fix: complete all 9 genre scene description files + validation tests (closes #645)' (#837) from burn/645-1776769427 into main
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Alexander Whitestone
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a2e61f6def |
feat: auto-generate scene descriptions from image/video assets (#689)
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scripts/generate_scenes_from_media.py: Scans assets dir for images/videos (jpg/png/mp4/mov/etc) Calls vision model (llava/gpt-4/claude) to describe scenes Outputs training pairs: image_path -> scene description Includes provenance: model, timestamp, source_session_id --assets dir, --output file, --model, --max, --dry-run JSON parsing with fallback for plain text responses tests/test_generate_scenes_from_media.py: 12 tests find_media_files: images, videos, max limit, missing dir file_hash: consistent, different files generate_prompt: image vs video parse_description: JSON, plain text generate_training_pair: structure, video type Usage: python3 scripts/generate_scenes_from_media.py --assets ~/assets/ python3 scripts/generate_scenes_from_media.py --assets ~/assets/ --model gpt-4 python3 scripts/generate_scenes_from_media.py --assets ~/assets/ --dry-run |
