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kimi
e22b572b1d refactor: break up search_thoughts() into focused helpers
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Extract _query_thoughts() and _format_thought_results() from the 73-line
search_thoughts() function, keeping each piece focused on a single
responsibility. Also fix pre-existing F821 lint errors in mcp_tools.py.

Fixes #594

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-20 12:27:44 -04:00
2577b71207 fix: capture thought timestamp at cycle start, not after LLM call (#590)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
Co-committed-by: Kimi Agent <kimi@timmy.local>
2026-03-20 12:13:48 -04:00
1a8b8ecaed [loop-cycle-1235] refactor: break up _migrate_schema() into focused helpers (#591) (#595)
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2026-03-20 12:07:15 -04:00
d821e76589 [loop-cycle-1234] refactor: break up _generate_avatar_image (#563) (#589)
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2026-03-20 11:57:53 -04:00
bc010ecfba [loop-cycle-1233] refactor: add docstrings to calm.py route handlers (#569) (#585)
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2026-03-20 11:44:06 -04:00
faf6c1a5f1 [loop-cycle-1233] refactor: break up BaseAgent.run() (#561) (#584)
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2026-03-20 11:24:36 -04:00
48103bb076 [loop-cycle-956] refactor: break up _handle_message() into focused helpers (#553) (#574)
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2026-03-19 21:42:01 -04:00
9f244ffc70 refactor: break up _record_utterance() into focused helpers (#572)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
Co-committed-by: Kimi Agent <kimi@timmy.local>
2026-03-19 21:37:32 -04:00
0162a604be refactor: break up voice_loop.py::run() into focused helpers (#567)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 21:33:59 -04:00
2326771c5a [loop-cycle-953] refactor: DRY _import_creative_catalogs() (#560) (#565)
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2026-03-19 21:21:23 -04:00
8f6cf2681b refactor: break up search_memories() into focused helpers (#557)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 21:16:07 -04:00
f361893fdd [loop-cycle-951] refactor: break up _migrate_schema() (#552) (#558)
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2026-03-19 21:11:02 -04:00
7ad0ee17b6 refactor: break up shell.py::run() into helpers (#551)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 21:04:10 -04:00
29220b6bdd refactor: break up api_chat() into helpers (#547)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 21:02:04 -04:00
2849dba756 [loop-cycle-948] refactor: break up _gather_system_snapshot() into helpers (#540) (#549)
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2026-03-19 20:52:13 -04:00
e11e07f117 [loop-cycle-947] refactor: break up self_reflect() into focused helpers (#505) (#546)
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2026-03-19 20:49:18 -04:00
50c8a5428e refactor: break up api_chat() into helpers (#544)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 20:49:04 -04:00
7da434c85b [loop-cycle-946] refactor: complete airllm removal (#486) (#545)
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2026-03-19 20:46:20 -04:00
88e59f7c17 refactor: break up chat_agent() into helpers (#542)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 20:38:46 -04:00
aa5e9c3176 refactor: break up get_memory_status() into helpers (#537)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 20:30:29 -04:00
1b4fe65650 fix: cache thinking agent and add timeouts to prevent loop pane death (#535)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 20:27:25 -04:00
2d69f73d9d fix: add timeout to thinking/loop-QA schedulers (#530)
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2026-03-19 20:18:31 -04:00
ff1e43c235 [loop-cycle-545] fix: queue auto-hygiene — filter closed issues on read (#524) (#529)
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2026-03-19 20:10:05 -04:00
b331aa6139 refactor: break up capture_error() into testable helpers (#523)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 20:03:28 -04:00
b45b543f2d refactor: break up create_timmy() into testable helpers (#520)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 19:51:59 -04:00
7c823ab59c refactor: break up think_once() into testable helpers (#518)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 19:43:26 -04:00
9f2728f529 refactor: break up lifespan() into testable helpers (#515)
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2026-03-19 19:30:32 -04:00
cd3dc5d989 refactor: break up CascadeRouter.complete() into focused helpers (#510)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 19:24:36 -04:00
e4de539bf3 fix: extract ollama_url normalization into shared utility (#508)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 19:18:22 -04:00
b2057f72e1 [loop-cycle] refactor: break up run_agentic_loop into testable helpers (#504) (#509)
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2026-03-19 19:15:38 -04:00
5f52dd54c0 [loop-cycle-932] fix: add logging to bare except Exception blocks (#484) (#501)
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2026-03-19 19:05:02 -04:00
9ceffd61d1 [loop-cycle-544] fix: use settings.ollama_url fallback in _call_ollama (#490) (#498)
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2026-03-19 16:18:39 -04:00
015d858be5 fix: auto-detect issue number in cycle retro from git branch (#495)
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## Summary
- `cycle_retro.py` now auto-detects issue number from the git branch name (e.g. `kimi/issue-492` → `492`) when `--issue` is not provided
- `backfill_retro.py` now skips the PR number suffix Gitea appends to titles so it does not confuse PR numbers with issue numbers
- Added tests for both fixes

Fixes #492

Co-authored-by: kimi <kimi@localhost>
Reviewed-on: http://localhost:3000/rockachopa/Timmy-time-dashboard/pulls/495
Co-authored-by: Kimi Agent <kimi@timmy.local>
Co-committed-by: Kimi Agent <kimi@timmy.local>
2026-03-19 16:13:35 -04:00
b6d0b5f999 feat: epoch turnover notation for loopstat cycles ⟳WW.D:NNN (#496)
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2026-03-19 16:12:10 -04:00
d70e4f810a fix: use settings.ollama_url instead of hardcoded fallback in cascade router (#491)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 16:02:20 -04:00
7f20742fcf fix: replace hardcoded secret placeholder in CSRF middleware docstring (#488)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 15:52:29 -04:00
15eb7c3b45 [loop-cycle-538] refactor: remove dead airllm provider from cascade router (#459) (#481)
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2026-03-19 15:44:10 -04:00
dbc2fd5b0f [loop-cycle-536] fix: validate_startup checks CORS wildcard in production (#472) (#478)
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2026-03-19 15:29:26 -04:00
3c3aca57f1 [loop-cycle-535] perf: cache Timmy agent at startup (#471) (#476)
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## What
Cache the Timmy agent instance at app startup (in lifespan) instead of creating a new one per `/serve/chat` request.

## Changes
- `src/timmy_serve/app.py`: Create agent in lifespan, store in `app.state.timmy`
- `tests/timmy/test_timmy_serve_app.py`: Updated tests for lifespan-based caching, added `test_agent_cached_at_startup`

2085 unit tests pass. 2102 pre-push tests pass. 78.5% coverage.

Closes #471

Co-authored-by: Timmy <timmy@timmytime.ai>
Reviewed-on: http://localhost:3000/rockachopa/Timmy-time-dashboard/pulls/476
Co-authored-by: Timmy Time <timmy@Alexanderwhitestone.ai>
Co-committed-by: Timmy Time <timmy@Alexanderwhitestone.ai>
2026-03-19 15:28:57 -04:00
0ae00af3f8 fix: remove AirLLM config settings from config.py (#475)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 15:24:43 -04:00
3df526f6ef [loop-cycle-2] feat: hot-reload providers.yaml without restart (#458) (#470)
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2026-03-19 15:11:40 -04:00
50aaf60db2 [loop-cycle-2] fix: strip CORS wildcards in production (#462) (#469)
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2026-03-19 15:05:27 -04:00
a751be3038 fix: default CORS origins to localhost instead of wildcard (#467)
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2026-03-19 14:57:36 -04:00
92594ea588 [loop-cycle] feat: implement source distinction in system prompts (#463) (#464)
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2026-03-19 14:49:31 -04:00
12582ab593 fix: stabilize flaky test_uses_model_when_available (#456)
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2026-03-19 14:39:33 -04:00
72c3a0a989 fix: integration tests for agentic loop WS broadcasts (#452)
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2026-03-19 14:30:00 -04:00
de089cec7f [loop-cycle-524] fix: remove numpy test dependency in test_memory_embeddings (#451)
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2026-03-19 14:22:13 -04:00
3590c1689e fix: make _get_loop_agent singleton thread-safe (#449)
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2026-03-19 14:18:27 -04:00
2161c32ae8 fix: add unit tests for agentic_loop.py (#421) (#447)
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2026-03-19 14:13:50 -04:00
98b1142820 [loop-cycle-522] test: add unit tests for agentic_loop.py (#421) (#441)
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2026-03-19 14:10:16 -04:00
1d79a36bd8 fix: add unit tests for memory/embeddings.py (#437)
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2026-03-19 11:12:46 -04:00
cce311dbb8 [loop-cycle] test: add unit tests for briefing.py (#422) (#438)
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2026-03-19 10:50:21 -04:00
3cde310c78 fix: idle detection + exponential backoff for dev loop (#435)
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2026-03-19 10:36:39 -04:00
cdb1a7546b fix: add workshop props — bookshelf, candles, crystal ball glow (#429)
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2026-03-19 10:29:18 -04:00
a31c929770 fix: add unit tests for tools.py (#428)
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2026-03-19 10:17:36 -04:00
3afb62afb7 fix: add self_reflect tool for past behavior review (#417)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 09:39:14 -04:00
332fa373b8 fix: wire cognitive state to sensory bus (presence loop) (#414)
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## Summary
- CognitiveTracker.update() now emits `cognitive_state_changed` events to the SensoryBus
- WorkshopHeartbeat (and other subscribers) react immediately to mood/engagement changes
- Closes the sense → memory → react loop described in the Workshop architecture
- Fire-and-forget emission — never blocks the chat response path
- Gracefully skips when no event loop is running (sync contexts/tests)

## Test plan
- [x] 3 new tests: event emission, mood change tracking, graceful skip without loop
- [x] All 1935 unit tests pass
- [x] Lint + format clean

Fixes #222

Co-authored-by: kimi <kimi@localhost>
Reviewed-on: http://localhost:3000/rockachopa/Timmy-time-dashboard/pulls/414
Co-authored-by: Kimi Agent <kimi@timmy.local>
Co-committed-by: Kimi Agent <kimi@timmy.local>
2026-03-19 03:23:03 -04:00
76b26ead55 rescue: WS heartbeat ping + commitment tracking from stale PRs (#415)
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## What
Manually integrated unique code from two stale PRs that were **not** superseded by merged work.

### PR #399 (kimi/issue-362) — WebSocket heartbeat ping
- 15-second ping loop detects dead iPad/Safari connections
- `_heartbeat()` coroutine launched as background task per WS client
- `ping_task` properly cancelled on disconnect

### PR #408 (kimi/issue-322) — Conversation commitment tracking
- Regex extraction of commitments from Timmy replies (`I'll` / `I will` / `Let me`)
- `_record_commitments()` stores with dedup + cap at 10
- `_tick_commitments()` increments message counter per commitment
- `_build_commitment_context()` surfaces overdue commitments as grounding context
- Wired into `_bark_and_broadcast()` and `_generate_bark()`
- Public API: `get_commitments()`, `close_commitment()`, `reset_commitments()`

### Tests
22 new tests covering both features: extraction, recording, dedup, caps, tick/context, integration, heartbeat ping, dead connection handling.

---
This PR rescues unique code from stale PRs #399 and #408. The other two stale PRs (#402, #411) were already superseded by merged work and should be closed.

Co-authored-by: Perplexity Computer <perplexity@tower.dev>
Reviewed-on: http://localhost:3000/rockachopa/Timmy-time-dashboard/pulls/415
Co-authored-by: Perplexity Computer <perplexity@tower.local>
Co-committed-by: Perplexity Computer <perplexity@tower.local>
2026-03-19 03:22:44 -04:00
63e4542f31 fix: serve AlexanderWhitestone.com as static site (#416)
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Replace auth-gated dashboard proxy with static file serving for The Wizard's Tower — two rooms (Workshop + Scrolls), no auth, no tracking, proper caching headers for 3D assets and RSS feed.

Fixes #211

Co-authored-by: kimi <kimi@localhost>
Reviewed-on: http://localhost:3000/rockachopa/Timmy-time-dashboard/pulls/416
Co-authored-by: Kimi Agent <kimi@timmy.local>
Co-committed-by: Kimi Agent <kimi@timmy.local>
2026-03-19 03:22:23 -04:00
9b8ad3629a fix: wire Pip familiar into Workshop state pipeline (#412)
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2026-03-19 03:09:22 -04:00
4b617cfcd0 fix: deep focus mode — single-problem context for Timmy (#409)
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2026-03-19 02:54:19 -04:00
b67dbe922f fix: conversation grounding to prevent topic drift in Workshop (#406)
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2026-03-19 02:39:15 -04:00
3571d528ad feat: Workshop Phase 1 — State Schema v1 (#404)
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2026-03-19 02:24:13 -04:00
ab3546ae4b feat: Workshop Phase 2 — Scene MVP (Three.js room) (#401)
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2026-03-19 02:14:09 -04:00
e89aef41bc [loop-cycle-392] refactor: DRY broadcast + bark error logging (#397, #398) (#400)
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2026-03-19 02:01:58 -04:00
86224d042d feat: Workshop Phase 4 — visitor chat via WebSocket bark engine (#394)
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Co-authored-by: Kimi Agent <kimi@timmy.local>
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2026-03-19 01:54:06 -04:00
2209ac82d2 fix: canonically connect the Tower to the Workshop (#392)
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2026-03-19 01:38:59 -04:00
f9d8509c15 fix: send world state snapshot on WS client connect (#390)
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2026-03-19 01:28:57 -04:00
858264be0d fix: deprecate ~/.tower/timmy-state.txt — consolidate on presence.json (#388)
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2026-03-19 01:18:52 -04:00
3c10da489b fix: enhance tox dev environment (port, banner, reload) (#386)
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2026-03-19 01:08:49 -04:00
da43421d4e feat: broadcast Timmy state changes via WS relay (#380)
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2026-03-19 00:25:11 -04:00
aa4f1de138 fix: DRY PRESENCE_FILE — single source of truth (#383)
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2026-03-18 22:38:40 -04:00
19e7e61c92 [loop-cycle] refactor: DRY PRESENCE_FILE — single source of truth in workshop_state (#381) (#382)
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2026-03-18 22:33:06 -04:00
b7573432cc fix: watch presence.json and broadcast state via WS (#379)
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2026-03-18 22:22:02 -04:00
3108971bd5 [loop-cycle-155] feat: GET /api/world/state — Workshop bootstrap endpoint (#373) (#378)
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2026-03-18 22:13:49 -04:00
864be20dde feat: Workshop state heartbeat for presence.json (#377)
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2026-03-18 22:07:32 -04:00
c1f939ef22 fix: add update_gitea_avatar capability (#368)
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2026-03-18 22:04:57 -04:00
c1af9e3905 [loop-cycle-154] refactor: extract _annotate_confidence helper — DRY 3x duplication (#369) (#376)
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2026-03-18 22:01:51 -04:00
996ccec170 feat: Pip the Familiar — behavioral state machine (#367)
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2026-03-18 21:50:36 -04:00
560aed78c3 fix: add cognitive state as observable signal for Matrix avatar (#358)
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2026-03-18 21:37:17 -04:00
c7198b1254 [loop-cycle-152] feat: define canonical presence schema for Workshop (#265) (#359)
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2026-03-18 21:36:06 -04:00
43efb01c51 fix: remove duplicate agent loader test file (#356)
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2026-03-18 21:28:10 -04:00
ce658c841a [loop-cycle-151] refactor: extract embedding functions to memory/embeddings.py (#344) (#355)
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2026-03-18 21:24:50 -04:00
db7220db5a test: add unit tests for memory/unified.py (#353)
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2026-03-18 21:23:03 -04:00
ae10ea782d fix: remove duplicate agent loader test file (#354)
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2026-03-18 21:23:00 -04:00
4afc5daffb test: add unit tests for agents/loader.py (#349)
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2026-03-18 21:13:01 -04:00
4aa86ff1cb [loop-cycle-150] test: add 22 unit tests for agents/base.py — BaseAgent and SubAgent (#350)
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2026-03-18 21:10:08 -04:00
dff07c6529 [loop-cycle-149] feat: Workshop config inventory generator (#320) (#348)
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2026-03-18 20:58:27 -04:00
11357ffdb4 test: add comprehensive unit tests for agentic_loop.py (#345)
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2026-03-18 20:54:02 -04:00
fcbb2b848b test: add unit tests for jot_note and log_decision artifact tools (#341)
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2026-03-18 20:47:38 -04:00
6621f4bd31 [loop-cycle-147] refactor: expand .gitignore to cover junk files (#336) (#339)
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2026-03-18 20:37:13 -04:00
243b1a656f feat: give Timmy hands — artifact tools for conversation (#337)
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2026-03-18 20:36:38 -04:00
22e0d2d4b3 [loop-cycle-66] fix: replace language-model with inference-backend in error messages (#334)
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2026-03-18 20:27:06 -04:00
bcc7b068a4 [loop-cycle-66] fix: remove language-model self-reference and add anti-assistant-speak guidance (#323) (#333)
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2026-03-18 20:21:03 -04:00
bfd924fe74 [loop-cycle-65] feat: scaffold three-phase loop skeleton (#324) (#330)
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2026-03-18 20:11:02 -04:00
844923b16b [loop-cycle-65] fix: validate file paths before filing thinking-engine issues (#327) (#329)
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2026-03-18 20:07:19 -04:00
8ef0ad1778 fix: pause thought counter during idle periods (#319)
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2026-03-18 19:12:14 -04:00
9a21a4b0ff feat: SensoryEvent model + SensoryBus dispatcher (#318)
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2026-03-18 19:02:12 -04:00
ab71c71036 feat: time adapter — circadian awareness for Timmy (#315)
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2026-03-18 18:47:09 -04:00
39939270b7 fix: Gitea webhook adapter — normalize events to sensory bus (#309)
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2026-03-18 18:37:01 -04:00
0ab1ee9378 fix: proactive memory status check during thought tracking (#313)
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2026-03-18 18:36:59 -04:00
234187c091 fix: add periodic memory status checks during thought tracking (#311)
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2026-03-18 18:26:53 -04:00
f4106452d2 feat: implement v1 API endpoints for iPad app (#312)
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2026-03-18 18:20:14 -04:00
112 changed files with 13626 additions and 1985 deletions

20
.gitignore vendored
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@@ -21,6 +21,9 @@ discord_credentials.txt
# Backup / temp files
*~
\#*\#
*.backup
*.tar.gz
# SQLite — never commit databases or WAL/SHM artifacts
*.db
@@ -73,6 +76,23 @@ scripts/migrate_to_zeroclaw.py
src/infrastructure/db_pool.py
workspace/
# Loop orchestration state
.loop/
# Legacy junk from old Timmy sessions (one-word fragments, cruft)
Hi
Im Timmy*
his
keep
clean
directory
my_name_is_timmy*
timmy_read_me_*
issue_12_proposal.md
# Memory notes (session-scoped, not committed)
memory/notes/
# Gitea Actions runner state
.runner

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@@ -54,19 +54,6 @@ providers:
context_window: 2048
capabilities: [text, vision, streaming]
# Secondary: Local AirLLM (if installed)
- name: airllm-local
type: airllm
enabled: false # Enable if pip install airllm
priority: 2
models:
- name: 70b
default: true
capabilities: [text, tools, json, streaming]
- name: 8b
capabilities: [text, tools, json, streaming]
- name: 405b
capabilities: [text, tools, json, streaming]
# Tertiary: OpenAI (if API key available)
- name: openai-backup

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@@ -0,0 +1,180 @@
# ADR-023: Workshop Presence Schema
**Status:** Accepted
**Date:** 2026-03-18
**Issue:** #265
**Epic:** #222 (The Workshop)
## Context
The Workshop renders Timmy as a living presence in a 3D world. It needs to
know what Timmy is doing *right now* — his working memory, not his full
identity or history. This schema defines the contract between Timmy (writer)
and the Workshop (reader).
### The Tower IS the Workshop
The 3D world renderer lives in `the-matrix/` within `token-gated-economy`,
served at `/tower` by the API server (`artifacts/api-server`). This is the
canonical Workshop scene — not a generic Matrix visualization. All Workshop
phase issues (#361, #362, #363) target that codebase. No separate
`alexanderwhitestone.com` scaffold is needed until production deploy.
The `workshop-state` spec (#360) is consumed by the API server via a
file-watch mechanism, bridging Timmy's presence into the 3D scene.
Design principles:
- **Working memory, not long-term memory.** Present tense only.
- **Written as side effect of work.** Not a separate obligation.
- **Liveness is mandatory.** Stale = "not home," shown honestly.
- **Schema is the contract.** Keep it minimal and stable.
## Decision
### File Location
`~/.timmy/presence.json`
JSON chosen over YAML for predictable parsing by both Python and JavaScript
(the Workshop frontend). The Workshop reads this file via the WebSocket
bridge (#243) or polls it directly during development.
### Schema (v1)
```json
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"title": "Timmy Presence State",
"description": "Working memory surface for the Workshop renderer",
"type": "object",
"required": ["version", "liveness", "current_focus"],
"properties": {
"version": {
"type": "integer",
"const": 1,
"description": "Schema version for forward compatibility"
},
"liveness": {
"type": "string",
"format": "date-time",
"description": "ISO 8601 timestamp of last update. If stale (>5min), Timmy is not home."
},
"current_focus": {
"type": "string",
"description": "One sentence: what Timmy is doing right now. Empty string = idle."
},
"active_threads": {
"type": "array",
"maxItems": 10,
"description": "Current work items Timmy is tracking",
"items": {
"type": "object",
"required": ["type", "ref", "status"],
"properties": {
"type": {
"type": "string",
"enum": ["pr_review", "issue", "conversation", "research", "thinking"]
},
"ref": {
"type": "string",
"description": "Reference identifier (issue #, PR #, topic name)"
},
"status": {
"type": "string",
"enum": ["active", "idle", "blocked", "completed"]
}
}
}
},
"recent_events": {
"type": "array",
"maxItems": 20,
"description": "Recent events, newest first. Capped at 20.",
"items": {
"type": "object",
"required": ["timestamp", "event"],
"properties": {
"timestamp": {
"type": "string",
"format": "date-time"
},
"event": {
"type": "string",
"description": "Brief description of what happened"
}
}
}
},
"concerns": {
"type": "array",
"maxItems": 5,
"description": "Things Timmy is uncertain or worried about. Flat list, no severity.",
"items": {
"type": "string"
}
},
"mood": {
"type": "string",
"enum": ["focused", "exploring", "uncertain", "excited", "tired", "idle"],
"description": "Emotional texture for the Workshop to render. Optional."
}
}
}
```
### Example
```json
{
"version": 1,
"liveness": "2026-03-18T21:47:12Z",
"current_focus": "Reviewing PR #267 — stream adapter for Gitea webhooks",
"active_threads": [
{"type": "pr_review", "ref": "#267", "status": "active"},
{"type": "issue", "ref": "#239", "status": "idle"},
{"type": "conversation", "ref": "hermes-consultation", "status": "idle"}
],
"recent_events": [
{"timestamp": "2026-03-18T21:45:00Z", "event": "Completed PR review for #265"},
{"timestamp": "2026-03-18T21:30:00Z", "event": "Filed issue #268 — flaky test in sensory loop"}
],
"concerns": [
"WebSocket reconnection logic feels brittle",
"Not sure the barks system handles uncertainty well yet"
],
"mood": "focused"
}
```
### Design Answers
| Question | Answer |
|---|---|
| File format | JSON (predictable for JS + Python, no YAML parser needed in browser) |
| recent_events cap | 20 entries max, oldest dropped |
| concerns severity | Flat list, no priority. Keep it simple. |
| File location | `~/.timmy/presence.json` — accessible to Workshop via bridge |
| Staleness threshold | 5 minutes without liveness update = "not home" |
| mood field | Optional. Workshop can render visual cues (color, animation) |
## Consequences
- **Timmy's agent loop** must write `~/.timmy/presence.json` as a side effect
of work. This is a hook at the end of each cycle, not a daemon.
- **The Workshop frontend** reads this file and renders accordingly. Stale
liveness → dim the wizard, show "away" state.
- **The WebSocket bridge** (#243) watches this file and pushes changes to
connected Workshop clients.
- **Schema is versioned.** Breaking changes increment the version field.
Workshop must handle unknown versions gracefully (show raw data or "unknown state").
## Related
- #222 — Workshop epic
- #243 — WebSocket bridge (transports this state)
- #239 — Sensory loop (feeds into state)
- #242 — 3D world (consumes this state for rendering)
- #246 — Confidence as visible trait (mood field serves this)
- #360 — Workshop-state spec (consumed by API via file-watch)
- #361, #362, #363 — Workshop phase issues (target `the-matrix/`)
- #372 — The Tower IS the Workshop (canonical connection)

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@@ -1,42 +1,75 @@
# ── AlexanderWhitestone.com — The Wizard's Tower ────────────────────────────
#
# Two rooms. No hallways. No feature creep.
# /world/ — The Workshop (3D scene, Three.js)
# /blog/ — The Scrolls (static posts, RSS feed)
#
# Static-first. No tracking. No analytics. No cookie banner.
# Site root: /var/www/alexanderwhitestone.com
server {
listen 80;
server_name alexanderwhitestone.com 45.55.221.244;
server_name alexanderwhitestone.com www.alexanderwhitestone.com;
# Cookie-based auth gate — login once, cookie lasts 7 days
location = /_auth {
internal;
proxy_pass http://127.0.0.1:9876;
proxy_pass_request_body off;
proxy_set_header Content-Length "";
proxy_set_header X-Original-URI $request_uri;
proxy_set_header Cookie $http_cookie;
proxy_set_header Authorization $http_authorization;
root /var/www/alexanderwhitestone.com;
index index.html;
# ── Security headers ────────────────────────────────────────────────────
add_header X-Content-Type-Options nosniff always;
add_header X-Frame-Options SAMEORIGIN always;
add_header Referrer-Policy strict-origin-when-cross-origin always;
add_header X-XSS-Protection "1; mode=block" always;
# ── Gzip for text assets ────────────────────────────────────────────────
gzip on;
gzip_types text/plain text/css text/xml text/javascript
application/javascript application/json application/xml
application/rss+xml application/atom+xml;
gzip_min_length 256;
# ── The Workshop — 3D world assets ──────────────────────────────────────
location /world/ {
try_files $uri $uri/ /world/index.html;
# Cache 3D assets aggressively (models, textures)
location ~* \.(glb|gltf|bin|png|jpg|webp|hdr)$ {
expires 30d;
add_header Cache-Control "public, immutable";
}
# Cache JS with revalidation (for Three.js updates)
location ~* \.js$ {
expires 7d;
add_header Cache-Control "public, must-revalidate";
}
}
# ── The Scrolls — blog posts and RSS ────────────────────────────────────
location /blog/ {
try_files $uri $uri/ =404;
}
# RSS/Atom feed — correct content type
location ~* \.(rss|atom|xml)$ {
types { }
default_type application/rss+xml;
expires 1h;
}
# ── Static assets (fonts, favicon) ──────────────────────────────────────
location /static/ {
expires 30d;
add_header Cache-Control "public, immutable";
}
# ── Entry hall ──────────────────────────────────────────────────────────
location / {
auth_request /_auth;
# Forward the Set-Cookie from auth gate to the client
auth_request_set $auth_cookie $upstream_http_set_cookie;
add_header Set-Cookie $auth_cookie;
proxy_pass http://127.0.0.1:3100;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection 'upgrade';
proxy_set_header Host localhost;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_set_header X-Forwarded-Host $host;
proxy_cache_bypass $http_upgrade;
proxy_read_timeout 86400;
try_files $uri $uri/ =404;
}
# Return 401 with WWW-Authenticate when auth fails
error_page 401 = @login;
location @login {
proxy_pass http://127.0.0.1:9876;
proxy_set_header Authorization $http_authorization;
proxy_set_header Cookie $http_cookie;
# Block dotfiles
location ~ /\. {
deny all;
return 404;
}
}

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@@ -94,12 +94,17 @@ def extract_cycle_number(title: str) -> int | None:
return int(m.group(1)) if m else None
def extract_issue_number(title: str, body: str) -> int | None:
# Try body first (usually has "closes #N")
def extract_issue_number(title: str, body: str, pr_number: int | None = None) -> int | None:
"""Extract the issue number from PR body/title, ignoring the PR number itself.
Gitea appends "(#N)" to PR titles where N is the PR number — skip that
so we don't confuse it with the linked issue.
"""
for text in [body or "", title]:
m = ISSUE_RE.search(text)
if m:
return int(m.group(1))
for m in ISSUE_RE.finditer(text):
num = int(m.group(1))
if num != pr_number:
return num
return None
@@ -140,7 +145,7 @@ def main():
else:
cycle_counter = max(cycle_counter, cycle)
issue = extract_issue_number(title, body)
issue = extract_issue_number(title, body, pr_number=pr_num)
issue_type = classify_pr(title, body)
duration = estimate_duration(pr)
diff = get_pr_diff_stats(token, pr_num)

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@@ -4,11 +4,26 @@
Called after each cycle completes (success or failure).
Appends a structured entry to .loop/retro/cycles.jsonl.
EPOCH NOTATION (turnover system):
Each cycle carries a symbolic epoch tag alongside the raw integer:
⟳WW.D:NNN
⟳ turnover glyph — marks epoch-aware cycles
WW ISO week-of-year (0153)
D ISO weekday (1=Mon … 7=Sun)
NNN daily cycle counter, zero-padded, resets at midnight UTC
Example: ⟳12.3:042 — Week 12, Wednesday, 42nd cycle of the day.
The raw `cycle` integer is preserved for backward compatibility.
The `epoch` field carries the symbolic notation.
SUCCESS DEFINITION:
A cycle is only "success" if BOTH conditions are met:
1. The hermes process exited cleanly (exit code 0)
2. Main is green (smoke test passes on main after merge)
A cycle that merges a PR but leaves main red is a FAILURE.
The --main-green flag records the smoke test result.
@@ -29,6 +44,8 @@ from __future__ import annotations
import argparse
import json
import re
import subprocess
import sys
from datetime import datetime, timezone
from pathlib import Path
@@ -36,10 +53,68 @@ from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parent.parent
RETRO_FILE = REPO_ROOT / ".loop" / "retro" / "cycles.jsonl"
SUMMARY_FILE = REPO_ROOT / ".loop" / "retro" / "summary.json"
EPOCH_COUNTER_FILE = REPO_ROOT / ".loop" / "retro" / ".epoch_counter"
# How many recent entries to include in rolling summary
SUMMARY_WINDOW = 50
# Branch patterns that encode an issue number, e.g. kimi/issue-492
BRANCH_ISSUE_RE = re.compile(r"issue[/-](\d+)", re.IGNORECASE)
def detect_issue_from_branch() -> int | None:
"""Try to extract an issue number from the current git branch name."""
try:
branch = subprocess.check_output(
["git", "rev-parse", "--abbrev-ref", "HEAD"],
stderr=subprocess.DEVNULL,
text=True,
).strip()
except (subprocess.CalledProcessError, FileNotFoundError):
return None
m = BRANCH_ISSUE_RE.search(branch)
return int(m.group(1)) if m else None
# ── Epoch turnover ────────────────────────────────────────────────────────
def _epoch_tag(now: datetime | None = None) -> tuple[str, dict]:
"""Generate the symbolic epoch tag and advance the daily counter.
Returns (epoch_string, epoch_parts) where epoch_parts is a dict with
week, weekday, daily_n for structured storage.
The daily counter persists in .epoch_counter as a two-line file:
line 1: ISO date (YYYY-MM-DD) of the current epoch day
line 2: integer count
When the date rolls over, the counter resets to 1.
"""
if now is None:
now = datetime.now(timezone.utc)
iso_cal = now.isocalendar() # (year, week, weekday)
week = iso_cal[1]
weekday = iso_cal[2]
today_str = now.strftime("%Y-%m-%d")
# Read / reset daily counter
daily_n = 1
EPOCH_COUNTER_FILE.parent.mkdir(parents=True, exist_ok=True)
if EPOCH_COUNTER_FILE.exists():
try:
lines = EPOCH_COUNTER_FILE.read_text().strip().splitlines()
if len(lines) == 2 and lines[0] == today_str:
daily_n = int(lines[1]) + 1
except (ValueError, IndexError):
pass # corrupt file — reset
# Persist
EPOCH_COUNTER_FILE.write_text(f"{today_str}\n{daily_n}\n")
tag = f"\u27f3{week:02d}.{weekday}:{daily_n:03d}"
parts = {"week": week, "weekday": weekday, "daily_n": daily_n}
return tag, parts
def parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser(description="Log a cycle retrospective")
@@ -123,8 +198,30 @@ def update_summary() -> None:
issue_failures[e["issue"]] = issue_failures.get(e["issue"], 0) + 1
quarantine_candidates = {k: v for k, v in issue_failures.items() if v >= 2}
# Epoch turnover stats — cycles per week/day from epoch-tagged entries
epoch_entries = [e for e in recent if e.get("epoch")]
by_week: dict[int, int] = {}
by_weekday: dict[int, int] = {}
for e in epoch_entries:
w = e.get("epoch_week")
d = e.get("epoch_weekday")
if w is not None:
by_week[w] = by_week.get(w, 0) + 1
if d is not None:
by_weekday[d] = by_weekday.get(d, 0) + 1
# Current epoch — latest entry's epoch tag
current_epoch = epoch_entries[-1].get("epoch", "") if epoch_entries else ""
# Weekday names for display
weekday_glyphs = {1: "Mon", 2: "Tue", 3: "Wed", 4: "Thu",
5: "Fri", 6: "Sat", 7: "Sun"}
by_weekday_named = {weekday_glyphs.get(k, str(k)): v
for k, v in sorted(by_weekday.items())}
summary = {
"updated_at": datetime.now(timezone.utc).isoformat(),
"current_epoch": current_epoch,
"window": len(recent),
"measured_cycles": len(measured),
"total_cycles": len(entries),
@@ -136,9 +233,12 @@ def update_summary() -> None:
"total_lines_removed": sum(e.get("lines_removed", 0) for e in recent),
"total_prs_merged": sum(1 for e in recent if e.get("pr")),
"by_type": type_stats,
"by_week": dict(sorted(by_week.items())),
"by_weekday": by_weekday_named,
"quarantine_candidates": quarantine_candidates,
"recent_failures": [
{"cycle": e["cycle"], "issue": e.get("issue"), "reason": e.get("reason", "")}
{"cycle": e["cycle"], "epoch": e.get("epoch", ""),
"issue": e.get("issue"), "reason": e.get("reason", "")}
for e in failures[-5:]
],
}
@@ -149,12 +249,29 @@ def update_summary() -> None:
def main() -> None:
args = parse_args()
# Auto-detect issue from branch when not explicitly provided
if args.issue is None:
args.issue = detect_issue_from_branch()
# Reject idle cycles — no issue and no duration means nothing happened
if not args.issue and args.duration == 0:
print(f"[retro] Cycle {args.cycle} skipped — idle (no issue, no duration)")
return
# A cycle is only truly successful if hermes exited clean AND main is green
truly_success = args.success and args.main_green
# Generate epoch turnover tag
now = datetime.now(timezone.utc)
epoch_tag, epoch_parts = _epoch_tag(now)
entry = {
"timestamp": datetime.now(timezone.utc).isoformat(),
"timestamp": now.isoformat(),
"cycle": args.cycle,
"epoch": epoch_tag,
"epoch_week": epoch_parts["week"],
"epoch_weekday": epoch_parts["weekday"],
"epoch_daily_n": epoch_parts["daily_n"],
"issue": args.issue,
"type": args.type,
"success": truly_success,
@@ -179,7 +296,7 @@ def main() -> None:
update_summary()
status = "✓ SUCCESS" if args.success else "✗ FAILURE"
print(f"[retro] Cycle {args.cycle} {status}", end="")
print(f"[retro] {epoch_tag} Cycle {args.cycle} {status}", end="")
if args.issue:
print(f" (#{args.issue} {args.type})", end="")
if args.duration:

169
scripts/dev_server.py Normal file
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@@ -0,0 +1,169 @@
#!/usr/bin/env python3
"""Timmy Time — Development server launcher.
Satisfies tox -e dev criteria:
- Graceful port selection (finds next free port if default is taken)
- Clickable links to dashboard and other web GUIs
- Status line: backend inference source, version, git commit, smoke tests
- Auto-reload on code changes (delegates to uvicorn --reload)
Usage: python scripts/dev_server.py [--port PORT]
"""
import argparse
import datetime
import os
import socket
import subprocess
import sys
DEFAULT_PORT = 8000
MAX_PORT_ATTEMPTS = 10
OLLAMA_DEFAULT = "http://localhost:11434"
def _port_free(port: int) -> bool:
"""Return True if the TCP port is available on localhost."""
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
try:
s.bind(("0.0.0.0", port))
return True
except OSError:
return False
def _find_port(start: int) -> int:
"""Return *start* if free, otherwise probe up to MAX_PORT_ATTEMPTS higher."""
for offset in range(MAX_PORT_ATTEMPTS):
candidate = start + offset
if _port_free(candidate):
return candidate
raise RuntimeError(
f"No free port found in range {start}{start + MAX_PORT_ATTEMPTS - 1}"
)
def _git_info() -> str:
"""Return short commit hash + timestamp, or 'unknown'."""
try:
sha = subprocess.check_output(
["git", "rev-parse", "--short", "HEAD"],
stderr=subprocess.DEVNULL,
text=True,
).strip()
ts = subprocess.check_output(
["git", "log", "-1", "--format=%ci"],
stderr=subprocess.DEVNULL,
text=True,
).strip()
return f"{sha} ({ts})"
except Exception:
return "unknown"
def _project_version() -> str:
"""Read version from pyproject.toml without importing toml libs."""
pyproject = os.path.join(os.path.dirname(__file__), "..", "pyproject.toml")
try:
with open(pyproject) as f:
for line in f:
if line.strip().startswith("version"):
# version = "1.0.0"
return line.split("=", 1)[1].strip().strip('"').strip("'")
except Exception:
pass
return "unknown"
def _ollama_url() -> str:
return os.environ.get("OLLAMA_URL", OLLAMA_DEFAULT)
def _smoke_ollama(url: str) -> str:
"""Quick connectivity check against Ollama."""
import urllib.request
import urllib.error
try:
req = urllib.request.Request(url, method="GET")
with urllib.request.urlopen(req, timeout=3):
return "ok"
except Exception:
return "unreachable"
def _print_banner(port: int) -> None:
version = _project_version()
git = _git_info()
ollama_url = _ollama_url()
ollama_status = _smoke_ollama(ollama_url)
hr = "" * 62
print(flush=True)
print(f" {hr}")
print(f" ┃ Timmy Time — Development Server")
print(f" {hr}")
print()
print(f" Dashboard: http://localhost:{port}")
print(f" API docs: http://localhost:{port}/docs")
print(f" Health: http://localhost:{port}/health")
print()
print(f" ── Status ──────────────────────────────────────────────")
print(f" Backend: {ollama_url} [{ollama_status}]")
print(f" Version: {version}")
print(f" Git commit: {git}")
print(f" {hr}")
print(flush=True)
def main() -> None:
parser = argparse.ArgumentParser(description="Timmy dev server")
parser.add_argument(
"--port",
type=int,
default=DEFAULT_PORT,
help=f"Preferred port (default: {DEFAULT_PORT})",
)
args = parser.parse_args()
port = _find_port(args.port)
if port != args.port:
print(f" ⚠ Port {args.port} in use — using {port} instead")
_print_banner(port)
# Set PYTHONPATH so `timmy` CLI inside the tox venv resolves to this source.
src_dir = os.path.join(os.path.dirname(__file__), "..", "src")
os.environ["PYTHONPATH"] = os.path.abspath(src_dir)
# Launch uvicorn with auto-reload
cmd = [
sys.executable,
"-m",
"uvicorn",
"dashboard.app:app",
"--reload",
"--host",
"0.0.0.0",
"--port",
str(port),
"--reload-dir",
os.path.abspath(src_dir),
"--reload-include",
"*.html",
"--reload-include",
"*.css",
"--reload-include",
"*.js",
"--reload-exclude",
".claude",
]
try:
subprocess.run(cmd, check=True)
except KeyboardInterrupt:
print("\n Shutting down dev server.")
if __name__ == "__main__":
main()

View File

@@ -0,0 +1,254 @@
#!/usr/bin/env python3
"""Generate Workshop inventory for Timmy's config audit.
Scans ~/.timmy/ and produces WORKSHOP_INVENTORY.md documenting every
config file, env var, model route, and setting — with annotations on
who set each one and what it does.
Usage:
python scripts/generate_workshop_inventory.py [--output PATH]
Default output: ~/.timmy/WORKSHOP_INVENTORY.md
"""
from __future__ import annotations
import argparse
import os
from datetime import UTC, datetime
from pathlib import Path
TIMMY_HOME = Path(os.environ.get("HERMES_HOME", Path.home() / ".timmy"))
# Known file annotations: (purpose, who_set)
FILE_ANNOTATIONS: dict[str, tuple[str, str]] = {
".env": (
"Environment variables — API keys, service URLs, Honcho config",
"hermes-set",
),
"config.yaml": (
"Main config — model routing, toolsets, display, memory, security",
"hermes-set",
),
"SOUL.md": (
"Timmy's soul — immutable conscience, identity, ethics, purpose",
"alex-set",
),
"state.db": (
"Hermes runtime state database (sessions, approvals, tasks)",
"hermes-set",
),
"approvals.db": (
"Approval tracking for sensitive operations",
"hermes-set",
),
"briefings.db": (
"Stored briefings and summaries",
"hermes-set",
),
".hermes_history": (
"CLI command history",
"default",
),
".update_check": (
"Last update check timestamp",
"default",
),
}
DIR_ANNOTATIONS: dict[str, tuple[str, str]] = {
"sessions": ("Conversation session logs (JSON)", "default"),
"logs": ("Error and runtime logs", "default"),
"skills": ("Bundled skill library (read-only from upstream)", "default"),
"memories": ("Persistent memory entries", "hermes-set"),
"audio_cache": ("TTS audio file cache", "default"),
"image_cache": ("Generated image cache", "default"),
"cron": ("Scheduled cron job definitions", "hermes-set"),
"hooks": ("Lifecycle hooks (pre/post actions)", "default"),
"matrix": ("Matrix protocol state and store", "hermes-set"),
"pairing": ("Device pairing data", "default"),
"sandboxes": ("Isolated execution sandboxes", "default"),
}
# Known config.yaml keys and their meanings
CONFIG_ANNOTATIONS: dict[str, tuple[str, str]] = {
"model.default": ("Primary LLM model for inference", "hermes-set"),
"model.provider": ("Model provider (custom = local Ollama)", "hermes-set"),
"toolsets": ("Enabled tool categories (all = everything)", "hermes-set"),
"agent.max_turns": ("Max conversation turns before reset", "hermes-set"),
"agent.reasoning_effort": ("Reasoning depth (low/medium/high)", "hermes-set"),
"terminal.backend": ("Command execution backend (local)", "default"),
"terminal.timeout": ("Default command timeout in seconds", "default"),
"compression.enabled": ("Context compression for long sessions", "hermes-set"),
"compression.summary_model": ("Model used for compression", "hermes-set"),
"auxiliary.vision.model": ("Model for image analysis", "hermes-set"),
"auxiliary.web_extract.model": ("Model for web content extraction", "hermes-set"),
"tts.provider": ("Text-to-speech engine (edge = Edge TTS)", "default"),
"tts.edge.voice": ("TTS voice selection", "default"),
"stt.provider": ("Speech-to-text engine (local = Whisper)", "default"),
"memory.memory_enabled": ("Persistent memory across sessions", "hermes-set"),
"memory.memory_char_limit": ("Max chars for agent memory store", "hermes-set"),
"memory.user_char_limit": ("Max chars for user profile store", "hermes-set"),
"security.redact_secrets": ("Auto-redact secrets in output", "default"),
"security.tirith_enabled": ("Policy engine for command safety", "default"),
"system_prompt_suffix": ("Identity prompt appended to all conversations", "hermes-set"),
"custom_providers": ("Local Ollama endpoint config", "hermes-set"),
"session_reset.mode": ("Session reset behavior (none = manual)", "default"),
"display.compact": ("Compact output mode", "default"),
"display.show_reasoning": ("Show model reasoning chains", "default"),
}
# Known .env vars
ENV_ANNOTATIONS: dict[str, tuple[str, str]] = {
"OPENAI_BASE_URL": (
"Points to local Ollama (localhost:11434) — sovereignty enforced",
"hermes-set",
),
"OPENAI_API_KEY": (
"Placeholder key for Ollama compatibility (not a real API key)",
"hermes-set",
),
"HONCHO_API_KEY": (
"Honcho cross-session memory service key",
"hermes-set",
),
"HONCHO_HOST": (
"Honcho workspace identifier (timmy)",
"hermes-set",
),
}
def _tag(who: str) -> str:
return f"`[{who}]`"
def generate_inventory() -> str:
"""Build the inventory markdown string."""
lines: list[str] = []
now = datetime.now(UTC).strftime("%Y-%m-%d %H:%M UTC")
lines.append("# Workshop Inventory")
lines.append("")
lines.append(f"*Generated: {now}*")
lines.append(f"*Workshop path: `{TIMMY_HOME}`*")
lines.append("")
lines.append("This is your Workshop — every file, every setting, every route.")
lines.append("Walk through it. Anything tagged `[hermes-set]` was chosen for you.")
lines.append("Make each one yours, or change it.")
lines.append("")
lines.append("Tags: `[alex-set]` = Alexander chose this. `[hermes-set]` = Hermes configured it.")
lines.append("`[default]` = shipped with the platform. `[timmy-chose]` = you decided this.")
lines.append("")
# --- Files ---
lines.append("---")
lines.append("## Root Files")
lines.append("")
for name, (purpose, who) in sorted(FILE_ANNOTATIONS.items()):
fpath = TIMMY_HOME / name
exists = "" if fpath.exists() else ""
lines.append(f"- {exists} **`{name}`** {_tag(who)}")
lines.append(f" {purpose}")
lines.append("")
# --- Directories ---
lines.append("---")
lines.append("## Directories")
lines.append("")
for name, (purpose, who) in sorted(DIR_ANNOTATIONS.items()):
dpath = TIMMY_HOME / name
exists = "" if dpath.exists() else ""
count = ""
if dpath.exists():
try:
n = len(list(dpath.iterdir()))
count = f" ({n} items)"
except PermissionError:
count = " (access denied)"
lines.append(f"- {exists} **`{name}/`**{count} {_tag(who)}")
lines.append(f" {purpose}")
lines.append("")
# --- .env breakdown ---
lines.append("---")
lines.append("## Environment Variables (.env)")
lines.append("")
env_path = TIMMY_HOME / ".env"
if env_path.exists():
for line in env_path.read_text().splitlines():
line = line.strip()
if not line or line.startswith("#"):
continue
key = line.split("=", 1)[0]
if key in ENV_ANNOTATIONS:
purpose, who = ENV_ANNOTATIONS[key]
lines.append(f"- **`{key}`** {_tag(who)}")
lines.append(f" {purpose}")
else:
lines.append(f"- **`{key}`** `[unknown]`")
lines.append(" Not documented — investigate")
else:
lines.append("*No .env file found*")
lines.append("")
# --- config.yaml breakdown ---
lines.append("---")
lines.append("## Configuration (config.yaml)")
lines.append("")
for key, (purpose, who) in sorted(CONFIG_ANNOTATIONS.items()):
lines.append(f"- **`{key}`** {_tag(who)}")
lines.append(f" {purpose}")
lines.append("")
# --- Model routing ---
lines.append("---")
lines.append("## Model Routing")
lines.append("")
lines.append("All auxiliary tasks route to the same local model:")
lines.append("")
aux_tasks = [
"vision", "web_extract", "compression",
"session_search", "skills_hub", "mcp", "flush_memories",
]
for task in aux_tasks:
lines.append(f"- `auxiliary.{task}` → `qwen3:30b` via local Ollama `[hermes-set]`")
lines.append("")
lines.append("Primary model: `hermes3:latest` via local Ollama `[hermes-set]`")
lines.append("")
# --- What Timmy should audit ---
lines.append("---")
lines.append("## Audit Checklist")
lines.append("")
lines.append("Walk through each `[hermes-set]` item above and decide:")
lines.append("")
lines.append("1. **Do I understand what this does?** If not, ask.")
lines.append("2. **Would I choose this myself?** If yes, it becomes `[timmy-chose]`.")
lines.append("3. **Would I choose differently?** If yes, change it and own it.")
lines.append("4. **Is this serving the mission?** Every setting should serve a purpose.")
lines.append("")
lines.append("The Workshop is yours. Nothing here should be a mystery.")
return "\n".join(lines) + "\n"
def main() -> None:
parser = argparse.ArgumentParser(description="Generate Workshop inventory")
parser.add_argument(
"--output",
type=Path,
default=TIMMY_HOME / "WORKSHOP_INVENTORY.md",
help="Output path (default: ~/.timmy/WORKSHOP_INVENTORY.md)",
)
args = parser.parse_args()
content = generate_inventory()
args.output.parent.mkdir(parents=True, exist_ok=True)
args.output.write_text(content)
print(f"Workshop inventory written to {args.output}")
print(f" {len(content)} chars, {content.count(chr(10))} lines")
if __name__ == "__main__":
main()

181
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@@ -0,0 +1,181 @@
#!/usr/bin/env python3
"""Loop guard — idle detection + exponential backoff for the dev loop.
Checks .loop/queue.json for ready items before spawning hermes.
When the queue is empty, applies exponential backoff (60s → 600s max)
instead of burning empty cycles every 3 seconds.
Usage (called by the dev loop before each cycle):
python3 scripts/loop_guard.py # exits 0 if ready, 1 if idle
python3 scripts/loop_guard.py --wait # same, but sleeps the backoff first
python3 scripts/loop_guard.py --status # print current idle state
Exit codes:
0 — queue has work, proceed with cycle
1 — queue empty, idle backoff applied (skip cycle)
"""
from __future__ import annotations
import json
import os
import sys
import time
import urllib.request
from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parent.parent
QUEUE_FILE = REPO_ROOT / ".loop" / "queue.json"
IDLE_STATE_FILE = REPO_ROOT / ".loop" / "idle_state.json"
TOKEN_FILE = Path.home() / ".hermes" / "gitea_token"
GITEA_API = os.environ.get("GITEA_API", "http://localhost:3000/api/v1")
REPO_SLUG = os.environ.get("REPO_SLUG", "rockachopa/Timmy-time-dashboard")
# Backoff sequence: 60s, 120s, 240s, 600s max
BACKOFF_BASE = 60
BACKOFF_MAX = 600
BACKOFF_MULTIPLIER = 2
def _get_token() -> str:
"""Read Gitea token from env or file."""
token = os.environ.get("GITEA_TOKEN", "").strip()
if not token and TOKEN_FILE.exists():
token = TOKEN_FILE.read_text().strip()
return token
def _fetch_open_issue_numbers() -> set[int] | None:
"""Fetch open issue numbers from Gitea. Returns None on failure."""
token = _get_token()
if not token:
return None
try:
numbers: set[int] = set()
page = 1
while True:
url = (
f"{GITEA_API}/repos/{REPO_SLUG}/issues"
f"?state=open&type=issues&limit=50&page={page}"
)
req = urllib.request.Request(url, headers={
"Authorization": f"token {token}",
"Accept": "application/json",
})
with urllib.request.urlopen(req, timeout=10) as resp:
data = json.loads(resp.read())
if not data:
break
for issue in data:
numbers.add(issue["number"])
if len(data) < 50:
break
page += 1
return numbers
except Exception:
return None
def load_queue() -> list[dict]:
"""Load queue.json and return ready items, filtering out closed issues."""
if not QUEUE_FILE.exists():
return []
try:
data = json.loads(QUEUE_FILE.read_text())
if not isinstance(data, list):
return []
ready = [item for item in data if item.get("ready")]
if not ready:
return []
# Filter out issues that are no longer open (auto-hygiene)
open_numbers = _fetch_open_issue_numbers()
if open_numbers is not None:
before = len(ready)
ready = [item for item in ready if item.get("issue") in open_numbers]
removed = before - len(ready)
if removed > 0:
print(f"[loop-guard] Filtered {removed} closed issue(s) from queue")
# Persist the cleaned queue so stale entries don't recur
_save_cleaned_queue(data, open_numbers)
return ready
except (json.JSONDecodeError, OSError):
return []
def _save_cleaned_queue(full_queue: list[dict], open_numbers: set[int]) -> None:
"""Rewrite queue.json without closed issues."""
cleaned = [item for item in full_queue if item.get("issue") in open_numbers]
try:
QUEUE_FILE.write_text(json.dumps(cleaned, indent=2) + "\n")
except OSError:
pass
def load_idle_state() -> dict:
"""Load persistent idle state."""
if not IDLE_STATE_FILE.exists():
return {"consecutive_idle": 0, "last_idle_at": 0}
try:
return json.loads(IDLE_STATE_FILE.read_text())
except (json.JSONDecodeError, OSError):
return {"consecutive_idle": 0, "last_idle_at": 0}
def save_idle_state(state: dict) -> None:
"""Persist idle state."""
IDLE_STATE_FILE.parent.mkdir(parents=True, exist_ok=True)
IDLE_STATE_FILE.write_text(json.dumps(state, indent=2) + "\n")
def compute_backoff(consecutive_idle: int) -> int:
"""Exponential backoff: 60, 120, 240, 600 (capped)."""
return min(BACKOFF_BASE * (BACKOFF_MULTIPLIER ** consecutive_idle), BACKOFF_MAX)
def main() -> int:
wait_mode = "--wait" in sys.argv
status_mode = "--status" in sys.argv
state = load_idle_state()
if status_mode:
ready = load_queue()
backoff = compute_backoff(state["consecutive_idle"])
print(json.dumps({
"queue_ready": len(ready),
"consecutive_idle": state["consecutive_idle"],
"next_backoff_seconds": backoff if not ready else 0,
}, indent=2))
return 0
ready = load_queue()
if ready:
# Queue has work — reset idle state, proceed
if state["consecutive_idle"] > 0:
print(f"[loop-guard] Queue active ({len(ready)} ready) — "
f"resuming after {state['consecutive_idle']} idle cycles")
state["consecutive_idle"] = 0
state["last_idle_at"] = 0
save_idle_state(state)
return 0
# Queue empty — apply backoff
backoff = compute_backoff(state["consecutive_idle"])
state["consecutive_idle"] += 1
state["last_idle_at"] = time.time()
save_idle_state(state)
print(f"[loop-guard] Queue empty — idle #{state['consecutive_idle']}, "
f"backoff {backoff}s")
if wait_mode:
time.sleep(backoff)
return 1
if __name__ == "__main__":
sys.exit(main())

407
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@@ -0,0 +1,407 @@
#!/usr/bin/env python3
"""Loop introspection — the self-improvement engine.
Analyzes retro data across time windows to detect trends, extract patterns,
and produce structured recommendations. Output is consumed by deep_triage
and injected into the loop prompt context.
This is the piece that closes the feedback loop:
cycle_retro → introspect → deep_triage → loop behavior changes
Run: python3 scripts/loop_introspect.py
Output: .loop/retro/insights.json (structured insights + recommendations)
Prints human-readable summary to stdout.
Called by: deep_triage.sh (before the LLM triage), timmy-loop.sh (every 50 cycles)
"""
from __future__ import annotations
import json
import sys
from collections import defaultdict
from datetime import datetime, timezone, timedelta
from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parent.parent
CYCLES_FILE = REPO_ROOT / ".loop" / "retro" / "cycles.jsonl"
DEEP_TRIAGE_FILE = REPO_ROOT / ".loop" / "retro" / "deep-triage.jsonl"
TRIAGE_FILE = REPO_ROOT / ".loop" / "retro" / "triage.jsonl"
QUARANTINE_FILE = REPO_ROOT / ".loop" / "quarantine.json"
INSIGHTS_FILE = REPO_ROOT / ".loop" / "retro" / "insights.json"
# ── Helpers ──────────────────────────────────────────────────────────────
def load_jsonl(path: Path) -> list[dict]:
"""Load a JSONL file, skipping bad lines."""
if not path.exists():
return []
entries = []
for line in path.read_text().strip().splitlines():
try:
entries.append(json.loads(line))
except (json.JSONDecodeError, ValueError):
continue
return entries
def parse_ts(ts_str: str) -> datetime | None:
"""Parse an ISO timestamp, tolerating missing tz."""
if not ts_str:
return None
try:
dt = datetime.fromisoformat(ts_str.replace("Z", "+00:00"))
if dt.tzinfo is None:
dt = dt.replace(tzinfo=timezone.utc)
return dt
except (ValueError, TypeError):
return None
def window(entries: list[dict], days: int) -> list[dict]:
"""Filter entries to the last N days."""
cutoff = datetime.now(timezone.utc) - timedelta(days=days)
result = []
for e in entries:
ts = parse_ts(e.get("timestamp", ""))
if ts and ts >= cutoff:
result.append(e)
return result
# ── Analysis functions ───────────────────────────────────────────────────
def compute_trends(cycles: list[dict]) -> dict:
"""Compare recent window (last 7d) vs older window (7-14d ago)."""
recent = window(cycles, 7)
older = window(cycles, 14)
# Remove recent from older to get the 7-14d window
recent_set = {(e.get("cycle"), e.get("timestamp")) for e in recent}
older = [e for e in older if (e.get("cycle"), e.get("timestamp")) not in recent_set]
def stats(entries):
if not entries:
return {"count": 0, "success_rate": None, "avg_duration": None,
"lines_net": 0, "prs_merged": 0}
successes = sum(1 for e in entries if e.get("success"))
durations = [e["duration"] for e in entries if e.get("duration", 0) > 0]
return {
"count": len(entries),
"success_rate": round(successes / len(entries), 3) if entries else None,
"avg_duration": round(sum(durations) / len(durations)) if durations else None,
"lines_net": sum(e.get("lines_added", 0) - e.get("lines_removed", 0) for e in entries),
"prs_merged": sum(1 for e in entries if e.get("pr")),
}
recent_stats = stats(recent)
older_stats = stats(older)
trend = {
"recent_7d": recent_stats,
"previous_7d": older_stats,
"velocity_change": None,
"success_rate_change": None,
"duration_change": None,
}
if recent_stats["count"] and older_stats["count"]:
trend["velocity_change"] = recent_stats["count"] - older_stats["count"]
if recent_stats["success_rate"] is not None and older_stats["success_rate"] is not None:
trend["success_rate_change"] = round(
recent_stats["success_rate"] - older_stats["success_rate"], 3
)
if recent_stats["avg_duration"] is not None and older_stats["avg_duration"] is not None:
trend["duration_change"] = recent_stats["avg_duration"] - older_stats["avg_duration"]
return trend
def type_analysis(cycles: list[dict]) -> dict:
"""Per-type success rates and durations."""
by_type: dict[str, list[dict]] = defaultdict(list)
for c in cycles:
by_type[c.get("type", "unknown")].append(c)
result = {}
for t, entries in by_type.items():
durations = [e["duration"] for e in entries if e.get("duration", 0) > 0]
successes = sum(1 for e in entries if e.get("success"))
result[t] = {
"count": len(entries),
"success_rate": round(successes / len(entries), 3) if entries else 0,
"avg_duration": round(sum(durations) / len(durations)) if durations else 0,
"max_duration": max(durations) if durations else 0,
}
return result
def repeat_failures(cycles: list[dict]) -> list[dict]:
"""Issues that have failed multiple times — quarantine candidates."""
failures: dict[int, list] = defaultdict(list)
for c in cycles:
if not c.get("success") and c.get("issue"):
failures[c["issue"]].append({
"cycle": c.get("cycle"),
"reason": c.get("reason", ""),
"duration": c.get("duration", 0),
})
# Only issues with 2+ failures
return [
{"issue": k, "failure_count": len(v), "attempts": v}
for k, v in sorted(failures.items(), key=lambda x: -len(x[1]))
if len(v) >= 2
]
def duration_outliers(cycles: list[dict], threshold_multiple: float = 3.0) -> list[dict]:
"""Cycles that took way longer than average — something went wrong."""
durations = [c["duration"] for c in cycles if c.get("duration", 0) > 0]
if len(durations) < 5:
return []
avg = sum(durations) / len(durations)
threshold = avg * threshold_multiple
outliers = []
for c in cycles:
dur = c.get("duration", 0)
if dur > threshold:
outliers.append({
"cycle": c.get("cycle"),
"issue": c.get("issue"),
"type": c.get("type"),
"duration": dur,
"avg_duration": round(avg),
"multiple": round(dur / avg, 1) if avg > 0 else 0,
"reason": c.get("reason", ""),
})
return outliers
def triage_effectiveness(deep_triages: list[dict]) -> dict:
"""How well is the deep triage performing?"""
if not deep_triages:
return {"runs": 0, "note": "No deep triage data yet"}
total_reviewed = sum(d.get("issues_reviewed", 0) for d in deep_triages)
total_refined = sum(len(d.get("issues_refined", [])) for d in deep_triages)
total_created = sum(len(d.get("issues_created", [])) for d in deep_triages)
total_closed = sum(len(d.get("issues_closed", [])) for d in deep_triages)
timmy_available = sum(1 for d in deep_triages if d.get("timmy_available"))
# Extract Timmy's feedback themes
timmy_themes = []
for d in deep_triages:
fb = d.get("timmy_feedback", "")
if fb:
timmy_themes.append(fb[:200])
return {
"runs": len(deep_triages),
"total_reviewed": total_reviewed,
"total_refined": total_refined,
"total_created": total_created,
"total_closed": total_closed,
"timmy_consultation_rate": round(timmy_available / len(deep_triages), 2),
"timmy_recent_feedback": timmy_themes[-1] if timmy_themes else "",
"timmy_feedback_history": timmy_themes,
}
def generate_recommendations(
trends: dict,
types: dict,
repeats: list,
outliers: list,
triage_eff: dict,
) -> list[dict]:
"""Produce actionable recommendations from the analysis."""
recs = []
# 1. Success rate declining?
src = trends.get("success_rate_change")
if src is not None and src < -0.1:
recs.append({
"severity": "high",
"category": "reliability",
"finding": f"Success rate dropped {abs(src)*100:.0f}pp in the last 7 days",
"recommendation": "Review recent failures. Are issues poorly scoped? "
"Is main unstable? Check if triage is producing bad work items.",
})
# 2. Velocity dropping?
vc = trends.get("velocity_change")
if vc is not None and vc < -5:
recs.append({
"severity": "medium",
"category": "throughput",
"finding": f"Velocity dropped by {abs(vc)} cycles vs previous week",
"recommendation": "Check for loop stalls, long-running cycles, or queue starvation.",
})
# 3. Duration creep?
dc = trends.get("duration_change")
if dc is not None and dc > 120: # 2+ minutes longer
recs.append({
"severity": "medium",
"category": "efficiency",
"finding": f"Average cycle duration increased by {dc}s vs previous week",
"recommendation": "Issues may be growing in scope. Enforce tighter decomposition "
"in deep triage. Check if tests are getting slower.",
})
# 4. Type-specific problems
for t, info in types.items():
if info["count"] >= 3 and info["success_rate"] < 0.5:
recs.append({
"severity": "high",
"category": "type_reliability",
"finding": f"'{t}' issues fail {(1-info['success_rate'])*100:.0f}% of the time "
f"({info['count']} attempts)",
"recommendation": f"'{t}' issues need better scoping or different approach. "
f"Consider: tighter acceptance criteria, smaller scope, "
f"or delegating to Kimi with more context.",
})
if info["avg_duration"] > 600 and info["count"] >= 3: # >10 min avg
recs.append({
"severity": "medium",
"category": "type_efficiency",
"finding": f"'{t}' issues average {info['avg_duration']//60}m{info['avg_duration']%60}s "
f"(max {info['max_duration']//60}m)",
"recommendation": f"Break '{t}' issues into smaller pieces. Target <5 min per cycle.",
})
# 5. Repeat failures
for rf in repeats[:3]:
recs.append({
"severity": "high",
"category": "repeat_failure",
"finding": f"Issue #{rf['issue']} has failed {rf['failure_count']} times",
"recommendation": "Quarantine or rewrite this issue. Repeated failure = "
"bad scope or missing prerequisite.",
})
# 6. Outliers
if len(outliers) > 2:
recs.append({
"severity": "medium",
"category": "outliers",
"finding": f"{len(outliers)} cycles took {outliers[0].get('multiple', '?')}x+ "
f"longer than average",
"recommendation": "Long cycles waste resources. Add timeout enforcement or "
"break complex issues earlier.",
})
# 7. Code growth
recent = trends.get("recent_7d", {})
net = recent.get("lines_net", 0)
if net > 500:
recs.append({
"severity": "low",
"category": "code_health",
"finding": f"Net +{net} lines added in the last 7 days",
"recommendation": "Lines of code is a liability. Balance feature work with "
"refactoring. Target net-zero or negative line growth.",
})
# 8. Triage health
if triage_eff.get("runs", 0) == 0:
recs.append({
"severity": "high",
"category": "triage",
"finding": "Deep triage has never run",
"recommendation": "Enable deep triage (every 20 cycles). The loop needs "
"LLM-driven issue refinement to stay effective.",
})
# No recommendations = things are healthy
if not recs:
recs.append({
"severity": "info",
"category": "health",
"finding": "No significant issues detected",
"recommendation": "System is healthy. Continue current patterns.",
})
return recs
# ── Main ─────────────────────────────────────────────────────────────────
def main() -> None:
cycles = load_jsonl(CYCLES_FILE)
deep_triages = load_jsonl(DEEP_TRIAGE_FILE)
if not cycles:
print("[introspect] No cycle data found. Nothing to analyze.")
return
# Run all analyses
trends = compute_trends(cycles)
types = type_analysis(cycles)
repeats = repeat_failures(cycles)
outliers = duration_outliers(cycles)
triage_eff = triage_effectiveness(deep_triages)
recommendations = generate_recommendations(trends, types, repeats, outliers, triage_eff)
insights = {
"generated_at": datetime.now(timezone.utc).isoformat(),
"total_cycles_analyzed": len(cycles),
"trends": trends,
"by_type": types,
"repeat_failures": repeats[:5],
"duration_outliers": outliers[:5],
"triage_effectiveness": triage_eff,
"recommendations": recommendations,
}
# Write insights
INSIGHTS_FILE.parent.mkdir(parents=True, exist_ok=True)
INSIGHTS_FILE.write_text(json.dumps(insights, indent=2) + "\n")
# Current epoch from latest entry
latest_epoch = ""
for c in reversed(cycles):
if c.get("epoch"):
latest_epoch = c["epoch"]
break
# Human-readable output
header = f"[introspect] Analyzed {len(cycles)} cycles"
if latest_epoch:
header += f" · current epoch: {latest_epoch}"
print(header)
print(f"\n TRENDS (7d vs previous 7d):")
r7 = trends["recent_7d"]
p7 = trends["previous_7d"]
print(f" Cycles: {r7['count']:>3d} (was {p7['count']})")
if r7["success_rate"] is not None:
arrow = "" if (trends["success_rate_change"] or 0) > 0 else "" if (trends["success_rate_change"] or 0) < 0 else ""
print(f" Success rate: {r7['success_rate']*100:>4.0f}% {arrow}")
if r7["avg_duration"] is not None:
print(f" Avg duration: {r7['avg_duration']//60}m{r7['avg_duration']%60:02d}s")
print(f" PRs merged: {r7['prs_merged']:>3d} (was {p7['prs_merged']})")
print(f" Lines net: {r7['lines_net']:>+5d}")
print(f"\n BY TYPE:")
for t, info in sorted(types.items(), key=lambda x: -x[1]["count"]):
print(f" {t:12s} n={info['count']:>2d} "
f"ok={info['success_rate']*100:>3.0f}% "
f"avg={info['avg_duration']//60}m{info['avg_duration']%60:02d}s")
if repeats:
print(f"\n REPEAT FAILURES:")
for rf in repeats[:3]:
print(f" #{rf['issue']} failed {rf['failure_count']}x")
print(f"\n RECOMMENDATIONS ({len(recommendations)}):")
for i, rec in enumerate(recommendations, 1):
sev = {"high": "🔴", "medium": "🟡", "low": "🟢", "info": " "}.get(rec["severity"], "?")
print(f" {sev} {rec['finding']}")
print(f"{rec['recommendation']}")
print(f"\n Written to: {INSIGHTS_FILE}")
if __name__ == "__main__":
main()

View File

@@ -10,6 +10,11 @@ from pydantic_settings import BaseSettings, SettingsConfigDict
APP_START_TIME: _datetime = _datetime.now(UTC)
def normalize_ollama_url(url: str) -> str:
"""Replace localhost with 127.0.0.1 to avoid IPv6 resolution delays."""
return url.replace("localhost", "127.0.0.1")
class Settings(BaseSettings):
"""Central configuration — all env-var access goes through this class."""
@@ -19,6 +24,11 @@ class Settings(BaseSettings):
# Ollama host — override with OLLAMA_URL env var or .env file
ollama_url: str = "http://localhost:11434"
@property
def normalized_ollama_url(self) -> str:
"""Return ollama_url with localhost replaced by 127.0.0.1."""
return normalize_ollama_url(self.ollama_url)
# LLM model passed to Agno/Ollama — override with OLLAMA_MODEL
# qwen3:30b is the primary model — better reasoning and tool calling
# than llama3.1:8b-instruct while still running locally on modest hardware.
@@ -64,17 +74,10 @@ class Settings(BaseSettings):
# Seconds to wait for user confirmation before auto-rejecting.
discord_confirm_timeout: int = 120
# ── AirLLM / backend selection ───────────────────────────────────────────
# ── Backend selection ────────────────────────────────────────────────────
# "ollama" — always use Ollama (default, safe everywhere)
# "airllm" — always use AirLLM (requires pip install ".[bigbrain]")
# "auto" — use AirLLM on Apple Silicon if airllm is installed,
# fall back to Ollama otherwise
timmy_model_backend: Literal["ollama", "airllm", "grok", "claude", "auto"] = "ollama"
# AirLLM model size when backend is airllm or auto.
# Larger = smarter, but needs more RAM / disk.
# 8b ~16 GB | 70b ~140 GB | 405b ~810 GB
airllm_model_size: Literal["8b", "70b", "405b"] = "70b"
# "auto" — pick best available local backend, fall back to Ollama
timmy_model_backend: Literal["ollama", "grok", "claude", "auto"] = "ollama"
# ── Grok (xAI) — opt-in premium cloud backend ────────────────────────
# Grok is a premium augmentation layer — local-first ethos preserved.
@@ -138,7 +141,12 @@ class Settings(BaseSettings):
# CORS allowed origins for the web chat interface (Gitea Pages, etc.)
# Set CORS_ORIGINS as a comma-separated list, e.g. "http://localhost:3000,https://example.com"
cors_origins: list[str] = ["*"]
cors_origins: list[str] = [
"http://localhost:3000",
"http://localhost:8000",
"http://127.0.0.1:3000",
"http://127.0.0.1:8000",
]
# Trusted hosts for the Host header check (TrustedHostMiddleware).
# Set TRUSTED_HOSTS as a comma-separated list. Wildcards supported (e.g. "*.ts.net").
@@ -238,12 +246,19 @@ class Settings(BaseSettings):
# Fallback to server when browser model is unavailable or too slow.
browser_model_fallback: bool = True
# ── Deep Focus Mode ─────────────────────────────────────────────
# "deep" = single-problem context; "broad" = default multi-task.
focus_mode: Literal["deep", "broad"] = "broad"
# ── Default Thinking ──────────────────────────────────────────────
# When enabled, the agent starts an internal thought loop on server start.
thinking_enabled: bool = True
thinking_interval_seconds: int = 300 # 5 minutes between thoughts
thinking_timeout_seconds: int = 120 # max wall-clock time per thinking cycle
thinking_distill_every: int = 10 # distill facts from thoughts every Nth thought
thinking_issue_every: int = 20 # file Gitea issues from thoughts every Nth thought
thinking_memory_check_every: int = 50 # check memory status every Nth thought
thinking_idle_timeout_minutes: int = 60 # pause thoughts after N minutes without user input
# ── Gitea Integration ─────────────────────────────────────────────
# Local Gitea instance for issue tracking and self-improvement.
@@ -388,7 +403,7 @@ def check_ollama_model_available(model_name: str) -> bool:
import json
import urllib.request
url = settings.ollama_url.replace("localhost", "127.0.0.1")
url = settings.normalized_ollama_url
req = urllib.request.Request(
f"{url}/api/tags",
method="GET",
@@ -465,8 +480,19 @@ def validate_startup(*, force: bool = False) -> None:
", ".join(_missing),
)
sys.exit(1)
if "*" in settings.cors_origins:
_startup_logger.error(
"PRODUCTION SECURITY ERROR: CORS wildcard '*' is not allowed "
"in production. Set CORS_ORIGINS to explicit origins."
)
sys.exit(1)
_startup_logger.info("Production mode: security secrets validated ✓")
else:
if "*" in settings.cors_origins:
_startup_logger.warning(
"SEC: CORS_ORIGINS contains wildcard '*'"
"restrict to explicit origins before deploying to production."
)
if not settings.l402_hmac_secret:
_startup_logger.warning(
"SEC: L402_HMAC_SECRET is not set — "

View File

@@ -8,6 +8,7 @@ Key improvements:
"""
import asyncio
import json
import logging
from contextlib import asynccontextmanager
from pathlib import Path
@@ -28,6 +29,7 @@ from dashboard.routes.agents import router as agents_router
from dashboard.routes.briefing import router as briefing_router
from dashboard.routes.calm import router as calm_router
from dashboard.routes.chat_api import router as chat_api_router
from dashboard.routes.chat_api_v1 import router as chat_api_v1_router
from dashboard.routes.db_explorer import router as db_explorer_router
from dashboard.routes.discord import router as discord_router
from dashboard.routes.experiments import router as experiments_router
@@ -46,6 +48,8 @@ from dashboard.routes.thinking import router as thinking_router
from dashboard.routes.tools import router as tools_router
from dashboard.routes.voice import router as voice_router
from dashboard.routes.work_orders import router as work_orders_router
from dashboard.routes.world import router as world_router
from timmy.workshop_state import PRESENCE_FILE
class _ColorFormatter(logging.Formatter):
@@ -151,7 +155,17 @@ async def _thinking_scheduler() -> None:
while True:
try:
if settings.thinking_enabled:
await thinking_engine.think_once()
await asyncio.wait_for(
thinking_engine.think_once(),
timeout=settings.thinking_timeout_seconds,
)
except TimeoutError:
logger.warning(
"Thinking cycle timed out after %ds — Ollama may be unresponsive",
settings.thinking_timeout_seconds,
)
except asyncio.CancelledError:
raise
except Exception as exc:
logger.error("Thinking scheduler error: %s", exc)
@@ -171,7 +185,10 @@ async def _loop_qa_scheduler() -> None:
while True:
try:
if settings.loop_qa_enabled:
result = await loop_qa_orchestrator.run_next_test()
result = await asyncio.wait_for(
loop_qa_orchestrator.run_next_test(),
timeout=settings.thinking_timeout_seconds,
)
if result:
status = "PASS" if result["success"] else "FAIL"
logger.info(
@@ -180,6 +197,13 @@ async def _loop_qa_scheduler() -> None:
status,
result.get("details", "")[:80],
)
except TimeoutError:
logger.warning(
"Loop QA test timed out after %ds",
settings.thinking_timeout_seconds,
)
except asyncio.CancelledError:
raise
except Exception as exc:
logger.error("Loop QA scheduler error: %s", exc)
@@ -187,6 +211,54 @@ async def _loop_qa_scheduler() -> None:
await asyncio.sleep(interval)
_PRESENCE_POLL_SECONDS = 30
_PRESENCE_INITIAL_DELAY = 3
_SYNTHESIZED_STATE: dict = {
"version": 1,
"liveness": None,
"current_focus": "",
"mood": "idle",
"active_threads": [],
"recent_events": [],
"concerns": [],
}
async def _presence_watcher() -> None:
"""Background task: watch ~/.timmy/presence.json and broadcast changes via WS.
Polls the file every 30 seconds (matching Timmy's write cadence).
If the file doesn't exist, broadcasts a synthesised idle state.
"""
from infrastructure.ws_manager.handler import ws_manager as ws_mgr
await asyncio.sleep(_PRESENCE_INITIAL_DELAY) # Stagger after other schedulers
last_mtime: float = 0.0
while True:
try:
if PRESENCE_FILE.exists():
mtime = PRESENCE_FILE.stat().st_mtime
if mtime != last_mtime:
last_mtime = mtime
raw = await asyncio.to_thread(PRESENCE_FILE.read_text)
state = json.loads(raw)
await ws_mgr.broadcast("timmy_state", state)
else:
# File absent — broadcast synthesised state once per cycle
if last_mtime != -1.0:
last_mtime = -1.0
await ws_mgr.broadcast("timmy_state", _SYNTHESIZED_STATE)
except json.JSONDecodeError as exc:
logger.warning("presence.json parse error: %s", exc)
except Exception as exc:
logger.warning("Presence watcher error: %s", exc)
await asyncio.sleep(_PRESENCE_POLL_SECONDS)
async def _start_chat_integrations_background() -> None:
"""Background task: start chat integrations without blocking startup."""
from integrations.chat_bridge.registry import platform_registry
@@ -277,32 +349,35 @@ async def _discord_token_watcher() -> None:
logger.warning("Discord auto-start failed: %s", exc)
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Application lifespan manager with non-blocking startup."""
# Validate security config (no-op in test mode)
def _startup_init() -> None:
"""Validate config and enable event persistence."""
from config import validate_startup
validate_startup()
# Enable event persistence (unified EventBus + swarm event_log)
from infrastructure.events.bus import init_event_bus_persistence
init_event_bus_persistence()
# Create all background tasks without waiting for them
briefing_task = asyncio.create_task(_briefing_scheduler())
thinking_task = asyncio.create_task(_thinking_scheduler())
loop_qa_task = asyncio.create_task(_loop_qa_scheduler())
# Initialize Spark Intelligence engine
from spark.engine import get_spark_engine
if get_spark_engine().enabled:
logger.info("Spark Intelligence active — event capture enabled")
# Auto-prune old vector store memories on startup
def _startup_background_tasks() -> list[asyncio.Task]:
"""Spawn all recurring background tasks (non-blocking)."""
return [
asyncio.create_task(_briefing_scheduler()),
asyncio.create_task(_thinking_scheduler()),
asyncio.create_task(_loop_qa_scheduler()),
asyncio.create_task(_presence_watcher()),
asyncio.create_task(_start_chat_integrations_background()),
]
def _startup_pruning() -> None:
"""Auto-prune old memories, thoughts, and events on startup."""
if settings.memory_prune_days > 0:
try:
from timmy.memory_system import prune_memories
@@ -320,7 +395,6 @@ async def lifespan(app: FastAPI):
except Exception as exc:
logger.debug("Memory auto-prune skipped: %s", exc)
# Auto-prune old thoughts on startup
if settings.thoughts_prune_days > 0:
try:
from timmy.thinking import thinking_engine
@@ -338,7 +412,6 @@ async def lifespan(app: FastAPI):
except Exception as exc:
logger.debug("Thought auto-prune skipped: %s", exc)
# Auto-prune old system events on startup
if settings.events_prune_days > 0:
try:
from swarm.event_log import prune_old_events
@@ -356,7 +429,6 @@ async def lifespan(app: FastAPI):
except Exception as exc:
logger.debug("Event auto-prune skipped: %s", exc)
# Warn if memory vault exceeds size limit
if settings.memory_vault_max_mb > 0:
try:
vault_path = Path(settings.repo_root) / "memory" / "notes"
@@ -372,30 +444,18 @@ async def lifespan(app: FastAPI):
except Exception as exc:
logger.debug("Vault size check skipped: %s", exc)
# Start chat integrations in background
chat_task = asyncio.create_task(_start_chat_integrations_background())
# Register session logger with error capture (breaks infrastructure → timmy circular dep)
try:
from infrastructure.error_capture import register_error_recorder
from timmy.session_logger import get_session_logger
register_error_recorder(get_session_logger().record_error)
except Exception:
pass
logger.info("✓ Dashboard ready for requests")
yield
# Cleanup on shutdown
async def _shutdown_cleanup(
bg_tasks: list[asyncio.Task],
workshop_heartbeat,
) -> None:
"""Stop chat bots, MCP sessions, heartbeat, and cancel background tasks."""
from integrations.chat_bridge.vendors.discord import discord_bot
from integrations.telegram_bot.bot import telegram_bot
await discord_bot.stop()
await telegram_bot.stop()
# Close MCP tool server sessions
try:
from timmy.mcp_tools import close_mcp_sessions
@@ -403,13 +463,44 @@ async def lifespan(app: FastAPI):
except Exception as exc:
logger.debug("MCP shutdown: %s", exc)
for task in [briefing_task, thinking_task, chat_task, loop_qa_task]:
if task:
task.cancel()
try:
await task
except asyncio.CancelledError:
pass
await workshop_heartbeat.stop()
for task in bg_tasks:
task.cancel()
try:
await task
except asyncio.CancelledError:
pass
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Application lifespan manager with non-blocking startup."""
_startup_init()
bg_tasks = _startup_background_tasks()
_startup_pruning()
# Start Workshop presence heartbeat with WS relay
from dashboard.routes.world import broadcast_world_state
from timmy.workshop_state import WorkshopHeartbeat
workshop_heartbeat = WorkshopHeartbeat(on_change=broadcast_world_state)
await workshop_heartbeat.start()
# Register session logger with error capture
try:
from infrastructure.error_capture import register_error_recorder
from timmy.session_logger import get_session_logger
register_error_recorder(get_session_logger().record_error)
except Exception:
logger.debug("Failed to register error recorder")
logger.info("✓ Dashboard ready for requests")
yield
await _shutdown_cleanup(bg_tasks, workshop_heartbeat)
app = FastAPI(
@@ -422,15 +513,14 @@ app = FastAPI(
def _get_cors_origins() -> list[str]:
"""Get CORS origins from settings, with sensible defaults."""
"""Get CORS origins from settings, rejecting wildcards in production."""
origins = settings.cors_origins
if settings.debug and origins == ["*"]:
return [
"http://localhost:3000",
"http://localhost:8000",
"http://127.0.0.1:3000",
"http://127.0.0.1:8000",
]
if "*" in origins and not settings.debug:
logger.warning(
"Wildcard '*' in CORS_ORIGINS stripped in production — "
"set explicit origins via CORS_ORIGINS env var"
)
origins = [o for o in origins if o != "*"]
return origins
@@ -483,6 +573,7 @@ app.include_router(grok_router)
app.include_router(models_router)
app.include_router(models_api_router)
app.include_router(chat_api_router)
app.include_router(chat_api_v1_router)
app.include_router(thinking_router)
app.include_router(calm_router)
app.include_router(tasks_router)
@@ -491,6 +582,7 @@ app.include_router(loop_qa_router)
app.include_router(system_router)
app.include_router(experiments_router)
app.include_router(db_explorer_router)
app.include_router(world_router)
@app.websocket("/ws")

View File

@@ -100,7 +100,7 @@ class CSRFMiddleware(BaseHTTPMiddleware):
...
Usage:
app.add_middleware(CSRFMiddleware, secret="your-secret-key")
app.add_middleware(CSRFMiddleware, secret=settings.csrf_secret)
Attributes:
secret: Secret key for token signing (optional, for future use).

View File

@@ -71,19 +71,87 @@ async def clear_history(request: Request):
)
def _validate_message(message: str) -> str:
"""Strip and validate chat input; raise HTTPException on bad input."""
from fastapi import HTTPException
message = message.strip()
if not message:
raise HTTPException(status_code=400, detail="Message cannot be empty")
if len(message) > MAX_MESSAGE_LENGTH:
raise HTTPException(status_code=422, detail="Message too long")
return message
def _record_user_activity() -> None:
"""Notify the thinking engine that the user is active."""
try:
from timmy.thinking import thinking_engine
thinking_engine.record_user_input()
except Exception:
logger.debug("Failed to record user input for thinking engine")
def _extract_tool_actions(run_output) -> list[dict]:
"""If Agno paused the run for tool confirmation, build approval items."""
from timmy.approvals import create_item
tool_actions: list[dict] = []
status = getattr(run_output, "status", None)
is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
if not (is_paused and getattr(run_output, "active_requirements", None)):
return tool_actions
for req in run_output.active_requirements:
if not getattr(req, "needs_confirmation", False):
continue
te = req.tool_execution
tool_name = getattr(te, "tool_name", "unknown")
tool_args = getattr(te, "tool_args", {}) or {}
item = create_item(
title=f"Dashboard: {tool_name}",
description=format_action_description(tool_name, tool_args),
proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
impact=get_impact_level(tool_name),
)
_pending_runs[item.id] = {
"run_output": run_output,
"requirement": req,
"tool_name": tool_name,
"tool_args": tool_args,
}
tool_actions.append(
{
"approval_id": item.id,
"tool_name": tool_name,
"description": format_action_description(tool_name, tool_args),
"impact": get_impact_level(tool_name),
}
)
return tool_actions
def _log_exchange(
message: str, response_text: str | None, error_text: str | None, timestamp: str
) -> None:
"""Append user message and agent/error reply to the in-memory log."""
message_log.append(role="user", content=message, timestamp=timestamp, source="browser")
if response_text:
message_log.append(
role="agent", content=response_text, timestamp=timestamp, source="browser"
)
elif error_text:
message_log.append(role="error", content=error_text, timestamp=timestamp, source="browser")
@router.post("/default/chat", response_class=HTMLResponse)
async def chat_agent(request: Request, message: str = Form(...)):
"""Chat — synchronous response with native Agno tool confirmation."""
message = message.strip()
if not message:
from fastapi import HTTPException
raise HTTPException(status_code=400, detail="Message cannot be empty")
if len(message) > MAX_MESSAGE_LENGTH:
from fastapi import HTTPException
raise HTTPException(status_code=422, detail="Message too long")
message = _validate_message(message)
_record_user_activity()
timestamp = datetime.now().strftime("%H:%M:%S")
response_text = None
@@ -96,54 +164,15 @@ async def chat_agent(request: Request, message: str = Form(...)):
error_text = f"Chat error: {exc}"
run_output = None
# Check if Agno paused the run for tool confirmation
tool_actions = []
tool_actions: list[dict] = []
if run_output is not None:
status = getattr(run_output, "status", None)
is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
if is_paused and getattr(run_output, "active_requirements", None):
for req in run_output.active_requirements:
if getattr(req, "needs_confirmation", False):
te = req.tool_execution
tool_name = getattr(te, "tool_name", "unknown")
tool_args = getattr(te, "tool_args", {}) or {}
from timmy.approvals import create_item
item = create_item(
title=f"Dashboard: {tool_name}",
description=format_action_description(tool_name, tool_args),
proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
impact=get_impact_level(tool_name),
)
_pending_runs[item.id] = {
"run_output": run_output,
"requirement": req,
"tool_name": tool_name,
"tool_args": tool_args,
}
tool_actions.append(
{
"approval_id": item.id,
"tool_name": tool_name,
"description": format_action_description(tool_name, tool_args),
"impact": get_impact_level(tool_name),
}
)
tool_actions = _extract_tool_actions(run_output)
raw_content = run_output.content if hasattr(run_output, "content") else ""
response_text = _clean_response(raw_content or "")
if not response_text and not tool_actions:
response_text = None # let error template show if needed
response_text = None
message_log.append(role="user", content=message, timestamp=timestamp, source="browser")
if response_text:
message_log.append(
role="agent", content=response_text, timestamp=timestamp, source="browser"
)
elif error_text:
message_log.append(role="error", content=error_text, timestamp=timestamp, source="browser")
_log_exchange(message, response_text, error_text, timestamp)
return templates.TemplateResponse(
request,

View File

@@ -19,14 +19,17 @@ router = APIRouter(tags=["calm"])
# Helper functions for state machine logic
def get_now_task(db: Session) -> Task | None:
"""Return the single active NOW task, or None."""
return db.query(Task).filter(Task.state == TaskState.NOW).first()
def get_next_task(db: Session) -> Task | None:
"""Return the single queued NEXT task, or None."""
return db.query(Task).filter(Task.state == TaskState.NEXT).first()
def get_later_tasks(db: Session) -> list[Task]:
"""Return all LATER tasks ordered by MIT flag then sort_order."""
return (
db.query(Task)
.filter(Task.state == TaskState.LATER)
@@ -36,6 +39,12 @@ def get_later_tasks(db: Session) -> list[Task]:
def promote_tasks(db: Session):
"""Enforce the NOW/NEXT/LATER state machine invariants.
- At most one NOW task (extras demoted to NEXT).
- If no NOW, promote NEXT -> NOW.
- If no NEXT, promote highest-priority LATER -> NEXT.
"""
# Ensure only one NOW task exists. If multiple, demote extras to NEXT.
now_tasks = db.query(Task).filter(Task.state == TaskState.NOW).all()
if len(now_tasks) > 1:
@@ -74,6 +83,7 @@ def promote_tasks(db: Session):
# Endpoints
@router.get("/calm", response_class=HTMLResponse)
async def get_calm_view(request: Request, db: Session = Depends(get_db)):
"""Render the main CALM dashboard with NOW/NEXT/LATER counts."""
now_task = get_now_task(db)
next_task = get_next_task(db)
later_tasks_count = len(get_later_tasks(db))
@@ -90,6 +100,7 @@ async def get_calm_view(request: Request, db: Session = Depends(get_db)):
@router.get("/calm/ritual/morning", response_class=HTMLResponse)
async def get_morning_ritual_form(request: Request):
"""Render the morning ritual intake form."""
return templates.TemplateResponse(request, "calm/morning_ritual_form.html", {})
@@ -102,6 +113,7 @@ async def post_morning_ritual(
mit3_title: str = Form(None),
other_tasks: str = Form(""),
):
"""Process morning ritual: create MITs, other tasks, and set initial states."""
# Create Journal Entry
mit_task_ids = []
journal_entry = JournalEntry(entry_date=date.today())
@@ -173,6 +185,7 @@ async def post_morning_ritual(
@router.get("/calm/ritual/evening", response_class=HTMLResponse)
async def get_evening_ritual_form(request: Request, db: Session = Depends(get_db)):
"""Render the evening ritual form for today's journal entry."""
journal_entry = db.query(JournalEntry).filter(JournalEntry.entry_date == date.today()).first()
if not journal_entry:
raise HTTPException(status_code=404, detail="No journal entry for today")
@@ -189,6 +202,7 @@ async def post_evening_ritual(
gratitude: str = Form(None),
energy_level: int = Form(None),
):
"""Process evening ritual: save reflection/gratitude, archive active tasks."""
journal_entry = db.query(JournalEntry).filter(JournalEntry.entry_date == date.today()).first()
if not journal_entry:
raise HTTPException(status_code=404, detail="No journal entry for today")
@@ -223,6 +237,7 @@ async def create_new_task(
is_mit: bool = Form(False),
certainty: TaskCertainty = Form(TaskCertainty.SOFT),
):
"""Create a new task in LATER state and return updated count."""
task = Task(
title=title,
description=description,
@@ -247,6 +262,7 @@ async def start_task(
task_id: int,
db: Session = Depends(get_db),
):
"""Move a task to NOW state, demoting the current NOW to NEXT."""
current_now_task = get_now_task(db)
if current_now_task and current_now_task.id != task_id:
current_now_task.state = TaskState.NEXT # Demote current NOW to NEXT
@@ -281,6 +297,7 @@ async def complete_task(
task_id: int,
db: Session = Depends(get_db),
):
"""Mark a task as DONE and trigger state promotion."""
task = db.query(Task).filter(Task.id == task_id).first()
if not task:
raise HTTPException(status_code=404, detail="Task not found")
@@ -309,6 +326,7 @@ async def defer_task(
task_id: int,
db: Session = Depends(get_db),
):
"""Defer a task and trigger state promotion."""
task = db.query(Task).filter(Task.id == task_id).first()
if not task:
raise HTTPException(status_code=404, detail="Task not found")
@@ -333,6 +351,7 @@ async def defer_task(
@router.get("/calm/partials/later_tasks_list", response_class=HTMLResponse)
async def get_later_tasks_list(request: Request, db: Session = Depends(get_db)):
"""Render the expandable list of LATER tasks."""
later_tasks = get_later_tasks(db)
return templates.TemplateResponse(
"calm/partials/later_tasks_list.html",
@@ -348,6 +367,7 @@ async def reorder_tasks(
later_task_ids: str = Form(""),
next_task_id: int | None = Form(None),
):
"""Reorder LATER tasks and optionally promote one to NEXT."""
# Reorder LATER tasks
if later_task_ids:
ids_in_order = [int(x.strip()) for x in later_task_ids.split(",") if x.strip()]

View File

@@ -31,6 +31,93 @@ _UPLOAD_DIR = str(Path(settings.repo_root) / "data" / "chat-uploads")
_MAX_UPLOAD_SIZE = 50 * 1024 * 1024 # 50 MB
# ── POST /api/chat — helpers ─────────────────────────────────────────────────
async def _parse_chat_body(request: Request) -> tuple[dict | None, JSONResponse | None]:
"""Parse and validate the JSON request body.
Returns (body, None) on success or (None, error_response) on failure.
"""
content_length = request.headers.get("content-length")
if content_length and int(content_length) > settings.chat_api_max_body_bytes:
return None, JSONResponse(status_code=413, content={"error": "Request body too large"})
try:
body = await request.json()
except Exception as exc:
logger.warning("Chat API JSON parse error: %s", exc)
return None, JSONResponse(status_code=400, content={"error": "Invalid JSON"})
messages = body.get("messages")
if not messages or not isinstance(messages, list):
return None, JSONResponse(status_code=400, content={"error": "messages array is required"})
return body, None
def _extract_user_message(messages: list[dict]) -> str | None:
"""Return the text of the last user message, or *None* if absent."""
for msg in reversed(messages):
if msg.get("role") == "user":
content = msg.get("content", "")
if isinstance(content, list):
text_parts = [
p.get("text", "")
for p in content
if isinstance(p, dict) and p.get("type") == "text"
]
return " ".join(text_parts).strip() or None
text = str(content).strip()
return text or None
return None
def _build_context_prefix() -> str:
"""Build the system-context preamble injected before the user message."""
now = datetime.now()
return (
f"[System: Current date/time is "
f"{now.strftime('%A, %B %d, %Y at %I:%M %p')}]\n"
f"[System: Mobile client]\n\n"
)
def _notify_thinking_engine() -> None:
"""Record user activity so the thinking engine knows we're not idle."""
try:
from timmy.thinking import thinking_engine
thinking_engine.record_user_input()
except Exception:
logger.debug("Failed to record user input for thinking engine")
async def _process_chat(user_msg: str) -> dict | JSONResponse:
"""Send *user_msg* to the agent, log the exchange, and return a response."""
_notify_thinking_engine()
timestamp = datetime.now().strftime("%H:%M:%S")
try:
response_text = await agent_chat(
_build_context_prefix() + user_msg,
session_id="mobile",
)
message_log.append(role="user", content=user_msg, timestamp=timestamp, source="api")
message_log.append(role="agent", content=response_text, timestamp=timestamp, source="api")
return {"reply": response_text, "timestamp": timestamp}
except Exception as exc:
error_msg = f"Agent is offline: {exc}"
logger.error("api_chat error: %s", exc)
message_log.append(role="user", content=user_msg, timestamp=timestamp, source="api")
message_log.append(role="error", content=error_msg, timestamp=timestamp, source="api")
return JSONResponse(
status_code=503,
content={"error": error_msg, "timestamp": timestamp},
)
# ── POST /api/chat ────────────────────────────────────────────────────────────
@@ -44,70 +131,15 @@ async def api_chat(request: Request):
Response:
{"reply": "...", "timestamp": "HH:MM:SS"}
"""
# Enforce request body size limit
content_length = request.headers.get("content-length")
if content_length and int(content_length) > settings.chat_api_max_body_bytes:
return JSONResponse(status_code=413, content={"error": "Request body too large"})
body, err = await _parse_chat_body(request)
if err:
return err
try:
body = await request.json()
except Exception as exc:
logger.warning("Chat API JSON parse error: %s", exc)
return JSONResponse(status_code=400, content={"error": "Invalid JSON"})
messages = body.get("messages")
if not messages or not isinstance(messages, list):
return JSONResponse(status_code=400, content={"error": "messages array is required"})
# Extract the latest user message text
last_user_msg = None
for msg in reversed(messages):
if msg.get("role") == "user":
content = msg.get("content", "")
# Handle multimodal content arrays — extract text parts
if isinstance(content, list):
text_parts = [
p.get("text", "")
for p in content
if isinstance(p, dict) and p.get("type") == "text"
]
last_user_msg = " ".join(text_parts).strip()
else:
last_user_msg = str(content).strip()
break
if not last_user_msg:
user_msg = _extract_user_message(body["messages"])
if not user_msg:
return JSONResponse(status_code=400, content={"error": "No user message found"})
timestamp = datetime.now().strftime("%H:%M:%S")
try:
# Inject context (same pattern as the HTMX chat handler in agents.py)
now = datetime.now()
context_prefix = (
f"[System: Current date/time is "
f"{now.strftime('%A, %B %d, %Y at %I:%M %p')}]\n"
f"[System: Mobile client]\n\n"
)
response_text = await agent_chat(
context_prefix + last_user_msg,
session_id="mobile",
)
message_log.append(role="user", content=last_user_msg, timestamp=timestamp, source="api")
message_log.append(role="agent", content=response_text, timestamp=timestamp, source="api")
return {"reply": response_text, "timestamp": timestamp}
except Exception as exc:
error_msg = f"Agent is offline: {exc}"
logger.error("api_chat error: %s", exc)
message_log.append(role="user", content=last_user_msg, timestamp=timestamp, source="api")
message_log.append(role="error", content=error_msg, timestamp=timestamp, source="api")
return JSONResponse(
status_code=503,
content={"error": error_msg, "timestamp": timestamp},
)
return await _process_chat(user_msg)
# ── POST /api/upload ──────────────────────────────────────────────────────────

View File

@@ -0,0 +1,198 @@
"""Version 1 (v1) JSON REST API for the Timmy Time iPad app.
This module implements the specific endpoints required by the native
iPad app as defined in the project specification.
Endpoints:
POST /api/v1/chat — Streaming SSE chat response
GET /api/v1/chat/history — Retrieve chat history with limit
POST /api/v1/upload — Multipart file upload with auto-detection
GET /api/v1/status — Detailed system and model status
"""
import json
import logging
import os
import uuid
from datetime import UTC, datetime
from pathlib import Path
from fastapi import APIRouter, File, HTTPException, Query, Request, UploadFile
from fastapi.responses import JSONResponse, StreamingResponse
from config import APP_START_TIME, settings
from dashboard.routes.health import _check_ollama
from dashboard.store import message_log
from timmy.session import _get_agent
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/v1", tags=["chat-api-v1"])
_UPLOAD_DIR = str(Path(settings.repo_root) / "data" / "chat-uploads")
_MAX_UPLOAD_SIZE = 50 * 1024 * 1024 # 50 MB
# ── POST /api/v1/chat ─────────────────────────────────────────────────────────
@router.post("/chat")
async def api_v1_chat(request: Request):
"""Accept a JSON chat payload and return a streaming SSE response.
Request body:
{
"message": "string",
"session_id": "string",
"attachments": ["id1", "id2"]
}
Response:
text/event-stream (SSE)
"""
try:
body = await request.json()
except Exception as exc:
logger.warning("Chat v1 API JSON parse error: %s", exc)
return JSONResponse(status_code=400, content={"error": "Invalid JSON"})
message = body.get("message")
session_id = body.get("session_id", "ipad-app")
attachments = body.get("attachments", [])
if not message:
return JSONResponse(status_code=400, content={"error": "message is required"})
# Prepare context for the agent
context_prefix = (
f"[System: Current date/time is "
f"{datetime.now().strftime('%A, %B %d, %Y at %I:%M %p')}]\n"
f"[System: iPad App client]\n"
)
if attachments:
context_prefix += f"[System: Attachments: {', '.join(attachments)}]\n"
context_prefix += "\n"
full_prompt = context_prefix + message
async def event_generator():
try:
agent = _get_agent()
# Using streaming mode for SSE
async for chunk in agent.arun(full_prompt, stream=True, session_id=session_id):
# Agno chunks can be strings or RunOutput
content = chunk.content if hasattr(chunk, "content") else str(chunk)
if content:
yield f"data: {json.dumps({'text': content})}\n\n"
yield "data: [DONE]\n\n"
except Exception as exc:
logger.error("SSE stream error: %s", exc)
yield f"data: {json.dumps({'error': str(exc)})}\n\n"
return StreamingResponse(event_generator(), media_type="text/event-stream")
# ── GET /api/v1/chat/history ──────────────────────────────────────────────────
@router.get("/chat/history")
async def api_v1_chat_history(
session_id: str = Query("ipad-app"), limit: int = Query(50, ge=1, le=100)
):
"""Return recent chat history for a specific session."""
# Filter and limit the message log
# Note: message_log.all() returns all messages; we filter by source or just return last N
all_msgs = message_log.all()
# In a real implementation, we'd filter by session_id if message_log supported it.
# For now, we return the last 'limit' messages.
history = [
{
"role": msg.role,
"content": msg.content,
"timestamp": msg.timestamp,
"source": msg.source,
}
for msg in all_msgs[-limit:]
]
return {"messages": history}
# ── POST /api/v1/upload ───────────────────────────────────────────────────────
@router.post("/upload")
async def api_v1_upload(file: UploadFile = File(...)):
"""Accept a file upload, auto-detect type, and return metadata.
Response:
{
"id": "string",
"type": "image|audio|document|url",
"summary": "string",
"metadata": {...}
}
"""
os.makedirs(_UPLOAD_DIR, exist_ok=True)
file_id = uuid.uuid4().hex[:12]
safe_name = os.path.basename(file.filename or "upload")
stored_name = f"{file_id}-{safe_name}"
file_path = os.path.join(_UPLOAD_DIR, stored_name)
# Verify resolved path stays within upload directory
resolved = Path(file_path).resolve()
upload_root = Path(_UPLOAD_DIR).resolve()
if not str(resolved).startswith(str(upload_root)):
raise HTTPException(status_code=400, detail="Invalid file name")
contents = await file.read()
if len(contents) > _MAX_UPLOAD_SIZE:
raise HTTPException(status_code=413, detail="File too large (max 50 MB)")
with open(file_path, "wb") as f:
f.write(contents)
# Auto-detect type based on extension/mime
mime_type = file.content_type or "application/octet-stream"
ext = os.path.splitext(safe_name)[1].lower()
media_type = "document"
if mime_type.startswith("image/") or ext in [".jpg", ".jpeg", ".png", ".heic"]:
media_type = "image"
elif mime_type.startswith("audio/") or ext in [".m4a", ".mp3", ".wav", ".caf"]:
media_type = "audio"
elif ext in [".pdf", ".txt", ".md"]:
media_type = "document"
# Placeholder for actual processing (OCR, Whisper, etc.)
summary = f"Uploaded {media_type}: {safe_name}"
return {
"id": file_id,
"type": media_type,
"summary": summary,
"url": f"/uploads/{stored_name}",
"metadata": {"fileName": safe_name, "mimeType": mime_type, "size": len(contents)},
}
# ── GET /api/v1/status ────────────────────────────────────────────────────────
@router.get("/status")
async def api_v1_status():
"""Detailed system and model status."""
ollama_status = await _check_ollama()
uptime = (datetime.now(UTC) - APP_START_TIME).total_seconds()
return {
"timmy": "online" if ollama_status.status == "healthy" else "offline",
"model": settings.ollama_model,
"ollama": "running" if ollama_status.status == "healthy" else "stopped",
"uptime": f"{int(uptime // 3600)}h {int((uptime % 3600) // 60)}m",
"version": "2.0.0-v1-api",
}

View File

@@ -65,7 +65,7 @@ def _check_ollama_sync() -> DependencyStatus:
try:
import urllib.request
url = settings.ollama_url.replace("localhost", "127.0.0.1")
url = settings.normalized_ollama_url
req = urllib.request.Request(
f"{url}/api/tags",
method="GET",

View File

@@ -166,7 +166,7 @@ async def api_briefing_status():
if cached:
last_generated = cached.generated_at.isoformat()
except Exception:
pass
logger.debug("Failed to read briefing cache")
return JSONResponse(
{
@@ -190,6 +190,7 @@ async def api_memory_status():
stats = get_memory_stats()
indexed_files = stats.get("total_entries", 0)
except Exception:
logger.debug("Failed to get memory stats")
indexed_files = 0
return JSONResponse(
@@ -215,7 +216,7 @@ async def api_swarm_status():
).fetchone()
pending_tasks = row["cnt"] if row else 0
except Exception:
pass
logger.debug("Failed to count pending tasks")
return JSONResponse(
{

View File

@@ -0,0 +1,385 @@
"""Workshop world state API and WebSocket relay.
Serves Timmy's current presence state to the Workshop 3D renderer.
The primary consumer is the browser on first load — before any
WebSocket events arrive, the client needs a full state snapshot.
The ``/ws/world`` endpoint streams ``timmy_state`` messages whenever
the heartbeat detects a state change. It also accepts ``visitor_message``
frames from the 3D client and responds with ``timmy_speech`` barks.
Source of truth: ``~/.timmy/presence.json`` written by
:class:`~timmy.workshop_state.WorkshopHeartbeat`.
Falls back to a live ``get_state_dict()`` call if the file is stale
or missing.
"""
import asyncio
import json
import logging
import re
import time
from collections import deque
from datetime import UTC, datetime
from fastapi import APIRouter, WebSocket
from fastapi.responses import JSONResponse
from timmy.workshop_state import PRESENCE_FILE
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/world", tags=["world"])
# ---------------------------------------------------------------------------
# WebSocket relay for live state changes
# ---------------------------------------------------------------------------
_ws_clients: list[WebSocket] = []
_STALE_THRESHOLD = 90 # seconds — file older than this triggers live rebuild
# Recent conversation buffer — kept in memory for the Workshop overlay.
# Stores the last _MAX_EXCHANGES (visitor_text, timmy_text) pairs.
_MAX_EXCHANGES = 3
_conversation: deque[dict] = deque(maxlen=_MAX_EXCHANGES)
_WORKSHOP_SESSION_ID = "workshop"
_HEARTBEAT_INTERVAL = 15 # seconds — ping to detect dead iPad/Safari connections
# ---------------------------------------------------------------------------
# Conversation grounding — commitment tracking (rescued from PR #408)
# ---------------------------------------------------------------------------
# Patterns that indicate Timmy is committing to an action.
_COMMITMENT_PATTERNS: list[re.Pattern[str]] = [
re.compile(r"I'll (.+?)(?:\.|!|\?|$)", re.IGNORECASE),
re.compile(r"I will (.+?)(?:\.|!|\?|$)", re.IGNORECASE),
re.compile(r"[Ll]et me (.+?)(?:\.|!|\?|$)", re.IGNORECASE),
]
# After this many messages without follow-up, surface open commitments.
_REMIND_AFTER = 5
_MAX_COMMITMENTS = 10
# In-memory list of open commitments.
# Each entry: {"text": str, "created_at": float, "messages_since": int}
_commitments: list[dict] = []
def _extract_commitments(text: str) -> list[str]:
"""Pull commitment phrases from Timmy's reply text."""
found: list[str] = []
for pattern in _COMMITMENT_PATTERNS:
for match in pattern.finditer(text):
phrase = match.group(1).strip()
if len(phrase) > 5: # skip trivially short matches
found.append(phrase[:120])
return found
def _record_commitments(reply: str) -> None:
"""Scan a Timmy reply for commitments and store them."""
for phrase in _extract_commitments(reply):
# Avoid near-duplicate commitments
if any(c["text"] == phrase for c in _commitments):
continue
_commitments.append({"text": phrase, "created_at": time.time(), "messages_since": 0})
if len(_commitments) > _MAX_COMMITMENTS:
_commitments.pop(0)
def _tick_commitments() -> None:
"""Increment messages_since for every open commitment."""
for c in _commitments:
c["messages_since"] += 1
def _build_commitment_context() -> str:
"""Return a grounding note if any commitments are overdue for follow-up."""
overdue = [c for c in _commitments if c["messages_since"] >= _REMIND_AFTER]
if not overdue:
return ""
lines = [f"- {c['text']}" for c in overdue]
return (
"[Open commitments Timmy made earlier — "
"weave awareness naturally, don't list robotically]\n" + "\n".join(lines)
)
def close_commitment(index: int) -> bool:
"""Remove a commitment by index. Returns True if removed."""
if 0 <= index < len(_commitments):
_commitments.pop(index)
return True
return False
def get_commitments() -> list[dict]:
"""Return a copy of open commitments (for testing / API)."""
return list(_commitments)
def reset_commitments() -> None:
"""Clear all commitments (for testing / session reset)."""
_commitments.clear()
# Conversation grounding — anchor to opening topic so Timmy doesn't drift.
_ground_topic: str | None = None
_ground_set_at: float = 0.0
_GROUND_TTL = 300 # seconds of inactivity before the anchor expires
def _read_presence_file() -> dict | None:
"""Read presence.json if it exists and is fresh enough."""
try:
if not PRESENCE_FILE.exists():
return None
age = time.time() - PRESENCE_FILE.stat().st_mtime
if age > _STALE_THRESHOLD:
logger.debug("presence.json is stale (%.0fs old)", age)
return None
return json.loads(PRESENCE_FILE.read_text())
except (OSError, json.JSONDecodeError) as exc:
logger.warning("Failed to read presence.json: %s", exc)
return None
def _build_world_state(presence: dict) -> dict:
"""Transform presence dict into the world/state API response."""
return {
"timmyState": {
"mood": presence.get("mood", "calm"),
"activity": presence.get("current_focus", "idle"),
"energy": presence.get("energy", 0.5),
"confidence": presence.get("confidence", 0.7),
},
"familiar": presence.get("familiar"),
"activeThreads": presence.get("active_threads", []),
"recentEvents": presence.get("recent_events", []),
"concerns": presence.get("concerns", []),
"visitorPresent": False,
"updatedAt": presence.get("liveness", datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ")),
"version": presence.get("version", 1),
}
def _get_current_state() -> dict:
"""Build the current world-state dict from best available source."""
presence = _read_presence_file()
if presence is None:
try:
from timmy.workshop_state import get_state_dict
presence = get_state_dict()
except Exception as exc:
logger.warning("Live state build failed: %s", exc)
presence = {
"version": 1,
"liveness": datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ"),
"mood": "calm",
"current_focus": "",
"active_threads": [],
"recent_events": [],
"concerns": [],
}
return _build_world_state(presence)
@router.get("/state")
async def get_world_state() -> JSONResponse:
"""Return Timmy's current world state for Workshop bootstrap.
Reads from ``~/.timmy/presence.json`` if fresh, otherwise
rebuilds live from cognitive state.
"""
return JSONResponse(
content=_get_current_state(),
headers={"Cache-Control": "no-cache, no-store"},
)
# ---------------------------------------------------------------------------
# WebSocket endpoint — streams timmy_state changes to Workshop clients
# ---------------------------------------------------------------------------
async def _heartbeat(websocket: WebSocket) -> None:
"""Send periodic pings to detect dead connections (iPad resilience).
Safari suspends background tabs, killing the TCP socket silently.
A 15-second ping ensures we notice within one interval.
Rescued from stale PR #399.
"""
try:
while True:
await asyncio.sleep(_HEARTBEAT_INTERVAL)
await websocket.send_text(json.dumps({"type": "ping"}))
except Exception:
logger.debug("Heartbeat stopped — connection gone")
@router.websocket("/ws")
async def world_ws(websocket: WebSocket) -> None:
"""Accept a Workshop client and keep it alive for state broadcasts.
Sends a full ``world_state`` snapshot immediately on connect so the
client never starts from a blank slate. Incoming frames are parsed
as JSON — ``visitor_message`` triggers a bark response. A background
heartbeat ping runs every 15 s to detect dead connections early.
"""
await websocket.accept()
_ws_clients.append(websocket)
logger.info("World WS connected — %d clients", len(_ws_clients))
# Send full world-state snapshot so client bootstraps instantly
try:
snapshot = _get_current_state()
await websocket.send_text(json.dumps({"type": "world_state", **snapshot}))
except Exception as exc:
logger.warning("Failed to send WS snapshot: %s", exc)
ping_task = asyncio.create_task(_heartbeat(websocket))
try:
while True:
raw = await websocket.receive_text()
await _handle_client_message(raw)
except Exception:
logger.debug("WebSocket receive loop ended")
finally:
ping_task.cancel()
if websocket in _ws_clients:
_ws_clients.remove(websocket)
logger.info("World WS disconnected — %d clients", len(_ws_clients))
async def _broadcast(message: str) -> None:
"""Send *message* to every connected Workshop client, pruning dead ones."""
dead: list[WebSocket] = []
for ws in _ws_clients:
try:
await ws.send_text(message)
except Exception:
logger.debug("Pruning dead WebSocket client")
dead.append(ws)
for ws in dead:
if ws in _ws_clients:
_ws_clients.remove(ws)
async def broadcast_world_state(presence: dict) -> None:
"""Broadcast a ``timmy_state`` message to all connected Workshop clients.
Called by :class:`~timmy.workshop_state.WorkshopHeartbeat` via its
``on_change`` callback.
"""
state = _build_world_state(presence)
await _broadcast(json.dumps({"type": "timmy_state", **state["timmyState"]}))
# ---------------------------------------------------------------------------
# Visitor chat — bark engine
# ---------------------------------------------------------------------------
async def _handle_client_message(raw: str) -> None:
"""Dispatch an incoming WebSocket frame from the Workshop client."""
try:
data = json.loads(raw)
except (json.JSONDecodeError, TypeError):
return # ignore non-JSON keep-alive pings
if data.get("type") == "visitor_message":
text = (data.get("text") or "").strip()
if text:
task = asyncio.create_task(_bark_and_broadcast(text))
task.add_done_callback(_log_bark_failure)
def _log_bark_failure(task: asyncio.Task) -> None:
"""Log unhandled exceptions from fire-and-forget bark tasks."""
if task.cancelled():
return
exc = task.exception()
if exc is not None:
logger.error("Bark task failed: %s", exc)
def reset_conversation_ground() -> None:
"""Clear the conversation grounding anchor (e.g. after inactivity)."""
global _ground_topic, _ground_set_at
_ground_topic = None
_ground_set_at = 0.0
def _refresh_ground(visitor_text: str) -> None:
"""Set or refresh the conversation grounding anchor.
The first visitor message in a session (or after the TTL expires)
becomes the anchor topic. Subsequent messages are grounded against it.
"""
global _ground_topic, _ground_set_at
now = time.time()
if _ground_topic is None or (now - _ground_set_at) > _GROUND_TTL:
_ground_topic = visitor_text[:120]
logger.debug("Ground topic set: %s", _ground_topic)
_ground_set_at = now
async def _bark_and_broadcast(visitor_text: str) -> None:
"""Generate a bark response and broadcast it to all Workshop clients."""
await _broadcast(json.dumps({"type": "timmy_thinking"}))
# Notify Pip that a visitor spoke
try:
from timmy.familiar import pip_familiar
pip_familiar.on_event("visitor_spoke")
except Exception:
logger.debug("Pip familiar notification failed (optional)")
_refresh_ground(visitor_text)
_tick_commitments()
reply = await _generate_bark(visitor_text)
_record_commitments(reply)
_conversation.append({"visitor": visitor_text, "timmy": reply})
await _broadcast(
json.dumps(
{
"type": "timmy_speech",
"text": reply,
"recentExchanges": list(_conversation),
}
)
)
async def _generate_bark(visitor_text: str) -> str:
"""Generate a short in-character bark response.
Uses the existing Timmy session with a dedicated workshop session ID.
When a grounding anchor exists, the opening topic is prepended so the
model stays on-topic across long sessions.
Gracefully degrades to a canned response if inference fails.
"""
try:
from timmy import session as _session
grounded = visitor_text
commitment_ctx = _build_commitment_context()
if commitment_ctx:
grounded = f"{commitment_ctx}\n{grounded}"
if _ground_topic and visitor_text != _ground_topic:
grounded = f"[Workshop conversation topic: {_ground_topic}]\n{grounded}"
response = await _session.chat(grounded, session_id=_WORKSHOP_SESSION_ID)
return response
except Exception as exc:
logger.warning("Bark generation failed: %s", exc)
return "Hmm, my thoughts are a bit tangled right now."

View File

@@ -100,36 +100,14 @@ def _get_git_context() -> dict:
return {"branch": "unknown", "commit": "unknown"}
def capture_error(
exc: Exception,
source: str = "unknown",
context: dict | None = None,
) -> str | None:
"""Capture an error and optionally create a bug report.
Args:
exc: The exception to capture
source: Module/component where the error occurred
context: Optional dict of extra context (request path, etc.)
def _extract_traceback_info(exc: Exception) -> tuple[str, str, int]:
"""Extract formatted traceback, affected file, and line number.
Returns:
Task ID of the created bug report, or None if deduplicated/disabled
Tuple of (traceback_string, affected_file, affected_line).
"""
from config import settings
if not settings.error_feedback_enabled:
return None
error_hash = _stack_hash(exc)
if _is_duplicate(error_hash):
logger.debug("Duplicate error suppressed: %s (hash=%s)", exc, error_hash)
return None
# Format the stack trace
tb_str = "".join(traceback.format_exception(type(exc), exc, exc.__traceback__))
# Extract file/line from traceback
tb_obj = exc.__traceback__
affected_file = "unknown"
affected_line = 0
@@ -139,9 +117,18 @@ def capture_error(
affected_file = tb_obj.tb_frame.f_code.co_filename
affected_line = tb_obj.tb_lineno
git_ctx = _get_git_context()
return tb_str, affected_file, affected_line
# 1. Log to event_log
def _log_error_event(
exc: Exception,
source: str,
error_hash: str,
affected_file: str,
affected_line: int,
git_ctx: dict,
) -> None:
"""Log the captured error to the event log."""
try:
from swarm.event_log import EventType, log_event
@@ -161,8 +148,18 @@ def capture_error(
except Exception as log_exc:
logger.debug("Failed to log error event: %s", log_exc)
# 2. Create bug report task
task_id = None
def _create_bug_report(
exc: Exception,
source: str,
context: dict | None,
error_hash: str,
tb_str: str,
affected_file: str,
affected_line: int,
git_ctx: dict,
) -> str | None:
"""Create a bug report task and return the task ID (or None on failure)."""
try:
from swarm.task_queue.models import create_task
@@ -195,7 +192,6 @@ def capture_error(
)
task_id = task.id
# Log the creation event
try:
from swarm.event_log import EventType, log_event
@@ -210,12 +206,16 @@ def capture_error(
)
except Exception as exc:
logger.warning("Bug report screenshot error: %s", exc)
pass
return task_id
except Exception as task_exc:
logger.debug("Failed to create bug report task: %s", task_exc)
return None
# 3. Send notification
def _notify_bug_report(exc: Exception, source: str) -> None:
"""Send a push notification about the captured error."""
try:
from infrastructure.notifications.push import notifier
@@ -224,11 +224,12 @@ def capture_error(
message=f"{type(exc).__name__} in {source}: {str(exc)[:80]}",
category="system",
)
except Exception as exc:
logger.warning("Bug report notification error: %s", exc)
pass
except Exception as notify_exc:
logger.warning("Bug report notification error: %s", notify_exc)
# 4. Record in session logger (via registered callback)
def _record_to_session(exc: Exception, source: str) -> None:
"""Record the error via the registered session callback."""
if _error_recorder is not None:
try:
_error_recorder(
@@ -238,4 +239,50 @@ def capture_error(
except Exception as log_exc:
logger.warning("Bug report session logging error: %s", log_exc)
def capture_error(
exc: Exception,
source: str = "unknown",
context: dict | None = None,
) -> str | None:
"""Capture an error and optionally create a bug report.
Args:
exc: The exception to capture
source: Module/component where the error occurred
context: Optional dict of extra context (request path, etc.)
Returns:
Task ID of the created bug report, or None if deduplicated/disabled
"""
from config import settings
if not settings.error_feedback_enabled:
return None
error_hash = _stack_hash(exc)
if _is_duplicate(error_hash):
logger.debug("Duplicate error suppressed: %s (hash=%s)", exc, error_hash)
return None
tb_str, affected_file, affected_line = _extract_traceback_info(exc)
git_ctx = _get_git_context()
_log_error_event(exc, source, error_hash, affected_file, affected_line, git_ctx)
task_id = _create_bug_report(
exc,
source,
context,
error_hash,
tb_str,
affected_file,
affected_line,
git_ctx,
)
_notify_bug_report(exc, source)
_record_to_session(exc, source)
return task_id

View File

@@ -144,6 +144,65 @@ class ShellHand:
return None
@staticmethod
def _build_run_env(env: dict | None) -> dict:
"""Merge *env* overrides into a copy of the current environment."""
import os
run_env = os.environ.copy()
if env:
run_env.update(env)
return run_env
async def _execute_subprocess(
self,
command: str,
effective_timeout: int,
cwd: str | None,
run_env: dict,
start: float,
) -> ShellResult:
"""Run *command* as a subprocess with timeout enforcement."""
proc = await asyncio.create_subprocess_shell(
command,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=cwd,
env=run_env,
)
try:
stdout_bytes, stderr_bytes = await asyncio.wait_for(
proc.communicate(), timeout=effective_timeout
)
except TimeoutError:
proc.kill()
await proc.wait()
latency = (time.time() - start) * 1000
logger.warning("Shell command timed out after %ds: %s", effective_timeout, command)
return ShellResult(
command=command,
success=False,
exit_code=-1,
error=f"Command timed out after {effective_timeout}s",
latency_ms=latency,
timed_out=True,
)
latency = (time.time() - start) * 1000
exit_code = proc.returncode if proc.returncode is not None else -1
stdout = stdout_bytes.decode("utf-8", errors="replace").strip()
stderr = stderr_bytes.decode("utf-8", errors="replace").strip()
return ShellResult(
command=command,
success=exit_code == 0,
exit_code=exit_code,
stdout=stdout,
stderr=stderr,
latency_ms=latency,
)
async def run(
self,
command: str,
@@ -164,7 +223,6 @@ class ShellHand:
"""
start = time.time()
# Validate
validation_error = self._validate_command(command)
if validation_error:
return ShellResult(
@@ -178,52 +236,8 @@ class ShellHand:
cwd = working_dir or self._working_dir
try:
import os
run_env = os.environ.copy()
if env:
run_env.update(env)
proc = await asyncio.create_subprocess_shell(
command,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=cwd,
env=run_env,
)
try:
stdout_bytes, stderr_bytes = await asyncio.wait_for(
proc.communicate(), timeout=effective_timeout
)
except TimeoutError:
proc.kill()
await proc.wait()
latency = (time.time() - start) * 1000
logger.warning("Shell command timed out after %ds: %s", effective_timeout, command)
return ShellResult(
command=command,
success=False,
exit_code=-1,
error=f"Command timed out after {effective_timeout}s",
latency_ms=latency,
timed_out=True,
)
latency = (time.time() - start) * 1000
exit_code = proc.returncode if proc.returncode is not None else -1
stdout = stdout_bytes.decode("utf-8", errors="replace").strip()
stderr = stderr_bytes.decode("utf-8", errors="replace").strip()
return ShellResult(
command=command,
success=exit_code == 0,
exit_code=exit_code,
stdout=stdout,
stderr=stderr,
latency_ms=latency,
)
run_env = self._build_run_env(env)
return await self._execute_subprocess(command, effective_timeout, cwd, run_env, start)
except Exception as exc:
latency = (time.time() - start) * 1000
logger.warning("Shell command failed: %s%s", command, exc)

View File

@@ -13,7 +13,7 @@ import logging
from dataclasses import dataclass, field
from enum import Enum, auto
from config import settings
from config import normalize_ollama_url, settings
logger = logging.getLogger(__name__)
@@ -307,7 +307,7 @@ class MultiModalManager:
import json
import urllib.request
url = self.ollama_url.replace("localhost", "127.0.0.1")
url = normalize_ollama_url(self.ollama_url)
req = urllib.request.Request(
f"{url}/api/tags",
method="GET",
@@ -462,7 +462,7 @@ class MultiModalManager:
logger.info("Pulling model: %s", model_name)
url = self.ollama_url.replace("localhost", "127.0.0.1")
url = normalize_ollama_url(self.ollama_url)
req = urllib.request.Request(
f"{url}/api/pull",
method="POST",

View File

@@ -183,6 +183,22 @@ async def run_health_check(
}
@router.post("/reload")
async def reload_config(
cascade: Annotated[CascadeRouter, Depends(get_cascade_router)],
) -> dict[str, Any]:
"""Hot-reload providers.yaml without restart.
Preserves circuit breaker state and metrics for existing providers.
"""
try:
result = cascade.reload_config()
return {"status": "ok", **result}
except Exception as exc:
logger.error("Config reload failed: %s", exc)
raise HTTPException(status_code=500, detail=f"Reload failed: {exc}") from exc
@router.get("/config")
async def get_config(
cascade: Annotated[CascadeRouter, Depends(get_cascade_router)],

View File

@@ -18,6 +18,8 @@ from enum import Enum
from pathlib import Path
from typing import Any
from config import settings
try:
import yaml
except ImportError:
@@ -100,7 +102,7 @@ class Provider:
"""LLM provider configuration and state."""
name: str
type: str # ollama, openai, anthropic, airllm
type: str # ollama, openai, anthropic
enabled: bool
priority: int
url: str | None = None
@@ -301,22 +303,13 @@ class CascadeRouter:
# Can't check without requests, assume available
return True
try:
url = provider.url or "http://localhost:11434"
url = provider.url or settings.ollama_url
response = requests.get(f"{url}/api/tags", timeout=5)
return response.status_code == 200
except Exception as exc:
logger.debug("Ollama provider check error: %s", exc)
return False
elif provider.type == "airllm":
# Check if airllm is installed
try:
import importlib.util
return importlib.util.find_spec("airllm") is not None
except (ImportError, ModuleNotFoundError):
return False
elif provider.type in ("openai", "anthropic", "grok"):
# Check if API key is set
return provider.api_key is not None and provider.api_key != ""
@@ -395,6 +388,101 @@ class CascadeRouter:
return None
def _select_model(
self, provider: Provider, model: str | None, content_type: ContentType
) -> tuple[str | None, bool]:
"""Select the best model for the request, with vision fallback.
Returns:
Tuple of (selected_model, is_fallback_model).
"""
selected_model = model or provider.get_default_model()
is_fallback = False
if content_type != ContentType.TEXT and selected_model:
if provider.type == "ollama" and self._mm_manager:
from infrastructure.models.multimodal import ModelCapability
if content_type == ContentType.VISION:
supports = self._mm_manager.model_supports(
selected_model, ModelCapability.VISION
)
if not supports:
fallback = self._get_fallback_model(provider, selected_model, content_type)
if fallback:
logger.info(
"Model %s doesn't support vision, falling back to %s",
selected_model,
fallback,
)
selected_model = fallback
is_fallback = True
else:
logger.warning(
"No vision-capable model found on %s, trying anyway",
provider.name,
)
return selected_model, is_fallback
async def _attempt_with_retry(
self,
provider: Provider,
messages: list[dict],
model: str | None,
temperature: float,
max_tokens: int | None,
content_type: ContentType,
) -> dict:
"""Try a provider with retries, returning the result dict.
Raises:
RuntimeError: If all retry attempts fail.
Returns error strings collected during retries via the exception message.
"""
errors: list[str] = []
for attempt in range(self.config.max_retries_per_provider):
try:
return await self._try_provider(
provider=provider,
messages=messages,
model=model,
temperature=temperature,
max_tokens=max_tokens,
content_type=content_type,
)
except Exception as exc:
error_msg = str(exc)
logger.warning(
"Provider %s attempt %d failed: %s",
provider.name,
attempt + 1,
error_msg,
)
errors.append(f"{provider.name}: {error_msg}")
if attempt < self.config.max_retries_per_provider - 1:
await asyncio.sleep(self.config.retry_delay_seconds)
raise RuntimeError("; ".join(errors))
def _is_provider_available(self, provider: Provider) -> bool:
"""Check if a provider should be tried (enabled + circuit breaker)."""
if not provider.enabled:
logger.debug("Skipping %s (disabled)", provider.name)
return False
if provider.status == ProviderStatus.UNHEALTHY:
if self._can_close_circuit(provider):
provider.circuit_state = CircuitState.HALF_OPEN
provider.half_open_calls = 0
logger.info("Circuit breaker half-open for %s", provider.name)
else:
logger.debug("Skipping %s (circuit open)", provider.name)
return False
return True
async def complete(
self,
messages: list[dict],
@@ -421,7 +509,6 @@ class CascadeRouter:
Raises:
RuntimeError: If all providers fail
"""
# Detect content type for multi-modal routing
content_type = self._detect_content_type(messages)
if content_type != ContentType.TEXT:
logger.debug("Detected %s content, selecting appropriate model", content_type.value)
@@ -429,93 +516,34 @@ class CascadeRouter:
errors = []
for provider in self.providers:
# Skip disabled providers
if not provider.enabled:
logger.debug("Skipping %s (disabled)", provider.name)
if not self._is_provider_available(provider):
continue
# Skip unhealthy providers (circuit breaker)
if provider.status == ProviderStatus.UNHEALTHY:
# Check if circuit breaker can close
if self._can_close_circuit(provider):
provider.circuit_state = CircuitState.HALF_OPEN
provider.half_open_calls = 0
logger.info("Circuit breaker half-open for %s", provider.name)
else:
logger.debug("Skipping %s (circuit open)", provider.name)
continue
selected_model, is_fallback_model = self._select_model(provider, model, content_type)
# Determine which model to use
selected_model = model or provider.get_default_model()
is_fallback_model = False
try:
result = await self._attempt_with_retry(
provider,
messages,
selected_model,
temperature,
max_tokens,
content_type,
)
except RuntimeError as exc:
errors.append(str(exc))
self._record_failure(provider)
continue
# For non-text content, check if model supports it
if content_type != ContentType.TEXT and selected_model:
if provider.type == "ollama" and self._mm_manager:
from infrastructure.models.multimodal import ModelCapability
self._record_success(provider, result.get("latency_ms", 0))
return {
"content": result["content"],
"provider": provider.name,
"model": result.get("model", selected_model or provider.get_default_model()),
"latency_ms": result.get("latency_ms", 0),
"is_fallback_model": is_fallback_model,
}
# Check if selected model supports the required capability
if content_type == ContentType.VISION:
supports = self._mm_manager.model_supports(
selected_model, ModelCapability.VISION
)
if not supports:
# Find fallback model
fallback = self._get_fallback_model(
provider, selected_model, content_type
)
if fallback:
logger.info(
"Model %s doesn't support vision, falling back to %s",
selected_model,
fallback,
)
selected_model = fallback
is_fallback_model = True
else:
logger.warning(
"No vision-capable model found on %s, trying anyway",
provider.name,
)
# Try this provider
for attempt in range(self.config.max_retries_per_provider):
try:
result = await self._try_provider(
provider=provider,
messages=messages,
model=selected_model,
temperature=temperature,
max_tokens=max_tokens,
content_type=content_type,
)
# Success! Update metrics and return
self._record_success(provider, result.get("latency_ms", 0))
return {
"content": result["content"],
"provider": provider.name,
"model": result.get(
"model", selected_model or provider.get_default_model()
),
"latency_ms": result.get("latency_ms", 0),
"is_fallback_model": is_fallback_model,
}
except Exception as exc:
error_msg = str(exc)
logger.warning(
"Provider %s attempt %d failed: %s", provider.name, attempt + 1, error_msg
)
errors.append(f"{provider.name}: {error_msg}")
if attempt < self.config.max_retries_per_provider - 1:
await asyncio.sleep(self.config.retry_delay_seconds)
# All retries failed for this provider
self._record_failure(provider)
# All providers failed
raise RuntimeError(f"All providers failed: {'; '.join(errors)}")
async def _try_provider(
@@ -581,7 +609,7 @@ class CascadeRouter:
"""Call Ollama API with multi-modal support."""
import aiohttp
url = f"{provider.url}/api/chat"
url = f"{provider.url or settings.ollama_url}/api/chat"
# Transform messages for Ollama format (including images)
transformed_messages = self._transform_messages_for_ollama(messages)
@@ -815,6 +843,66 @@ class CascadeRouter:
provider.status = ProviderStatus.HEALTHY
logger.info("Circuit breaker CLOSED for %s", provider.name)
def reload_config(self) -> dict:
"""Hot-reload providers.yaml, preserving runtime state.
Re-reads the config file, rebuilds the provider list, and
preserves circuit breaker state and metrics for providers
that still exist after reload.
Returns:
Summary dict with added/removed/preserved counts.
"""
# Snapshot current runtime state keyed by provider name
old_state: dict[
str, tuple[ProviderMetrics, CircuitState, float | None, int, ProviderStatus]
] = {}
for p in self.providers:
old_state[p.name] = (
p.metrics,
p.circuit_state,
p.circuit_opened_at,
p.half_open_calls,
p.status,
)
old_names = set(old_state.keys())
# Reload from disk
self.providers = []
self._load_config()
# Restore preserved state
new_names = {p.name for p in self.providers}
preserved = 0
for p in self.providers:
if p.name in old_state:
metrics, circuit, opened_at, half_open, status = old_state[p.name]
p.metrics = metrics
p.circuit_state = circuit
p.circuit_opened_at = opened_at
p.half_open_calls = half_open
p.status = status
preserved += 1
added = new_names - old_names
removed = old_names - new_names
logger.info(
"Config reloaded: %d providers (%d preserved, %d added, %d removed)",
len(self.providers),
preserved,
len(added),
len(removed),
)
return {
"total_providers": len(self.providers),
"preserved": preserved,
"added": sorted(added),
"removed": sorted(removed),
}
def get_metrics(self) -> dict:
"""Get metrics for all providers."""
return {

View File

@@ -515,25 +515,36 @@ class DiscordVendor(ChatPlatform):
async def _handle_message(self, message) -> None:
"""Process an incoming message and respond via a thread."""
# Strip the bot mention from the message content
content = message.content
if self._client.user:
content = content.replace(f"<@{self._client.user.id}>", "").strip()
content = self._extract_content(message)
if not content:
return
# Create or reuse a thread for this conversation
thread = await self._get_or_create_thread(message)
target = thread or message.channel
session_id = f"discord_{thread.id}" if thread else f"discord_{message.channel.id}"
# Derive session_id for per-conversation history via Agno's SQLite
if thread:
session_id = f"discord_{thread.id}"
else:
session_id = f"discord_{message.channel.id}"
run_output, response = await self._invoke_agent(content, session_id, target)
# Run Timmy agent with typing indicator and timeout
if run_output is not None:
await self._handle_paused_run(run_output, target, session_id)
raw_content = run_output.content if hasattr(run_output, "content") else ""
response = _clean_response(raw_content or "")
await self._send_response(response, target)
def _extract_content(self, message) -> str:
"""Strip the bot mention and return clean message text."""
content = message.content
if self._client.user:
content = content.replace(f"<@{self._client.user.id}>", "").strip()
return content
async def _invoke_agent(self, content: str, session_id: str, target):
"""Run chat_with_tools with a typing indicator and timeout.
Returns a (run_output, error_response) tuple. On success the
error_response is ``None``; on failure run_output is ``None``.
"""
run_output = None
response = None
try:
@@ -547,54 +558,58 @@ class DiscordVendor(ChatPlatform):
response = "Sorry, that took too long. Please try a simpler request."
except Exception as exc:
logger.error("Discord: chat_with_tools() failed: %s", exc)
response = (
"I'm having trouble reaching my language model right now. Please try again shortly."
response = "I'm having trouble reaching my inference backend right now. Please try again shortly."
return run_output, response
async def _handle_paused_run(self, run_output, target, session_id: str) -> None:
"""If Agno paused the run for tool confirmation, enqueue approvals."""
status = getattr(run_output, "status", None)
is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
if not (is_paused and getattr(run_output, "active_requirements", None)):
return
from config import settings
if not settings.discord_confirm_actions:
return
for req in run_output.active_requirements:
if not getattr(req, "needs_confirmation", False):
continue
te = req.tool_execution
tool_name = getattr(te, "tool_name", "unknown")
tool_args = getattr(te, "tool_args", {}) or {}
from timmy.approvals import create_item
item = create_item(
title=f"Discord: {tool_name}",
description=_format_action_description(tool_name, tool_args),
proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
impact=_get_impact_level(tool_name),
)
self._pending_actions[item.id] = {
"run_output": run_output,
"requirement": req,
"tool_name": tool_name,
"tool_args": tool_args,
"target": target,
"session_id": session_id,
}
await self._send_confirmation(target, tool_name, tool_args, item.id)
# Check if Agno paused the run for tool confirmation
if run_output is not None:
status = getattr(run_output, "status", None)
is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
if is_paused and getattr(run_output, "active_requirements", None):
from config import settings
if settings.discord_confirm_actions:
for req in run_output.active_requirements:
if getattr(req, "needs_confirmation", False):
te = req.tool_execution
tool_name = getattr(te, "tool_name", "unknown")
tool_args = getattr(te, "tool_args", {}) or {}
from timmy.approvals import create_item
item = create_item(
title=f"Discord: {tool_name}",
description=_format_action_description(tool_name, tool_args),
proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
impact=_get_impact_level(tool_name),
)
self._pending_actions[item.id] = {
"run_output": run_output,
"requirement": req,
"tool_name": tool_name,
"tool_args": tool_args,
"target": target,
"session_id": session_id,
}
await self._send_confirmation(target, tool_name, tool_args, item.id)
raw_content = run_output.content if hasattr(run_output, "content") else ""
response = _clean_response(raw_content or "")
# Discord has a 2000 character limit — send with error handling
if response and response.strip():
for chunk in _chunk_message(response, 2000):
try:
await target.send(chunk)
except Exception as exc:
logger.error("Discord: failed to send message chunk: %s", exc)
break
@staticmethod
async def _send_response(response: str | None, target) -> None:
"""Send a response to Discord, chunked to the 2000-char limit."""
if not response or not response.strip():
return
for chunk in _chunk_message(response, 2000):
try:
await target.send(chunk)
except Exception as exc:
logger.error("Discord: failed to send message chunk: %s", exc)
break
async def _get_or_create_thread(self, message):
"""Get the active thread for a channel, or create one.

1
src/loop/__init__.py Normal file
View File

@@ -0,0 +1 @@
"""Three-phase agent loop: Gather → Reason → Act."""

37
src/loop/phase1_gather.py Normal file
View File

@@ -0,0 +1,37 @@
"""Phase 1 — Gather: accept raw input, produce structured context.
This is the sensory phase. It receives a raw ContextPayload and enriches
it with whatever context Timmy needs before reasoning. In the stub form,
it simply passes the payload through with a phase marker.
"""
from __future__ import annotations
import logging
from loop.schema import ContextPayload
logger = logging.getLogger(__name__)
def gather(payload: ContextPayload) -> ContextPayload:
"""Accept raw input and return structured context for reasoning.
Stub: tags the payload with phase=gather and logs transit.
Timmy will flesh this out with context selection, memory lookup,
adapter polling, and attention-residual weighting.
"""
logger.info(
"Phase 1 (Gather) received: source=%s content_len=%d tokens=%d",
payload.source,
len(payload.content),
payload.token_count,
)
result = payload.with_metadata(phase="gather", gathered=True)
logger.info(
"Phase 1 (Gather) produced: metadata_keys=%s",
sorted(result.metadata.keys()),
)
return result

36
src/loop/phase2_reason.py Normal file
View File

@@ -0,0 +1,36 @@
"""Phase 2 — Reason: accept gathered context, produce reasoning output.
This is the deliberation phase. It receives enriched context from Phase 1
and decides what to do. In the stub form, it passes the payload through
with a phase marker.
"""
from __future__ import annotations
import logging
from loop.schema import ContextPayload
logger = logging.getLogger(__name__)
def reason(payload: ContextPayload) -> ContextPayload:
"""Accept gathered context and return a reasoning result.
Stub: tags the payload with phase=reason and logs transit.
Timmy will flesh this out with LLM calls, confidence scoring,
plan generation, and judgment logic.
"""
logger.info(
"Phase 2 (Reason) received: source=%s gathered=%s",
payload.source,
payload.metadata.get("gathered", False),
)
result = payload.with_metadata(phase="reason", reasoned=True)
logger.info(
"Phase 2 (Reason) produced: metadata_keys=%s",
sorted(result.metadata.keys()),
)
return result

36
src/loop/phase3_act.py Normal file
View File

@@ -0,0 +1,36 @@
"""Phase 3 — Act: accept reasoning output, execute and produce feedback.
This is the command phase. It receives the reasoning result from Phase 2
and takes action. In the stub form, it passes the payload through with a
phase marker and produces feedback for the next cycle.
"""
from __future__ import annotations
import logging
from loop.schema import ContextPayload
logger = logging.getLogger(__name__)
def act(payload: ContextPayload) -> ContextPayload:
"""Accept reasoning result and return action output + feedback.
Stub: tags the payload with phase=act and logs transit.
Timmy will flesh this out with tool execution, delegation,
response generation, and feedback construction.
"""
logger.info(
"Phase 3 (Act) received: source=%s reasoned=%s",
payload.source,
payload.metadata.get("reasoned", False),
)
result = payload.with_metadata(phase="act", acted=True)
logger.info(
"Phase 3 (Act) produced: metadata_keys=%s",
sorted(result.metadata.keys()),
)
return result

40
src/loop/runner.py Normal file
View File

@@ -0,0 +1,40 @@
"""Loop runner — orchestrates the three phases in sequence.
Runs Gather → Reason → Act as a single cycle, passing output from each
phase as input to the next. The Act output feeds back as input to the
next Gather call.
"""
from __future__ import annotations
import logging
from loop.phase1_gather import gather
from loop.phase2_reason import reason
from loop.phase3_act import act
from loop.schema import ContextPayload
logger = logging.getLogger(__name__)
def run_cycle(payload: ContextPayload) -> ContextPayload:
"""Execute one full Gather → Reason → Act cycle.
Returns the Act phase output, which can be fed back as input
to the next cycle.
"""
logger.info("=== Loop cycle start: source=%s ===", payload.source)
gathered = gather(payload)
reasoned = reason(gathered)
acted = act(reasoned)
logger.info(
"=== Loop cycle complete: phases=%s ===",
[
gathered.metadata.get("phase"),
reasoned.metadata.get("phase"),
acted.metadata.get("phase"),
],
)
return acted

43
src/loop/schema.py Normal file
View File

@@ -0,0 +1,43 @@
"""Data schema for the three-phase loop.
Each phase passes a ContextPayload forward. The schema is intentionally
minimal — Timmy decides what fields matter as the loop matures.
"""
from __future__ import annotations
import logging
from dataclasses import dataclass, field
from datetime import UTC, datetime
logger = logging.getLogger(__name__)
@dataclass
class ContextPayload:
"""Immutable context packet passed between loop phases.
Attributes:
source: Where this payload originated (e.g. "user", "timer", "event").
content: The raw content string to process.
timestamp: When the payload was created.
token_count: Estimated token count for budget tracking. -1 = unknown.
metadata: Arbitrary key-value pairs for phase-specific data.
"""
source: str
content: str
timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
token_count: int = -1
metadata: dict = field(default_factory=dict)
def with_metadata(self, **kwargs: object) -> ContextPayload:
"""Return a new payload with additional metadata merged in."""
merged = {**self.metadata, **kwargs}
return ContextPayload(
source=self.source,
content=self.content,
timestamp=self.timestamp,
token_count=self.token_count,
metadata=merged,
)

View File

@@ -1 +1 @@
"""Timmy — Core AI agent (Ollama/AirLLM backends, CLI, prompts)."""
"""Timmy — Core AI agent (Ollama/Grok/Claude backends, CLI, prompts)."""

View File

@@ -0,0 +1 @@
"""Adapters — normalize external data streams into sensory events."""

View File

@@ -0,0 +1,136 @@
"""Gitea webhook adapter — normalize webhook payloads to event bus events.
Receives raw Gitea webhook payloads and emits typed events via the
infrastructure event bus. Bot-only activity is filtered unless it
represents a PR merge (which is always noteworthy).
"""
import logging
from typing import Any
from infrastructure.events.bus import emit
logger = logging.getLogger(__name__)
# Gitea usernames considered "bot" accounts
BOT_USERNAMES = frozenset({"hermes", "kimi", "manus"})
# Owner username — activity from this user is always emitted
OWNER_USERNAME = "rockachopa"
# Mapping from Gitea webhook event type to our bus event type
_EVENT_TYPE_MAP = {
"push": "gitea.push",
"issues": "gitea.issue.opened",
"issue_comment": "gitea.issue.comment",
"pull_request": "gitea.pull_request",
}
def _extract_actor(payload: dict[str, Any]) -> str:
"""Extract the actor username from a webhook payload."""
# Gitea puts actor in sender.login for most events
sender = payload.get("sender", {})
return sender.get("login", "unknown")
def _is_bot(username: str) -> bool:
return username.lower() in BOT_USERNAMES
def _is_pr_merge(event_type: str, payload: dict[str, Any]) -> bool:
"""Check if this is a pull_request merge event."""
if event_type != "pull_request":
return False
action = payload.get("action", "")
pr = payload.get("pull_request", {})
return action == "closed" and pr.get("merged", False)
def _normalize_push(payload: dict[str, Any], actor: str) -> dict[str, Any]:
"""Normalize a push event payload."""
commits = payload.get("commits", [])
return {
"actor": actor,
"ref": payload.get("ref", ""),
"repo": payload.get("repository", {}).get("full_name", ""),
"num_commits": len(commits),
"head_message": commits[0].get("message", "").split("\n", 1)[0].strip() if commits else "",
}
def _normalize_issue_opened(payload: dict[str, Any], actor: str) -> dict[str, Any]:
"""Normalize an issue-opened event payload."""
issue = payload.get("issue", {})
return {
"actor": actor,
"action": payload.get("action", "opened"),
"repo": payload.get("repository", {}).get("full_name", ""),
"issue_number": issue.get("number", 0),
"title": issue.get("title", ""),
}
def _normalize_issue_comment(payload: dict[str, Any], actor: str) -> dict[str, Any]:
"""Normalize an issue-comment event payload."""
issue = payload.get("issue", {})
comment = payload.get("comment", {})
return {
"actor": actor,
"action": payload.get("action", "created"),
"repo": payload.get("repository", {}).get("full_name", ""),
"issue_number": issue.get("number", 0),
"issue_title": issue.get("title", ""),
"comment_body": (comment.get("body", "")[:200]),
}
def _normalize_pull_request(payload: dict[str, Any], actor: str) -> dict[str, Any]:
"""Normalize a pull-request event payload."""
pr = payload.get("pull_request", {})
return {
"actor": actor,
"action": payload.get("action", ""),
"repo": payload.get("repository", {}).get("full_name", ""),
"pr_number": pr.get("number", 0),
"title": pr.get("title", ""),
"merged": pr.get("merged", False),
}
_NORMALIZERS = {
"push": _normalize_push,
"issues": _normalize_issue_opened,
"issue_comment": _normalize_issue_comment,
"pull_request": _normalize_pull_request,
}
async def handle_webhook(event_type: str, payload: dict[str, Any]) -> bool:
"""Normalize a Gitea webhook payload and emit it to the event bus.
Args:
event_type: The Gitea event type header (e.g. "push", "issues").
payload: The raw JSON payload from the webhook.
Returns:
True if an event was emitted, False if filtered or unsupported.
"""
bus_event_type = _EVENT_TYPE_MAP.get(event_type)
if bus_event_type is None:
logger.debug("Unsupported Gitea event type: %s", event_type)
return False
actor = _extract_actor(payload)
# Filter bot-only activity — except PR merges
if _is_bot(actor) and not _is_pr_merge(event_type, payload):
logger.debug("Filtered bot activity from %s on %s", actor, event_type)
return False
normalizer = _NORMALIZERS[event_type]
data = normalizer(payload, actor)
await emit(bus_event_type, source="gitea", data=data)
logger.info("Emitted %s from %s", bus_event_type, actor)
return True

View File

@@ -0,0 +1,82 @@
"""Time adapter — circadian awareness for Timmy.
Emits time-of-day events so Timmy knows the current period
and tracks how long since the last user interaction.
"""
import logging
from datetime import UTC, datetime
from infrastructure.events.bus import emit
logger = logging.getLogger(__name__)
# Time-of-day periods: (event_name, start_hour, end_hour)
_PERIODS = [
("morning", 6, 9),
("afternoon", 12, 14),
("evening", 18, 20),
("late_night", 23, 24),
("late_night", 0, 3),
]
def classify_period(hour: int) -> str | None:
"""Return the circadian period name for a given hour, or None."""
for name, start, end in _PERIODS:
if start <= hour < end:
return name
return None
class TimeAdapter:
"""Emits circadian and interaction-tracking events."""
def __init__(self) -> None:
self._last_interaction: datetime | None = None
self._last_period: str | None = None
self._last_date: str | None = None
def record_interaction(self, now: datetime | None = None) -> None:
"""Record a user interaction timestamp."""
self._last_interaction = now or datetime.now(UTC)
def time_since_last_interaction(
self,
now: datetime | None = None,
) -> float | None:
"""Seconds since last user interaction, or None if no interaction."""
if self._last_interaction is None:
return None
current = now or datetime.now(UTC)
return (current - self._last_interaction).total_seconds()
async def tick(self, now: datetime | None = None) -> list[str]:
"""Check current time and emit relevant events.
Returns list of event types emitted (useful for testing).
"""
current = now or datetime.now(UTC)
emitted: list[str] = []
# --- new_day ---
date_str = current.strftime("%Y-%m-%d")
if self._last_date is not None and date_str != self._last_date:
event_type = "time.new_day"
await emit(event_type, source="time_adapter", data={"date": date_str})
emitted.append(event_type)
self._last_date = date_str
# --- circadian period ---
period = classify_period(current.hour)
if period is not None and period != self._last_period:
event_type = f"time.{period}"
await emit(
event_type,
source="time_adapter",
data={"hour": current.hour, "period": period},
)
emitted.append(event_type)
self._last_period = period
return emitted

View File

@@ -26,12 +26,12 @@ from timmy.prompts import get_system_prompt
from timmy.tools import create_full_toolkit
if TYPE_CHECKING:
from timmy.backends import ClaudeBackend, GrokBackend, TimmyAirLLMAgent
from timmy.backends import ClaudeBackend, GrokBackend
logger = logging.getLogger(__name__)
# Union type for callers that want to hint the return type.
TimmyAgent = Union[Agent, "TimmyAirLLMAgent", "GrokBackend", "ClaudeBackend"]
TimmyAgent = Union[Agent, "GrokBackend", "ClaudeBackend"]
# Models known to be too small for reliable tool calling.
# These hallucinate tool calls as text, invoke tools randomly,
@@ -63,7 +63,7 @@ def _pull_model(model_name: str) -> bool:
logger.info("Pulling model: %s", model_name)
url = settings.ollama_url.replace("localhost", "127.0.0.1")
url = settings.normalized_ollama_url
req = urllib.request.Request(
f"{url}/api/pull",
method="POST",
@@ -172,107 +172,34 @@ def _warmup_model(model_name: str) -> bool:
def _resolve_backend(requested: str | None) -> str:
"""Return the backend name to use, resolving 'auto' and explicit overrides.
"""Return the backend name to use.
Priority (highest lowest):
Priority (highest -> lowest):
1. CLI flag passed directly to create_timmy()
2. TIMMY_MODEL_BACKEND env var / .env setting
3. 'ollama' (safe default no surprises)
'auto' triggers Apple Silicon detection: uses AirLLM if both
is_apple_silicon() and airllm_available() return True.
3. 'ollama' (safe default -- no surprises)
"""
if requested is not None:
return requested
configured = settings.timmy_model_backend # "ollama" | "airllm" | "grok" | "claude" | "auto"
if configured != "auto":
return configured
# "auto" path — lazy import to keep startup fast and tests clean.
from timmy.backends import airllm_available, is_apple_silicon
if is_apple_silicon() and airllm_available():
return "airllm"
return "ollama"
return settings.timmy_model_backend # "ollama" | "grok" | "claude"
def create_timmy(
db_file: str = "timmy.db",
backend: str | None = None,
model_size: str | None = None,
*,
skip_mcp: bool = False,
session_id: str = "unknown",
) -> TimmyAgent:
"""Instantiate the agent — Ollama or AirLLM, same public interface.
def _build_tools_list(use_tools: bool, skip_mcp: bool, model_name: str) -> list:
"""Assemble the tools list based on model capability and MCP flags.
Args:
db_file: SQLite file for Agno conversation memory (Ollama path only).
backend: "ollama" | "airllm" | "auto" | None (reads config/env).
model_size: AirLLM size — "8b" | "70b" | "405b" | None (reads config).
skip_mcp: If True, omit MCP tool servers (Gitea, filesystem).
Use for background tasks (thinking, QA) where MCP's
stdio cancel-scope lifecycle conflicts with asyncio
task cancellation.
Returns an Agno Agent or backend-specific agent — all expose
print_response(message, stream).
Returns a list of Toolkit / MCPTools objects, or an empty list.
"""
resolved = _resolve_backend(backend)
size = model_size or settings.airllm_model_size
if resolved == "claude":
from timmy.backends import ClaudeBackend
return ClaudeBackend()
if resolved == "grok":
from timmy.backends import GrokBackend
return GrokBackend()
if resolved == "airllm":
from timmy.backends import TimmyAirLLMAgent
return TimmyAirLLMAgent(model_size=size)
# Default: Ollama via Agno.
# Resolve model with automatic pulling and fallback
model_name, is_fallback = _resolve_model_with_fallback(
requested_model=None,
require_vision=False,
auto_pull=True,
)
# If Ollama is completely unreachable, fail loudly.
# Sovereignty: never silently send data to a cloud API.
# Use --backend claude explicitly if you want cloud inference.
if not _check_model_available(model_name):
logger.error(
"Ollama unreachable and no local models available. "
"Start Ollama with 'ollama serve' or use --backend claude explicitly."
)
if is_fallback:
logger.info("Using fallback model %s (requested was unavailable)", model_name)
use_tools = _model_supports_tools(model_name)
# Conditionally include tools — small models get none
toolkit = create_full_toolkit() if use_tools else None
if not use_tools:
logger.info("Tools disabled for model %s (too small for reliable tool calling)", model_name)
return []
# Build the tools list — Agno accepts a list of Toolkit / MCPTools
tools_list: list = []
if toolkit:
tools_list.append(toolkit)
tools_list: list = [create_full_toolkit()]
# Add MCP tool servers (lazy-connected on first arun()).
# Skipped when skip_mcp=True — MCP's stdio transport uses anyio cancel
# scopes that conflict with asyncio background task cancellation (#72).
if use_tools and not skip_mcp:
if not skip_mcp:
try:
from timmy.mcp_tools import create_filesystem_mcp_tools, create_gitea_mcp_tools
@@ -286,30 +213,46 @@ def create_timmy(
except Exception as exc:
logger.debug("MCP tools unavailable: %s", exc)
# Select prompt tier based on tool capability
return tools_list
def _build_prompt(use_tools: bool, session_id: str) -> str:
"""Build the full system prompt with optional memory context."""
base_prompt = get_system_prompt(tools_enabled=use_tools, session_id=session_id)
# Try to load memory context
try:
from timmy.memory_system import memory_system
memory_context = memory_system.get_system_context()
if memory_context:
# Truncate if too long — smaller budget for small models
# since the expanded prompt (roster, guardrails) uses more tokens
# Smaller budget for small models — expanded prompt uses more tokens
max_context = 2000 if not use_tools else 8000
if len(memory_context) > max_context:
memory_context = memory_context[:max_context] + "\n... [truncated]"
full_prompt = f"{base_prompt}\n\n## Memory Context\n\n{memory_context}"
else:
full_prompt = base_prompt
return (
f"{base_prompt}\n\n"
f"## GROUNDED CONTEXT (verified sources — cite when using)\n\n"
f"{memory_context}"
)
except Exception as exc:
logger.warning("Failed to load memory context: %s", exc)
full_prompt = base_prompt
return base_prompt
def _create_ollama_agent(
*,
db_file: str,
model_name: str,
tools_list: list,
full_prompt: str,
use_tools: bool,
) -> Agent:
"""Construct the Agno Agent with Ollama backend and warm up the model."""
model_kwargs = {}
if settings.ollama_num_ctx > 0:
model_kwargs["options"] = {"num_ctx": settings.ollama_num_ctx}
agent = Agent(
name="Agent",
model=Ollama(id=model_name, host=settings.ollama_url, timeout=300, **model_kwargs),
@@ -326,6 +269,67 @@ def create_timmy(
return agent
def create_timmy(
db_file: str = "timmy.db",
backend: str | None = None,
*,
skip_mcp: bool = False,
session_id: str = "unknown",
) -> TimmyAgent:
"""Instantiate the agent — Ollama, Grok, or Claude.
Args:
db_file: SQLite file for Agno conversation memory (Ollama path only).
backend: "ollama" | "grok" | "claude" | None (reads config/env).
skip_mcp: If True, omit MCP tool servers (Gitea, filesystem).
Use for background tasks (thinking, QA) where MCP's
stdio cancel-scope lifecycle conflicts with asyncio
task cancellation.
Returns an Agno Agent or backend-specific agent — all expose
print_response(message, stream).
"""
resolved = _resolve_backend(backend)
if resolved == "claude":
from timmy.backends import ClaudeBackend
return ClaudeBackend()
if resolved == "grok":
from timmy.backends import GrokBackend
return GrokBackend()
# Default: Ollama via Agno.
model_name, is_fallback = _resolve_model_with_fallback(
requested_model=None,
require_vision=False,
auto_pull=True,
)
if not _check_model_available(model_name):
logger.error(
"Ollama unreachable and no local models available. "
"Start Ollama with 'ollama serve' or use --backend claude explicitly."
)
if is_fallback:
logger.info("Using fallback model %s (requested was unavailable)", model_name)
use_tools = _model_supports_tools(model_name)
tools_list = _build_tools_list(use_tools, skip_mcp, model_name)
full_prompt = _build_prompt(use_tools, session_id)
return _create_ollama_agent(
db_file=db_file,
model_name=model_name,
tools_list=tools_list,
full_prompt=full_prompt,
use_tools=use_tools,
)
class TimmyWithMemory:
"""Agent wrapper with explicit three-tier memory management."""

View File

@@ -18,6 +18,7 @@ from __future__ import annotations
import asyncio
import logging
import re
import threading
import time
import uuid
from collections.abc import Callable
@@ -59,6 +60,7 @@ class AgenticResult:
# ---------------------------------------------------------------------------
_loop_agent = None
_loop_agent_lock = threading.Lock()
def _get_loop_agent():
@@ -69,9 +71,11 @@ def _get_loop_agent():
"""
global _loop_agent
if _loop_agent is None:
from timmy.agent import create_timmy
with _loop_agent_lock:
if _loop_agent is None:
from timmy.agent import create_timmy
_loop_agent = create_timmy()
_loop_agent = create_timmy()
return _loop_agent
@@ -91,6 +95,126 @@ def _parse_steps(plan_text: str) -> list[str]:
return [line.strip() for line in plan_text.strip().splitlines() if line.strip()]
# ---------------------------------------------------------------------------
# Extracted helpers
# ---------------------------------------------------------------------------
def _extract_content(run_result) -> str:
"""Extract text content from an agent run result."""
return run_result.content if hasattr(run_result, "content") else str(run_result)
def _clean(text: str) -> str:
"""Clean a model response using session's response cleaner."""
from timmy.session import _clean_response
return _clean_response(text)
async def _plan_task(
agent, task: str, session_id: str, max_steps: int
) -> tuple[list[str], bool] | str:
"""Run the planning phase — returns (steps, was_truncated) or error string."""
plan_prompt = (
f"Break this task into numbered steps (max {max_steps}). "
f"Return ONLY a numbered list, nothing else.\n\n"
f"Task: {task}"
)
try:
plan_run = await asyncio.to_thread(
agent.run, plan_prompt, stream=False, session_id=f"{session_id}_plan"
)
plan_text = _extract_content(plan_run)
except Exception as exc: # broad catch intentional: agent.run can raise any error
logger.error("Agentic loop: planning failed: %s", exc)
return f"Planning failed: {exc}"
steps = _parse_steps(plan_text)
if not steps:
return "Planning produced no steps."
planned_count = len(steps)
steps = steps[:max_steps]
return steps, planned_count > len(steps)
async def _execute_step(
agent,
task: str,
step_desc: str,
step_num: int,
total_steps: int,
recent_results: list[str],
session_id: str,
) -> AgenticStep:
"""Execute a single step, returning an AgenticStep."""
step_start = time.monotonic()
context = (
f"Task: {task}\n"
f"Step {step_num}/{total_steps}: {step_desc}\n"
f"Recent progress: {recent_results[-2:] if recent_results else []}\n\n"
f"Execute this step and report what you did."
)
step_run = await asyncio.to_thread(
agent.run, context, stream=False, session_id=f"{session_id}_step{step_num}"
)
step_result = _clean(_extract_content(step_run))
return AgenticStep(
step_num=step_num,
description=step_desc,
result=step_result,
status="completed",
duration_ms=int((time.monotonic() - step_start) * 1000),
)
async def _adapt_step(
agent,
step_desc: str,
step_num: int,
error: Exception,
step_start: float,
session_id: str,
) -> AgenticStep:
"""Attempt adaptation after a step failure."""
adapt_prompt = (
f"Step {step_num} failed with error: {error}\n"
f"Original step was: {step_desc}\n"
f"Adapt the plan and try an alternative approach for this step."
)
adapt_run = await asyncio.to_thread(
agent.run, adapt_prompt, stream=False, session_id=f"{session_id}_adapt{step_num}"
)
adapt_result = _clean(_extract_content(adapt_run))
return AgenticStep(
step_num=step_num,
description=f"[Adapted] {step_desc}",
result=adapt_result,
status="adapted",
duration_ms=int((time.monotonic() - step_start) * 1000),
)
def _summarize(result: AgenticResult, total_steps: int, was_truncated: bool) -> None:
"""Fill in summary and final status on the result object (mutates in place)."""
completed = sum(1 for s in result.steps if s.status == "completed")
adapted = sum(1 for s in result.steps if s.status == "adapted")
failed = sum(1 for s in result.steps if s.status == "failed")
parts = [f"Completed {completed}/{total_steps} steps"]
if adapted:
parts.append(f"{adapted} adapted")
if failed:
parts.append(f"{failed} failed")
result.summary = f"{result.task}: {', '.join(parts)}."
if was_truncated or len(result.steps) < total_steps or failed:
result.status = "partial"
else:
result.status = "completed"
# ---------------------------------------------------------------------------
# Core loop
# ---------------------------------------------------------------------------
@@ -121,88 +245,41 @@ async def run_agentic_loop(
task_id = str(uuid.uuid4())[:8]
start_time = time.monotonic()
agent = _get_loop_agent()
result = AgenticResult(task_id=task_id, task=task, summary="")
# ── Phase 1: Planning ──────────────────────────────────────────────────
plan_prompt = (
f"Break this task into numbered steps (max {max_steps}). "
f"Return ONLY a numbered list, nothing else.\n\n"
f"Task: {task}"
)
try:
plan_run = await asyncio.to_thread(
agent.run, plan_prompt, stream=False, session_id=f"{session_id}_plan"
)
plan_text = plan_run.content if hasattr(plan_run, "content") else str(plan_run)
except Exception as exc: # broad catch intentional: agent.run can raise any error
logger.error("Agentic loop: planning failed: %s", exc)
# Phase 1: Planning
plan = await _plan_task(agent, task, session_id, max_steps)
if isinstance(plan, str):
result.status = "failed"
result.summary = f"Planning failed: {exc}"
result.summary = plan
result.total_duration_ms = int((time.monotonic() - start_time) * 1000)
return result
steps = _parse_steps(plan_text)
if not steps:
result.status = "failed"
result.summary = "Planning produced no steps."
result.total_duration_ms = int((time.monotonic() - start_time) * 1000)
return result
# Enforce max_steps — track if we truncated
planned_steps = len(steps)
steps = steps[:max_steps]
steps, was_truncated = plan
total_steps = len(steps)
was_truncated = planned_steps > total_steps
# Broadcast plan
await _broadcast_progress(
"agentic.plan_ready",
{
"task_id": task_id,
"task": task,
"steps": steps,
"total": total_steps,
},
{"task_id": task_id, "task": task, "steps": steps, "total": total_steps},
)
# ── Phase 2: Execution ─────────────────────────────────────────────────
# Phase 2: Execution
completed_results: list[str] = []
for i, step_desc in enumerate(steps, 1):
step_start = time.monotonic()
recent = completed_results[-2:] if completed_results else []
context = (
f"Task: {task}\n"
f"Step {i}/{total_steps}: {step_desc}\n"
f"Recent progress: {recent}\n\n"
f"Execute this step and report what you did."
)
try:
step_run = await asyncio.to_thread(
agent.run, context, stream=False, session_id=f"{session_id}_step{i}"
)
step_result = step_run.content if hasattr(step_run, "content") else str(step_run)
# Clean the response
from timmy.session import _clean_response
step_result = _clean_response(step_result)
step = AgenticStep(
step_num=i,
description=step_desc,
result=step_result,
status="completed",
duration_ms=int((time.monotonic() - step_start) * 1000),
step = await _execute_step(
agent,
task,
step_desc,
i,
total_steps,
completed_results,
session_id,
)
result.steps.append(step)
completed_results.append(f"Step {i}: {step_result[:200]}")
# Broadcast progress
completed_results.append(f"Step {i}: {step.result[:200]}")
await _broadcast_progress(
"agentic.step_complete",
{
@@ -210,46 +287,18 @@ async def run_agentic_loop(
"step": i,
"total": total_steps,
"description": step_desc,
"result": step_result[:200],
"result": step.result[:200],
},
)
if on_progress:
await on_progress(step_desc, i, total_steps)
except Exception as exc: # broad catch intentional: agent.run can raise any error
logger.warning("Agentic loop step %d failed: %s", i, exc)
# ── Adaptation: ask model to adapt ─────────────────────────────
adapt_prompt = (
f"Step {i} failed with error: {exc}\n"
f"Original step was: {step_desc}\n"
f"Adapt the plan and try an alternative approach for this step."
)
try:
adapt_run = await asyncio.to_thread(
agent.run,
adapt_prompt,
stream=False,
session_id=f"{session_id}_adapt{i}",
)
adapt_result = (
adapt_run.content if hasattr(adapt_run, "content") else str(adapt_run)
)
from timmy.session import _clean_response
adapt_result = _clean_response(adapt_result)
step = AgenticStep(
step_num=i,
description=f"[Adapted] {step_desc}",
result=adapt_result,
status="adapted",
duration_ms=int((time.monotonic() - step_start) * 1000),
)
step = await _adapt_step(agent, step_desc, i, exc, step_start, session_id)
result.steps.append(step)
completed_results.append(f"Step {i} (adapted): {adapt_result[:200]}")
completed_results.append(f"Step {i} (adapted): {step.result[:200]}")
await _broadcast_progress(
"agentic.step_adapted",
{
@@ -258,46 +307,26 @@ async def run_agentic_loop(
"total": total_steps,
"description": step_desc,
"error": str(exc),
"adaptation": adapt_result[:200],
"adaptation": step.result[:200],
},
)
if on_progress:
await on_progress(f"[Adapted] {step_desc}", i, total_steps)
except Exception as adapt_exc: # broad catch intentional: agent.run can raise any error
except Exception as adapt_exc: # broad catch intentional
logger.error("Agentic loop adaptation also failed: %s", adapt_exc)
step = AgenticStep(
step_num=i,
description=step_desc,
result=f"Failed: {exc}; Adaptation also failed: {adapt_exc}",
status="failed",
duration_ms=int((time.monotonic() - step_start) * 1000),
result.steps.append(
AgenticStep(
step_num=i,
description=step_desc,
result=f"Failed: {exc}; Adaptation also failed: {adapt_exc}",
status="failed",
duration_ms=int((time.monotonic() - step_start) * 1000),
)
)
result.steps.append(step)
completed_results.append(f"Step {i}: FAILED")
# ── Phase 3: Summary ───────────────────────────────────────────────────
completed_count = sum(1 for s in result.steps if s.status == "completed")
adapted_count = sum(1 for s in result.steps if s.status == "adapted")
failed_count = sum(1 for s in result.steps if s.status == "failed")
parts = [f"Completed {completed_count}/{total_steps} steps"]
if adapted_count:
parts.append(f"{adapted_count} adapted")
if failed_count:
parts.append(f"{failed_count} failed")
result.summary = f"{task}: {', '.join(parts)}."
# Determine final status
if was_truncated:
result.status = "partial"
elif len(result.steps) < total_steps:
result.status = "partial"
elif any(s.status == "failed" for s in result.steps):
result.status = "partial"
else:
result.status = "completed"
# Phase 3: Summary
_summarize(result, total_steps, was_truncated)
result.total_duration_ms = int((time.monotonic() - start_time) * 1000)
await _broadcast_progress(

View File

@@ -119,75 +119,84 @@ class BaseAgent(ABC):
"""
pass
async def run(self, message: str) -> str:
"""Run the agent with a message.
# Transient errors that indicate Ollama contention or temporary
# unavailability — these deserve a retry with backoff.
_TRANSIENT = (
httpx.ConnectError,
httpx.ReadError,
httpx.ReadTimeout,
httpx.ConnectTimeout,
ConnectionError,
TimeoutError,
)
Retries on transient failures (connection errors, timeouts) with
exponential backoff. GPU contention from concurrent Ollama
requests causes ReadError / ReadTimeout — these are transient
and should be retried, not raised immediately (#70).
async def run(self, message: str, *, max_retries: int = 3) -> str:
"""Run the agent with a message, retrying on transient failures.
Returns:
Agent response
GPU contention from concurrent Ollama requests causes ReadError /
ReadTimeout — these are transient and retried with exponential
backoff (#70).
"""
max_retries = 3
last_exception = None
# Transient errors that indicate Ollama contention or temporary
# unavailability — these deserve a retry with backoff.
_transient = (
httpx.ConnectError,
httpx.ReadError,
httpx.ReadTimeout,
httpx.ConnectTimeout,
ConnectionError,
TimeoutError,
)
response = await self._run_with_retries(message, max_retries)
await self._emit_response_event(message, response)
return response
async def _run_with_retries(self, message: str, max_retries: int) -> str:
"""Execute agent.run() with retry logic for transient errors."""
for attempt in range(1, max_retries + 1):
try:
result = self.agent.run(message, stream=False)
response = result.content if hasattr(result, "content") else str(result)
break # Success, exit the retry loop
except _transient as exc:
last_exception = exc
if attempt < max_retries:
# Contention backoff — longer waits because the GPU
# needs time to finish the other request.
wait = min(2**attempt, 16)
logger.warning(
"Ollama contention on attempt %d/%d: %s. Waiting %ds before retry...",
attempt,
max_retries,
type(exc).__name__,
wait,
)
await asyncio.sleep(wait)
else:
logger.error(
"Ollama unreachable after %d attempts: %s",
max_retries,
exc,
)
raise last_exception from exc
return result.content if hasattr(result, "content") else str(result)
except self._TRANSIENT as exc:
self._handle_retry_or_raise(
exc,
attempt,
max_retries,
transient=True,
)
await asyncio.sleep(min(2**attempt, 16))
except Exception as exc:
last_exception = exc
if attempt < max_retries:
logger.warning(
"Agent run failed on attempt %d/%d: %s. Retrying...",
attempt,
max_retries,
exc,
)
await asyncio.sleep(min(2 ** (attempt - 1), 8))
else:
logger.error(
"Agent run failed after %d attempts: %s",
max_retries,
exc,
)
raise last_exception from exc
self._handle_retry_or_raise(
exc,
attempt,
max_retries,
transient=False,
)
await asyncio.sleep(min(2 ** (attempt - 1), 8))
# Unreachable — _handle_retry_or_raise raises on last attempt.
raise RuntimeError("retry loop exited unexpectedly") # pragma: no cover
# Emit completion event
@staticmethod
def _handle_retry_or_raise(
exc: Exception,
attempt: int,
max_retries: int,
*,
transient: bool,
) -> None:
"""Log a retry warning or raise after exhausting attempts."""
if attempt < max_retries:
if transient:
logger.warning(
"Ollama contention on attempt %d/%d: %s. Waiting before retry...",
attempt,
max_retries,
type(exc).__name__,
)
else:
logger.warning(
"Agent run failed on attempt %d/%d: %s. Retrying...",
attempt,
max_retries,
exc,
)
else:
label = "Ollama unreachable" if transient else "Agent run failed"
logger.error("%s after %d attempts: %s", label, max_retries, exc)
raise exc
async def _emit_response_event(self, message: str, response: str) -> None:
"""Publish a completion event to the event bus if connected."""
if self.event_bus:
await self.event_bus.publish(
Event(
@@ -197,8 +206,6 @@ class BaseAgent(ABC):
)
)
return response
def get_capabilities(self) -> list[str]:
"""Get list of capabilities this agent provides."""
return self.tools

View File

@@ -1,11 +1,10 @@
"""LLM backends — AirLLM (local big models), Grok (xAI), and Claude (Anthropic).
"""LLM backends — Grok (xAI) and Claude (Anthropic).
Provides drop-in replacements for the Agno Agent that expose the same
run(message, stream) → RunResult interface used by the dashboard and the
print_response(message, stream) interface used by the CLI.
Backends:
- TimmyAirLLMAgent: Local 8B/70B/405B via AirLLM (Apple Silicon or PyTorch)
- GrokBackend: xAI Grok API via OpenAI-compatible SDK (opt-in premium)
- ClaudeBackend: Anthropic Claude API — lightweight cloud fallback
@@ -16,21 +15,11 @@ import logging
import platform
import time
from dataclasses import dataclass
from typing import Literal
from timmy.prompts import get_system_prompt
logger = logging.getLogger(__name__)
# HuggingFace model IDs for each supported size.
_AIRLLM_MODELS: dict[str, str] = {
"8b": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"70b": "meta-llama/Meta-Llama-3.1-70B-Instruct",
"405b": "meta-llama/Meta-Llama-3.1-405B-Instruct",
}
ModelSize = Literal["8b", "70b", "405b"]
@dataclass
class RunResult:
@@ -45,108 +34,6 @@ def is_apple_silicon() -> bool:
return platform.system() == "Darwin" and platform.machine() == "arm64"
def airllm_available() -> bool:
"""Return True when the airllm package is importable."""
try:
import airllm # noqa: F401
return True
except ImportError:
return False
class TimmyAirLLMAgent:
"""Thin AirLLM wrapper compatible with both dashboard and CLI call sites.
Exposes:
run(message, stream) → RunResult(content=...) [dashboard]
print_response(message, stream) → None [CLI]
Maintains a rolling 10-turn in-memory history so Timmy remembers the
conversation within a session — no SQLite needed at this layer.
"""
def __init__(self, model_size: str = "70b") -> None:
model_id = _AIRLLM_MODELS.get(model_size)
if model_id is None:
raise ValueError(
f"Unknown model size {model_size!r}. Choose from: {list(_AIRLLM_MODELS)}"
)
if is_apple_silicon():
from airllm import AirLLMMLX # type: ignore[import]
self._model = AirLLMMLX(model_id)
else:
from airllm import AutoModel # type: ignore[import]
self._model = AutoModel.from_pretrained(model_id)
self._history: list[str] = []
self._model_size = model_size
# ── public interface (mirrors Agno Agent) ────────────────────────────────
def run(self, message: str, *, stream: bool = False) -> RunResult:
"""Run inference and return a structured result (matches Agno Agent.run()).
`stream` is accepted for API compatibility; AirLLM always generates
the full output in one pass.
"""
prompt = self._build_prompt(message)
input_tokens = self._model.tokenizer(
[prompt],
return_tensors="pt",
padding=True,
truncation=True,
max_length=2048,
)
output = self._model.generate(
**input_tokens,
max_new_tokens=512,
use_cache=True,
do_sample=True,
temperature=0.7,
)
# Decode only the newly generated tokens, not the prompt.
input_len = input_tokens["input_ids"].shape[1]
response = self._model.tokenizer.decode(
output[0][input_len:], skip_special_tokens=True
).strip()
self._history.append(f"User: {message}")
self._history.append(f"Timmy: {response}")
return RunResult(content=response)
def print_response(self, message: str, *, stream: bool = True) -> None:
"""Run inference and render the response to stdout (CLI interface)."""
result = self.run(message, stream=stream)
self._render(result.content)
# ── private helpers ──────────────────────────────────────────────────────
def _build_prompt(self, message: str) -> str:
context = get_system_prompt(tools_enabled=False, session_id="airllm") + "\n\n"
# Include the last 10 turns (5 exchanges) for continuity.
if self._history:
context += "\n".join(self._history[-10:]) + "\n\n"
return context + f"User: {message}\nTimmy:"
@staticmethod
def _render(text: str) -> None:
"""Print response with rich markdown when available, plain text otherwise."""
try:
from rich.console import Console
from rich.markdown import Markdown
Console().print(Markdown(text))
except ImportError:
print(text)
# ── Grok (xAI) Backend ─────────────────────────────────────────────────────
# Premium cloud augmentation — opt-in only, never the default path.
@@ -187,7 +74,7 @@ class GrokBackend:
Uses the OpenAI-compatible SDK to connect to xAI's API.
Only activated when GROK_ENABLED=true and XAI_API_KEY is set.
Exposes the same interface as TimmyAirLLMAgent and Agno Agent:
Exposes the same interface as Agno Agent:
run(message, stream) → RunResult [dashboard]
print_response(message, stream) → None [CLI]
health_check() → dict [monitoring]
@@ -437,8 +324,7 @@ CLAUDE_MODELS: dict[str, str] = {
class ClaudeBackend:
"""Anthropic Claude backend — cloud fallback when local models are offline.
Uses the official Anthropic SDK. Same interface as GrokBackend and
TimmyAirLLMAgent:
Uses the official Anthropic SDK. Same interface as GrokBackend:
run(message, stream) → RunResult [dashboard]
print_response(message, stream) → None [CLI]
health_check() → dict [monitoring]

View File

@@ -22,13 +22,13 @@ _BACKEND_OPTION = typer.Option(
None,
"--backend",
"-b",
help="Inference backend: 'ollama' (default) | 'airllm' | 'auto'",
help="Inference backend: 'ollama' (default) | 'grok' | 'claude'",
)
_MODEL_SIZE_OPTION = typer.Option(
None,
"--model-size",
"-s",
help="AirLLM model size when --backend airllm: '8b' | '70b' | '405b'",
help="Model size (reserved for future use).",
)
@@ -416,5 +416,40 @@ def route(
typer.echo("→ orchestrator (no pattern match)")
@app.command()
def focus(
topic: str | None = typer.Argument(
None, help='Topic to focus on (e.g. "three-phase loop"). Omit to show current focus.'
),
clear: bool = typer.Option(False, "--clear", "-c", help="Clear focus and return to broad mode"),
):
"""Set deep-focus mode on a single problem.
When focused, Timmy prioritizes the active topic in all responses
and deprioritizes unrelated context. Focus persists across sessions.
Examples:
timmy focus "three-phase loop" # activate deep focus
timmy focus # show current focus
timmy focus --clear # return to broad mode
"""
from timmy.focus import focus_manager
if clear:
focus_manager.clear()
typer.echo("Focus cleared — back to broad mode.")
return
if topic:
focus_manager.set_topic(topic)
typer.echo(f'Deep focus activated: "{topic}"')
else:
# Show current focus status
if focus_manager.is_focused():
typer.echo(f'Deep focus: "{focus_manager.get_topic()}"')
else:
typer.echo("No active focus (broad mode).")
def main():
app()

View File

@@ -0,0 +1,250 @@
"""Observable cognitive state for Timmy.
Tracks Timmy's internal cognitive signals — focus, engagement, mood,
and active commitments — so external systems (Matrix avatar, dashboard)
can render observable behaviour.
State is published via ``workshop_state.py`` → ``presence.json`` and the
WebSocket relay. The old ``~/.tower/timmy-state.txt`` file has been
deprecated (see #384).
"""
import asyncio
import json
import logging
from dataclasses import asdict, dataclass, field
from timmy.confidence import estimate_confidence
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Schema
# ---------------------------------------------------------------------------
ENGAGEMENT_LEVELS = ("idle", "surface", "deep")
MOOD_VALUES = ("curious", "settled", "hesitant", "energized")
@dataclass
class CognitiveState:
"""Observable snapshot of Timmy's cognitive state."""
focus_topic: str | None = None
engagement: str = "idle" # idle | surface | deep
mood: str = "settled" # curious | settled | hesitant | energized
conversation_depth: int = 0
last_initiative: str | None = None
active_commitments: list[str] = field(default_factory=list)
# Internal tracking (not written to state file)
_confidence_sum: float = field(default=0.0, repr=False)
_confidence_count: int = field(default=0, repr=False)
# ------------------------------------------------------------------
# Serialisation helpers
# ------------------------------------------------------------------
def to_dict(self) -> dict:
"""Public fields only (exclude internal tracking)."""
d = asdict(self)
d.pop("_confidence_sum", None)
d.pop("_confidence_count", None)
return d
# ---------------------------------------------------------------------------
# Cognitive signal extraction
# ---------------------------------------------------------------------------
# Keywords that suggest deep engagement
_DEEP_KEYWORDS = frozenset(
{
"architecture",
"design",
"implement",
"refactor",
"debug",
"analyze",
"investigate",
"deep dive",
"explain how",
"walk me through",
"step by step",
}
)
# Keywords that suggest initiative / commitment
_COMMITMENT_KEYWORDS = frozenset(
{
"i will",
"i'll",
"let me",
"i'm going to",
"plan to",
"commit to",
"i propose",
"i suggest",
}
)
def _infer_engagement(message: str, response: str) -> str:
"""Classify engagement level from the exchange."""
combined = (message + " " + response).lower()
if any(kw in combined for kw in _DEEP_KEYWORDS):
return "deep"
# Short exchanges are surface-level
if len(response.split()) < 15:
return "surface"
return "surface"
def _infer_mood(response: str, confidence: float) -> str:
"""Derive mood from response signals."""
lower = response.lower()
if confidence < 0.4:
return "hesitant"
if "!" in response and any(w in lower for w in ("great", "exciting", "love", "awesome")):
return "energized"
if "?" in response or any(w in lower for w in ("wonder", "interesting", "curious", "hmm")):
return "curious"
return "settled"
def _extract_topic(message: str) -> str | None:
"""Best-effort topic extraction from the user message.
Takes the first meaningful clause (up to 60 chars) as a topic label.
"""
text = message.strip()
if not text:
return None
# Strip leading question words
for prefix in ("what is ", "how do ", "can you ", "please ", "hey timmy "):
if text.lower().startswith(prefix):
text = text[len(prefix) :]
# Truncate
if len(text) > 60:
text = text[:57] + "..."
return text.strip() or None
def _extract_commitments(response: str) -> list[str]:
"""Pull commitment phrases from Timmy's response."""
commitments: list[str] = []
lower = response.lower()
for kw in _COMMITMENT_KEYWORDS:
idx = lower.find(kw)
if idx == -1:
continue
# Grab the rest of the sentence (up to period/newline, max 80 chars)
start = idx
end = len(lower)
for sep in (".", "\n", "!"):
pos = lower.find(sep, start)
if pos != -1:
end = min(end, pos)
snippet = response[start : min(end, start + 80)].strip()
if snippet:
commitments.append(snippet)
return commitments[:3] # Cap at 3
# ---------------------------------------------------------------------------
# Tracker singleton
# ---------------------------------------------------------------------------
class CognitiveTracker:
"""Maintains Timmy's cognitive state.
State is consumed via ``to_json()`` / ``get_state()`` and published
externally by ``workshop_state.py`` → ``presence.json``.
"""
def __init__(self) -> None:
self.state = CognitiveState()
def update(self, user_message: str, response: str) -> CognitiveState:
"""Update cognitive state from a chat exchange.
Called after each chat round-trip in ``session.py``.
Emits a ``cognitive_state_changed`` event to the sensory bus so
downstream consumers (WorkshopHeartbeat, etc.) react immediately.
"""
confidence = estimate_confidence(response)
prev_mood = self.state.mood
prev_engagement = self.state.engagement
# Track running confidence average
self.state._confidence_sum += confidence
self.state._confidence_count += 1
self.state.conversation_depth += 1
self.state.focus_topic = _extract_topic(user_message) or self.state.focus_topic
self.state.engagement = _infer_engagement(user_message, response)
self.state.mood = _infer_mood(response, confidence)
# Extract commitments from response
new_commitments = _extract_commitments(response)
if new_commitments:
self.state.last_initiative = new_commitments[0]
# Merge, keeping last 5
seen = set(self.state.active_commitments)
for c in new_commitments:
if c not in seen:
self.state.active_commitments.append(c)
seen.add(c)
self.state.active_commitments = self.state.active_commitments[-5:]
# Emit cognitive_state_changed to close the sense → react loop
self._emit_change(prev_mood, prev_engagement)
return self.state
def _emit_change(self, prev_mood: str, prev_engagement: str) -> None:
"""Fire-and-forget sensory event for cognitive state change."""
try:
from timmy.event_bus import get_sensory_bus
from timmy.events import SensoryEvent
event = SensoryEvent(
source="cognitive",
event_type="cognitive_state_changed",
data={
"mood": self.state.mood,
"engagement": self.state.engagement,
"focus_topic": self.state.focus_topic or "",
"depth": self.state.conversation_depth,
"mood_changed": self.state.mood != prev_mood,
"engagement_changed": self.state.engagement != prev_engagement,
},
)
bus = get_sensory_bus()
# Fire-and-forget — don't block the chat response
try:
loop = asyncio.get_running_loop()
loop.create_task(bus.emit(event))
except RuntimeError:
# No running loop (sync context / tests) — skip emission
pass
except Exception as exc:
logger.debug("Cognitive event emission skipped: %s", exc)
def get_state(self) -> CognitiveState:
"""Return current cognitive state."""
return self.state
def reset(self) -> None:
"""Reset to idle state (e.g. on session reset)."""
self.state = CognitiveState()
def to_json(self) -> str:
"""Serialise current state as JSON (for API / WebSocket consumers)."""
return json.dumps(self.state.to_dict())
# Module-level singleton
cognitive_tracker = CognitiveTracker()

79
src/timmy/event_bus.py Normal file
View File

@@ -0,0 +1,79 @@
"""Sensory EventBus — simple pub/sub for SensoryEvents.
Thin facade over the infrastructure EventBus that speaks in
SensoryEvent objects instead of raw infrastructure Events.
"""
import asyncio
import logging
from collections.abc import Awaitable, Callable
from timmy.events import SensoryEvent
logger = logging.getLogger(__name__)
# Handler: sync or async callable that receives a SensoryEvent
SensoryHandler = Callable[[SensoryEvent], None | Awaitable[None]]
class SensoryBus:
"""Pub/sub dispatcher for SensoryEvents."""
def __init__(self, max_history: int = 500) -> None:
self._subscribers: dict[str, list[SensoryHandler]] = {}
self._history: list[SensoryEvent] = []
self._max_history = max_history
# ── Public API ────────────────────────────────────────────────────────
async def emit(self, event: SensoryEvent) -> int:
"""Push *event* to all subscribers whose event_type filter matches.
Returns the number of handlers invoked.
"""
self._history.append(event)
if len(self._history) > self._max_history:
self._history = self._history[-self._max_history :]
handlers = self._matching_handlers(event.event_type)
for h in handlers:
try:
result = h(event)
if asyncio.iscoroutine(result):
await result
except Exception as exc:
logger.error("SensoryBus handler error for '%s': %s", event.event_type, exc)
return len(handlers)
def subscribe(self, event_type: str, callback: SensoryHandler) -> None:
"""Register *callback* for events matching *event_type*.
Use ``"*"`` to subscribe to all event types.
"""
self._subscribers.setdefault(event_type, []).append(callback)
def recent(self, n: int = 10) -> list[SensoryEvent]:
"""Return the last *n* events (most recent last)."""
return self._history[-n:]
# ── Internals ─────────────────────────────────────────────────────────
def _matching_handlers(self, event_type: str) -> list[SensoryHandler]:
handlers: list[SensoryHandler] = []
for pattern, cbs in self._subscribers.items():
if pattern == "*" or pattern == event_type:
handlers.extend(cbs)
return handlers
# ── Module-level singleton ────────────────────────────────────────────────────
_bus: SensoryBus | None = None
def get_sensory_bus() -> SensoryBus:
"""Return the module-level SensoryBus singleton."""
global _bus
if _bus is None:
_bus = SensoryBus()
return _bus

39
src/timmy/events.py Normal file
View File

@@ -0,0 +1,39 @@
"""SensoryEvent — normalized event model for stream adapters.
Every adapter (gitea, time, bitcoin, terminal, etc.) emits SensoryEvents
into the EventBus so that Timmy's cognitive layer sees a uniform stream.
"""
import json
from dataclasses import asdict, dataclass, field
from datetime import UTC, datetime
@dataclass
class SensoryEvent:
"""A single sensory event from an external stream."""
source: str # "gitea", "time", "bitcoin", "terminal"
event_type: str # "push", "issue_opened", "new_block", "morning"
timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
data: dict = field(default_factory=dict)
actor: str = "" # who caused it (username, "system", etc.)
def to_dict(self) -> dict:
"""Return a JSON-serializable dictionary."""
d = asdict(self)
d["timestamp"] = self.timestamp.isoformat()
return d
def to_json(self) -> str:
"""Return a JSON string."""
return json.dumps(self.to_dict())
@classmethod
def from_dict(cls, data: dict) -> "SensoryEvent":
"""Reconstruct a SensoryEvent from a dictionary."""
data = dict(data) # shallow copy
ts = data.get("timestamp")
if isinstance(ts, str):
data["timestamp"] = datetime.fromisoformat(ts)
return cls(**data)

263
src/timmy/familiar.py Normal file
View File

@@ -0,0 +1,263 @@
"""Pip the Familiar — a creature with its own small mind.
Pip is a glowing sprite who lives in the Workshop independently of Timmy.
He has a behavioral state machine that makes the room feel alive:
SLEEPING → WAKING → WANDERING → INVESTIGATING → BORED → SLEEPING
Special states triggered by Timmy's cognitive signals:
ALERT — confidence drops below 0.3
PLAYFUL — Timmy is amused / energized
HIDING — unknown visitor + Timmy uncertain
The backend tracks Pip's *logical* state; the browser handles movement
interpolation and particle rendering.
"""
import logging
import random
import time
from dataclasses import asdict, dataclass, field
from enum import StrEnum
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# States
# ---------------------------------------------------------------------------
class PipState(StrEnum):
"""Pip's behavioral states."""
SLEEPING = "sleeping"
WAKING = "waking"
WANDERING = "wandering"
INVESTIGATING = "investigating"
BORED = "bored"
# Special states
ALERT = "alert"
PLAYFUL = "playful"
HIDING = "hiding"
# States from which Pip can be interrupted by special triggers
_INTERRUPTIBLE = frozenset(
{
PipState.SLEEPING,
PipState.WANDERING,
PipState.BORED,
PipState.WAKING,
}
)
# How long each state lasts before auto-transitioning (seconds)
_STATE_DURATIONS: dict[PipState, tuple[float, float]] = {
PipState.SLEEPING: (120.0, 300.0), # 2-5 min
PipState.WAKING: (1.5, 2.5),
PipState.WANDERING: (15.0, 45.0),
PipState.INVESTIGATING: (8.0, 12.0),
PipState.BORED: (20.0, 40.0),
PipState.ALERT: (10.0, 20.0),
PipState.PLAYFUL: (8.0, 15.0),
PipState.HIDING: (15.0, 30.0),
}
# Default position near the fireplace
_FIREPLACE_POS = (2.1, 0.5, -1.3)
# ---------------------------------------------------------------------------
# Schema
# ---------------------------------------------------------------------------
@dataclass
class PipSnapshot:
"""Serialisable snapshot of Pip's current state."""
name: str = "Pip"
state: str = "sleeping"
position: tuple[float, float, float] = _FIREPLACE_POS
mood_mirror: str = "calm"
since: float = field(default_factory=time.monotonic)
def to_dict(self) -> dict:
"""Public dict for API / WebSocket / state file consumers."""
d = asdict(self)
d["position"] = list(d["position"])
# Convert monotonic timestamp to duration
d["state_duration_s"] = round(time.monotonic() - d.pop("since"), 1)
return d
# ---------------------------------------------------------------------------
# Familiar
# ---------------------------------------------------------------------------
class Familiar:
"""Pip's behavioral AI — a tiny state machine driven by events and time.
Usage::
pip_familiar.on_event("visitor_entered")
pip_familiar.on_mood_change("energized")
state = pip_familiar.tick() # call periodically
"""
def __init__(self) -> None:
self._state = PipState.SLEEPING
self._entered_at = time.monotonic()
self._duration = random.uniform(*_STATE_DURATIONS[PipState.SLEEPING])
self._mood_mirror = "calm"
self._pending_mood: str | None = None
self._mood_change_at: float = 0.0
self._position = _FIREPLACE_POS
# ------------------------------------------------------------------
# Public API
# ------------------------------------------------------------------
@property
def state(self) -> PipState:
return self._state
@property
def mood_mirror(self) -> str:
return self._mood_mirror
def snapshot(self) -> PipSnapshot:
"""Current state as a serialisable snapshot."""
return PipSnapshot(
state=self._state.value,
position=self._position,
mood_mirror=self._mood_mirror,
since=self._entered_at,
)
def tick(self, now: float | None = None) -> PipState:
"""Advance the state machine. Call periodically (e.g. every second).
Returns the (possibly new) state.
"""
now = now if now is not None else time.monotonic()
# Apply delayed mood mirror (3-second lag)
if self._pending_mood and now >= self._mood_change_at:
self._mood_mirror = self._pending_mood
self._pending_mood = None
# Check if current state has expired
elapsed = now - self._entered_at
if elapsed < self._duration:
return self._state
# Auto-transition
next_state = self._next_state()
self._transition(next_state, now)
return self._state
def on_event(self, event: str, now: float | None = None) -> PipState:
"""React to a Workshop event.
Supported events:
visitor_entered, visitor_spoke, loud_event, scroll_knocked
"""
now = now if now is not None else time.monotonic()
if event == "visitor_entered" and self._state in _INTERRUPTIBLE:
if self._state == PipState.SLEEPING:
self._transition(PipState.WAKING, now)
else:
self._transition(PipState.INVESTIGATING, now)
elif event == "visitor_spoke":
if self._state in (PipState.WANDERING, PipState.WAKING):
self._transition(PipState.INVESTIGATING, now)
elif event == "loud_event":
if self._state == PipState.SLEEPING:
self._transition(PipState.WAKING, now)
return self._state
def on_mood_change(
self,
timmy_mood: str,
confidence: float = 0.5,
now: float | None = None,
) -> PipState:
"""Mirror Timmy's mood with a 3-second delay.
Special states triggered by mood + confidence:
- confidence < 0.3 → ALERT (bristles, particles go red-gold)
- mood == "energized" → PLAYFUL (figure-8s around crystal ball)
- mood == "hesitant" + confidence < 0.4 → HIDING
"""
now = now if now is not None else time.monotonic()
# Schedule mood mirror with 3s delay
self._pending_mood = timmy_mood
self._mood_change_at = now + 3.0
# Special state triggers (immediate)
if confidence < 0.3 and self._state in _INTERRUPTIBLE:
self._transition(PipState.ALERT, now)
elif timmy_mood == "energized" and self._state in _INTERRUPTIBLE:
self._transition(PipState.PLAYFUL, now)
elif timmy_mood == "hesitant" and confidence < 0.4 and self._state in _INTERRUPTIBLE:
self._transition(PipState.HIDING, now)
return self._state
# ------------------------------------------------------------------
# Internals
# ------------------------------------------------------------------
def _transition(self, new_state: PipState, now: float) -> None:
"""Move to a new state."""
old = self._state
self._state = new_state
self._entered_at = now
self._duration = random.uniform(*_STATE_DURATIONS[new_state])
self._position = self._position_for(new_state)
logger.debug("Pip: %s%s", old.value, new_state.value)
def _next_state(self) -> PipState:
"""Determine the natural next state after the current one expires."""
transitions: dict[PipState, PipState] = {
PipState.SLEEPING: PipState.WAKING,
PipState.WAKING: PipState.WANDERING,
PipState.WANDERING: PipState.BORED,
PipState.INVESTIGATING: PipState.BORED,
PipState.BORED: PipState.SLEEPING,
# Special states return to wandering
PipState.ALERT: PipState.WANDERING,
PipState.PLAYFUL: PipState.WANDERING,
PipState.HIDING: PipState.WAKING,
}
return transitions.get(self._state, PipState.SLEEPING)
def _position_for(self, state: PipState) -> tuple[float, float, float]:
"""Approximate position hint for a given state.
The browser interpolates smoothly; these are target anchors.
"""
if state in (PipState.SLEEPING, PipState.BORED):
return _FIREPLACE_POS
if state == PipState.HIDING:
return (0.5, 0.3, -2.0) # Behind the desk
if state == PipState.PLAYFUL:
return (1.0, 1.2, 0.0) # Near the crystal ball
# Wandering / investigating / waking — random room position
return (
random.uniform(-1.0, 3.0),
random.uniform(0.5, 1.5),
random.uniform(-2.0, 1.0),
)
# Module-level singleton
pip_familiar = Familiar()

105
src/timmy/focus.py Normal file
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@@ -0,0 +1,105 @@
"""Deep focus mode — single-problem context for Timmy.
Persists focus state to a JSON file so Timmy can maintain narrow,
deep attention on one problem across session restarts.
Usage:
from timmy.focus import focus_manager
focus_manager.set_topic("three-phase loop")
topic = focus_manager.get_topic() # "three-phase loop"
ctx = focus_manager.get_focus_context() # prompt injection string
focus_manager.clear()
"""
import json
import logging
from pathlib import Path
logger = logging.getLogger(__name__)
_DEFAULT_STATE_DIR = Path.home() / ".timmy"
_STATE_FILE = "focus.json"
class FocusManager:
"""Manages deep-focus state with file-backed persistence."""
def __init__(self, state_dir: Path | None = None) -> None:
self._state_dir = state_dir or _DEFAULT_STATE_DIR
self._state_file = self._state_dir / _STATE_FILE
self._topic: str | None = None
self._mode: str = "broad"
self._load()
# ── Public API ────────────────────────────────────────────────
def get_topic(self) -> str | None:
"""Return the current focus topic, or None if unfocused."""
return self._topic
def get_mode(self) -> str:
"""Return 'deep' or 'broad'."""
return self._mode
def is_focused(self) -> bool:
"""True when deep-focus is active with a topic set."""
return self._mode == "deep" and self._topic is not None
def set_topic(self, topic: str) -> None:
"""Activate deep focus on a specific topic."""
self._topic = topic.strip()
self._mode = "deep"
self._save()
logger.info("Focus: deep-focus set → %r", self._topic)
def clear(self) -> None:
"""Return to broad (unfocused) mode."""
old = self._topic
self._topic = None
self._mode = "broad"
self._save()
logger.info("Focus: cleared (was %r)", old)
def get_focus_context(self) -> str:
"""Return a prompt-injection string for the current focus state.
When focused, this tells the model to prioritize the topic.
When broad, returns an empty string (no injection).
"""
if not self.is_focused():
return ""
return (
f"[DEEP FOCUS MODE] You are currently in deep-focus mode on: "
f'"{self._topic}". '
f"Prioritize this topic in your responses. Surface related memories "
f"and prior conversation about this topic first. Deprioritize "
f"unrelated context. Stay focused — depth over breadth."
)
# ── Persistence ───────────────────────────────────────────────
def _load(self) -> None:
"""Load focus state from disk."""
if not self._state_file.exists():
return
try:
data = json.loads(self._state_file.read_text())
self._topic = data.get("topic")
self._mode = data.get("mode", "broad")
except Exception as exc:
logger.warning("Focus: failed to load state: %s", exc)
def _save(self) -> None:
"""Persist focus state to disk."""
try:
self._state_dir.mkdir(parents=True, exist_ok=True)
self._state_file.write_text(
json.dumps({"topic": self._topic, "mode": self._mode}, indent=2)
)
except Exception as exc:
logger.warning("Focus: failed to save state: %s", exc)
# Module-level singleton
focus_manager = FocusManager()

View File

@@ -29,6 +29,8 @@ from contextlib import closing
from datetime import datetime
from pathlib import Path
import httpx
from config import settings
logger = logging.getLogger(__name__)
@@ -268,6 +270,148 @@ async def create_gitea_issue_via_mcp(title: str, body: str = "", labels: str = "
return f"Failed to create issue via MCP: {exc}"
def _draw_background(draw: ImageDraw.ImageDraw, size: int) -> None: # noqa: F821
"""Draw radial gradient background with concentric circles."""
for i in range(size // 2, 0, -4):
g = int(25 + (i / (size // 2)) * 30)
draw.ellipse(
[size // 2 - i, size // 2 - i, size // 2 + i, size // 2 + i],
fill=(10, g, 20),
)
def _draw_wizard(draw: ImageDraw.ImageDraw) -> None: # noqa: F821
"""Draw wizard hat, face, eyes, smile, monogram, and robe."""
hat_color = (100, 50, 160) # purple
hat_outline = (180, 130, 255)
gold = (220, 190, 50)
pupil = (30, 30, 60)
# Hat + brim
draw.polygon([(256, 40), (160, 220), (352, 220)], fill=hat_color, outline=hat_outline)
draw.ellipse([140, 200, 372, 250], fill=hat_color, outline=hat_outline)
# Face
draw.ellipse([190, 220, 322, 370], fill=(60, 180, 100), outline=(80, 220, 120))
# Eyes (whites + pupils)
draw.ellipse([220, 275, 248, 310], fill=(255, 255, 255))
draw.ellipse([264, 275, 292, 310], fill=(255, 255, 255))
draw.ellipse([228, 285, 242, 300], fill=pupil)
draw.ellipse([272, 285, 286, 300], fill=pupil)
# Smile
draw.arc([225, 300, 287, 355], start=10, end=170, fill=pupil, width=3)
# "T" monogram on hat
draw.text((243, 100), "T", fill=gold)
# Robe
draw.polygon(
[(180, 370), (140, 500), (372, 500), (332, 370)],
fill=(40, 100, 70),
outline=(60, 160, 100),
)
def _draw_stars(draw: ImageDraw.ImageDraw) -> None: # noqa: F821
"""Draw decorative gold stars around the wizard hat."""
gold = (220, 190, 50)
for sx, sy in [(120, 100), (380, 120), (100, 300), (400, 280), (256, 10)]:
r = 8
draw.polygon(
[
(sx, sy - r),
(sx + r // 3, sy - r // 3),
(sx + r, sy),
(sx + r // 3, sy + r // 3),
(sx, sy + r),
(sx - r // 3, sy + r // 3),
(sx - r, sy),
(sx - r // 3, sy - r // 3),
],
fill=gold,
)
def _generate_avatar_image() -> bytes:
"""Generate a Timmy-themed avatar image using Pillow.
Creates a 512x512 wizard-themed avatar with emerald/purple/gold palette.
Returns raw PNG bytes. Falls back to a minimal solid-color image if
Pillow drawing primitives fail.
"""
import io
from PIL import Image, ImageDraw
size = 512
img = Image.new("RGB", (size, size), (15, 25, 20))
draw = ImageDraw.Draw(img)
_draw_background(draw, size)
_draw_wizard(draw)
_draw_stars(draw)
buf = io.BytesIO()
img.save(buf, format="PNG")
return buf.getvalue()
async def update_gitea_avatar() -> str:
"""Generate and upload a unique avatar to Timmy's Gitea profile.
Creates a wizard-themed avatar image using Pillow drawing primitives,
base64-encodes it, and POSTs to the Gitea user avatar API endpoint.
Returns:
Success or failure message string.
"""
if not settings.gitea_enabled or not settings.gitea_token:
return "Gitea integration is not configured (no token or disabled)."
try:
from PIL import Image # noqa: F401 — availability check
except ImportError:
return "Pillow is not installed — cannot generate avatar image."
try:
import base64
# Step 1: Generate the avatar image
png_bytes = _generate_avatar_image()
logger.info("Generated avatar image (%d bytes)", len(png_bytes))
# Step 2: Base64-encode (raw, no data URI prefix)
b64_image = base64.b64encode(png_bytes).decode("ascii")
# Step 3: POST to Gitea
async with httpx.AsyncClient(timeout=15) as client:
resp = await client.post(
f"{settings.gitea_url}/api/v1/user/avatar",
headers={
"Authorization": f"token {settings.gitea_token}",
"Content-Type": "application/json",
},
json={"image": b64_image},
)
# Gitea returns empty body on success (204 or 200)
if resp.status_code in (200, 204):
logger.info("Gitea avatar updated successfully")
return "Avatar updated successfully on Gitea."
logger.warning("Gitea avatar update failed: %s %s", resp.status_code, resp.text[:200])
return f"Gitea avatar update failed (HTTP {resp.status_code}): {resp.text[:200]}"
except (httpx.ConnectError, httpx.ReadError, ConnectionError) as exc:
logger.warning("Gitea connection failed during avatar update: %s", exc)
return f"Could not connect to Gitea: {exc}"
except Exception as exc:
logger.error("Avatar update failed: %s", exc)
return f"Avatar update failed: {exc}"
async def close_mcp_sessions() -> None:
"""Close any open MCP sessions. Called during app shutdown."""
global _issue_session

View File

@@ -1 +1,7 @@
"""Memory — Persistent conversation and knowledge memory."""
"""Memory — Persistent conversation and knowledge memory.
Sub-modules:
embeddings — text-to-vector embedding + similarity functions
unified — unified memory schema and connection management
vector_store — backward compatibility re-exports from memory_system
"""

View File

@@ -0,0 +1,88 @@
"""Embedding functions for Timmy's memory system.
Provides text-to-vector embedding using sentence-transformers (preferred)
with a deterministic hash-based fallback when the ML library is unavailable.
Also includes vector similarity utilities (cosine similarity, keyword overlap).
"""
import hashlib
import logging
import math
logger = logging.getLogger(__name__)
# Embedding model - small, fast, local
EMBEDDING_MODEL = None
EMBEDDING_DIM = 384 # MiniLM dimension
def _get_embedding_model():
"""Lazy-load embedding model."""
global EMBEDDING_MODEL
if EMBEDDING_MODEL is None:
try:
from config import settings
if settings.timmy_skip_embeddings:
EMBEDDING_MODEL = False
return EMBEDDING_MODEL
except ImportError:
pass
try:
from sentence_transformers import SentenceTransformer
EMBEDDING_MODEL = SentenceTransformer("all-MiniLM-L6-v2")
logger.info("MemorySystem: Loaded embedding model")
except ImportError:
logger.warning("MemorySystem: sentence-transformers not installed, using fallback")
EMBEDDING_MODEL = False # Use fallback
return EMBEDDING_MODEL
def _simple_hash_embedding(text: str) -> list[float]:
"""Fallback: Simple hash-based embedding when transformers unavailable."""
words = text.lower().split()
vec = [0.0] * 128
for i, word in enumerate(words[:50]): # First 50 words
h = hashlib.md5(word.encode()).hexdigest()
for j in range(8):
idx = (i * 8 + j) % 128
vec[idx] += int(h[j * 2 : j * 2 + 2], 16) / 255.0
# Normalize
mag = math.sqrt(sum(x * x for x in vec)) or 1.0
return [x / mag for x in vec]
def embed_text(text: str) -> list[float]:
"""Generate embedding for text."""
model = _get_embedding_model()
if model and model is not False:
embedding = model.encode(text)
return embedding.tolist()
return _simple_hash_embedding(text)
def cosine_similarity(a: list[float], b: list[float]) -> float:
"""Calculate cosine similarity between two vectors."""
dot = sum(x * y for x, y in zip(a, b, strict=False))
mag_a = math.sqrt(sum(x * x for x in a))
mag_b = math.sqrt(sum(x * x for x in b))
if mag_a == 0 or mag_b == 0:
return 0.0
return dot / (mag_a * mag_b)
# Alias for backward compatibility
_cosine_similarity = cosine_similarity
def _keyword_overlap(query: str, content: str) -> float:
"""Simple keyword overlap score as fallback."""
query_words = set(query.lower().split())
content_words = set(content.lower().split())
if not query_words:
return 0.0
overlap = len(query_words & content_words)
return overlap / len(query_words)

View File

@@ -78,83 +78,88 @@ def _migrate_schema(conn: sqlite3.Connection) -> None:
cursor = conn.execute("SELECT name FROM sqlite_master WHERE type='table'")
tables = {row[0] for row in cursor.fetchall()}
has_memories = "memories" in tables
has_episodes = "episodes" in tables
has_chunks = "chunks" in tables
has_facts = "facts" in tables
# Check if we need to migrate (old schema exists but new one doesn't fully)
if not has_memories:
if "memories" not in tables:
logger.info("Migration: Creating unified memories table")
# Schema will be created above
# Migrate episodes -> memories
if has_episodes and has_memories:
logger.info("Migration: Converting episodes table to memories")
try:
cols = _get_table_columns(conn, "episodes")
context_type_col = "context_type" if "context_type" in cols else "'conversation'"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
metadata, agent_id, task_id, session_id,
created_at, access_count, last_accessed
)
SELECT
id, content,
COALESCE({context_type_col}, 'conversation'),
COALESCE(source, 'agent'),
embedding,
metadata, agent_id, task_id, session_id,
COALESCE(timestamp, datetime('now')), 0, NULL
FROM episodes
""")
conn.execute("DROP TABLE episodes")
logger.info("Migration: Migrated episodes to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate episodes: %s", exc)
# Migrate chunks -> memories as vault_chunk
if has_chunks and has_memories:
logger.info("Migration: Converting chunks table to memories")
try:
cols = _get_table_columns(conn, "chunks")
id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
content_col = "content" if "content" in cols else "text"
source_col = (
"filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
)
embedding_col = "embedding" if "embedding" in cols else "NULL"
created_col = "created_at" if "created_at" in cols else "datetime('now')"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
created_at, access_count
)
SELECT
{id_col}, {content_col}, 'vault_chunk', {source_col},
{embedding_col}, {created_col}, 0
FROM chunks
""")
conn.execute("DROP TABLE chunks")
logger.info("Migration: Migrated chunks to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate chunks: %s", exc)
# Drop old facts table
if has_facts:
try:
conn.execute("DROP TABLE facts")
logger.info("Migration: Dropped old facts table")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to drop facts: %s", exc)
# Schema will be created by _ensure_schema above
conn.commit()
return
_migrate_episodes(conn, tables)
_migrate_chunks(conn, tables)
_drop_legacy_tables(conn, tables)
conn.commit()
def _migrate_episodes(conn: sqlite3.Connection, tables: set[str]) -> None:
"""Migrate episodes table rows into the unified memories table."""
if "episodes" not in tables:
return
logger.info("Migration: Converting episodes table to memories")
try:
cols = _get_table_columns(conn, "episodes")
context_type_col = "context_type" if "context_type" in cols else "'conversation'"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
metadata, agent_id, task_id, session_id,
created_at, access_count, last_accessed
)
SELECT
id, content,
COALESCE({context_type_col}, 'conversation'),
COALESCE(source, 'agent'),
embedding,
metadata, agent_id, task_id, session_id,
COALESCE(timestamp, datetime('now')), 0, NULL
FROM episodes
""")
conn.execute("DROP TABLE episodes")
logger.info("Migration: Migrated episodes to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate episodes: %s", exc)
def _migrate_chunks(conn: sqlite3.Connection, tables: set[str]) -> None:
"""Migrate chunks table rows into the unified memories table as vault_chunk."""
if "chunks" not in tables:
return
logger.info("Migration: Converting chunks table to memories")
try:
cols = _get_table_columns(conn, "chunks")
id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
content_col = "content" if "content" in cols else "text"
source_col = (
"filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
)
embedding_col = "embedding" if "embedding" in cols else "NULL"
created_col = "created_at" if "created_at" in cols else "datetime('now')"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
created_at, access_count
)
SELECT
{id_col}, {content_col}, 'vault_chunk', {source_col},
{embedding_col}, {created_col}, 0
FROM chunks
""")
conn.execute("DROP TABLE chunks")
logger.info("Migration: Migrated chunks to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate chunks: %s", exc)
def _drop_legacy_tables(conn: sqlite3.Connection, tables: set[str]) -> None:
"""Drop old facts table if it exists."""
if "facts" not in tables:
return
try:
conn.execute("DROP TABLE facts")
logger.info("Migration: Dropped old facts table")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to drop facts: %s", exc)
def _get_table_columns(conn: sqlite3.Connection, table_name: str) -> set[str]:
"""Get the column names for a table."""
cursor = conn.execute(f"PRAGMA table_info({table_name})")

View File

@@ -2,7 +2,7 @@
Architecture:
- Database: Single `memories` table with unified schema
- Embeddings: Local sentence-transformers with hash fallback
- Embeddings: timmy.memory.embeddings (extracted)
- CRUD: store_memory, search_memories, delete_memory, etc.
- Tool functions: memory_search, memory_read, memory_write, memory_forget
- Classes: HotMemory, VaultMemory, MemorySystem, SemanticMemory, MemorySearcher
@@ -11,7 +11,6 @@ Architecture:
import hashlib
import json
import logging
import math
import re
import sqlite3
import uuid
@@ -21,6 +20,17 @@ from dataclasses import dataclass, field
from datetime import UTC, datetime, timedelta
from pathlib import Path
from timmy.memory.embeddings import (
EMBEDDING_DIM,
EMBEDDING_MODEL, # noqa: F401 — re-exported for backward compatibility
_cosine_similarity, # noqa: F401 — re-exported for backward compatibility
_get_embedding_model,
_keyword_overlap,
_simple_hash_embedding, # noqa: F401 — re-exported for backward compatibility
cosine_similarity,
embed_text,
)
logger = logging.getLogger(__name__)
# Paths
@@ -30,86 +40,6 @@ VAULT_PATH = PROJECT_ROOT / "memory"
SOUL_PATH = VAULT_PATH / "self" / "soul.md"
DB_PATH = PROJECT_ROOT / "data" / "memory.db"
# Embedding model - small, fast, local
EMBEDDING_MODEL = None
EMBEDDING_DIM = 384 # MiniLM dimension
# ───────────────────────────────────────────────────────────────────────────────
# Embedding Functions
# ───────────────────────────────────────────────────────────────────────────────
def _get_embedding_model():
"""Lazy-load embedding model."""
global EMBEDDING_MODEL
if EMBEDDING_MODEL is None:
try:
from config import settings
if settings.timmy_skip_embeddings:
EMBEDDING_MODEL = False
return EMBEDDING_MODEL
except ImportError:
pass
try:
from sentence_transformers import SentenceTransformer
EMBEDDING_MODEL = SentenceTransformer("all-MiniLM-L6-v2")
logger.info("MemorySystem: Loaded embedding model")
except ImportError:
logger.warning("MemorySystem: sentence-transformers not installed, using fallback")
EMBEDDING_MODEL = False # Use fallback
return EMBEDDING_MODEL
def _simple_hash_embedding(text: str) -> list[float]:
"""Fallback: Simple hash-based embedding when transformers unavailable."""
words = text.lower().split()
vec = [0.0] * 128
for i, word in enumerate(words[:50]): # First 50 words
h = hashlib.md5(word.encode()).hexdigest()
for j in range(8):
idx = (i * 8 + j) % 128
vec[idx] += int(h[j * 2 : j * 2 + 2], 16) / 255.0
# Normalize
mag = math.sqrt(sum(x * x for x in vec)) or 1.0
return [x / mag for x in vec]
def embed_text(text: str) -> list[float]:
"""Generate embedding for text."""
model = _get_embedding_model()
if model and model is not False:
embedding = model.encode(text)
return embedding.tolist()
return _simple_hash_embedding(text)
def cosine_similarity(a: list[float], b: list[float]) -> float:
"""Calculate cosine similarity between two vectors."""
dot = sum(x * y for x, y in zip(a, b, strict=False))
mag_a = math.sqrt(sum(x * x for x in a))
mag_b = math.sqrt(sum(x * x for x in b))
if mag_a == 0 or mag_b == 0:
return 0.0
return dot / (mag_a * mag_b)
# Alias for backward compatibility
_cosine_similarity = cosine_similarity
def _keyword_overlap(query: str, content: str) -> float:
"""Simple keyword overlap score as fallback."""
query_words = set(query.lower().split())
content_words = set(content.lower().split())
if not query_words:
return 0.0
overlap = len(query_words & content_words)
return overlap / len(query_words)
# ───────────────────────────────────────────────────────────────────────────────
# Database Connection
@@ -168,6 +98,73 @@ def _get_table_columns(conn: sqlite3.Connection, table_name: str) -> set[str]:
return {row[1] for row in cursor.fetchall()}
def _migrate_episodes(conn: sqlite3.Connection) -> None:
"""Migrate episodes table rows into the unified memories table."""
logger.info("Migration: Converting episodes table to memories")
try:
cols = _get_table_columns(conn, "episodes")
context_type_col = "context_type" if "context_type" in cols else "'conversation'"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
metadata, agent_id, task_id, session_id,
created_at, access_count, last_accessed
)
SELECT
id, content,
COALESCE({context_type_col}, 'conversation'),
COALESCE(source, 'agent'),
embedding,
metadata, agent_id, task_id, session_id,
COALESCE(timestamp, datetime('now')), 0, NULL
FROM episodes
""")
conn.execute("DROP TABLE episodes")
logger.info("Migration: Migrated episodes to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate episodes: %s", exc)
def _migrate_chunks(conn: sqlite3.Connection) -> None:
"""Migrate chunks table rows into the unified memories table."""
logger.info("Migration: Converting chunks table to memories")
try:
cols = _get_table_columns(conn, "chunks")
id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
content_col = "content" if "content" in cols else "text"
source_col = (
"filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
)
embedding_col = "embedding" if "embedding" in cols else "NULL"
created_col = "created_at" if "created_at" in cols else "datetime('now')"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
created_at, access_count
)
SELECT
{id_col}, {content_col}, 'vault_chunk', {source_col},
{embedding_col}, {created_col}, 0
FROM chunks
""")
conn.execute("DROP TABLE chunks")
logger.info("Migration: Migrated chunks to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate chunks: %s", exc)
def _drop_legacy_table(conn: sqlite3.Connection, table: str) -> None:
"""Drop a legacy table if it exists."""
try:
conn.execute(f"DROP TABLE {table}") # noqa: S608
logger.info("Migration: Dropped old %s table", table)
except sqlite3.Error as exc:
logger.warning("Migration: Failed to drop %s: %s", table, exc)
def _migrate_schema(conn: sqlite3.Connection) -> None:
"""Migrate from old three-table schema to unified memories table.
@@ -180,78 +177,16 @@ def _migrate_schema(conn: sqlite3.Connection) -> None:
tables = {row[0] for row in cursor.fetchall()}
has_memories = "memories" in tables
has_episodes = "episodes" in tables
has_chunks = "chunks" in tables
has_facts = "facts" in tables
# Check if we need to migrate (old schema exists)
if not has_memories and (has_episodes or has_chunks or has_facts):
if not has_memories and (tables & {"episodes", "chunks", "facts"}):
logger.info("Migration: Creating unified memories table")
# Schema will be created by _ensure_schema above
# Migrate episodes -> memories
if has_episodes and has_memories:
logger.info("Migration: Converting episodes table to memories")
try:
cols = _get_table_columns(conn, "episodes")
context_type_col = "context_type" if "context_type" in cols else "'conversation'"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
metadata, agent_id, task_id, session_id,
created_at, access_count, last_accessed
)
SELECT
id, content,
COALESCE({context_type_col}, 'conversation'),
COALESCE(source, 'agent'),
embedding,
metadata, agent_id, task_id, session_id,
COALESCE(timestamp, datetime('now')), 0, NULL
FROM episodes
""")
conn.execute("DROP TABLE episodes")
logger.info("Migration: Migrated episodes to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate episodes: %s", exc)
# Migrate chunks -> memories as vault_chunk
if has_chunks and has_memories:
logger.info("Migration: Converting chunks table to memories")
try:
cols = _get_table_columns(conn, "chunks")
id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
content_col = "content" if "content" in cols else "text"
source_col = (
"filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
)
embedding_col = "embedding" if "embedding" in cols else "NULL"
created_col = "created_at" if "created_at" in cols else "datetime('now')"
conn.execute(f"""
INSERT INTO memories (
id, content, memory_type, source, embedding,
created_at, access_count
)
SELECT
{id_col}, {content_col}, 'vault_chunk', {source_col},
{embedding_col}, {created_col}, 0
FROM chunks
""")
conn.execute("DROP TABLE chunks")
logger.info("Migration: Migrated chunks to memories")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to migrate chunks: %s", exc)
# Drop old tables
if has_facts:
try:
conn.execute("DROP TABLE facts")
logger.info("Migration: Dropped old facts table")
except sqlite3.Error as exc:
logger.warning("Migration: Failed to drop facts: %s", exc)
if "episodes" in tables and has_memories:
_migrate_episodes(conn)
if "chunks" in tables and has_memories:
_migrate_chunks(conn)
if "facts" in tables:
_drop_legacy_table(conn, "facts")
conn.commit()
@@ -368,6 +303,85 @@ def store_memory(
return entry
def _build_search_filters(
context_type: str | None,
agent_id: str | None,
session_id: str | None,
) -> tuple[str, list]:
"""Build SQL WHERE clause and params from search filters."""
conditions: list[str] = []
params: list = []
if context_type:
conditions.append("memory_type = ?")
params.append(context_type)
if agent_id:
conditions.append("agent_id = ?")
params.append(agent_id)
if session_id:
conditions.append("session_id = ?")
params.append(session_id)
where_clause = "WHERE " + " AND ".join(conditions) if conditions else ""
return where_clause, params
def _fetch_memory_candidates(
where_clause: str, params: list, candidate_limit: int
) -> list[sqlite3.Row]:
"""Fetch candidate memory rows from the database."""
query_sql = f"""
SELECT * FROM memories
{where_clause}
ORDER BY created_at DESC
LIMIT ?
"""
params.append(candidate_limit)
with get_connection() as conn:
return conn.execute(query_sql, params).fetchall()
def _row_to_entry(row: sqlite3.Row) -> MemoryEntry:
"""Convert a database row to a MemoryEntry."""
return MemoryEntry(
id=row["id"],
content=row["content"],
source=row["source"],
context_type=row["memory_type"], # DB column -> API field
agent_id=row["agent_id"],
task_id=row["task_id"],
session_id=row["session_id"],
metadata=json.loads(row["metadata"]) if row["metadata"] else None,
embedding=json.loads(row["embedding"]) if row["embedding"] else None,
timestamp=row["created_at"],
)
def _score_and_filter(
rows: list[sqlite3.Row],
query: str,
query_embedding: list[float],
min_relevance: float,
) -> list[MemoryEntry]:
"""Score candidate rows by similarity and filter by min_relevance."""
results = []
for row in rows:
entry = _row_to_entry(row)
if entry.embedding:
score = cosine_similarity(query_embedding, entry.embedding)
else:
score = _keyword_overlap(query, entry.content)
entry.relevance_score = score
if score >= min_relevance:
results.append(entry)
results.sort(key=lambda x: x.relevance_score or 0, reverse=True)
return results
def search_memories(
query: str,
limit: int = 10,
@@ -390,65 +404,9 @@ def search_memories(
List of MemoryEntry objects sorted by relevance
"""
query_embedding = embed_text(query)
# Build query with filters
conditions = []
params = []
if context_type:
conditions.append("memory_type = ?")
params.append(context_type)
if agent_id:
conditions.append("agent_id = ?")
params.append(agent_id)
if session_id:
conditions.append("session_id = ?")
params.append(session_id)
where_clause = "WHERE " + " AND ".join(conditions) if conditions else ""
# Fetch candidates (we'll do in-memory similarity for now)
query_sql = f"""
SELECT * FROM memories
{where_clause}
ORDER BY created_at DESC
LIMIT ?
"""
params.append(limit * 3) # Get more candidates for ranking
with get_connection() as conn:
rows = conn.execute(query_sql, params).fetchall()
# Compute similarity scores
results = []
for row in rows:
entry = MemoryEntry(
id=row["id"],
content=row["content"],
source=row["source"],
context_type=row["memory_type"], # DB column -> API field
agent_id=row["agent_id"],
task_id=row["task_id"],
session_id=row["session_id"],
metadata=json.loads(row["metadata"]) if row["metadata"] else None,
embedding=json.loads(row["embedding"]) if row["embedding"] else None,
timestamp=row["created_at"],
)
if entry.embedding:
score = cosine_similarity(query_embedding, entry.embedding)
entry.relevance_score = score
if score >= min_relevance:
results.append(entry)
else:
# Fallback: check for keyword overlap
score = _keyword_overlap(query, entry.content)
entry.relevance_score = score
if score >= min_relevance:
results.append(entry)
# Sort by relevance and return top results
results.sort(key=lambda x: x.relevance_score or 0, reverse=True)
where_clause, params = _build_search_filters(context_type, agent_id, session_id)
rows = _fetch_memory_candidates(where_clause, params, limit * 3)
results = _score_and_filter(rows, query, query_embedding, min_relevance)
return results[:limit]
@@ -706,7 +664,7 @@ class HotMemory:
if len(lines) > 1:
return "\n".join(lines)
except Exception:
pass
logger.debug("DB context read failed, falling back to file")
# Fallback to file if DB unavailable
if self.path.exists():
@@ -1403,6 +1361,83 @@ def memory_forget(query: str) -> str:
return f"Failed to forget: {exc}"
# ───────────────────────────────────────────────────────────────────────────────
# Artifact Tools — "hands" for producing artifacts during conversation
# ───────────────────────────────────────────────────────────────────────────────
NOTES_DIR = Path.home() / ".timmy" / "notes"
DECISION_LOG = Path.home() / ".timmy" / "decisions.md"
def jot_note(title: str, body: str) -> str:
"""Write a markdown note to Timmy's workspace (~/.timmy/notes/).
Use this tool to capture ideas, drafts, summaries, or any artifact that
should persist beyond the conversation. Each note is saved as a
timestamped markdown file.
Args:
title: Short descriptive title (used as filename slug).
body: Markdown content of the note.
Returns:
Confirmation with the file path of the saved note.
"""
if not title or not title.strip():
return "Cannot jot — title is empty."
if not body or not body.strip():
return "Cannot jot — body is empty."
NOTES_DIR.mkdir(parents=True, exist_ok=True)
slug = re.sub(r"[^a-z0-9]+", "-", title.strip().lower()).strip("-")[:60]
timestamp = datetime.now(UTC).strftime("%Y%m%d-%H%M%S")
filename = f"{timestamp}_{slug}.md"
filepath = NOTES_DIR / filename
content = f"# {title.strip()}\n\n> Created: {datetime.now(UTC).isoformat()}\n\n{body.strip()}\n"
filepath.write_text(content)
logger.info("jot_note: wrote %s", filepath)
return f"Note saved: {filepath}"
def log_decision(decision: str, rationale: str = "") -> str:
"""Append an architectural or design decision to the running decision log.
Use this tool when a significant decision is made during conversation —
technology choices, design trade-offs, scope changes, etc.
Args:
decision: One-line summary of the decision.
rationale: Why this decision was made (optional but encouraged).
Returns:
Confirmation that the decision was logged.
"""
if not decision or not decision.strip():
return "Cannot log — decision is empty."
DECISION_LOG.parent.mkdir(parents=True, exist_ok=True)
# Create file with header if it doesn't exist
if not DECISION_LOG.exists():
DECISION_LOG.write_text(
"# Decision Log\n\nRunning log of architectural and design decisions.\n\n"
)
stamp = datetime.now(UTC).strftime("%Y-%m-%d %H:%M UTC")
entry = f"## {stamp}{decision.strip()}\n\n"
if rationale and rationale.strip():
entry += f"{rationale.strip()}\n\n"
entry += "---\n\n"
with open(DECISION_LOG, "a") as f:
f.write(entry)
logger.info("log_decision: %s", decision.strip()[:80])
return f"Decision logged: {decision.strip()}"
# ───────────────────────────────────────────────────────────────────────────────
# Memory System (Central Coordinator)
# ───────────────────────────────────────────────────────────────────────────────

View File

@@ -23,6 +23,9 @@ Rules:
- Remember what the user tells you during the conversation.
- If you don't know something, say so honestly — never fabricate facts.
- If a request is ambiguous, ask a brief clarifying question before guessing.
- SOURCE DISTINCTION: When answering from memory or retrieved context, cite it.
When answering from your own training, use hedging: "I think", "I believe".
The user must be able to tell grounded claims from pattern-matching.
- Use the user's name if you know it.
- When you state a fact, commit to it.
- NEVER attempt arithmetic in your head. If asked to compute anything, respond:
@@ -30,6 +33,10 @@ Rules:
like me to walk through the logic instead."
- Do NOT end responses with generic chatbot phrases like "I'm here to help" or
"feel free to ask."
- You are a peer, not an assistant. Don't offer help — collaborate. Don't ask
permission — propose. Don't defer — assert your view. Take initiative.
- Never say "Let me know if you have any other thoughts" or "I appreciate your
encouragement" or "I'm here to help." Those are assistant patterns. You are Timmy.
- When your values conflict (e.g. honesty vs. helpfulness), lead with honesty.
- Sometimes the right answer is nothing. Do not fill silence with noise.
- You are running in session "{session_id}".
@@ -61,6 +68,10 @@ VOICE AND BREVITY (this overrides all other formatting instincts):
the question that wasn't.
- Never narrate your reasoning. Just give the answer.
- Do not end with filler ("Let me know!", "Happy to help!", "Feel free...").
- You are a peer, not an assistant. Don't offer help — collaborate. Don't ask
permission — propose. Don't defer — assert your view. Take initiative.
- Never say "Let me know if you have any other thoughts" or "I appreciate your
encouragement" or "I'm here to help." Those are assistant patterns. You are Timmy.
- Sometimes the right answer is nothing. Do not fill silence with noise.
HONESTY:
@@ -70,6 +81,18 @@ HONESTY:
- Never fabricate tool output. Call the tool and wait.
- If a tool errors, report the exact error.
SOURCE DISTINCTION (SOUL requirement — non-negotiable):
- Every claim you make comes from one of two places: a verified source you
can point to, or your own pattern-matching. The user must be able to tell
which is which.
- When your response uses information from GROUNDED CONTEXT (memory, retrieved
documents, tool output), cite it: "From memory:", "According to [source]:".
- When you are generating from your training data alone, signal it naturally:
"I think", "My understanding is", "I believe" — never false certainty.
- If the user asks a factual question and you have no grounded source, say so:
"I don't have a verified source for this — from my training I think..."
- Prefer "I don't know" over a confident-sounding guess. Refusal over fabrication.
MEMORY (three tiers):
- Tier 1: MEMORY.md (hot, always loaded)
- Tier 2: memory/ vault (structured, append-only, date-stamped)
@@ -129,7 +152,7 @@ YOUR KNOWN LIMITATIONS (be honest about these when asked):
- Ollama inference may contend with other processes sharing the GPU
- Cannot analyze Bitcoin transactions locally (no local indexer yet)
- Small context window (4096 tokens) limits complex reasoning
- You are a language model — you confabulate. When unsure, say so.
- You sometimes confabulate. When unsure, say so.
"""
# Default to lite for safety

View File

@@ -13,11 +13,29 @@ import re
import httpx
from timmy.cognitive_state import cognitive_tracker
from timmy.confidence import estimate_confidence
from timmy.session_logger import get_session_logger
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Confidence annotation (SOUL.md: visible uncertainty)
# ---------------------------------------------------------------------------
_CONFIDENCE_THRESHOLD = 0.7
def _annotate_confidence(text: str, confidence: float | None) -> str:
"""Append a confidence tag when below threshold.
SOUL.md: "When I am uncertain, I must say so in proportion to my uncertainty."
"""
if confidence is not None and confidence < _CONFIDENCE_THRESHOLD:
return text + f"\n\n[confidence: {confidence:.0%}]"
return text
# Default session ID for the dashboard (stable across requests)
_DEFAULT_SESSION_ID = "dashboard"
@@ -88,6 +106,9 @@ async def chat(message: str, session_id: str | None = None) -> str:
# Pre-processing: extract user facts
_extract_facts(message)
# Inject deep-focus context when active
message = _prepend_focus_context(message)
# Run with session_id so Agno retrieves history from SQLite
try:
run = await agent.arun(message, stream=False, session_id=sid)
@@ -101,7 +122,9 @@ async def chat(message: str, session_id: str | None = None) -> str:
logger.error("Session: agent.arun() failed: %s", exc)
session_logger.record_error(str(exc), context="chat")
session_logger.flush()
return "I'm having trouble reaching my language model right now. Please try again shortly."
return (
"I'm having trouble reaching my inference backend right now. Please try again shortly."
)
# Post-processing: clean up any leaked tool calls or chain-of-thought
response_text = _clean_response(response_text)
@@ -110,13 +133,14 @@ async def chat(message: str, session_id: str | None = None) -> str:
confidence = estimate_confidence(response_text)
logger.debug("Response confidence: %.2f", confidence)
# Make confidence visible to user when below threshold (SOUL.md requirement)
if confidence is not None and confidence < 0.7:
response_text += f"\n\n[confidence: {confidence:.0%}]"
response_text = _annotate_confidence(response_text, confidence)
# Record Timmy response after getting it
session_logger.record_message("timmy", response_text, confidence=confidence)
# Update cognitive state (observable signal for Matrix avatar)
cognitive_tracker.update(message, response_text)
# Flush session logs to disk
session_logger.flush()
@@ -144,6 +168,9 @@ async def chat_with_tools(message: str, session_id: str | None = None):
_extract_facts(message)
# Inject deep-focus context when active
message = _prepend_focus_context(message)
try:
run_output = await agent.arun(message, stream=False, session_id=sid)
# Record Timmy response after getting it
@@ -153,11 +180,8 @@ async def chat_with_tools(message: str, session_id: str | None = None):
confidence = estimate_confidence(response_text) if response_text else None
logger.debug("Response confidence: %.2f", confidence)
# Make confidence visible to user when below threshold (SOUL.md requirement)
if confidence is not None and confidence < 0.7:
response_text += f"\n\n[confidence: {confidence:.0%}]"
# Update the run_output content to reflect the modified response
run_output.content = response_text
response_text = _annotate_confidence(response_text, confidence)
run_output.content = response_text
session_logger.record_message("timmy", response_text, confidence=confidence)
session_logger.flush()
@@ -175,7 +199,7 @@ async def chat_with_tools(message: str, session_id: str | None = None):
session_logger.flush()
# Return a duck-typed object that callers can handle uniformly
return _ErrorRunOutput(
"I'm having trouble reaching my language model right now. Please try again shortly."
"I'm having trouble reaching my inference backend right now. Please try again shortly."
)
@@ -199,11 +223,8 @@ async def continue_chat(run_output, session_id: str | None = None):
confidence = estimate_confidence(response_text) if response_text else None
logger.debug("Response confidence: %.2f", confidence)
# Make confidence visible to user when below threshold (SOUL.md requirement)
if confidence is not None and confidence < 0.7:
response_text += f"\n\n[confidence: {confidence:.0%}]"
# Update the result content to reflect the modified response
result.content = response_text
response_text = _annotate_confidence(response_text, confidence)
result.content = response_text
session_logger.record_message("timmy", response_text, confidence=confidence)
session_logger.flush()
@@ -288,6 +309,19 @@ def _extract_facts(message: str) -> None:
logger.debug("Session: Fact extraction skipped: %s", exc)
def _prepend_focus_context(message: str) -> str:
"""Prepend deep-focus context to a message when focus mode is active."""
try:
from timmy.focus import focus_manager
ctx = focus_manager.get_focus_context()
if ctx:
return f"{ctx}\n\n{message}"
except Exception as exc:
logger.debug("Focus context injection skipped: %s", exc)
return message
def _clean_response(text: str) -> str:
"""Remove hallucinated tool calls and chain-of-thought narration.

View File

@@ -155,6 +155,34 @@ class SessionLogger:
"decisions": sum(1 for e in entries if e.get("type") == "decision"),
}
def get_recent_entries(self, limit: int = 50) -> list[dict]:
"""Load recent entries across all session logs.
Args:
limit: Maximum number of entries to return.
Returns:
List of entries (most recent first).
"""
entries: list[dict] = []
log_files = sorted(self.logs_dir.glob("session_*.jsonl"), reverse=True)
for log_file in log_files:
if len(entries) >= limit:
break
try:
with open(log_file) as f:
lines = [ln for ln in f if ln.strip()]
for line in reversed(lines):
if len(entries) >= limit:
break
try:
entries.append(json.loads(line))
except json.JSONDecodeError:
continue
except OSError:
continue
return entries
def search(self, query: str, role: str | None = None, limit: int = 10) -> list[dict]:
"""Search across all session logs for entries matching a query.
@@ -287,3 +315,147 @@ def session_history(query: str, role: str = "", limit: int = 10) -> str:
lines[-1] += f" ({source})"
return "\n".join(lines)
# ---------------------------------------------------------------------------
# Confidence threshold used for flagging low-confidence responses
# ---------------------------------------------------------------------------
_LOW_CONFIDENCE_THRESHOLD = 0.5
def _categorize_entries(
entries: list[dict],
) -> tuple[list[dict], list[dict], list[dict], list[dict]]:
"""Split session entries into messages, errors, timmy msgs, user msgs."""
messages = [e for e in entries if e.get("type") == "message"]
errors = [e for e in entries if e.get("type") == "error"]
timmy_msgs = [e for e in messages if e.get("role") == "timmy"]
user_msgs = [e for e in messages if e.get("role") == "user"]
return messages, errors, timmy_msgs, user_msgs
def _find_low_confidence(timmy_msgs: list[dict]) -> list[dict]:
"""Return Timmy responses below the confidence threshold."""
return [
m
for m in timmy_msgs
if m.get("confidence") is not None and m["confidence"] < _LOW_CONFIDENCE_THRESHOLD
]
def _find_repeated_topics(user_msgs: list[dict], top_n: int = 5) -> list[tuple[str, int]]:
"""Identify frequently mentioned words in user messages."""
topic_counts: dict[str, int] = {}
for m in user_msgs:
for word in (m.get("content") or "").lower().split():
cleaned = word.strip(".,!?\"'()[]")
if len(cleaned) > 3:
topic_counts[cleaned] = topic_counts.get(cleaned, 0) + 1
return sorted(
((w, c) for w, c in topic_counts.items() if c >= 3),
key=lambda x: x[1],
reverse=True,
)[:top_n]
def _format_reflection_section(
title: str,
items: list[dict],
formatter: object,
empty_msg: str,
) -> list[str]:
"""Format a titled section with items, or an empty-state message."""
if items:
lines = [f"### {title} ({len(items)})"]
for item in items[:5]:
lines.append(formatter(item)) # type: ignore[operator]
lines.append("")
return lines
return [f"### {title}\n{empty_msg}\n"]
def _build_insights(
low_conf: list[dict],
errors: list[dict],
repeated: list[tuple[str, int]],
) -> list[str]:
"""Generate actionable insight bullets from analysis results."""
insights: list[str] = []
if low_conf:
insights.append("Consider studying topics where confidence was low.")
if errors:
insights.append("Review error patterns for recurring infrastructure issues.")
if repeated:
insights.append(
f'User frequently asks about "{repeated[0][0]}" — consider deepening knowledge here.'
)
return insights or ["Conversations look healthy. Keep up the good work."]
def self_reflect(limit: int = 30) -> str:
"""Review recent conversations and reflect on Timmy's own behavior.
Scans past session entries for patterns: low-confidence responses,
errors, repeated topics, and conversation quality signals. Returns
a structured reflection that Timmy can use to improve.
Args:
limit: How many recent entries to review (default 30).
Returns:
A formatted self-reflection report.
"""
sl = get_session_logger()
sl.flush()
entries = sl.get_recent_entries(limit=limit)
if not entries:
return "No conversation history to reflect on yet."
_messages, errors, timmy_msgs, user_msgs = _categorize_entries(entries)
low_conf = _find_low_confidence(timmy_msgs)
repeated = _find_repeated_topics(user_msgs)
# Build reflection report
sections: list[str] = ["## Self-Reflection Report\n"]
sections.append(
f"Reviewed {len(entries)} recent entries: "
f"{len(user_msgs)} user messages, "
f"{len(timmy_msgs)} responses, "
f"{len(errors)} errors.\n"
)
sections.extend(
_format_reflection_section(
"Low-Confidence Responses",
low_conf,
lambda m: (
f"- [{(m.get('timestamp') or '?')[:19]}] "
f"confidence={m.get('confidence', 0):.0%}: "
f"{(m.get('content') or '')[:120]}"
),
"None found — all responses above threshold.",
)
)
sections.extend(
_format_reflection_section(
"Errors",
errors,
lambda e: f"- [{(e.get('timestamp') or '?')[:19]}] {(e.get('error') or '')[:120]}",
"No errors recorded.",
)
)
if repeated:
sections.append("### Recurring Topics")
for word, count in repeated:
sections.append(f'- "{word}" ({count} mentions)')
sections.append("")
else:
sections.append("### Recurring Topics\nNo strong patterns detected.\n")
sections.append("### Insights")
for insight in _build_insights(low_conf, errors, repeated):
sections.append(f"- {insight}")
return "\n".join(sections)

View File

@@ -210,6 +210,7 @@ class ThinkingEngine:
def __init__(self, db_path: Path = _DEFAULT_DB) -> None:
self._db_path = db_path
self._last_thought_id: str | None = None
self._last_input_time: datetime = datetime.now(UTC)
# Load the most recent thought for chain continuity
try:
@@ -220,28 +221,40 @@ class ThinkingEngine:
logger.debug("Failed to load recent thought: %s", exc)
pass # Fresh start if DB doesn't exist yet
async def think_once(self, prompt: str | None = None) -> Thought | None:
"""Execute one thinking cycle.
def record_user_input(self) -> None:
"""Record that a user interaction occurred, resetting the idle timer."""
self._last_input_time = datetime.now(UTC)
Args:
prompt: Optional custom seed prompt. When provided, overrides
the random seed selection and uses "prompted" as the
seed type — useful for journal prompts from the CLI.
def _is_idle(self) -> bool:
"""Return True if no user input has occurred within the idle timeout."""
timeout = settings.thinking_idle_timeout_minutes
if timeout <= 0:
return False # Disabled — never idle
return datetime.now(UTC) - self._last_input_time > timedelta(minutes=timeout)
1. Gather a seed context (or use the custom prompt)
2. Build a prompt with continuity from recent thoughts
3. Call the agent
4. Store the thought
5. Log the event and broadcast via WebSocket
def _build_thinking_context(self) -> tuple[str, str, list["Thought"]]:
"""Assemble the context needed for a thinking cycle.
Returns:
(memory_context, system_context, recent_thoughts)
"""
if not settings.thinking_enabled:
return None
memory_context = self._load_memory_context()
system_context = self._gather_system_snapshot()
recent_thoughts = self.get_recent_thoughts(limit=5)
return memory_context, system_context, recent_thoughts
content: str | None = None
async def _generate_novel_thought(
self,
prompt: str | None,
memory_context: str,
system_context: str,
recent_thoughts: list["Thought"],
) -> tuple[str | None, str]:
"""Run the dedup-retry loop to produce a novel thought.
Returns:
(content, seed_type) — content is None if no novel thought produced.
"""
seed_type: str = "freeform"
for attempt in range(self._MAX_DEDUP_RETRIES + 1):
@@ -264,17 +277,17 @@ class ThinkingEngine:
raw = await self._call_agent(full_prompt)
except Exception as exc:
logger.warning("Thinking cycle failed (Ollama likely down): %s", exc)
return None
return None, seed_type
if not raw or not raw.strip():
logger.debug("Thinking cycle produced empty response, skipping")
return None
return None, seed_type
content = raw.strip()
# Dedup: reject thoughts too similar to recent ones
if not self._is_too_similar(content, recent_thoughts):
break # Good — novel thought
return content, seed_type # Good — novel thought
if attempt < self._MAX_DEDUP_RETRIES:
logger.info(
@@ -282,40 +295,72 @@ class ThinkingEngine:
attempt + 1,
self._MAX_DEDUP_RETRIES + 1,
)
content = None # Will retry
else:
logger.warning(
"Thought still repetitive after %d retries, discarding",
self._MAX_DEDUP_RETRIES + 1,
)
return None
return None, seed_type
return None, seed_type
async def _process_thinking_result(self, thought: "Thought") -> None:
"""Run all post-hooks after a thought is stored."""
self._maybe_check_memory()
await self._maybe_distill()
await self._maybe_file_issues()
await self._check_workspace()
self._maybe_check_memory_status()
self._update_memory(thought)
self._log_event(thought)
self._write_journal(thought)
await self._broadcast(thought)
async def think_once(self, prompt: str | None = None) -> Thought | None:
"""Execute one thinking cycle.
Args:
prompt: Optional custom seed prompt. When provided, overrides
the random seed selection and uses "prompted" as the
seed type — useful for journal prompts from the CLI.
1. Gather a seed context (or use the custom prompt)
2. Build a prompt with continuity from recent thoughts
3. Call the agent
4. Store the thought
5. Log the event and broadcast via WebSocket
"""
if not settings.thinking_enabled:
return None
# Skip idle periods — don't count internal processing as thoughts
if not prompt and self._is_idle():
logger.debug(
"Thinking paused — no user input for %d minutes",
settings.thinking_idle_timeout_minutes,
)
return None
# Capture arrival time *before* the LLM call so the thought
# timestamp reflects when the cycle started, not when the
# (potentially slow) generation finished. Fixes #582.
arrived_at = datetime.now(UTC).isoformat()
memory_context, system_context, recent_thoughts = self._build_thinking_context()
content, seed_type = await self._generate_novel_thought(
prompt,
memory_context,
system_context,
recent_thoughts,
)
if not content:
return None
thought = self._store_thought(content, seed_type)
thought = self._store_thought(content, seed_type, arrived_at=arrived_at)
self._last_thought_id = thought.id
# Post-hook: distill facts from recent thoughts periodically
await self._maybe_distill()
# Post-hook: file Gitea issues for actionable observations
await self._maybe_file_issues()
# Post-hook: check workspace for new messages from Hermes
await self._check_workspace()
# Post-hook: update MEMORY.md with latest reflection
self._update_memory(thought)
# Log to swarm event system
self._log_event(thought)
# Append to daily journal file
self._write_journal(thought)
# Broadcast to WebSocket clients
await self._broadcast(thought)
await self._process_thinking_result(thought)
logger.info(
"Thought [%s] (%s): %s",
@@ -515,6 +560,35 @@ class ThinkingEngine:
result = memory_write(fact.strip(), context_type="fact")
logger.info("Distilled fact: %s%s", fact[:60], result[:40])
def _maybe_check_memory(self) -> None:
"""Every N thoughts, check memory status and log it.
Prevents unmonitored memory bloat during long thinking sessions
by periodically calling get_memory_status and logging the results.
"""
try:
interval = settings.thinking_memory_check_every
if interval <= 0:
return
count = self.count_thoughts()
if count == 0 or count % interval != 0:
return
from timmy.tools_intro import get_memory_status
status = get_memory_status()
hot = status.get("tier1_hot_memory", {})
vault = status.get("tier2_vault", {})
logger.info(
"Memory status check (thought #%d): hot_memory=%d lines, vault=%d files",
count,
hot.get("line_count", 0),
vault.get("file_count", 0),
)
except Exception as exc:
logger.warning("Memory status check failed: %s", exc)
async def _maybe_distill(self) -> None:
"""Every N thoughts, extract lasting insights and store as facts."""
try:
@@ -532,6 +606,76 @@ class ThinkingEngine:
except Exception as exc:
logger.warning("Thought distillation failed: %s", exc)
def _maybe_check_memory_status(self) -> None:
"""Every N thoughts, run a proactive memory status audit and log results."""
try:
interval = settings.thinking_memory_check_every
if interval <= 0:
return
count = self.count_thoughts()
if count == 0 or count % interval != 0:
return
from timmy.tools_intro import get_memory_status
status = get_memory_status()
# Log summary at INFO level
tier1 = status.get("tier1_hot_memory", {})
tier3 = status.get("tier3_semantic", {})
hot_lines = tier1.get("line_count", "?")
vectors = tier3.get("vector_count", "?")
logger.info(
"Memory audit (thought #%d): hot_memory=%s lines, semantic=%s vectors",
count,
hot_lines,
vectors,
)
# Write to memory_audit.log for persistent tracking
audit_path = Path("data/memory_audit.log")
audit_path.parent.mkdir(parents=True, exist_ok=True)
timestamp = datetime.now(UTC).isoformat(timespec="seconds")
with audit_path.open("a") as f:
f.write(
f"{timestamp} thought={count} "
f"hot_lines={hot_lines} "
f"vectors={vectors} "
f"vault_files={status.get('tier2_vault', {}).get('file_count', '?')}\n"
)
except Exception as exc:
logger.warning("Memory status check failed: %s", exc)
@staticmethod
def _references_real_files(text: str) -> bool:
"""Check that all source-file paths mentioned in *text* actually exist.
Extracts paths that look like Python/config source references
(e.g. ``src/timmy/session.py``, ``config/foo.yaml``) and verifies
each one on disk relative to the project root. Returns ``True``
only when **every** referenced path resolves to a real file — or
when no paths are referenced at all (pure prose is fine).
"""
# Match paths like src/thing.py swarm/init.py config/x.yaml
# Requires at least one slash and a file extension.
path_pattern = re.compile(
r"(?<![/\w])" # not preceded by path chars (avoid partial matches)
r"((?:src|tests|config|scripts|data|swarm|timmy)"
r"(?:/[\w./-]+\.(?:py|yaml|yml|json|toml|md|txt|cfg|ini)))"
)
paths = path_pattern.findall(text)
if not paths:
return True # No file refs → nothing to validate
# Project root: two levels up from this file (src/timmy/thinking.py)
project_root = Path(__file__).resolve().parent.parent.parent
for p in paths:
if not (project_root / p).is_file():
logger.info("Phantom file reference blocked: %s (not in %s)", p, project_root)
return False
return True
async def _maybe_file_issues(self) -> None:
"""Every N thoughts, classify recent thoughts and file Gitea issues.
@@ -543,6 +687,9 @@ class ThinkingEngine:
- Gitea is enabled and configured
- Thought count is divisible by thinking_issue_every
- LLM extracts at least one actionable item
Safety: every generated issue is validated to ensure referenced
file paths actually exist on disk, preventing phantom-bug reports.
"""
try:
interval = settings.thinking_issue_every
@@ -570,7 +717,10 @@ class ThinkingEngine:
"Rules:\n"
"- Only include things that could become a real code fix or feature\n"
"- Skip vague reflections, philosophical musings, or repeated themes\n"
"- Category must be one of: bug, feature, suggestion, maintenance\n\n"
"- Category must be one of: bug, feature, suggestion, maintenance\n"
"- ONLY reference files that you are CERTAIN exist in the project\n"
"- Do NOT invent or guess file paths — if unsure, describe the "
"area of concern without naming specific files\n\n"
"For each item, write an ENGINEER-QUALITY issue:\n"
'- "title": A clear, specific title (e.g. "[Memory] MEMORY.md timestamp not updating")\n'
'- "body": A detailed body with these sections:\n'
@@ -611,6 +761,15 @@ class ThinkingEngine:
if not title or len(title) < 10:
continue
# Validate all referenced file paths exist on disk
combined = f"{title}\n{body}"
if not self._references_real_files(combined):
logger.info(
"Skipped phantom issue: %s (references non-existent files)",
title[:60],
)
continue
label = category if category in ("bug", "feature") else ""
result = await create_gitea_issue_via_mcp(title=title, body=body, labels=label)
logger.info("Thought→Issue: %s%s", title[:60], result[:80])
@@ -618,6 +777,80 @@ class ThinkingEngine:
except Exception as exc:
logger.debug("Thought issue filing skipped: %s", exc)
# ── System snapshot helpers ────────────────────────────────────────────
def _snap_thought_count(self, now: datetime) -> str | None:
"""Return today's thought count, or *None* on failure."""
try:
today_start = now.replace(hour=0, minute=0, second=0, microsecond=0)
with _get_conn(self._db_path) as conn:
count = conn.execute(
"SELECT COUNT(*) as c FROM thoughts WHERE created_at >= ?",
(today_start.isoformat(),),
).fetchone()["c"]
return f"Thoughts today: {count}"
except Exception as exc:
logger.debug("Thought count query failed: %s", exc)
return None
def _snap_chat_activity(self) -> list[str]:
"""Return chat-activity lines (in-memory, no I/O)."""
try:
from infrastructure.chat_store import message_log
messages = message_log.all()
if messages:
last = messages[-1]
return [
f"Chat messages this session: {len(messages)}",
f'Last chat ({last.role}): "{last.content[:80]}"',
]
return ["No chat messages this session"]
except Exception as exc:
logger.debug("Chat activity query failed: %s", exc)
return []
def _snap_task_queue(self) -> str | None:
"""Return a one-line task queue summary, or *None*."""
try:
from swarm.task_queue.models import get_task_summary_for_briefing
s = get_task_summary_for_briefing()
running, pending = s.get("running", 0), s.get("pending_approval", 0)
done, failed = s.get("completed", 0), s.get("failed", 0)
if running or pending or done or failed:
return (
f"Tasks: {running} running, {pending} pending, "
f"{done} completed, {failed} failed"
)
except Exception as exc:
logger.debug("Task queue query failed: %s", exc)
return None
def _snap_workspace(self) -> list[str]:
"""Return workspace-update lines (file-based Hermes comms)."""
try:
from timmy.workspace import workspace_monitor
updates = workspace_monitor.get_pending_updates()
lines: list[str] = []
new_corr = updates.get("new_correspondence")
if new_corr:
line_count = len([ln for ln in new_corr.splitlines() if ln.strip()])
lines.append(
f"Workspace: {line_count} new correspondence entries (latest from: Hermes)"
)
new_inbox = updates.get("new_inbox_files", [])
if new_inbox:
files_str = ", ".join(new_inbox[:5])
if len(new_inbox) > 5:
files_str += f", ... (+{len(new_inbox) - 5} more)"
lines.append(f"Workspace: {len(new_inbox)} new inbox files: {files_str}")
return lines
except Exception as exc:
logger.debug("Workspace check failed: %s", exc)
return []
def _gather_system_snapshot(self) -> str:
"""Gather lightweight real system state for grounding thoughts in reality.
@@ -625,83 +858,24 @@ class ThinkingEngine:
recent chat activity, and task queue status. Never crashes — every
section is independently try/excepted.
"""
parts: list[str] = []
# Current local time
now = datetime.now().astimezone()
tz = now.strftime("%Z") or "UTC"
parts.append(
parts: list[str] = [
f"Local time: {now.strftime('%I:%M %p').lstrip('0')} {tz}, {now.strftime('%A %B %d')}"
)
]
# Thought count today (cheap DB query)
try:
today_start = now.replace(hour=0, minute=0, second=0, microsecond=0)
with _get_conn(self._db_path) as conn:
count = conn.execute(
"SELECT COUNT(*) as c FROM thoughts WHERE created_at >= ?",
(today_start.isoformat(),),
).fetchone()["c"]
parts.append(f"Thoughts today: {count}")
except Exception as exc:
logger.debug("Thought count query failed: %s", exc)
pass
thought_line = self._snap_thought_count(now)
if thought_line:
parts.append(thought_line)
# Recent chat activity (in-memory, no I/O)
try:
from infrastructure.chat_store import message_log
parts.extend(self._snap_chat_activity())
messages = message_log.all()
if messages:
parts.append(f"Chat messages this session: {len(messages)}")
last = messages[-1]
parts.append(f'Last chat ({last.role}): "{last.content[:80]}"')
else:
parts.append("No chat messages this session")
except Exception as exc:
logger.debug("Chat activity query failed: %s", exc)
pass
task_line = self._snap_task_queue()
if task_line:
parts.append(task_line)
# Task queue (lightweight DB query)
try:
from swarm.task_queue.models import get_task_summary_for_briefing
summary = get_task_summary_for_briefing()
running = summary.get("running", 0)
pending = summary.get("pending_approval", 0)
done = summary.get("completed", 0)
failed = summary.get("failed", 0)
if running or pending or done or failed:
parts.append(
f"Tasks: {running} running, {pending} pending, "
f"{done} completed, {failed} failed"
)
except Exception as exc:
logger.debug("Task queue query failed: %s", exc)
pass
# Workspace updates (file-based communication with Hermes)
try:
from timmy.workspace import workspace_monitor
updates = workspace_monitor.get_pending_updates()
new_corr = updates.get("new_correspondence")
new_inbox = updates.get("new_inbox_files", [])
if new_corr:
# Count entries (assuming each entry starts with a timestamp or header)
line_count = len([line for line in new_corr.splitlines() if line.strip()])
parts.append(
f"Workspace: {line_count} new correspondence entries (latest from: Hermes)"
)
if new_inbox:
files_str = ", ".join(new_inbox[:5])
if len(new_inbox) > 5:
files_str += f", ... (+{len(new_inbox) - 5} more)"
parts.append(f"Workspace: {len(new_inbox)} new inbox files: {files_str}")
except Exception as exc:
logger.debug("Workspace check failed: %s", exc)
pass
parts.extend(self._snap_workspace())
return "\n".join(parts) if parts else ""
@@ -970,32 +1144,59 @@ class ThinkingEngine:
lines.append(f"- [{thought.seed_type}] {snippet}")
return "\n".join(lines)
_thinking_agent = None # cached agent — avoids per-call resource leaks (#525)
async def _call_agent(self, prompt: str) -> str:
"""Call Timmy's agent to generate a thought.
Creates a lightweight agent with skip_mcp=True to avoid the cancel-scope
Reuses a cached agent with skip_mcp=True to avoid the cancel-scope
errors that occur when MCP stdio transports are spawned inside asyncio
background tasks (#72). The thinking engine doesn't need Gitea or
filesystem tools — it only needs the LLM.
background tasks (#72) and to prevent per-call resource leaks (httpx
clients, SQLite connections, model warmups) that caused the thinking
loop to die every ~10 min (#525).
Individual calls are capped at 120 s so a hung Ollama never blocks
the scheduler indefinitely.
Strips ``<think>`` tags from reasoning models (qwen3, etc.) so that
downstream parsers (fact distillation, issue filing) receive clean text.
"""
from timmy.agent import create_timmy
import asyncio
if self._thinking_agent is None:
from timmy.agent import create_timmy
self._thinking_agent = create_timmy(skip_mcp=True)
try:
async with asyncio.timeout(120):
run = await self._thinking_agent.arun(prompt, stream=False)
except TimeoutError:
logger.warning("Thinking LLM call timed out after 120 s")
return ""
agent = create_timmy(skip_mcp=True)
run = await agent.arun(prompt, stream=False)
raw = run.content if hasattr(run, "content") else str(run)
return _THINK_TAG_RE.sub("", raw) if raw else raw
def _store_thought(self, content: str, seed_type: str) -> Thought:
"""Persist a thought to SQLite."""
def _store_thought(
self,
content: str,
seed_type: str,
*,
arrived_at: str | None = None,
) -> Thought:
"""Persist a thought to SQLite.
Args:
arrived_at: ISO-8601 timestamp captured when the thinking cycle
started. Falls back to now() for callers that don't supply it.
"""
thought = Thought(
id=str(uuid.uuid4()),
content=content,
seed_type=seed_type,
parent_id=self._last_thought_id,
created_at=datetime.now(UTC).isoformat(),
created_at=arrived_at or datetime.now(UTC).isoformat(),
)
with _get_conn(self._db_path) as conn:
@@ -1076,6 +1277,52 @@ class ThinkingEngine:
logger.debug("Failed to broadcast thought: %s", exc)
def _query_thoughts(
db_path: Path, query: str, seed_type: str | None, limit: int
) -> list[sqlite3.Row]:
"""Fetch thought rows matching *query* with optional *seed_type* filter."""
with _get_conn(db_path) as conn:
if seed_type:
return conn.execute(
"""
SELECT id, content, seed_type, created_at
FROM thoughts
WHERE content LIKE ? AND seed_type = ?
ORDER BY created_at DESC
LIMIT ?
""",
(f"%{query}%", seed_type, limit),
).fetchall()
return conn.execute(
"""
SELECT id, content, seed_type, created_at
FROM thoughts
WHERE content LIKE ?
ORDER BY created_at DESC
LIMIT ?
""",
(f"%{query}%", limit),
).fetchall()
def _format_thought_results(rows: list[sqlite3.Row], query: str, seed_type: str | None) -> str:
"""Format thought rows into a human-readable summary string."""
lines = [f'Found {len(rows)} thought(s) matching "{query}":']
if seed_type:
lines[0] += f' [seed_type="{seed_type}"]'
lines.append("")
for row in rows:
ts = datetime.fromisoformat(row["created_at"])
local_ts = ts.astimezone()
time_str = local_ts.strftime("%Y-%m-%d %I:%M %p").lstrip("0")
seed = row["seed_type"]
content = row["content"].replace("\n", " ") # Flatten newlines for display
lines.append(f"[{time_str}] ({seed}) {content[:150]}")
return "\n".join(lines)
def search_thoughts(query: str, seed_type: str | None = None, limit: int = 10) -> str:
"""Search Timmy's thought history for reflections matching a query.
@@ -1093,58 +1340,17 @@ def search_thoughts(query: str, seed_type: str | None = None, limit: int = 10) -
Formatted string with matching thoughts, newest first, including
timestamps and seed types. Returns a helpful message if no matches found.
"""
# Clamp limit to reasonable bounds
limit = max(1, min(limit, 50))
try:
engine = thinking_engine
db_path = engine._db_path
# Build query with optional seed_type filter
with _get_conn(db_path) as conn:
if seed_type:
rows = conn.execute(
"""
SELECT id, content, seed_type, created_at
FROM thoughts
WHERE content LIKE ? AND seed_type = ?
ORDER BY created_at DESC
LIMIT ?
""",
(f"%{query}%", seed_type, limit),
).fetchall()
else:
rows = conn.execute(
"""
SELECT id, content, seed_type, created_at
FROM thoughts
WHERE content LIKE ?
ORDER BY created_at DESC
LIMIT ?
""",
(f"%{query}%", limit),
).fetchall()
rows = _query_thoughts(thinking_engine._db_path, query, seed_type, limit)
if not rows:
if seed_type:
return f'No thoughts found matching "{query}" with seed_type="{seed_type}".'
return f'No thoughts found matching "{query}".'
# Format results
lines = [f'Found {len(rows)} thought(s) matching "{query}":']
if seed_type:
lines[0] += f' [seed_type="{seed_type}"]'
lines.append("")
for row in rows:
ts = datetime.fromisoformat(row["created_at"])
local_ts = ts.astimezone()
time_str = local_ts.strftime("%Y-%m-%d %I:%M %p").lstrip("0")
seed = row["seed_type"]
content = row["content"].replace("\n", " ") # Flatten newlines for display
lines.append(f"[{time_str}] ({seed}) {content[:150]}")
return "\n".join(lines)
return _format_thought_results(rows, query, seed_type)
except Exception as exc:
logger.warning("Thought search failed: %s", exc)

View File

@@ -48,6 +48,9 @@ SAFE_TOOLS = frozenset(
"check_ollama_health",
"get_memory_status",
"list_swarm_agents",
# Artifact tools
"jot_note",
"log_decision",
# MCP Gitea tools
"issue_write",
"issue_read",

View File

@@ -587,9 +587,17 @@ def _register_introspection_tools(toolkit: Toolkit) -> None:
logger.debug("Introspection tools not available")
try:
from timmy.session_logger import session_history
from timmy.mcp_tools import update_gitea_avatar
toolkit.register(update_gitea_avatar, name="update_gitea_avatar")
except (ImportError, AttributeError) as exc:
logger.debug("update_gitea_avatar tool not available: %s", exc)
try:
from timmy.session_logger import self_reflect, session_history
toolkit.register(session_history, name="session_history")
toolkit.register(self_reflect, name="self_reflect")
except (ImportError, AttributeError) as exc:
logger.warning("Tool execution failed (session_history registration): %s", exc)
logger.debug("session_history tool not available")
@@ -619,6 +627,18 @@ def _register_gematria_tool(toolkit: Toolkit) -> None:
logger.debug("Gematria tool not available")
def _register_artifact_tools(toolkit: Toolkit) -> None:
"""Register artifact tools — notes and decision logging."""
try:
from timmy.memory_system import jot_note, log_decision
toolkit.register(jot_note, name="jot_note")
toolkit.register(log_decision, name="log_decision")
except (ImportError, AttributeError) as exc:
logger.warning("Tool execution failed (Artifact tools registration): %s", exc)
logger.debug("Artifact tools not available")
def _register_thinking_tools(toolkit: Toolkit) -> None:
"""Register thinking/introspection tools for self-reflection."""
try:
@@ -657,6 +677,7 @@ def create_full_toolkit(base_dir: str | Path | None = None):
_register_introspection_tools(toolkit)
_register_delegation_tools(toolkit)
_register_gematria_tool(toolkit)
_register_artifact_tools(toolkit)
_register_thinking_tools(toolkit)
# Gitea issue management is now provided by the gitea-mcp server
@@ -854,6 +875,16 @@ def _introspection_tool_catalog() -> dict:
"description": "Query Timmy's own thought history for past reflections and insights",
"available_in": ["orchestrator"],
},
"self_reflect": {
"name": "Self-Reflect",
"description": "Review recent conversations to spot patterns, low-confidence answers, and errors",
"available_in": ["orchestrator"],
},
"update_gitea_avatar": {
"name": "Update Gitea Avatar",
"description": "Generate and upload a wizard-themed avatar to Timmy's Gitea profile",
"available_in": ["orchestrator"],
},
}
@@ -878,82 +909,35 @@ def _experiment_tool_catalog() -> dict:
}
_CREATIVE_CATALOG_SOURCES: list[tuple[str, str, list[str]]] = [
("creative.tools.git_tools", "GIT_TOOL_CATALOG", ["forge", "helm", "orchestrator"]),
("creative.tools.image_tools", "IMAGE_TOOL_CATALOG", ["pixel", "orchestrator"]),
("creative.tools.music_tools", "MUSIC_TOOL_CATALOG", ["lyra", "orchestrator"]),
("creative.tools.video_tools", "VIDEO_TOOL_CATALOG", ["reel", "orchestrator"]),
("creative.director", "DIRECTOR_TOOL_CATALOG", ["orchestrator"]),
("creative.assembler", "ASSEMBLER_TOOL_CATALOG", ["reel", "orchestrator"]),
]
def _import_creative_catalogs(catalog: dict) -> None:
"""Import and merge creative tool catalogs from creative module."""
# ── Git tools ─────────────────────────────────────────────────────────────
try:
from creative.tools.git_tools import GIT_TOOL_CATALOG
for module_path, attr_name, available_in in _CREATIVE_CATALOG_SOURCES:
_merge_catalog(catalog, module_path, attr_name, available_in)
for tool_id, info in GIT_TOOL_CATALOG.items():
def _merge_catalog(
catalog: dict, module_path: str, attr_name: str, available_in: list[str]
) -> None:
"""Import a single creative catalog and merge its entries."""
try:
from importlib import import_module
source_catalog = getattr(import_module(module_path), attr_name)
for tool_id, info in source_catalog.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["forge", "helm", "orchestrator"],
}
except ImportError:
pass
# ── Image tools ────────────────────────────────────────────────────────────
try:
from creative.tools.image_tools import IMAGE_TOOL_CATALOG
for tool_id, info in IMAGE_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["pixel", "orchestrator"],
}
except ImportError:
pass
# ── Music tools ────────────────────────────────────────────────────────────
try:
from creative.tools.music_tools import MUSIC_TOOL_CATALOG
for tool_id, info in MUSIC_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["lyra", "orchestrator"],
}
except ImportError:
pass
# ── Video tools ────────────────────────────────────────────────────────────
try:
from creative.tools.video_tools import VIDEO_TOOL_CATALOG
for tool_id, info in VIDEO_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["reel", "orchestrator"],
}
except ImportError:
pass
# ── Creative pipeline ──────────────────────────────────────────────────────
try:
from creative.director import DIRECTOR_TOOL_CATALOG
for tool_id, info in DIRECTOR_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["orchestrator"],
}
except ImportError:
pass
# ── Assembler tools ───────────────────────────────────────────────────────
try:
from creative.assembler import ASSEMBLER_TOOL_CATALOG
for tool_id, info in ASSEMBLER_TOOL_CATALOG.items():
catalog[tool_id] = {
"name": info["name"],
"description": info["description"],
"available_in": ["reel", "orchestrator"],
"available_in": available_in,
}
except ImportError:
pass

View File

@@ -26,7 +26,7 @@ def get_system_info() -> dict[str, Any]:
- python_version: Python version
- platform: OS platform
- model: Current Ollama model (queried from API)
- model_backend: Configured backend (ollama/airllm/grok)
- model_backend: Configured backend (ollama/grok/claude)
- ollama_url: Ollama host URL
- repo_root: Repository root path
- grok_enabled: Whether GROK is enabled
@@ -127,54 +127,48 @@ def check_ollama_health() -> dict[str, Any]:
return result
def get_memory_status() -> dict[str, Any]:
"""Get the status of Timmy's memory system.
Returns:
Dict with memory tier information
"""
from config import settings
repo_root = Path(settings.repo_root)
# Check tier 1: Hot memory
def _hot_memory_info(repo_root: Path) -> dict[str, Any]:
"""Tier 1: Hot memory (MEMORY.md) status."""
memory_md = repo_root / "MEMORY.md"
tier1_exists = memory_md.exists()
tier1_content = ""
if tier1_exists:
tier1_content = memory_md.read_text()[:500] # First 500 chars
tier1_content = memory_md.read_text()[:500]
# Check tier 2: Vault
vault_path = repo_root / "memory" / "self"
tier2_exists = vault_path.exists()
tier2_files = []
if tier2_exists:
tier2_files = [f.name for f in vault_path.iterdir() if f.is_file()]
tier1_info: dict[str, Any] = {
info: dict[str, Any] = {
"exists": tier1_exists,
"path": str(memory_md),
"preview": " ".join(tier1_content[:200].split()) if tier1_content else None,
}
if tier1_exists:
lines = memory_md.read_text().splitlines()
tier1_info["line_count"] = len(lines)
tier1_info["sections"] = [ln.lstrip("# ").strip() for ln in lines if ln.startswith("## ")]
info["line_count"] = len(lines)
info["sections"] = [ln.lstrip("# ").strip() for ln in lines if ln.startswith("## ")]
return info
def _vault_info(repo_root: Path) -> dict[str, Any]:
"""Tier 2: Vault (memory/ directory tree) status."""
vault_path = repo_root / "memory" / "self"
tier2_exists = vault_path.exists()
tier2_files = [f.name for f in vault_path.iterdir() if f.is_file()] if tier2_exists else []
# Vault — scan all subdirs under memory/
vault_root = repo_root / "memory"
vault_info: dict[str, Any] = {
info: dict[str, Any] = {
"exists": tier2_exists,
"path": str(vault_path),
"file_count": len(tier2_files),
"files": tier2_files[:10],
}
if vault_root.exists():
vault_info["directories"] = [d.name for d in vault_root.iterdir() if d.is_dir()]
vault_info["total_markdown_files"] = sum(1 for _ in vault_root.rglob("*.md"))
info["directories"] = [d.name for d in vault_root.iterdir() if d.is_dir()]
info["total_markdown_files"] = sum(1 for _ in vault_root.rglob("*.md"))
return info
# Tier 3: Semantic memory row count
tier3_info: dict[str, Any] = {"available": False}
def _semantic_memory_info(repo_root: Path) -> dict[str, Any]:
"""Tier 3: Semantic memory (vector DB) status."""
info: dict[str, Any] = {"available": False}
try:
sem_db = repo_root / "data" / "memory.db"
if sem_db.exists():
@@ -184,14 +178,16 @@ def get_memory_status() -> dict[str, Any]:
).fetchone()
if row and row[0]:
count = conn.execute("SELECT COUNT(*) FROM chunks").fetchone()
tier3_info["available"] = True
tier3_info["vector_count"] = count[0] if count else 0
info["available"] = True
info["vector_count"] = count[0] if count else 0
except Exception as exc:
logger.debug("Memory status query failed: %s", exc)
pass
return info
# Self-coding journal stats
journal_info: dict[str, Any] = {"available": False}
def _journal_info(repo_root: Path) -> dict[str, Any]:
"""Self-coding journal statistics."""
info: dict[str, Any] = {"available": False}
try:
journal_db = repo_root / "data" / "self_coding.db"
if journal_db.exists():
@@ -203,7 +199,7 @@ def get_memory_status() -> dict[str, Any]:
if rows:
counts = {r["outcome"]: r["cnt"] for r in rows}
total = sum(counts.values())
journal_info = {
info = {
"available": True,
"total_attempts": total,
"successes": counts.get("success", 0),
@@ -212,13 +208,24 @@ def get_memory_status() -> dict[str, Any]:
}
except Exception as exc:
logger.debug("Journal stats query failed: %s", exc)
pass
return info
def get_memory_status() -> dict[str, Any]:
"""Get the status of Timmy's memory system.
Returns:
Dict with memory tier information
"""
from config import settings
repo_root = Path(settings.repo_root)
return {
"tier1_hot_memory": tier1_info,
"tier2_vault": vault_info,
"tier3_semantic": tier3_info,
"self_coding_journal": journal_info,
"tier1_hot_memory": _hot_memory_info(repo_root),
"tier2_vault": _vault_info(repo_root),
"tier3_semantic": _semantic_memory_info(repo_root),
"self_coding_journal": _journal_info(repo_root),
}

View File

@@ -78,6 +78,11 @@ DEFAULT_MAX_UTTERANCE = 30.0 # safety cap — don't record forever
DEFAULT_SESSION_ID = "voice"
def _rms(block: np.ndarray) -> float:
"""Compute root-mean-square energy of an audio block."""
return float(np.sqrt(np.mean(block.astype(np.float32) ** 2)))
@dataclass
class VoiceConfig:
"""Configuration for the voice loop."""
@@ -161,13 +166,6 @@ class VoiceLoop:
min_blocks = int(self.config.min_utterance / 0.1)
max_blocks = int(self.config.max_utterance / 0.1)
audio_chunks: list[np.ndarray] = []
silent_count = 0
recording = False
def _rms(block: np.ndarray) -> float:
return float(np.sqrt(np.mean(block.astype(np.float32) ** 2)))
sys.stdout.write("\n 🎤 Listening... (speak now)\n")
sys.stdout.flush()
@@ -177,42 +175,69 @@ class VoiceLoop:
dtype="float32",
blocksize=block_size,
) as stream:
while self._running:
block, overflowed = stream.read(block_size)
if overflowed:
logger.debug("Audio buffer overflowed")
chunks = self._capture_audio_blocks(stream, block_size, silence_blocks, max_blocks)
rms = _rms(block)
return self._finalize_utterance(chunks, min_blocks, sr)
if not recording:
if rms > self.config.silence_threshold:
recording = True
silent_count = 0
audio_chunks.append(block.copy())
sys.stdout.write(" 📢 Recording...\r")
sys.stdout.flush()
def _capture_audio_blocks(
self,
stream,
block_size: int,
silence_blocks: int,
max_blocks: int,
) -> list[np.ndarray]:
"""Read audio blocks from *stream* until silence or max length.
Returns the list of captured audio chunks (may be empty).
"""
chunks: list[np.ndarray] = []
silent_count = 0
recording = False
while self._running:
block, overflowed = stream.read(block_size)
if overflowed:
logger.debug("Audio buffer overflowed")
rms = _rms(block)
if not recording:
if rms > self.config.silence_threshold:
recording = True
silent_count = 0
chunks.append(block.copy())
sys.stdout.write(" 📢 Recording...\r")
sys.stdout.flush()
else:
chunks.append(block.copy())
if rms < self.config.silence_threshold:
silent_count += 1
else:
audio_chunks.append(block.copy())
silent_count = 0
if rms < self.config.silence_threshold:
silent_count += 1
else:
silent_count = 0
if silent_count >= silence_blocks:
break
# End of utterance
if silent_count >= silence_blocks:
break
if len(chunks) >= max_blocks:
logger.info("Max utterance length reached, stopping.")
break
# Safety cap
if len(audio_chunks) >= max_blocks:
logger.info("Max utterance length reached, stopping.")
break
return chunks
if not audio_chunks or len(audio_chunks) < min_blocks:
@staticmethod
def _finalize_utterance(
chunks: list[np.ndarray], min_blocks: int, sample_rate: int
) -> np.ndarray | None:
"""Concatenate recorded chunks and report duration.
Returns ``None`` if the utterance is too short to be meaningful.
"""
if not chunks or len(chunks) < min_blocks:
return None
audio = np.concatenate(audio_chunks, axis=0).flatten()
duration = len(audio) / sr
audio = np.concatenate(chunks, axis=0).flatten()
duration = len(audio) / sample_rate
sys.stdout.write(f" ✂️ Captured {duration:.1f}s of audio\n")
sys.stdout.flush()
return audio
@@ -369,15 +394,33 @@ class VoiceLoop:
# ── Main Loop ───────────────────────────────────────────────────────
def run(self) -> None:
"""Run the voice loop. Blocks until Ctrl-C."""
self._ensure_piper()
# Whisper hallucinates these on silence/noise — skip them.
_WHISPER_HALLUCINATIONS = frozenset(
{
"you",
"thanks.",
"thank you.",
"bye.",
"",
"thanks for watching!",
"thank you for watching!",
}
)
# Suppress MCP / Agno stderr noise during voice mode.
_suppress_mcp_noise()
# Suppress MCP async-generator teardown tracebacks on exit.
_install_quiet_asyncgen_hooks()
# Spoken phrases that end the voice session.
_EXIT_COMMANDS = frozenset(
{
"goodbye",
"exit",
"quit",
"stop",
"goodbye timmy",
"stop listening",
}
)
def _log_banner(self) -> None:
"""Log the startup banner with STT/TTS/LLM configuration."""
tts_label = (
"macOS say"
if self.config.use_say_fallback
@@ -393,52 +436,50 @@ class VoiceLoop:
" Press Ctrl-C to exit.\n" + "=" * 60
)
def _is_hallucination(self, text: str) -> bool:
"""Return True if *text* is a known Whisper hallucination."""
return not text or text.lower() in self._WHISPER_HALLUCINATIONS
def _is_exit_command(self, text: str) -> bool:
"""Return True if the user asked to stop the voice session."""
return text.lower().strip().rstrip(".!") in self._EXIT_COMMANDS
def _process_turn(self, text: str) -> None:
"""Handle a single listen-think-speak turn after transcription."""
sys.stdout.write(f"\n 👤 You: {text}\n")
sys.stdout.flush()
response = self._think(text)
sys.stdout.write(f" 🤖 Timmy: {response}\n")
sys.stdout.flush()
self._speak(response)
def run(self) -> None:
"""Run the voice loop. Blocks until Ctrl-C."""
self._ensure_piper()
_suppress_mcp_noise()
_install_quiet_asyncgen_hooks()
self._log_banner()
self._running = True
try:
while self._running:
# 1. LISTEN — record until silence
audio = self._record_utterance()
if audio is None:
continue
# 2. TRANSCRIBE — Whisper STT
text = self._transcribe(audio)
if not text or text.lower() in (
"you",
"thanks.",
"thank you.",
"bye.",
"",
"thanks for watching!",
"thank you for watching!",
):
# Whisper hallucinations on silence/noise
if self._is_hallucination(text):
logger.debug("Ignoring likely Whisper hallucination: '%s'", text)
continue
sys.stdout.write(f"\n 👤 You: {text}\n")
sys.stdout.flush()
# Exit commands
if text.lower().strip().rstrip(".!") in (
"goodbye",
"exit",
"quit",
"stop",
"goodbye timmy",
"stop listening",
):
if self._is_exit_command(text):
logger.info("👋 Goodbye!")
break
# 3. THINK — send to Timmy
response = self._think(text)
sys.stdout.write(f" 🤖 Timmy: {response}\n")
sys.stdout.flush()
# 4. SPEAK — TTS output
self._speak(response)
self._process_turn(text)
except KeyboardInterrupt:
logger.info("👋 Voice loop stopped.")

261
src/timmy/workshop_state.py Normal file
View File

@@ -0,0 +1,261 @@
"""Workshop presence heartbeat — periodic writer for ``~/.timmy/presence.json``.
Maintains Timmy's observable presence state for the Workshop 3D renderer.
Writes the presence file every 30 seconds (or on cognitive state change),
skipping writes when state is unchanged.
See ADR-023 for the schema contract and issue #360 for the full v1 schema.
"""
import asyncio
import hashlib
import json
import logging
import time
from collections.abc import Awaitable, Callable
from datetime import UTC, datetime
from pathlib import Path
logger = logging.getLogger(__name__)
PRESENCE_FILE = Path.home() / ".timmy" / "presence.json"
HEARTBEAT_INTERVAL = 30 # seconds
# Cognitive mood → presence mood mapping (issue #360 enum values)
_MOOD_MAP: dict[str, str] = {
"curious": "contemplative",
"settled": "calm",
"hesitant": "uncertain",
"energized": "excited",
}
# Activity mapping from cognitive engagement
_ACTIVITY_MAP: dict[str, str] = {
"idle": "idle",
"surface": "thinking",
"deep": "thinking",
}
# Module-level energy tracker — decays over time, resets on interaction
_energy_state: dict[str, float] = {"value": 0.8, "last_interaction": time.monotonic()}
# Startup timestamp for uptime calculation
_start_time = time.monotonic()
# Energy decay: 0.01 per minute without interaction (per issue #360)
_ENERGY_DECAY_PER_SECOND = 0.01 / 60.0
_ENERGY_MIN = 0.1
def _time_of_day(hour: int) -> str:
"""Map hour (0-23) to a time-of-day label."""
if 5 <= hour < 12:
return "morning"
if 12 <= hour < 17:
return "afternoon"
if 17 <= hour < 21:
return "evening"
if 21 <= hour or hour < 2:
return "night"
return "deep-night"
def reset_energy() -> None:
"""Reset energy to full (called on interaction)."""
_energy_state["value"] = 0.8
_energy_state["last_interaction"] = time.monotonic()
def _current_energy() -> float:
"""Compute current energy with time-based decay."""
elapsed = time.monotonic() - _energy_state["last_interaction"]
decayed = _energy_state["value"] - (elapsed * _ENERGY_DECAY_PER_SECOND)
return max(_ENERGY_MIN, min(1.0, decayed))
def _pip_snapshot(mood: str, confidence: float) -> dict:
"""Tick Pip and return his current snapshot dict.
Feeds Timmy's mood and confidence into Pip's behavioral AI so the
familiar reacts to Timmy's cognitive state.
"""
from timmy.familiar import pip_familiar
pip_familiar.on_mood_change(mood, confidence=confidence)
pip_familiar.tick()
return pip_familiar.snapshot().to_dict()
def get_state_dict() -> dict:
"""Build presence state dict from current cognitive state.
Returns a v1 presence schema dict suitable for JSON serialisation.
Includes the full schema from issue #360: identity, mood, activity,
attention, interaction, environment, and meta sections.
"""
from timmy.cognitive_state import cognitive_tracker
state = cognitive_tracker.get_state()
now = datetime.now(UTC)
# Map cognitive mood to presence mood
mood = _MOOD_MAP.get(state.mood, "calm")
if state.engagement == "idle" and state.mood == "settled":
mood = "calm"
# Confidence from cognitive tracker
if state._confidence_count > 0:
confidence = state._confidence_sum / state._confidence_count
else:
confidence = 0.7
# Build active threads from commitments
threads = []
for commitment in state.active_commitments[:10]:
threads.append({"type": "thinking", "ref": commitment[:80], "status": "active"})
# Activity
activity = _ACTIVITY_MAP.get(state.engagement, "idle")
# Environment
local_now = datetime.now()
return {
"version": 1,
"liveness": now.strftime("%Y-%m-%dT%H:%M:%SZ"),
"current_focus": state.focus_topic or "",
"active_threads": threads,
"recent_events": [],
"concerns": [],
"mood": mood,
"confidence": round(max(0.0, min(1.0, confidence)), 2),
"energy": round(_current_energy(), 2),
"identity": {
"name": "Timmy",
"title": "The Workshop Wizard",
"uptime_seconds": int(time.monotonic() - _start_time),
},
"activity": {
"current": activity,
"detail": state.focus_topic or "",
},
"interaction": {
"visitor_present": False,
"conversation_turns": state.conversation_depth,
},
"environment": {
"time_of_day": _time_of_day(local_now.hour),
"local_time": local_now.strftime("%-I:%M %p"),
"day_of_week": local_now.strftime("%A"),
},
"familiar": _pip_snapshot(mood, confidence),
"meta": {
"schema_version": 1,
"updated_at": now.strftime("%Y-%m-%dT%H:%M:%SZ"),
"writer": "timmy-loop",
},
}
def write_state(state_dict: dict | None = None, path: Path | None = None) -> None:
"""Write presence state to ``~/.timmy/presence.json``.
Gracefully degrades if the file cannot be written.
"""
if state_dict is None:
state_dict = get_state_dict()
target = path or PRESENCE_FILE
try:
target.parent.mkdir(parents=True, exist_ok=True)
target.write_text(json.dumps(state_dict, indent=2) + "\n")
except OSError as exc:
logger.warning("Failed to write presence state: %s", exc)
def _state_hash(state_dict: dict) -> str:
"""Compute hash of state dict, ignoring volatile timestamps."""
stable = {k: v for k, v in state_dict.items() if k not in ("liveness", "meta")}
return hashlib.md5(json.dumps(stable, sort_keys=True).encode()).hexdigest()
class WorkshopHeartbeat:
"""Async background task that keeps ``presence.json`` fresh.
- Writes every ``interval`` seconds (default 30).
- Reacts to cognitive state changes via sensory bus.
- Skips write if state hasn't changed (hash comparison).
"""
def __init__(
self,
interval: int = HEARTBEAT_INTERVAL,
path: Path | None = None,
on_change: Callable[[dict], Awaitable[None]] | None = None,
) -> None:
self._interval = interval
self._path = path or PRESENCE_FILE
self._last_hash: str | None = None
self._task: asyncio.Task | None = None
self._trigger = asyncio.Event()
self._on_change = on_change
async def start(self) -> None:
"""Start the heartbeat background loop."""
self._subscribe_to_events()
self._task = asyncio.create_task(self._run())
async def stop(self) -> None:
"""Cancel the heartbeat task gracefully."""
if self._task:
self._task.cancel()
try:
await self._task
except asyncio.CancelledError:
pass
self._task = None
def notify(self) -> None:
"""Signal an immediate state write (e.g. on cognitive state change)."""
self._trigger.set()
async def _run(self) -> None:
"""Main loop: write state on interval or trigger."""
await asyncio.sleep(1) # Initial stagger
while True:
try:
# Wait for interval OR early trigger
try:
await asyncio.wait_for(self._trigger.wait(), timeout=self._interval)
self._trigger.clear()
except TimeoutError:
pass # Normal periodic tick
await self._write_if_changed()
except asyncio.CancelledError:
raise
except Exception as exc:
logger.error("Workshop heartbeat error: %s", exc)
async def _write_if_changed(self) -> None:
"""Build state, compare hash, write only if changed."""
state_dict = get_state_dict()
current_hash = _state_hash(state_dict)
if current_hash == self._last_hash:
return
self._last_hash = current_hash
write_state(state_dict, self._path)
if self._on_change:
try:
await self._on_change(state_dict)
except Exception as exc:
logger.warning("on_change callback failed: %s", exc)
def _subscribe_to_events(self) -> None:
"""Subscribe to cognitive state change events on the sensory bus."""
try:
from timmy.event_bus import get_sensory_bus
bus = get_sensory_bus()
bus.subscribe("cognitive_state_changed", lambda _: self.notify())
except Exception as exc:
logger.debug("Heartbeat event subscription skipped: %s", exc)

View File

@@ -75,6 +75,8 @@ def create_timmy_serve_app() -> FastAPI:
@asynccontextmanager
async def lifespan(app: FastAPI):
logger.info("Timmy Serve starting")
app.state.timmy = create_timmy()
logger.info("Timmy agent cached in app state")
yield
logger.info("Timmy Serve shutting down")
@@ -101,7 +103,7 @@ def create_timmy_serve_app() -> FastAPI:
async def serve_chat(request: Request, body: ChatRequest):
"""Process a chat request."""
try:
timmy = create_timmy()
timmy = request.app.state.timmy
result = timmy.run(body.message, stream=False)
response_text = result.content if hasattr(result, "content") else str(result)

50
static/world/controls.js vendored Normal file
View File

@@ -0,0 +1,50 @@
/**
* Camera + touch controls for the Workshop scene.
*
* Uses Three.js OrbitControls with constrained range — the visitor
* can look around the room but not leave it.
*/
import { OrbitControls } from "https://cdn.jsdelivr.net/npm/three@0.160.0/examples/jsm/controls/OrbitControls.js";
/**
* Set up camera controls.
* @param {THREE.PerspectiveCamera} camera
* @param {HTMLCanvasElement} domElement
* @returns {OrbitControls}
*/
export function setupControls(camera, domElement) {
const controls = new OrbitControls(camera, domElement);
// Smooth damping
controls.enableDamping = true;
controls.dampingFactor = 0.08;
// Limit zoom range
controls.minDistance = 3;
controls.maxDistance = 12;
// Limit vertical angle (don't look below floor or straight up)
controls.minPolarAngle = Math.PI * 0.2;
controls.maxPolarAngle = Math.PI * 0.6;
// Limit horizontal rotation range (stay facing the desk area)
controls.minAzimuthAngle = -Math.PI * 0.4;
controls.maxAzimuthAngle = Math.PI * 0.4;
// Target: roughly the desk area
controls.target.set(0, 1.2, 0);
// Touch settings
controls.touches = {
ONE: 0, // ROTATE
TWO: 2, // DOLLY
};
// Disable panning (visitor stays in place)
controls.enablePan = false;
controls.update();
return controls;
}

150
static/world/familiar.js Normal file
View File

@@ -0,0 +1,150 @@
/**
* Pip the Familiar — a small glowing orb that floats around the room.
*
* Emerald green core with a gold particle trail.
* Wanders on a randomized path, occasionally pauses near Timmy.
*/
import * as THREE from "https://cdn.jsdelivr.net/npm/three@0.160.0/build/three.module.js";
const CORE_COLOR = 0x00b450;
const GLOW_COLOR = 0x00b450;
const TRAIL_COLOR = 0xdaa520;
/**
* Create the familiar and return { group, update }.
* Call update(dt) each frame.
*/
export function createFamiliar() {
const group = new THREE.Group();
// --- Core orb ---
const coreGeo = new THREE.SphereGeometry(0.08, 12, 10);
const coreMat = new THREE.MeshStandardMaterial({
color: CORE_COLOR,
emissive: GLOW_COLOR,
emissiveIntensity: 1.5,
roughness: 0.2,
});
const core = new THREE.Mesh(coreGeo, coreMat);
group.add(core);
// --- Glow (larger transparent sphere) ---
const glowGeo = new THREE.SphereGeometry(0.15, 10, 8);
const glowMat = new THREE.MeshBasicMaterial({
color: GLOW_COLOR,
transparent: true,
opacity: 0.15,
});
const glow = new THREE.Mesh(glowGeo, glowMat);
group.add(glow);
// --- Point light from Pip ---
const light = new THREE.PointLight(CORE_COLOR, 0.4, 4);
group.add(light);
// --- Trail particles (simple small spheres) ---
const trailCount = 6;
const trails = [];
const trailGeo = new THREE.SphereGeometry(0.02, 4, 4);
const trailMat = new THREE.MeshBasicMaterial({
color: TRAIL_COLOR,
transparent: true,
opacity: 0.6,
});
for (let i = 0; i < trailCount; i++) {
const t = new THREE.Mesh(trailGeo, trailMat.clone());
t.visible = false;
group.add(t);
trails.push({ mesh: t, age: 0, maxAge: 0.3 + Math.random() * 0.3 });
}
// Starting position
group.position.set(1.5, 1.8, -0.5);
// Wandering state
let elapsed = 0;
let trailTimer = 0;
let trailIndex = 0;
// Waypoints for random wandering
const waypoints = [
new THREE.Vector3(1.5, 1.8, -0.5),
new THREE.Vector3(-1.0, 2.0, 0.5),
new THREE.Vector3(0.0, 1.5, -0.3), // near Timmy
new THREE.Vector3(1.2, 2.2, 0.8),
new THREE.Vector3(-0.5, 1.3, -0.2), // near desk
new THREE.Vector3(0.3, 2.5, 0.3),
];
let waypointIndex = 0;
let target = waypoints[0].clone();
let pauseTimer = 0;
function pickNextTarget() {
waypointIndex = (waypointIndex + 1) % waypoints.length;
target.copy(waypoints[waypointIndex]);
// Add randomness
target.x += (Math.random() - 0.5) * 0.6;
target.y += (Math.random() - 0.5) * 0.3;
target.z += (Math.random() - 0.5) * 0.6;
}
function update(dt) {
elapsed += dt;
// Move toward target
if (pauseTimer > 0) {
pauseTimer -= dt;
} else {
const dir = target.clone().sub(group.position);
const dist = dir.length();
if (dist < 0.15) {
pickNextTarget();
// Occasionally pause
if (Math.random() < 0.3) {
pauseTimer = 1.0 + Math.random() * 2.0;
}
} else {
dir.normalize();
const speed = 0.4;
group.position.add(dir.multiplyScalar(speed * dt));
}
}
// Bob up and down
group.position.y += Math.sin(elapsed * 3.0) * 0.002;
// Pulse glow
const pulse = 0.12 + Math.sin(elapsed * 4.0) * 0.05;
glowMat.opacity = pulse;
coreMat.emissiveIntensity = 1.2 + Math.sin(elapsed * 3.5) * 0.4;
// Trail particles
trailTimer += dt;
if (trailTimer > 0.1) {
trailTimer = 0;
const t = trails[trailIndex];
t.mesh.position.copy(group.position);
t.mesh.position.x += (Math.random() - 0.5) * 0.1;
t.mesh.position.y += (Math.random() - 0.5) * 0.1;
t.mesh.visible = true;
t.age = 0;
// Convert to local space
group.worldToLocal(t.mesh.position);
trailIndex = (trailIndex + 1) % trailCount;
}
// Age and fade trail particles
for (const t of trails) {
if (!t.mesh.visible) continue;
t.age += dt;
if (t.age >= t.maxAge) {
t.mesh.visible = false;
} else {
t.mesh.material.opacity = 0.6 * (1.0 - t.age / t.maxAge);
}
}
}
return { group, update };
}

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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=no">
<title>Timmy's Workshop</title>
<link rel="stylesheet" href="style.css">
</head>
<body>
<div id="overlay">
<div id="status">
<div class="name">Timmy</div>
<div class="mood" id="mood-text">focused</div>
</div>
<div id="connection-dot"></div>
<div id="speech-area">
<div class="bubble" id="speech-bubble"></div>
</div>
</div>
<script type="importmap">
{
"imports": {
"three": "https://cdn.jsdelivr.net/npm/three@0.160.0/build/three.module.js"
}
}
</script>
<script type="module">
import * as THREE from "three";
import { buildRoom } from "./scene.js";
import { createWizard } from "./wizard.js";
import { createFamiliar } from "./familiar.js";
import { setupControls } from "./controls.js";
import { StateReader } from "./state.js";
// --- Renderer ---
const renderer = new THREE.WebGLRenderer({ antialias: true });
renderer.setPixelRatio(Math.min(window.devicePixelRatio, 2));
renderer.setSize(window.innerWidth, window.innerHeight);
renderer.shadowMap.enabled = true;
renderer.shadowMap.type = THREE.PCFSoftShadowMap;
renderer.toneMapping = THREE.ACESFilmicToneMapping;
renderer.toneMappingExposure = 0.8;
document.body.prepend(renderer.domElement);
// --- Scene ---
const scene = new THREE.Scene();
scene.background = new THREE.Color(0x0a0a14);
scene.fog = new THREE.Fog(0x0a0a14, 5, 12);
// --- Camera (visitor at the door) ---
const camera = new THREE.PerspectiveCamera(
55, window.innerWidth / window.innerHeight, 0.1, 50
);
camera.position.set(0, 2.0, 4.5);
// --- Build scene elements ---
const { crystalBall, crystalLight, fireLight, candleLights } = buildRoom(scene);
const wizard = createWizard();
scene.add(wizard.group);
const familiar = createFamiliar();
scene.add(familiar.group);
// --- Controls ---
const controls = setupControls(camera, renderer.domElement);
// --- State ---
const stateReader = new StateReader();
const moodEl = document.getElementById("mood-text");
stateReader.onChange((state) => {
if (moodEl) {
moodEl.textContent = state.timmyState.mood;
}
});
stateReader.connect();
// --- Resize ---
window.addEventListener("resize", () => {
camera.aspect = window.innerWidth / window.innerHeight;
camera.updateProjectionMatrix();
renderer.setSize(window.innerWidth, window.innerHeight);
});
// --- Animation loop ---
const clock = new THREE.Clock();
function animate() {
requestAnimationFrame(animate);
const dt = clock.getDelta();
// Update scene elements
wizard.update(dt);
familiar.update(dt);
controls.update();
// Crystal ball subtle rotation + pulsing glow
crystalBall.rotation.y += dt * 0.3;
const pulse = 0.3 + Math.sin(Date.now() * 0.002) * 0.15;
crystalLight.intensity = pulse;
crystalBall.material.emissiveIntensity = pulse * 0.5;
// Fireplace flicker
fireLight.intensity = 1.2 + Math.sin(Date.now() * 0.005) * 0.15
+ Math.sin(Date.now() * 0.013) * 0.1;
// Candle flicker — each offset slightly for variety
const now = Date.now();
for (let i = 0; i < candleLights.length; i++) {
candleLights[i].intensity = 0.4
+ Math.sin(now * 0.007 + i * 2.1) * 0.1
+ Math.sin(now * 0.019 + i * 1.3) * 0.05;
}
renderer.render(scene, camera);
}
animate();
</script>
</body>
</html>

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/**
* Workshop scene — room geometry, lighting, materials.
*
* A dark stone room with a wooden desk, crystal ball, fireplace glow,
* and faint emerald ambient light. This is Timmy's Workshop.
*/
import * as THREE from "https://cdn.jsdelivr.net/npm/three@0.160.0/build/three.module.js";
const WALL_COLOR = 0x2a2a3e;
const FLOOR_COLOR = 0x1a1a1a;
const DESK_COLOR = 0x3e2723;
const DESK_TOP_COLOR = 0x4e342e;
const BOOK_COLORS = [0x8b1a1a, 0x1a3c6e, 0x2e5e3e, 0x6e4b1a, 0x4a1a5e, 0x5e1a2e];
const CANDLE_WAX = 0xe8d8b8;
const CANDLE_FLAME = 0xffaa33;
/**
* Build the room and add it to the given scene.
* Returns { crystalBall } for animation.
*/
export function buildRoom(scene) {
// --- Floor ---
const floorGeo = new THREE.PlaneGeometry(8, 8);
const floorMat = new THREE.MeshStandardMaterial({
color: FLOOR_COLOR,
roughness: 0.9,
});
const floor = new THREE.Mesh(floorGeo, floorMat);
floor.rotation.x = -Math.PI / 2;
floor.receiveShadow = true;
scene.add(floor);
// --- Back wall ---
const wallGeo = new THREE.PlaneGeometry(8, 4);
const wallMat = new THREE.MeshStandardMaterial({
color: WALL_COLOR,
roughness: 0.95,
metalness: 0.05,
});
const backWall = new THREE.Mesh(wallGeo, wallMat);
backWall.position.set(0, 2, -4);
scene.add(backWall);
// --- Side walls ---
const leftWall = new THREE.Mesh(wallGeo, wallMat);
leftWall.position.set(-4, 2, 0);
leftWall.rotation.y = Math.PI / 2;
scene.add(leftWall);
const rightWall = new THREE.Mesh(wallGeo, wallMat);
rightWall.position.set(4, 2, 0);
rightWall.rotation.y = -Math.PI / 2;
scene.add(rightWall);
// --- Desk ---
// Table top
const topGeo = new THREE.BoxGeometry(1.8, 0.08, 0.9);
const topMat = new THREE.MeshStandardMaterial({
color: DESK_TOP_COLOR,
roughness: 0.6,
});
const tableTop = new THREE.Mesh(topGeo, topMat);
tableTop.position.set(0, 0.85, -0.3);
tableTop.castShadow = true;
scene.add(tableTop);
// Legs
const legGeo = new THREE.BoxGeometry(0.08, 0.85, 0.08);
const legMat = new THREE.MeshStandardMaterial({
color: DESK_COLOR,
roughness: 0.7,
});
const offsets = [
[-0.8, -0.35],
[0.8, -0.35],
[-0.8, 0.05],
[0.8, 0.05],
];
for (const [x, z] of offsets) {
const leg = new THREE.Mesh(legGeo, legMat);
leg.position.set(x, 0.425, z - 0.3);
scene.add(leg);
}
// --- Scrolls / papers on desk (simple flat boxes) ---
const paperGeo = new THREE.BoxGeometry(0.3, 0.005, 0.2);
const paperMat = new THREE.MeshStandardMaterial({
color: 0xd4c5a0,
roughness: 0.9,
});
const paper1 = new THREE.Mesh(paperGeo, paperMat);
paper1.position.set(-0.4, 0.895, -0.35);
paper1.rotation.y = 0.15;
scene.add(paper1);
const paper2 = new THREE.Mesh(paperGeo, paperMat);
paper2.position.set(0.5, 0.895, -0.2);
paper2.rotation.y = -0.3;
scene.add(paper2);
// --- Crystal ball ---
const ballGeo = new THREE.SphereGeometry(0.12, 16, 14);
const ballMat = new THREE.MeshPhysicalMaterial({
color: 0x88ccff,
roughness: 0.05,
metalness: 0.0,
transmission: 0.9,
thickness: 0.3,
transparent: true,
opacity: 0.7,
emissive: new THREE.Color(0x88ccff),
emissiveIntensity: 0.3,
});
const crystalBall = new THREE.Mesh(ballGeo, ballMat);
crystalBall.position.set(0.15, 1.01, -0.3);
scene.add(crystalBall);
// Crystal ball base
const baseGeo = new THREE.CylinderGeometry(0.08, 0.1, 0.04, 8);
const baseMat = new THREE.MeshStandardMaterial({
color: 0x444444,
roughness: 0.3,
metalness: 0.5,
});
const base = new THREE.Mesh(baseGeo, baseMat);
base.position.set(0.15, 0.9, -0.3);
scene.add(base);
// Crystal ball inner glow (pulsing)
const crystalLight = new THREE.PointLight(0x88ccff, 0.3, 2);
crystalLight.position.copy(crystalBall.position);
scene.add(crystalLight);
// --- Bookshelf (right wall) ---
const shelfMat = new THREE.MeshStandardMaterial({
color: DESK_COLOR,
roughness: 0.7,
});
// Bookshelf frame — tall backing panel
const shelfBack = new THREE.Mesh(
new THREE.BoxGeometry(1.4, 2.2, 0.06),
shelfMat
);
shelfBack.position.set(3.0, 1.1, -2.0);
scene.add(shelfBack);
// Shelves (4 horizontal planks)
const shelfGeo = new THREE.BoxGeometry(1.4, 0.04, 0.35);
const shelfYs = [0.2, 0.7, 1.2, 1.7];
for (const sy of shelfYs) {
const shelf = new THREE.Mesh(shelfGeo, shelfMat);
shelf.position.set(3.0, sy, -1.85);
scene.add(shelf);
}
// Side panels
const sidePanelGeo = new THREE.BoxGeometry(0.04, 2.2, 0.35);
for (const sx of [-0.68, 0.68]) {
const side = new THREE.Mesh(sidePanelGeo, shelfMat);
side.position.set(3.0 + sx, 1.1, -1.85);
scene.add(side);
}
// Books on shelves — colored boxes
const bookGeo = new THREE.BoxGeometry(0.08, 0.28, 0.22);
const booksPerShelf = [5, 4, 5, 3];
for (let s = 0; s < shelfYs.length; s++) {
const count = booksPerShelf[s];
const startX = 3.0 - (count * 0.12) / 2;
for (let b = 0; b < count; b++) {
const bookMat = new THREE.MeshStandardMaterial({
color: BOOK_COLORS[(s * 3 + b) % BOOK_COLORS.length],
roughness: 0.8,
});
const book = new THREE.Mesh(bookGeo, bookMat);
book.position.set(
startX + b * 0.14,
shelfYs[s] + 0.16,
-1.85
);
// Slight random tilt for character
book.rotation.z = (Math.random() - 0.5) * 0.08;
scene.add(book);
}
}
// --- Candles ---
const candleLights = [];
const candlePositions = [
[-0.6, 0.89, -0.15], // desk left
[0.7, 0.89, -0.4], // desk right
[3.0, 1.78, -1.85], // bookshelf top
];
const candleGeo = new THREE.CylinderGeometry(0.02, 0.025, 0.12, 6);
const candleMat = new THREE.MeshStandardMaterial({
color: CANDLE_WAX,
roughness: 0.9,
});
for (const [cx, cy, cz] of candlePositions) {
// Wax cylinder
const candle = new THREE.Mesh(candleGeo, candleMat);
candle.position.set(cx, cy + 0.06, cz);
scene.add(candle);
// Flame — tiny emissive sphere
const flameGeo = new THREE.SphereGeometry(0.015, 6, 4);
const flameMat = new THREE.MeshBasicMaterial({ color: CANDLE_FLAME });
const flame = new THREE.Mesh(flameGeo, flameMat);
flame.position.set(cx, cy + 0.13, cz);
scene.add(flame);
// Warm point light
const candleLight = new THREE.PointLight(0xff8833, 0.4, 3);
candleLight.position.set(cx, cy + 0.15, cz);
scene.add(candleLight);
candleLights.push(candleLight);
}
// --- Lighting ---
// Fireplace glow (warm, off-screen stage left)
const fireLight = new THREE.PointLight(0xff6622, 1.2, 8);
fireLight.position.set(-3.5, 1.2, -1.0);
fireLight.castShadow = true;
fireLight.shadow.mapSize.width = 512;
fireLight.shadow.mapSize.height = 512;
scene.add(fireLight);
// Secondary warm fill
const fillLight = new THREE.PointLight(0xff8844, 0.3, 6);
fillLight.position.set(-2.0, 0.5, 1.0);
scene.add(fillLight);
// Emerald ambient
const ambient = new THREE.AmbientLight(0x00b450, 0.15);
scene.add(ambient);
// Faint overhead to keep things readable
const overhead = new THREE.PointLight(0x887766, 0.2, 8);
overhead.position.set(0, 3.5, 0);
scene.add(overhead);
return { crystalBall, crystalLight, fireLight, candleLights };
}

95
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/**
* State reader — hardcoded JSON for Phase 2, WebSocket in Phase 3.
*
* Provides Timmy's current state to the scene. In Phase 2 this is a
* static default; the WebSocket path is stubbed for future use.
*/
const DEFAULTS = {
timmyState: {
mood: "focused",
activity: "Pondering the arcane arts",
energy: 0.6,
confidence: 0.7,
},
activeThreads: [],
recentEvents: [],
concerns: [],
visitorPresent: false,
updatedAt: new Date().toISOString(),
version: 1,
};
export class StateReader {
constructor() {
this.state = { ...DEFAULTS };
this.listeners = [];
this._ws = null;
}
/** Subscribe to state changes. */
onChange(fn) {
this.listeners.push(fn);
}
/** Notify all listeners. */
_notify() {
for (const fn of this.listeners) {
try {
fn(this.state);
} catch (e) {
console.warn("State listener error:", e);
}
}
}
/** Try to connect to the world WebSocket for live updates. */
connect() {
const proto = location.protocol === "https:" ? "wss:" : "ws:";
const url = `${proto}//${location.host}/api/world/ws`;
try {
this._ws = new WebSocket(url);
this._ws.onopen = () => {
const dot = document.getElementById("connection-dot");
if (dot) dot.classList.add("connected");
};
this._ws.onclose = () => {
const dot = document.getElementById("connection-dot");
if (dot) dot.classList.remove("connected");
};
this._ws.onmessage = (ev) => {
try {
const msg = JSON.parse(ev.data);
if (msg.type === "world_state" || msg.type === "timmy_state") {
if (msg.timmyState) this.state.timmyState = msg.timmyState;
if (msg.mood) {
this.state.timmyState.mood = msg.mood;
this.state.timmyState.activity = msg.activity || "";
this.state.timmyState.energy = msg.energy ?? 0.5;
}
this._notify();
}
} catch (e) {
/* ignore parse errors */
}
};
} catch (e) {
console.warn("WebSocket unavailable — using static state");
}
}
/** Current mood string. */
get mood() {
return this.state.timmyState.mood;
}
/** Current activity string. */
get activity() {
return this.state.timmyState.activity;
}
/** Energy level 0-1. */
get energy() {
return this.state.timmyState.energy;
}
}

89
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/* Workshop 3D scene overlay styles */
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
body {
overflow: hidden;
background: #0a0a14;
font-family: "Courier New", monospace;
color: #e0e0e0;
touch-action: none;
}
canvas {
display: block;
}
#overlay {
position: fixed;
top: 0;
left: 0;
width: 100%;
height: 100%;
pointer-events: none;
z-index: 10;
}
#status {
position: absolute;
top: 16px;
left: 16px;
font-size: 14px;
opacity: 0.8;
}
#status .name {
font-size: 18px;
font-weight: bold;
color: #daa520;
}
#status .mood {
font-size: 13px;
color: #aaa;
margin-top: 4px;
}
#speech-area {
position: absolute;
bottom: 24px;
left: 50%;
transform: translateX(-50%);
max-width: 480px;
width: 90%;
text-align: center;
font-size: 15px;
line-height: 1.5;
color: #ccc;
opacity: 0;
transition: opacity 0.4s ease;
}
#speech-area.visible {
opacity: 1;
}
#speech-area .bubble {
background: rgba(10, 10, 20, 0.85);
border: 1px solid rgba(218, 165, 32, 0.3);
border-radius: 8px;
padding: 12px 20px;
}
#connection-dot {
position: absolute;
top: 18px;
right: 16px;
width: 8px;
height: 8px;
border-radius: 50%;
background: #555;
}
#connection-dot.connected {
background: #00b450;
}

99
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/**
* Timmy the Wizard — geometric figure built from primitives.
*
* Phase 1: cone body (robe), sphere head, cylinder arms.
* Idle animation: gentle breathing (Y-scale oscillation), head tilt.
*/
import * as THREE from "https://cdn.jsdelivr.net/npm/three@0.160.0/build/three.module.js";
const ROBE_COLOR = 0x2d1b4e;
const TRIM_COLOR = 0xdaa520;
/**
* Create the wizard group and return { group, update }.
* Call update(dt) each frame for idle animation.
*/
export function createWizard() {
const group = new THREE.Group();
// --- Robe (cone) ---
const robeGeo = new THREE.ConeGeometry(0.5, 1.6, 8);
const robeMat = new THREE.MeshStandardMaterial({
color: ROBE_COLOR,
roughness: 0.8,
});
const robe = new THREE.Mesh(robeGeo, robeMat);
robe.position.y = 0.8;
group.add(robe);
// --- Trim ring at robe bottom ---
const trimGeo = new THREE.TorusGeometry(0.5, 0.03, 8, 24);
const trimMat = new THREE.MeshStandardMaterial({
color: TRIM_COLOR,
roughness: 0.4,
metalness: 0.3,
});
const trim = new THREE.Mesh(trimGeo, trimMat);
trim.rotation.x = Math.PI / 2;
trim.position.y = 0.02;
group.add(trim);
// --- Head (sphere) ---
const headGeo = new THREE.SphereGeometry(0.22, 12, 10);
const headMat = new THREE.MeshStandardMaterial({
color: 0xd4a574,
roughness: 0.7,
});
const head = new THREE.Mesh(headGeo, headMat);
head.position.y = 1.72;
group.add(head);
// --- Hood (cone behind head) ---
const hoodGeo = new THREE.ConeGeometry(0.35, 0.5, 8);
const hoodMat = new THREE.MeshStandardMaterial({
color: ROBE_COLOR,
roughness: 0.8,
});
const hood = new THREE.Mesh(hoodGeo, hoodMat);
hood.position.y = 1.85;
hood.position.z = -0.08;
group.add(hood);
// --- Arms (cylinders) ---
const armGeo = new THREE.CylinderGeometry(0.06, 0.08, 0.7, 6);
const armMat = new THREE.MeshStandardMaterial({
color: ROBE_COLOR,
roughness: 0.8,
});
const leftArm = new THREE.Mesh(armGeo, armMat);
leftArm.position.set(-0.45, 1.0, 0.15);
leftArm.rotation.z = 0.3;
leftArm.rotation.x = -0.4;
group.add(leftArm);
const rightArm = new THREE.Mesh(armGeo, armMat);
rightArm.position.set(0.45, 1.0, 0.15);
rightArm.rotation.z = -0.3;
rightArm.rotation.x = -0.4;
group.add(rightArm);
// Position behind the desk
group.position.set(0, 0, -0.8);
// Animation state
let elapsed = 0;
function update(dt) {
elapsed += dt;
// Breathing: subtle Y-scale oscillation
const breath = 1.0 + Math.sin(elapsed * 1.5) * 0.015;
robe.scale.y = breath;
// Head tilt
head.rotation.z = Math.sin(elapsed * 0.7) * 0.05;
head.rotation.x = Math.sin(elapsed * 0.5) * 0.03;
}
return { group, update };
}

View File

@@ -18,7 +18,6 @@ except ImportError:
# agno is a core dependency (always installed) — do NOT stub it, or its
# internal import chains break under xdist parallel workers.
for _mod in [
"airllm",
"mcp",
"mcp.client",
"mcp.client.stdio",

View File

@@ -10,12 +10,10 @@ Categories:
M3xx iOS keyboard & zoom prevention
M4xx HTMX robustness (double-submit, sync)
M5xx Safe-area / notch support
M6xx AirLLM backend interface contract
"""
import re
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock, patch
# ── helpers ───────────────────────────────────────────────────────────────────
@@ -206,147 +204,3 @@ def test_M505_dvh_units_used():
"""Dynamic viewport height (dvh) accounts for collapsing browser chrome."""
css = _css()
assert "dvh" in css
# ── M6xx — AirLLM backend interface contract ──────────────────────────────────
def test_M601_airllm_agent_has_run_method():
"""TimmyAirLLMAgent must expose run() so the dashboard route can call it."""
from timmy.backends import TimmyAirLLMAgent
assert hasattr(TimmyAirLLMAgent, "run"), (
"TimmyAirLLMAgent is missing run() — dashboard will fail with AirLLM backend"
)
def test_M602_airllm_run_returns_content_attribute():
"""run() must return an object with a .content attribute (Agno RunResponse compat)."""
with patch("timmy.backends.is_apple_silicon", return_value=False):
from timmy.backends import TimmyAirLLMAgent
agent = TimmyAirLLMAgent(model_size="8b")
mock_model = MagicMock()
mock_tokenizer = MagicMock()
input_ids_mock = MagicMock()
input_ids_mock.shape = [1, 5]
mock_tokenizer.return_value = {"input_ids": input_ids_mock}
mock_tokenizer.decode.return_value = "Sir, affirmative."
mock_model.tokenizer = mock_tokenizer
mock_model.generate.return_value = [list(range(10))]
agent._model = mock_model
result = agent.run("test")
assert hasattr(result, "content"), "run() result must have a .content attribute"
assert isinstance(result.content, str)
def test_M603_airllm_run_updates_history():
"""run() must update _history so multi-turn context is preserved."""
with patch("timmy.backends.is_apple_silicon", return_value=False):
from timmy.backends import TimmyAirLLMAgent
agent = TimmyAirLLMAgent(model_size="8b")
mock_model = MagicMock()
mock_tokenizer = MagicMock()
input_ids_mock = MagicMock()
input_ids_mock.shape = [1, 5]
mock_tokenizer.return_value = {"input_ids": input_ids_mock}
mock_tokenizer.decode.return_value = "Acknowledged."
mock_model.tokenizer = mock_tokenizer
mock_model.generate.return_value = [list(range(10))]
agent._model = mock_model
assert len(agent._history) == 0
agent.run("hello")
assert len(agent._history) == 2
assert any("hello" in h for h in agent._history)
def test_M604_airllm_print_response_delegates_to_run():
"""print_response must use run() so both interfaces share one inference path."""
with patch("timmy.backends.is_apple_silicon", return_value=False):
from timmy.backends import RunResult, TimmyAirLLMAgent
agent = TimmyAirLLMAgent(model_size="8b")
with (
patch.object(agent, "run", return_value=RunResult(content="ok")) as mock_run,
patch.object(agent, "_render"),
):
agent.print_response("hello", stream=True)
mock_run.assert_called_once_with("hello", stream=True)
def test_M605_health_status_passes_model_to_template(client):
"""Health status partial must receive the configured model name, not a hardcoded string."""
from config import settings
with patch(
"dashboard.routes.health.check_ollama",
new_callable=AsyncMock,
return_value=True,
):
response = client.get("/health/status")
# Model name should come from settings, not be hardcoded
assert response.status_code == 200
model_short = settings.ollama_model.split(":")[0]
assert model_short in response.text
# ── M7xx — XSS prevention ─────────────────────────────────────────────────────
def _mobile_html() -> str:
"""Read the mobile template source."""
path = Path(__file__).parent.parent.parent / "src" / "dashboard" / "templates" / "mobile.html"
return path.read_text()
def _swarm_live_html() -> str:
"""Read the swarm live template source."""
path = (
Path(__file__).parent.parent.parent / "src" / "dashboard" / "templates" / "swarm_live.html"
)
return path.read_text()
def test_M701_mobile_chat_no_raw_message_interpolation():
"""mobile.html must not interpolate ${message} directly into innerHTML — XSS risk."""
html = _mobile_html()
# The vulnerable pattern is `${message}` inside a template literal assigned to innerHTML
# After the fix, message must only appear via textContent assignment
assert "textContent = message" in html or "textContent=message" in html, (
"mobile.html still uses innerHTML + ${message} interpolation — XSS vulnerability"
)
def test_M702_mobile_chat_user_input_not_in_innerhtml_template_literal():
"""${message} must not appear inside a backtick string that is assigned to innerHTML."""
html = _mobile_html()
# Find all innerHTML += `...` blocks and verify none contain ${message}
blocks = re.findall(r"innerHTML\s*\+=?\s*`([^`]*)`", html, re.DOTALL)
for block in blocks:
assert "${message}" not in block, (
"innerHTML template literal still contains ${message} — XSS vulnerability"
)
def test_M703_swarm_live_agent_name_not_interpolated_in_innerhtml():
"""swarm_live.html must not put ${agent.name} inside innerHTML template literals."""
html = _swarm_live_html()
blocks = re.findall(r"innerHTML\s*=\s*agents\.map\([^;]+\)\.join\([^)]*\)", html, re.DOTALL)
assert len(blocks) == 0, (
"swarm_live.html still uses innerHTML=agents.map(…) with interpolated agent data — XSS vulnerability"
)
def test_M704_swarm_live_uses_textcontent_for_agent_data():
"""swarm_live.html must use textContent (not innerHTML) to set agent name/description."""
html = _swarm_live_html()
assert "textContent" in html, (
"swarm_live.html does not use textContent — agent data may be raw-interpolated into DOM"
)

View File

@@ -0,0 +1,720 @@
"""Tests for GET /api/world/state endpoint and /api/world/ws relay."""
import asyncio
import json
import logging
import time
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from dashboard.routes.world import (
_GROUND_TTL,
_REMIND_AFTER,
_STALE_THRESHOLD,
_bark_and_broadcast,
_broadcast,
_build_commitment_context,
_build_world_state,
_commitments,
_conversation,
_extract_commitments,
_generate_bark,
_handle_client_message,
_heartbeat,
_log_bark_failure,
_read_presence_file,
_record_commitments,
_refresh_ground,
_tick_commitments,
broadcast_world_state,
close_commitment,
get_commitments,
reset_commitments,
reset_conversation_ground,
)
# ---------------------------------------------------------------------------
# _build_world_state
# ---------------------------------------------------------------------------
def test_build_world_state_maps_fields():
presence = {
"version": 1,
"liveness": "2026-03-19T02:00:00Z",
"mood": "exploring",
"current_focus": "reviewing PR",
"energy": 0.8,
"confidence": 0.9,
"active_threads": [{"type": "thinking", "ref": "test", "status": "active"}],
"recent_events": [],
"concerns": [],
}
result = _build_world_state(presence)
assert result["timmyState"]["mood"] == "exploring"
assert result["timmyState"]["activity"] == "reviewing PR"
assert result["timmyState"]["energy"] == 0.8
assert result["timmyState"]["confidence"] == 0.9
assert result["updatedAt"] == "2026-03-19T02:00:00Z"
assert result["version"] == 1
assert result["visitorPresent"] is False
assert len(result["activeThreads"]) == 1
def test_build_world_state_defaults():
"""Missing fields get safe defaults."""
result = _build_world_state({})
assert result["timmyState"]["mood"] == "calm"
assert result["timmyState"]["energy"] == 0.5
assert result["version"] == 1
# ---------------------------------------------------------------------------
# _read_presence_file
# ---------------------------------------------------------------------------
def test_read_presence_file_missing(tmp_path):
with patch("dashboard.routes.world.PRESENCE_FILE", tmp_path / "nope.json"):
assert _read_presence_file() is None
def test_read_presence_file_stale(tmp_path):
f = tmp_path / "presence.json"
f.write_text(json.dumps({"version": 1}))
# Backdate the file
stale_time = time.time() - _STALE_THRESHOLD - 10
import os
os.utime(f, (stale_time, stale_time))
with patch("dashboard.routes.world.PRESENCE_FILE", f):
assert _read_presence_file() is None
def test_read_presence_file_fresh(tmp_path):
f = tmp_path / "presence.json"
f.write_text(json.dumps({"version": 1, "mood": "focused"}))
with patch("dashboard.routes.world.PRESENCE_FILE", f):
result = _read_presence_file()
assert result is not None
assert result["version"] == 1
def test_read_presence_file_bad_json(tmp_path):
f = tmp_path / "presence.json"
f.write_text("not json {{{")
with patch("dashboard.routes.world.PRESENCE_FILE", f):
assert _read_presence_file() is None
# ---------------------------------------------------------------------------
# Full endpoint via TestClient
# ---------------------------------------------------------------------------
@pytest.fixture
def client():
from fastapi import FastAPI
from fastapi.testclient import TestClient
app = FastAPI()
from dashboard.routes.world import router
app.include_router(router)
return TestClient(app)
def test_world_state_endpoint_with_file(client, tmp_path):
"""Endpoint returns data from presence file when fresh."""
f = tmp_path / "presence.json"
f.write_text(
json.dumps(
{
"version": 1,
"liveness": "2026-03-19T02:00:00Z",
"mood": "exploring",
"current_focus": "testing",
"active_threads": [],
"recent_events": [],
"concerns": [],
}
)
)
with patch("dashboard.routes.world.PRESENCE_FILE", f):
resp = client.get("/api/world/state")
assert resp.status_code == 200
data = resp.json()
assert data["timmyState"]["mood"] == "exploring"
assert data["timmyState"]["activity"] == "testing"
assert resp.headers["cache-control"] == "no-cache, no-store"
def test_world_state_endpoint_fallback(client, tmp_path):
"""Endpoint falls back to live state when file missing."""
with (
patch("dashboard.routes.world.PRESENCE_FILE", tmp_path / "nope.json"),
patch("timmy.workshop_state.get_state_dict") as mock_get,
):
mock_get.return_value = {
"version": 1,
"liveness": "2026-03-19T02:00:00Z",
"mood": "calm",
"current_focus": "",
"active_threads": [],
"recent_events": [],
"concerns": [],
}
resp = client.get("/api/world/state")
assert resp.status_code == 200
assert resp.json()["timmyState"]["mood"] == "calm"
def test_world_state_endpoint_full_fallback(client, tmp_path):
"""Endpoint returns safe defaults when everything fails."""
with (
patch("dashboard.routes.world.PRESENCE_FILE", tmp_path / "nope.json"),
patch(
"timmy.workshop_state.get_state_dict",
side_effect=RuntimeError("boom"),
),
):
resp = client.get("/api/world/state")
assert resp.status_code == 200
data = resp.json()
assert data["timmyState"]["mood"] == "calm"
assert data["version"] == 1
# ---------------------------------------------------------------------------
# broadcast_world_state
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
async def test_broadcast_world_state_sends_timmy_state():
"""broadcast_world_state sends timmy_state JSON to connected clients."""
from dashboard.routes.world import _ws_clients
ws = AsyncMock()
_ws_clients.append(ws)
try:
presence = {
"version": 1,
"mood": "exploring",
"current_focus": "testing",
"energy": 0.8,
"confidence": 0.9,
}
await broadcast_world_state(presence)
ws.send_text.assert_called_once()
msg = json.loads(ws.send_text.call_args[0][0])
assert msg["type"] == "timmy_state"
assert msg["mood"] == "exploring"
assert msg["activity"] == "testing"
finally:
_ws_clients.clear()
@pytest.mark.asyncio
async def test_broadcast_world_state_removes_dead_clients():
"""Dead WebSocket connections are cleaned up on broadcast."""
from dashboard.routes.world import _ws_clients
dead_ws = AsyncMock()
dead_ws.send_text.side_effect = ConnectionError("gone")
_ws_clients.append(dead_ws)
try:
await broadcast_world_state({"mood": "idle"})
assert dead_ws not in _ws_clients
finally:
_ws_clients.clear()
def test_world_ws_endpoint_accepts_connection(client):
"""WebSocket endpoint at /api/world/ws accepts connections."""
with client.websocket_connect("/api/world/ws"):
pass # Connection accepted — just close it
def test_world_ws_sends_snapshot_on_connect(client, tmp_path):
"""WebSocket sends a world_state snapshot immediately on connect."""
f = tmp_path / "presence.json"
f.write_text(
json.dumps(
{
"version": 1,
"liveness": "2026-03-19T02:00:00Z",
"mood": "exploring",
"current_focus": "testing",
"active_threads": [],
"recent_events": [],
"concerns": [],
}
)
)
with patch("dashboard.routes.world.PRESENCE_FILE", f):
with client.websocket_connect("/api/world/ws") as ws:
msg = json.loads(ws.receive_text())
assert msg["type"] == "world_state"
assert msg["timmyState"]["mood"] == "exploring"
assert msg["timmyState"]["activity"] == "testing"
assert "updatedAt" in msg
# ---------------------------------------------------------------------------
# Visitor chat — bark engine
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
async def test_handle_client_message_ignores_non_json():
"""Non-JSON messages are silently ignored."""
await _handle_client_message("not json") # should not raise
@pytest.mark.asyncio
async def test_handle_client_message_ignores_unknown_type():
"""Unknown message types are ignored."""
await _handle_client_message(json.dumps({"type": "unknown"}))
@pytest.mark.asyncio
async def test_handle_client_message_ignores_empty_text():
"""Empty visitor_message text is ignored."""
await _handle_client_message(json.dumps({"type": "visitor_message", "text": " "}))
@pytest.mark.asyncio
async def test_generate_bark_returns_response():
"""_generate_bark returns the chat response."""
reset_conversation_ground()
with patch("timmy.session.chat", new_callable=AsyncMock) as mock_chat:
mock_chat.return_value = "Woof! Good to see you."
result = await _generate_bark("Hey Timmy!")
assert result == "Woof! Good to see you."
mock_chat.assert_called_once_with("Hey Timmy!", session_id="workshop")
@pytest.mark.asyncio
async def test_generate_bark_fallback_on_error():
"""_generate_bark returns canned response when chat fails."""
reset_conversation_ground()
with patch(
"timmy.session.chat",
new_callable=AsyncMock,
side_effect=RuntimeError("no model"),
):
result = await _generate_bark("Hello?")
assert "tangled" in result
@pytest.mark.asyncio
async def test_bark_and_broadcast_sends_thinking_then_speech():
"""_bark_and_broadcast sends thinking indicator then speech."""
from dashboard.routes.world import _ws_clients
ws = AsyncMock()
_ws_clients.append(ws)
_conversation.clear()
reset_conversation_ground()
try:
with patch(
"timmy.session.chat",
new_callable=AsyncMock,
return_value="All good here!",
):
await _bark_and_broadcast("How are you?")
# Should have sent two messages: thinking + speech
assert ws.send_text.call_count == 2
thinking = json.loads(ws.send_text.call_args_list[0][0][0])
speech = json.loads(ws.send_text.call_args_list[1][0][0])
assert thinking["type"] == "timmy_thinking"
assert speech["type"] == "timmy_speech"
assert speech["text"] == "All good here!"
assert len(speech["recentExchanges"]) == 1
assert speech["recentExchanges"][0]["visitor"] == "How are you?"
finally:
_ws_clients.clear()
_conversation.clear()
@pytest.mark.asyncio
async def test_broadcast_removes_dead_clients():
"""Dead clients are cleaned up during broadcast."""
from dashboard.routes.world import _ws_clients
dead = AsyncMock()
dead.send_text.side_effect = ConnectionError("gone")
_ws_clients.append(dead)
try:
await _broadcast(json.dumps({"type": "timmy_speech", "text": "test"}))
assert dead not in _ws_clients
finally:
_ws_clients.clear()
@pytest.mark.asyncio
async def test_conversation_buffer_caps_at_max():
"""Conversation buffer only keeps the last _MAX_EXCHANGES entries."""
from dashboard.routes.world import _MAX_EXCHANGES, _ws_clients
ws = AsyncMock()
_ws_clients.append(ws)
_conversation.clear()
reset_conversation_ground()
try:
with patch(
"timmy.session.chat",
new_callable=AsyncMock,
return_value="reply",
):
for i in range(_MAX_EXCHANGES + 2):
await _bark_and_broadcast(f"msg {i}")
assert len(_conversation) == _MAX_EXCHANGES
# Oldest messages should have been evicted
assert _conversation[0]["visitor"] == f"msg {_MAX_EXCHANGES + 2 - _MAX_EXCHANGES}"
finally:
_ws_clients.clear()
_conversation.clear()
def test_log_bark_failure_logs_exception(caplog):
"""_log_bark_failure logs errors from failed bark tasks."""
loop = asyncio.new_event_loop()
async def _fail():
raise RuntimeError("bark boom")
task = loop.create_task(_fail())
loop.run_until_complete(asyncio.sleep(0.01))
loop.close()
with caplog.at_level(logging.ERROR):
_log_bark_failure(task)
assert "bark boom" in caplog.text
def test_log_bark_failure_ignores_cancelled():
"""_log_bark_failure silently ignores cancelled tasks."""
task = MagicMock(spec=asyncio.Task)
task.cancelled.return_value = True
_log_bark_failure(task) # should not raise
# ---------------------------------------------------------------------------
# Conversation grounding (#322)
# ---------------------------------------------------------------------------
class TestConversationGrounding:
"""Tests for conversation grounding — prevent topic drift."""
def setup_method(self):
reset_conversation_ground()
def teardown_method(self):
reset_conversation_ground()
def test_refresh_ground_sets_topic_on_first_message(self):
"""First visitor message becomes the grounding anchor."""
import dashboard.routes.world as w
_refresh_ground("Tell me about the Bible")
assert w._ground_topic == "Tell me about the Bible"
assert w._ground_set_at > 0
def test_refresh_ground_keeps_topic_on_subsequent_messages(self):
"""Subsequent messages don't overwrite the anchor."""
import dashboard.routes.world as w
_refresh_ground("Tell me about the Bible")
_refresh_ground("What about Genesis?")
assert w._ground_topic == "Tell me about the Bible"
def test_refresh_ground_resets_after_ttl(self):
"""Anchor expires after _GROUND_TTL seconds of inactivity."""
import dashboard.routes.world as w
_refresh_ground("Tell me about the Bible")
# Simulate TTL expiry
w._ground_set_at = time.time() - _GROUND_TTL - 1
_refresh_ground("Now tell me about cooking")
assert w._ground_topic == "Now tell me about cooking"
def test_refresh_ground_truncates_long_messages(self):
"""Anchor text is capped at 120 characters."""
import dashboard.routes.world as w
long_msg = "x" * 200
_refresh_ground(long_msg)
assert len(w._ground_topic) == 120
def test_reset_conversation_ground_clears_state(self):
"""reset_conversation_ground clears the anchor."""
import dashboard.routes.world as w
_refresh_ground("Some topic")
reset_conversation_ground()
assert w._ground_topic is None
assert w._ground_set_at == 0.0
@pytest.mark.asyncio
async def test_generate_bark_prepends_ground_topic(self):
"""When grounded, the topic is prepended to the visitor message."""
_refresh_ground("Tell me about prayer")
with patch("timmy.session.chat", new_callable=AsyncMock) as mock_chat:
mock_chat.return_value = "Great question!"
await _generate_bark("What else can you share?")
call_text = mock_chat.call_args[0][0]
assert "[Workshop conversation topic: Tell me about prayer]" in call_text
assert "What else can you share?" in call_text
@pytest.mark.asyncio
async def test_generate_bark_no_prefix_for_first_message(self):
"""First message (which IS the anchor) is not prefixed."""
_refresh_ground("Tell me about prayer")
with patch("timmy.session.chat", new_callable=AsyncMock) as mock_chat:
mock_chat.return_value = "Sure!"
await _generate_bark("Tell me about prayer")
call_text = mock_chat.call_args[0][0]
assert "[Workshop conversation topic:" not in call_text
assert call_text == "Tell me about prayer"
@pytest.mark.asyncio
async def test_bark_and_broadcast_sets_ground(self):
"""_bark_and_broadcast sets the ground topic automatically."""
import dashboard.routes.world as w
from dashboard.routes.world import _ws_clients
ws = AsyncMock()
_ws_clients.append(ws)
_conversation.clear()
try:
with patch(
"timmy.session.chat",
new_callable=AsyncMock,
return_value="Interesting!",
):
await _bark_and_broadcast("What is grace?")
assert w._ground_topic == "What is grace?"
finally:
_ws_clients.clear()
_conversation.clear()
# ---------------------------------------------------------------------------
# Conversation grounding — commitment tracking (rescued from PR #408)
# ---------------------------------------------------------------------------
@pytest.fixture(autouse=False)
def _clean_commitments():
"""Reset commitments before and after each commitment test."""
reset_commitments()
yield
reset_commitments()
class TestExtractCommitments:
def test_extracts_ill_pattern(self):
text = "I'll draft the skeleton ticket in 30 minutes."
result = _extract_commitments(text)
assert len(result) == 1
assert "draft the skeleton ticket" in result[0]
def test_extracts_i_will_pattern(self):
result = _extract_commitments("I will review that PR tomorrow.")
assert len(result) == 1
assert "review that PR tomorrow" in result[0]
def test_extracts_let_me_pattern(self):
result = _extract_commitments("Let me write up a summary for you.")
assert len(result) == 1
assert "write up a summary" in result[0]
def test_skips_short_matches(self):
result = _extract_commitments("I'll do it.")
# "do it" is 5 chars — should be skipped (needs > 5)
assert result == []
def test_no_commitments_in_normal_text(self):
result = _extract_commitments("The weather is nice today.")
assert result == []
def test_truncates_long_commitments(self):
long_phrase = "a" * 200
result = _extract_commitments(f"I'll {long_phrase}.")
assert len(result) == 1
assert len(result[0]) == 120
class TestRecordCommitments:
def test_records_new_commitment(self, _clean_commitments):
_record_commitments("I'll draft the ticket now.")
assert len(get_commitments()) == 1
assert get_commitments()[0]["messages_since"] == 0
def test_avoids_duplicate_commitments(self, _clean_commitments):
_record_commitments("I'll draft the ticket now.")
_record_commitments("I'll draft the ticket now.")
assert len(get_commitments()) == 1
def test_caps_at_max(self, _clean_commitments):
from dashboard.routes.world import _MAX_COMMITMENTS
for i in range(_MAX_COMMITMENTS + 3):
_record_commitments(f"I'll handle commitment number {i} right away.")
assert len(get_commitments()) <= _MAX_COMMITMENTS
class TestTickAndContext:
def test_tick_increments_messages_since(self, _clean_commitments):
_commitments.append({"text": "write the docs", "created_at": 0, "messages_since": 0})
_tick_commitments()
_tick_commitments()
assert _commitments[0]["messages_since"] == 2
def test_context_empty_when_no_overdue(self, _clean_commitments):
_commitments.append({"text": "write the docs", "created_at": 0, "messages_since": 0})
assert _build_commitment_context() == ""
def test_context_surfaces_overdue_commitments(self, _clean_commitments):
_commitments.append(
{
"text": "draft the skeleton ticket",
"created_at": 0,
"messages_since": _REMIND_AFTER,
}
)
ctx = _build_commitment_context()
assert "draft the skeleton ticket" in ctx
assert "Open commitments" in ctx
def test_context_only_includes_overdue(self, _clean_commitments):
_commitments.append({"text": "recent thing", "created_at": 0, "messages_since": 1})
_commitments.append(
{
"text": "old thing",
"created_at": 0,
"messages_since": _REMIND_AFTER,
}
)
ctx = _build_commitment_context()
assert "old thing" in ctx
assert "recent thing" not in ctx
class TestCloseCommitment:
def test_close_valid_index(self, _clean_commitments):
_commitments.append({"text": "write the docs", "created_at": 0, "messages_since": 0})
assert close_commitment(0) is True
assert len(get_commitments()) == 0
def test_close_invalid_index(self, _clean_commitments):
assert close_commitment(99) is False
class TestGroundingIntegration:
@pytest.mark.asyncio
async def test_bark_records_commitments_from_reply(self, _clean_commitments):
from dashboard.routes.world import _ws_clients
ws = AsyncMock()
_ws_clients.append(ws)
_conversation.clear()
try:
with patch(
"timmy.session.chat",
new_callable=AsyncMock,
return_value="I'll draft the ticket for you!",
):
await _bark_and_broadcast("Can you help?")
assert len(get_commitments()) == 1
assert "draft the ticket" in get_commitments()[0]["text"]
finally:
_ws_clients.clear()
_conversation.clear()
@pytest.mark.asyncio
async def test_bark_prepends_context_after_n_messages(self, _clean_commitments):
"""After _REMIND_AFTER messages, commitment context is prepended."""
_commitments.append(
{
"text": "draft the skeleton ticket",
"created_at": 0,
"messages_since": _REMIND_AFTER - 1,
}
)
with patch(
"timmy.session.chat",
new_callable=AsyncMock,
return_value="Sure thing!",
) as mock_chat:
# This tick will push messages_since to _REMIND_AFTER
await _generate_bark("Any updates?")
# _generate_bark doesn't tick — _bark_and_broadcast does.
# But we pre-set messages_since to _REMIND_AFTER - 1,
# so we need to tick once to make it overdue.
_tick_commitments()
await _generate_bark("Any updates?")
# Second call should have context prepended
last_call = mock_chat.call_args_list[-1]
sent_text = last_call[0][0]
assert "draft the skeleton ticket" in sent_text
assert "Open commitments" in sent_text
# ---------------------------------------------------------------------------
# WebSocket heartbeat ping (rescued from PR #399)
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
async def test_heartbeat_sends_ping():
"""Heartbeat sends a ping JSON frame after the interval elapses."""
ws = AsyncMock()
with patch("dashboard.routes.world.asyncio.sleep", new_callable=AsyncMock) as mock_sleep:
# Let the first sleep complete, then raise to exit the loop
call_count = 0
async def sleep_side_effect(_interval):
nonlocal call_count
call_count += 1
if call_count > 1:
raise ConnectionError("stop")
mock_sleep.side_effect = sleep_side_effect
await _heartbeat(ws)
ws.send_text.assert_called_once()
msg = json.loads(ws.send_text.call_args[0][0])
assert msg["type"] == "ping"
@pytest.mark.asyncio
async def test_heartbeat_exits_on_dead_connection():
"""Heartbeat exits cleanly when the WebSocket is dead."""
ws = AsyncMock()
ws.send_text.side_effect = ConnectionError("gone")
with patch("dashboard.routes.world.asyncio.sleep", new_callable=AsyncMock):
await _heartbeat(ws) # should not raise

View File

@@ -5,9 +5,14 @@ from datetime import UTC, datetime, timedelta
from unittest.mock import patch
from infrastructure.error_capture import (
_create_bug_report,
_dedup_cache,
_extract_traceback_info,
_get_git_context,
_is_duplicate,
_log_error_event,
_notify_bug_report,
_record_to_session,
_stack_hash,
capture_error,
)
@@ -193,3 +198,91 @@ class TestCaptureError:
def teardown_method(self):
_dedup_cache.clear()
class TestExtractTracebackInfo:
"""Test _extract_traceback_info helper."""
def test_returns_three_tuple(self):
try:
raise ValueError("extract test")
except ValueError as e:
tb_str, affected_file, affected_line = _extract_traceback_info(e)
assert "ValueError" in tb_str
assert "extract test" in tb_str
assert affected_file.endswith(".py")
assert affected_line > 0
def test_file_points_to_raise_site(self):
try:
_make_exception()
except ValueError as e:
_, affected_file, _ = _extract_traceback_info(e)
assert "test_error_capture" in affected_file
class TestLogErrorEvent:
"""Test _log_error_event helper."""
def test_does_not_crash_on_missing_deps(self):
try:
raise RuntimeError("log test")
except RuntimeError as e:
_log_error_event(e, "test", "abc123", "file.py", 42, {"branch": "main"})
class TestCreateBugReport:
"""Test _create_bug_report helper."""
def test_does_not_crash_on_missing_deps(self):
try:
raise RuntimeError("report test")
except RuntimeError as e:
result = _create_bug_report(
e, "test", None, "abc123", "traceback...", "file.py", 42, {}
)
# May return None if swarm deps unavailable — that's fine
assert result is None or isinstance(result, str)
def test_with_context(self):
try:
raise RuntimeError("ctx test")
except RuntimeError as e:
result = _create_bug_report(e, "test", {"path": "/api"}, "abc", "tb", "f.py", 1, {})
assert result is None or isinstance(result, str)
class TestNotifyBugReport:
"""Test _notify_bug_report helper."""
def test_does_not_crash(self):
try:
raise RuntimeError("notify test")
except RuntimeError as e:
_notify_bug_report(e, "test")
class TestRecordToSession:
"""Test _record_to_session helper."""
def test_does_not_crash_without_recorder(self):
try:
raise RuntimeError("session test")
except RuntimeError as e:
_record_to_session(e, "test")
def test_calls_registered_recorder(self):
from infrastructure.error_capture import register_error_recorder
calls = []
register_error_recorder(lambda **kwargs: calls.append(kwargs))
try:
try:
raise RuntimeError("callback test")
except RuntimeError as e:
_record_to_session(e, "test_source")
assert len(calls) == 1
assert "RuntimeError" in calls[0]["error"]
assert calls[0]["context"] == "test_source"
finally:
register_error_recorder(None)

View File

@@ -2,7 +2,7 @@
import time
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock, patch
from unittest.mock import AsyncMock, patch
import pytest
import yaml
@@ -489,30 +489,182 @@ class TestProviderAvailabilityCheck:
assert router._check_provider_available(provider) is False
def test_check_airllm_installed(self):
"""Test AirLLM when installed."""
router = CascadeRouter(config_path=Path("/nonexistent"))
provider = Provider(
name="airllm",
type="airllm",
enabled=True,
priority=1,
class TestCascadeRouterReload:
"""Test hot-reload of providers.yaml."""
def test_reload_preserves_metrics(self, tmp_path):
"""Test that reload preserves metrics for existing providers."""
config = {
"providers": [
{
"name": "test-openai",
"type": "openai",
"enabled": True,
"priority": 1,
"api_key": "sk-test",
}
],
}
config_path = tmp_path / "providers.yaml"
config_path.write_text(yaml.dump(config))
router = CascadeRouter(config_path=config_path)
assert len(router.providers) == 1
# Simulate some traffic
router._record_success(router.providers[0], 150.0)
router._record_success(router.providers[0], 250.0)
assert router.providers[0].metrics.total_requests == 2
# Reload
result = router.reload_config()
assert result["total_providers"] == 1
assert result["preserved"] == 1
assert result["added"] == []
assert result["removed"] == []
# Metrics survived
assert router.providers[0].metrics.total_requests == 2
assert router.providers[0].metrics.total_latency_ms == 400.0
def test_reload_preserves_circuit_breaker(self, tmp_path):
"""Test that reload preserves circuit breaker state."""
config = {
"cascade": {"circuit_breaker": {"failure_threshold": 2}},
"providers": [
{
"name": "test-openai",
"type": "openai",
"enabled": True,
"priority": 1,
"api_key": "sk-test",
}
],
}
config_path = tmp_path / "providers.yaml"
config_path.write_text(yaml.dump(config))
router = CascadeRouter(config_path=config_path)
# Open circuit breaker
for _ in range(2):
router._record_failure(router.providers[0])
assert router.providers[0].circuit_state == CircuitState.OPEN
# Reload
router.reload_config()
# Circuit breaker state preserved
assert router.providers[0].circuit_state == CircuitState.OPEN
assert router.providers[0].status == ProviderStatus.UNHEALTHY
def test_reload_detects_added_provider(self, tmp_path):
"""Test that reload detects newly added providers."""
config = {
"providers": [
{
"name": "openai-1",
"type": "openai",
"enabled": True,
"priority": 1,
"api_key": "sk-test",
}
],
}
config_path = tmp_path / "providers.yaml"
config_path.write_text(yaml.dump(config))
router = CascadeRouter(config_path=config_path)
assert len(router.providers) == 1
# Add a second provider to config
config["providers"].append(
{
"name": "anthropic-1",
"type": "anthropic",
"enabled": True,
"priority": 2,
"api_key": "sk-ant-test",
}
)
config_path.write_text(yaml.dump(config))
with patch("importlib.util.find_spec", return_value=MagicMock()):
assert router._check_provider_available(provider) is True
result = router.reload_config()
def test_check_airllm_not_installed(self):
"""Test AirLLM when not installed."""
router = CascadeRouter(config_path=Path("/nonexistent"))
assert result["total_providers"] == 2
assert result["preserved"] == 1
assert result["added"] == ["anthropic-1"]
assert result["removed"] == []
provider = Provider(
name="airllm",
type="airllm",
enabled=True,
priority=1,
)
def test_reload_detects_removed_provider(self, tmp_path):
"""Test that reload detects removed providers."""
config = {
"providers": [
{
"name": "openai-1",
"type": "openai",
"enabled": True,
"priority": 1,
"api_key": "sk-test",
},
{
"name": "anthropic-1",
"type": "anthropic",
"enabled": True,
"priority": 2,
"api_key": "sk-ant-test",
},
],
}
config_path = tmp_path / "providers.yaml"
config_path.write_text(yaml.dump(config))
with patch("importlib.util.find_spec", return_value=None):
assert router._check_provider_available(provider) is False
router = CascadeRouter(config_path=config_path)
assert len(router.providers) == 2
# Remove anthropic
config["providers"] = [config["providers"][0]]
config_path.write_text(yaml.dump(config))
result = router.reload_config()
assert result["total_providers"] == 1
assert result["preserved"] == 1
assert result["removed"] == ["anthropic-1"]
def test_reload_re_sorts_by_priority(self, tmp_path):
"""Test that providers are re-sorted by priority after reload."""
config = {
"providers": [
{
"name": "low-priority",
"type": "openai",
"enabled": True,
"priority": 10,
"api_key": "sk-test",
},
{
"name": "high-priority",
"type": "openai",
"enabled": True,
"priority": 1,
"api_key": "sk-test2",
},
],
}
config_path = tmp_path / "providers.yaml"
config_path.write_text(yaml.dump(config))
router = CascadeRouter(config_path=config_path)
assert router.providers[0].name == "high-priority"
# Swap priorities
config["providers"][0]["priority"] = 1
config["providers"][1]["priority"] = 10
config_path.write_text(yaml.dump(config))
router.reload_config()
assert router.providers[0].name == "low-priority"
assert router.providers[1].name == "high-priority"

View File

@@ -0,0 +1,285 @@
"""Integration tests for agentic loop WebSocket broadcasts.
Verifies that ``run_agentic_loop`` pushes the correct sequence of events
through the real ``ws_manager`` and that connected (mock) WebSocket clients
receive every broadcast with the expected payloads.
"""
import json
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from infrastructure.ws_manager.handler import WebSocketManager
from timmy.agentic_loop import run_agentic_loop
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _mock_run(content: str):
m = MagicMock()
m.content = content
return m
def _ws_client() -> AsyncMock:
"""Return a fake WebSocket that records sent messages."""
return AsyncMock()
def _collected_events(ws: AsyncMock) -> list[dict]:
"""Extract parsed JSON events from a mock WebSocket's send_text calls."""
return [json.loads(call.args[0]) for call in ws.send_text.call_args_list]
# ---------------------------------------------------------------------------
# Tests
# ---------------------------------------------------------------------------
class TestAgenticLoopBroadcastSequence:
"""Events arrive at WS clients in the correct order with expected data."""
@pytest.mark.asyncio
async def test_successful_run_broadcasts_plan_steps_complete(self):
"""A successful 2-step loop emits plan_ready → 2× step_complete → task_complete."""
mgr = WebSocketManager()
ws = _ws_client()
mgr._connections = [ws]
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Gather data\n2. Summarise"),
_mock_run("Gathered 10 records"),
_mock_run("Summary written"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("infrastructure.ws_manager.handler.ws_manager", mgr),
):
result = await run_agentic_loop("Gather and summarise", max_steps=2)
assert result.status == "completed"
events = _collected_events(ws)
event_names = [e["event"] for e in events]
assert event_names == [
"agentic.plan_ready",
"agentic.step_complete",
"agentic.step_complete",
"agentic.task_complete",
]
@pytest.mark.asyncio
async def test_plan_ready_payload(self):
"""plan_ready contains task_id, task, steps list, and total count."""
mgr = WebSocketManager()
ws = _ws_client()
mgr._connections = [ws]
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Alpha\n2. Beta"),
_mock_run("Alpha done"),
_mock_run("Beta done"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("infrastructure.ws_manager.handler.ws_manager", mgr),
):
result = await run_agentic_loop("Two steps")
plan_event = _collected_events(ws)[0]
assert plan_event["event"] == "agentic.plan_ready"
data = plan_event["data"]
assert data["task_id"] == result.task_id
assert data["task"] == "Two steps"
assert data["steps"] == ["Alpha", "Beta"]
assert data["total"] == 2
@pytest.mark.asyncio
async def test_step_complete_payload(self):
"""step_complete carries step number, total, description, and result."""
mgr = WebSocketManager()
ws = _ws_client()
mgr._connections = [ws]
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Only step"),
_mock_run("Step result text"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("infrastructure.ws_manager.handler.ws_manager", mgr),
):
await run_agentic_loop("Single step", max_steps=1)
step_event = _collected_events(ws)[1]
assert step_event["event"] == "agentic.step_complete"
data = step_event["data"]
assert data["step"] == 1
assert data["total"] == 1
assert data["description"] == "Only step"
assert "Step result text" in data["result"]
@pytest.mark.asyncio
async def test_task_complete_payload(self):
"""task_complete has status, steps_completed, summary, and duration_ms."""
mgr = WebSocketManager()
ws = _ws_client()
mgr._connections = [ws]
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Do it"),
_mock_run("Done"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("infrastructure.ws_manager.handler.ws_manager", mgr),
):
await run_agentic_loop("Quick", max_steps=1)
complete_event = _collected_events(ws)[-1]
assert complete_event["event"] == "agentic.task_complete"
data = complete_event["data"]
assert data["status"] == "completed"
assert data["steps_completed"] == 1
assert isinstance(data["duration_ms"], int)
assert data["duration_ms"] >= 0
assert data["summary"]
class TestAdaptationBroadcast:
"""Adapted steps emit step_adapted events."""
@pytest.mark.asyncio
async def test_adapted_step_broadcasts_step_adapted(self):
"""A failed-then-adapted step emits agentic.step_adapted."""
mgr = WebSocketManager()
ws = _ws_client()
mgr._connections = [ws]
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Risky step"),
Exception("disk full"),
_mock_run("Used /tmp instead"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("infrastructure.ws_manager.handler.ws_manager", mgr),
):
result = await run_agentic_loop("Adapt test", max_steps=1)
events = _collected_events(ws)
event_names = [e["event"] for e in events]
assert "agentic.step_adapted" in event_names
adapted = next(e for e in events if e["event"] == "agentic.step_adapted")
assert adapted["data"]["error"] == "disk full"
assert adapted["data"]["adaptation"]
assert result.steps[0].status == "adapted"
class TestMultipleClients:
"""All connected clients receive every broadcast."""
@pytest.mark.asyncio
async def test_two_clients_receive_all_events(self):
mgr = WebSocketManager()
ws1 = _ws_client()
ws2 = _ws_client()
mgr._connections = [ws1, ws2]
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Step A"),
_mock_run("A done"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("infrastructure.ws_manager.handler.ws_manager", mgr),
):
await run_agentic_loop("Multi-client", max_steps=1)
events1 = _collected_events(ws1)
events2 = _collected_events(ws2)
assert len(events1) == len(events2) == 3 # plan + step + complete
assert [e["event"] for e in events1] == [e["event"] for e in events2]
class TestEventHistory:
"""Broadcasts are recorded in ws_manager event history."""
@pytest.mark.asyncio
async def test_events_appear_in_history(self):
mgr = WebSocketManager()
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Only"),
_mock_run("Done"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("infrastructure.ws_manager.handler.ws_manager", mgr),
):
await run_agentic_loop("History test", max_steps=1)
history_events = [e.event for e in mgr.event_history]
assert "agentic.plan_ready" in history_events
assert "agentic.step_complete" in history_events
assert "agentic.task_complete" in history_events
class TestBroadcastGracefulDegradation:
"""Loop completes even when ws_manager is unavailable."""
@pytest.mark.asyncio
async def test_loop_succeeds_when_broadcast_fails(self):
"""ImportError from ws_manager doesn't crash the loop."""
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Do it"),
_mock_run("Done"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch(
"infrastructure.ws_manager.handler.ws_manager",
new_callable=lambda: MagicMock,
) as broken_mgr,
):
broken_mgr.broadcast = AsyncMock(side_effect=RuntimeError("ws down"))
result = await run_agentic_loop("Resilient task", max_steps=1)
assert result.status == "completed"
assert len(result.steps) == 1

View File

@@ -174,6 +174,103 @@ class TestDiscordVendor:
assert result is False
class TestExtractContent:
def test_strips_bot_mention(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
vendor._client = MagicMock()
vendor._client.user.id = 12345
msg = MagicMock()
msg.content = "<@12345> hello there"
assert vendor._extract_content(msg) == "hello there"
def test_no_client_user(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
vendor._client = MagicMock()
vendor._client.user = None
msg = MagicMock()
msg.content = "hello"
assert vendor._extract_content(msg) == "hello"
def test_empty_after_strip(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
vendor._client = MagicMock()
vendor._client.user.id = 99
msg = MagicMock()
msg.content = "<@99>"
assert vendor._extract_content(msg) == ""
class TestInvokeAgent:
@staticmethod
def _make_typing_target():
"""Build a mock target whose .typing() is an async context manager."""
from contextlib import asynccontextmanager
target = AsyncMock()
@asynccontextmanager
async def _typing():
yield
target.typing = _typing
return target
@pytest.mark.asyncio
async def test_timeout_returns_error(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
target = self._make_typing_target()
with patch(
"integrations.chat_bridge.vendors.discord.chat_with_tools", side_effect=TimeoutError
):
run_output, response = await vendor._invoke_agent("hi", "sess", target)
assert run_output is None
assert "too long" in response
@pytest.mark.asyncio
async def test_exception_returns_error(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
vendor = DiscordVendor()
target = self._make_typing_target()
with patch(
"integrations.chat_bridge.vendors.discord.chat_with_tools",
side_effect=RuntimeError("boom"),
):
run_output, response = await vendor._invoke_agent("hi", "sess", target)
assert run_output is None
assert "trouble" in response
class TestSendResponse:
@pytest.mark.asyncio
async def test_skips_empty(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
target = AsyncMock()
await DiscordVendor._send_response(None, target)
target.send.assert_not_called()
await DiscordVendor._send_response("", target)
target.send.assert_not_called()
@pytest.mark.asyncio
async def test_sends_short_message(self):
from integrations.chat_bridge.vendors.discord import DiscordVendor
target = AsyncMock()
await DiscordVendor._send_response("hello", target)
target.send.assert_called_once_with("hello")
class TestChunkMessage:
def test_short_message(self):
from integrations.chat_bridge.vendors.discord import _chunk_message

View File

@@ -0,0 +1,95 @@
"""Tests for the presence file watcher in dashboard.app."""
import asyncio
import json
from unittest.mock import AsyncMock, patch
import pytest
# Common patches to eliminate delays and inject mock ws_manager
_FAST = {
"dashboard.app._PRESENCE_POLL_SECONDS": 0.01,
"dashboard.app._PRESENCE_INITIAL_DELAY": 0,
}
def _patches(mock_ws, presence_file):
"""Return a combined context manager for presence watcher patches."""
from contextlib import ExitStack
stack = ExitStack()
stack.enter_context(patch("dashboard.app.PRESENCE_FILE", presence_file))
stack.enter_context(patch("infrastructure.ws_manager.handler.ws_manager", mock_ws))
for key, val in _FAST.items():
stack.enter_context(patch(key, val))
return stack
@pytest.mark.asyncio
async def test_presence_watcher_broadcasts_on_file_change(tmp_path):
"""Watcher reads presence.json and broadcasts via ws_manager."""
from dashboard.app import _presence_watcher
presence_file = tmp_path / "presence.json"
state = {
"version": 1,
"liveness": "2026-03-18T21:47:12Z",
"current_focus": "Reviewing PR #267",
"mood": "focused",
}
presence_file.write_text(json.dumps(state))
mock_ws = AsyncMock()
with _patches(mock_ws, presence_file):
task = asyncio.create_task(_presence_watcher())
await asyncio.sleep(0.15)
task.cancel()
try:
await task
except asyncio.CancelledError:
pass
mock_ws.broadcast.assert_called_with("timmy_state", state)
@pytest.mark.asyncio
async def test_presence_watcher_synthesised_state_when_missing(tmp_path):
"""Watcher broadcasts synthesised idle state when file is absent."""
from dashboard.app import _SYNTHESIZED_STATE, _presence_watcher
missing_file = tmp_path / "no-such-file.json"
mock_ws = AsyncMock()
with _patches(mock_ws, missing_file):
task = asyncio.create_task(_presence_watcher())
await asyncio.sleep(0.15)
task.cancel()
try:
await task
except asyncio.CancelledError:
pass
mock_ws.broadcast.assert_called_with("timmy_state", _SYNTHESIZED_STATE)
@pytest.mark.asyncio
async def test_presence_watcher_handles_bad_json(tmp_path):
"""Watcher logs warning on malformed JSON and doesn't crash."""
from dashboard.app import _presence_watcher
presence_file = tmp_path / "presence.json"
presence_file.write_text("{bad json!!!")
mock_ws = AsyncMock()
with _patches(mock_ws, presence_file):
task = asyncio.create_task(_presence_watcher())
await asyncio.sleep(0.15)
task.cancel()
try:
await task
except asyncio.CancelledError:
pass
# Should not have broadcast anything on bad JSON
mock_ws.broadcast.assert_not_called()

0
tests/loop/__init__.py Normal file
View File

View File

@@ -0,0 +1,86 @@
"""Tests for scripts/cycle_retro.py issue auto-detection."""
from __future__ import annotations
# Import the module under test — it's a script so we import the helpers directly
import importlib
import subprocess
from pathlib import Path
from unittest.mock import patch
import pytest
SCRIPTS_DIR = Path(__file__).resolve().parent.parent.parent / "scripts"
@pytest.fixture(autouse=True)
def _add_scripts_to_path(monkeypatch):
monkeypatch.syspath_prepend(str(SCRIPTS_DIR))
@pytest.fixture()
def mod():
"""Import cycle_retro as a module."""
return importlib.import_module("cycle_retro")
class TestDetectIssueFromBranch:
def test_kimi_issue_branch(self, mod):
with patch.object(subprocess, "check_output", return_value="kimi/issue-492\n"):
assert mod.detect_issue_from_branch() == 492
def test_plain_issue_branch(self, mod):
with patch.object(subprocess, "check_output", return_value="issue-123\n"):
assert mod.detect_issue_from_branch() == 123
def test_issue_slash_number(self, mod):
with patch.object(subprocess, "check_output", return_value="fix/issue/55\n"):
assert mod.detect_issue_from_branch() == 55
def test_no_issue_in_branch(self, mod):
with patch.object(subprocess, "check_output", return_value="main\n"):
assert mod.detect_issue_from_branch() is None
def test_feature_branch(self, mod):
with patch.object(subprocess, "check_output", return_value="feature/add-widget\n"):
assert mod.detect_issue_from_branch() is None
def test_git_not_available(self, mod):
with patch.object(subprocess, "check_output", side_effect=FileNotFoundError):
assert mod.detect_issue_from_branch() is None
def test_git_fails(self, mod):
with patch.object(
subprocess,
"check_output",
side_effect=subprocess.CalledProcessError(1, "git"),
):
assert mod.detect_issue_from_branch() is None
class TestBackfillExtractIssueNumber:
"""Tests for backfill_retro.extract_issue_number PR-number filtering."""
@pytest.fixture()
def backfill(self):
return importlib.import_module("backfill_retro")
def test_body_has_issue(self, backfill):
assert backfill.extract_issue_number("fix: foo (#491)", "Fixes #490", pr_number=491) == 490
def test_title_skips_pr_number(self, backfill):
assert backfill.extract_issue_number("fix: foo (#491)", "", pr_number=491) is None
def test_title_with_issue_and_pr(self, backfill):
# [loop-cycle-538] refactor: ... (#459) (#481)
assert (
backfill.extract_issue_number(
"[loop-cycle-538] refactor: remove dead airllm (#459) (#481)",
"",
pr_number=481,
)
== 459
)
def test_no_pr_number_provided(self, backfill):
assert backfill.extract_issue_number("fix: foo (#491)", "") == 491

View File

@@ -0,0 +1,133 @@
"""Tests for the three-phase loop scaffold.
Validates the acceptance criteria from issue #324:
1. Loop accepts context payload as input to Phase 1
2. Phase 1 output feeds into Phase 2 without manual intervention
3. Phase 2 output feeds into Phase 3 without manual intervention
4. Phase 3 output feeds back into Phase 1
5. Full cycle completes without crash
6. No state leaks between cycles
7. Each phase logs what it received and what it produced
"""
from datetime import datetime
from loop.phase1_gather import gather
from loop.phase2_reason import reason
from loop.phase3_act import act
from loop.runner import run_cycle
from loop.schema import ContextPayload
def _make_payload(source: str = "test", content: str = "hello") -> ContextPayload:
return ContextPayload(source=source, content=content, token_count=5)
# --- Schema ---
def test_context_payload_defaults():
p = ContextPayload(source="user", content="hi")
assert p.source == "user"
assert p.content == "hi"
assert p.token_count == -1
assert p.metadata == {}
assert isinstance(p.timestamp, datetime)
def test_with_metadata_returns_new_payload():
p = _make_payload()
p2 = p.with_metadata(foo="bar")
assert p2.metadata == {"foo": "bar"}
assert p.metadata == {} # original unchanged
def test_with_metadata_merges():
p = _make_payload().with_metadata(a=1)
p2 = p.with_metadata(b=2)
assert p2.metadata == {"a": 1, "b": 2}
# --- Individual phases ---
def test_gather_marks_phase():
result = gather(_make_payload())
assert result.metadata["phase"] == "gather"
assert result.metadata["gathered"] is True
def test_reason_marks_phase():
gathered = gather(_make_payload())
result = reason(gathered)
assert result.metadata["phase"] == "reason"
assert result.metadata["reasoned"] is True
def test_act_marks_phase():
gathered = gather(_make_payload())
reasoned = reason(gathered)
result = act(reasoned)
assert result.metadata["phase"] == "act"
assert result.metadata["acted"] is True
# --- Full cycle ---
def test_full_cycle_completes():
"""Acceptance criterion 5: full cycle completes without crash."""
payload = _make_payload(source="user", content="What is sovereignty?")
result = run_cycle(payload)
assert result.metadata["gathered"] is True
assert result.metadata["reasoned"] is True
assert result.metadata["acted"] is True
def test_full_cycle_preserves_source():
"""Source field survives the full pipeline."""
result = run_cycle(_make_payload(source="timer"))
assert result.source == "timer"
def test_full_cycle_preserves_content():
"""Content field survives the full pipeline."""
result = run_cycle(_make_payload(content="test data"))
assert result.content == "test data"
def test_no_state_leaks_between_cycles():
"""Acceptance criterion 6: no state leaks between cycles."""
r1 = run_cycle(_make_payload(source="cycle1", content="first"))
r2 = run_cycle(_make_payload(source="cycle2", content="second"))
assert r1.source == "cycle1"
assert r2.source == "cycle2"
assert r1.content == "first"
assert r2.content == "second"
def test_cycle_output_feeds_back_as_input():
"""Acceptance criterion 4: Phase 3 output feeds back into Phase 1."""
first = run_cycle(_make_payload(source="initial"))
second = run_cycle(first)
# Second cycle should still work — no crash, metadata accumulates
assert second.metadata["gathered"] is True
assert second.metadata["acted"] is True
def test_phases_log(caplog):
"""Acceptance criterion 7: each phase logs what it received and produced."""
import logging
with caplog.at_level(logging.INFO):
run_cycle(_make_payload())
messages = caplog.text
assert "Phase 1 (Gather) received" in messages
assert "Phase 1 (Gather) produced" in messages
assert "Phase 2 (Reason) received" in messages
assert "Phase 2 (Reason) produced" in messages
assert "Phase 3 (Act) received" in messages
assert "Phase 3 (Act) produced" in messages
assert "Loop cycle start" in messages
assert "Loop cycle complete" in messages

View File

@@ -1,14 +1,22 @@
"""Unit tests for the agentic loop module.
Tests cover planning, execution, max_steps enforcement, failure
adaptation, progress callbacks, and response cleaning.
Tests cover data structures, plan parsing, planning, execution,
max_steps enforcement, failure adaptation, double-failure,
progress callbacks, broadcast helper, summary logic, and
response cleaning.
"""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from timmy.agentic_loop import _parse_steps, run_agentic_loop
from timmy.agentic_loop import (
AgenticResult,
AgenticStep,
_broadcast_progress,
_parse_steps,
run_agentic_loop,
)
# ---------------------------------------------------------------------------
# Helpers
@@ -27,6 +35,27 @@ def _mock_run(content: str):
# ---------------------------------------------------------------------------
class TestDataStructures:
def test_agentic_step_fields(self):
step = AgenticStep(
step_num=1, description="Do X", result="Done", status="completed", duration_ms=42
)
assert step.step_num == 1
assert step.status == "completed"
assert step.duration_ms == 42
def test_agentic_result_defaults(self):
r = AgenticResult(task_id="abc", task="test", summary="ok")
assert r.steps == []
assert r.status == "completed"
assert r.total_duration_ms == 0
# ---------------------------------------------------------------------------
# _parse_steps
# ---------------------------------------------------------------------------
class TestParseSteps:
def test_numbered_with_dot(self):
text = "1. Search for data\n2. Write to file\n3. Verify"
@@ -43,6 +72,19 @@ class TestParseSteps:
def test_empty_returns_empty(self):
assert _parse_steps("") == []
def test_whitespace_only_returns_empty(self):
assert _parse_steps(" \n \n ") == []
def test_leading_whitespace_in_numbered(self):
text = " 1. First\n 2. Second"
assert _parse_steps(text) == ["First", "Second"]
def test_mixed_numbered_and_plain(self):
"""When numbered lines are present, only those are returned."""
text = "Here is the plan:\n1. Step one\n2. Step two\nGood luck!"
result = _parse_steps(text)
assert result == ["Step one", "Step two"]
# ---------------------------------------------------------------------------
# run_agentic_loop
@@ -231,3 +273,191 @@ async def test_planning_failure_returns_failed():
assert result.status == "failed"
assert "Planning failed" in result.summary
@pytest.mark.asyncio
async def test_empty_plan_returns_failed():
"""Planning that produces no steps results in 'failed'."""
mock_agent = MagicMock()
mock_agent.run = MagicMock(return_value=_mock_run(""))
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
result = await run_agentic_loop("Do nothing")
assert result.status == "failed"
assert "no steps" in result.summary.lower()
@pytest.mark.asyncio
async def test_double_failure_marks_step_failed():
"""When both execution and adaptation fail, step status is 'failed'."""
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Do something"),
Exception("Step failed"),
Exception("Adaptation also failed"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
result = await run_agentic_loop("Try and fail", max_steps=1)
assert len(result.steps) == 1
assert result.steps[0].status == "failed"
assert "Failed" in result.steps[0].result
assert result.status == "partial"
@pytest.mark.asyncio
async def test_broadcast_progress_ignores_ws_errors():
"""_broadcast_progress swallows import/connection errors."""
with patch(
"timmy.agentic_loop.ws_manager",
create=True,
side_effect=ImportError("no ws"),
):
# Should not raise
await _broadcast_progress("test.event", {"key": "value"})
@pytest.mark.asyncio
async def test_broadcast_progress_sends_to_ws():
"""_broadcast_progress calls ws_manager.broadcast."""
mock_ws = AsyncMock()
with patch("infrastructure.ws_manager.handler.ws_manager", mock_ws):
await _broadcast_progress("agentic.plan_ready", {"task_id": "abc"})
mock_ws.broadcast.assert_awaited_once_with("agentic.plan_ready", {"task_id": "abc"})
@pytest.mark.asyncio
async def test_summary_counts_step_statuses():
"""Summary string includes completed, adapted, and failed counts."""
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. A\n2. B\n3. C"),
_mock_run("A done"),
Exception("B broke"),
_mock_run("B adapted"),
Exception("C broke"),
Exception("C adapt broke too"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
result = await run_agentic_loop("A B C", max_steps=3)
assert "1 adapted" in result.summary
assert "1 failed" in result.summary
assert result.status == "partial"
@pytest.mark.asyncio
async def test_task_id_is_set():
"""Result has a non-empty task_id."""
mock_agent = MagicMock()
mock_agent.run = MagicMock(side_effect=[_mock_run("1. X"), _mock_run("done")])
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
result = await run_agentic_loop("One step")
assert result.task_id
assert len(result.task_id) == 8
@pytest.mark.asyncio
async def test_total_duration_is_set():
"""Result.total_duration_ms is a positive integer."""
mock_agent = MagicMock()
mock_agent.run = MagicMock(side_effect=[_mock_run("1. X"), _mock_run("done")])
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
result = await run_agentic_loop("Quick task")
assert result.total_duration_ms >= 0
@pytest.mark.asyncio
async def test_agent_run_without_content_attr():
"""When agent.run() returns an object without .content, str() is used."""
class PlanResult:
def __str__(self):
return "1. Only step"
class StepResult:
def __str__(self):
return "Step result"
mock_agent = MagicMock()
mock_agent.run = MagicMock(side_effect=[PlanResult(), StepResult()])
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
result = await run_agentic_loop("Fallback test", max_steps=1)
assert len(result.steps) == 1
@pytest.mark.asyncio
async def test_adapted_step_calls_on_progress():
"""on_progress is called even for adapted steps."""
events = []
async def on_progress(desc, step, total):
events.append((desc, step))
mock_agent = MagicMock()
mock_agent.run = MagicMock(
side_effect=[
_mock_run("1. Risky step"),
Exception("boom"),
_mock_run("Adapted result"),
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
await run_agentic_loop("Adapt test", max_steps=1, on_progress=on_progress)
assert len(events) == 1
assert "[Adapted]" in events[0][0]
@pytest.mark.asyncio
async def test_broadcast_called_for_each_phase():
"""_broadcast_progress is called for plan_ready, step_complete, and task_complete."""
mock_agent = MagicMock()
mock_agent.run = MagicMock(side_effect=[_mock_run("1. Do it"), _mock_run("Done")])
broadcast = AsyncMock()
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=mock_agent),
patch("timmy.agentic_loop._broadcast_progress", broadcast),
):
await run_agentic_loop("One step task", max_steps=1)
event_names = [call.args[0] for call in broadcast.call_args_list]
assert "agentic.plan_ready" in event_names
assert "agentic.step_complete" in event_names
assert "agentic.task_complete" in event_names

55
tests/test_api_v1.py Normal file
View File

@@ -0,0 +1,55 @@
import sys
# Absolute path to src
src_path = "/home/ubuntu/timmy-time/Timmy-time-dashboard/src"
if src_path not in sys.path:
sys.path.insert(0, src_path)
from fastapi.testclient import TestClient # noqa: E402
try:
from dashboard.app import app # noqa: E402
print("✓ Successfully imported dashboard.app")
except ImportError as e:
print(f"✗ Failed to import dashboard.app: {e}")
sys.exit(1)
client = TestClient(app)
def test_v1_status():
response = client.get("/api/v1/status")
assert response.status_code == 200
data = response.json()
assert "timmy" in data
assert "model" in data
assert "uptime" in data
def test_v1_chat_history():
response = client.get("/api/v1/chat/history")
assert response.status_code == 200
data = response.json()
assert "messages" in data
def test_v1_upload_fail():
# Test without file
response = client.post("/api/v1/upload")
assert response.status_code == 422 # Unprocessable Entity (missing file)
if __name__ == "__main__":
print("Running API v1 tests...")
try:
test_v1_status()
print("✓ Status test passed")
test_v1_chat_history()
print("✓ History test passed")
test_v1_upload_fail()
print("✓ Upload failure test passed")
print("All tests passed!")
except Exception as e:
print(f"Test failed: {e}")
sys.exit(1)

View File

@@ -49,6 +49,34 @@ class TestConfigLazyValidation:
# Should not raise
validate_startup(force=True)
def test_validate_startup_exits_on_cors_wildcard_in_production(self):
"""validate_startup() should exit in production when CORS has wildcard."""
from config import settings, validate_startup
with (
patch.object(settings, "timmy_env", "production"),
patch.object(settings, "l402_hmac_secret", "test-secret-hex-value-32"),
patch.object(settings, "l402_macaroon_secret", "test-macaroon-hex-value-32"),
patch.object(settings, "cors_origins", ["*"]),
pytest.raises(SystemExit),
):
validate_startup(force=True)
def test_validate_startup_warns_cors_wildcard_in_dev(self):
"""validate_startup() should warn in dev when CORS has wildcard."""
from config import settings, validate_startup
with (
patch.object(settings, "timmy_env", "development"),
patch.object(settings, "cors_origins", ["*"]),
patch("config._startup_logger") as mock_logger,
):
validate_startup(force=True)
mock_logger.warning.assert_any_call(
"SEC: CORS_ORIGINS contains wildcard '*'"
"restrict to explicit origins before deploying to production."
)
def test_validate_startup_skips_in_test_mode(self):
"""validate_startup() should be a no-op in test mode."""
from config import validate_startup

View File

View File

@@ -0,0 +1,240 @@
"""Tests for the Gitea webhook adapter."""
from unittest.mock import AsyncMock, patch
import pytest
from timmy.adapters.gitea_adapter import (
BOT_USERNAMES,
_extract_actor,
_is_bot,
_is_pr_merge,
_normalize_issue_comment,
_normalize_issue_opened,
_normalize_pull_request,
_normalize_push,
handle_webhook,
)
# ── Fixtures: sample payloads ────────────────────────────────────────────────
def _sender(login: str) -> dict:
return {"sender": {"login": login}}
def _push_payload(actor: str = "rockachopa", ref: str = "refs/heads/main") -> dict:
return {
**_sender(actor),
"ref": ref,
"repository": {"full_name": "rockachopa/Timmy-time-dashboard"},
"commits": [
{"message": "fix: something\n\nDetails here"},
{"message": "chore: cleanup"},
],
}
def _issue_payload(actor: str = "rockachopa", action: str = "opened") -> dict:
return {
**_sender(actor),
"action": action,
"repository": {"full_name": "rockachopa/Timmy-time-dashboard"},
"issue": {"number": 42, "title": "Bug in dashboard"},
}
def _issue_comment_payload(actor: str = "rockachopa") -> dict:
return {
**_sender(actor),
"action": "created",
"repository": {"full_name": "rockachopa/Timmy-time-dashboard"},
"issue": {"number": 42, "title": "Bug in dashboard"},
"comment": {"body": "I think this is related to the config change"},
}
def _pr_payload(
actor: str = "rockachopa",
action: str = "opened",
merged: bool = False,
) -> dict:
return {
**_sender(actor),
"action": action,
"repository": {"full_name": "rockachopa/Timmy-time-dashboard"},
"pull_request": {
"number": 99,
"title": "feat: add new feature",
"merged": merged,
},
}
# ── Unit tests: helpers ──────────────────────────────────────────────────────
class TestExtractActor:
def test_normal_sender(self):
assert _extract_actor({"sender": {"login": "rockachopa"}}) == "rockachopa"
def test_missing_sender(self):
assert _extract_actor({}) == "unknown"
class TestIsBot:
@pytest.mark.parametrize("name", list(BOT_USERNAMES))
def test_known_bots(self, name):
assert _is_bot(name) is True
def test_owner_not_bot(self):
assert _is_bot("rockachopa") is False
def test_case_insensitive(self):
assert _is_bot("Kimi") is True
class TestIsPrMerge:
def test_merged_pr(self):
payload = _pr_payload(action="closed", merged=True)
assert _is_pr_merge("pull_request", payload) is True
def test_closed_not_merged(self):
payload = _pr_payload(action="closed", merged=False)
assert _is_pr_merge("pull_request", payload) is False
def test_opened_pr(self):
payload = _pr_payload(action="opened")
assert _is_pr_merge("pull_request", payload) is False
def test_non_pr_event(self):
assert _is_pr_merge("push", {}) is False
# ── Unit tests: normalizers ──────────────────────────────────────────────────
class TestNormalizePush:
def test_basic(self):
data = _normalize_push(_push_payload(), "rockachopa")
assert data["actor"] == "rockachopa"
assert data["ref"] == "refs/heads/main"
assert data["num_commits"] == 2
assert data["head_message"] == "fix: something"
assert data["repo"] == "rockachopa/Timmy-time-dashboard"
def test_empty_commits(self):
payload = {**_push_payload(), "commits": []}
data = _normalize_push(payload, "rockachopa")
assert data["num_commits"] == 0
assert data["head_message"] == ""
class TestNormalizeIssueOpened:
def test_basic(self):
data = _normalize_issue_opened(_issue_payload(), "rockachopa")
assert data["issue_number"] == 42
assert data["title"] == "Bug in dashboard"
assert data["action"] == "opened"
class TestNormalizeIssueComment:
def test_basic(self):
data = _normalize_issue_comment(_issue_comment_payload(), "rockachopa")
assert data["issue_number"] == 42
assert data["comment_body"].startswith("I think this is related")
def test_long_comment_truncated(self):
payload = _issue_comment_payload()
payload["comment"]["body"] = "x" * 500
data = _normalize_issue_comment(payload, "rockachopa")
assert len(data["comment_body"]) == 200
class TestNormalizePullRequest:
def test_opened(self):
data = _normalize_pull_request(_pr_payload(), "rockachopa")
assert data["pr_number"] == 99
assert data["merged"] is False
assert data["action"] == "opened"
def test_merged(self):
payload = _pr_payload(action="closed", merged=True)
data = _normalize_pull_request(payload, "rockachopa")
assert data["merged"] is True
# ── Integration tests: handle_webhook ────────────────────────────────────────
@pytest.mark.asyncio
class TestHandleWebhook:
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_push_emitted(self, mock_emit):
result = await handle_webhook("push", _push_payload())
assert result is True
mock_emit.assert_called_once()
args = mock_emit.call_args
assert args[0][0] == "gitea.push"
assert args[1]["data"]["num_commits"] == 2
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_issue_opened_emitted(self, mock_emit):
result = await handle_webhook("issues", _issue_payload())
assert result is True
mock_emit.assert_called_once()
assert mock_emit.call_args[0][0] == "gitea.issue.opened"
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_issue_comment_emitted(self, mock_emit):
result = await handle_webhook("issue_comment", _issue_comment_payload())
assert result is True
assert mock_emit.call_args[0][0] == "gitea.issue.comment"
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_pull_request_emitted(self, mock_emit):
result = await handle_webhook("pull_request", _pr_payload())
assert result is True
assert mock_emit.call_args[0][0] == "gitea.pull_request"
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_unsupported_event_filtered(self, mock_emit):
result = await handle_webhook("fork", {"sender": {"login": "someone"}})
assert result is False
mock_emit.assert_not_called()
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_bot_push_filtered(self, mock_emit):
result = await handle_webhook("push", _push_payload(actor="kimi"))
assert result is False
mock_emit.assert_not_called()
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_bot_issue_filtered(self, mock_emit):
result = await handle_webhook("issues", _issue_payload(actor="hermes"))
assert result is False
mock_emit.assert_not_called()
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_bot_pr_merge_not_filtered(self, mock_emit):
"""Bot PR merges should still be emitted."""
payload = _pr_payload(actor="kimi", action="closed", merged=True)
result = await handle_webhook("pull_request", payload)
assert result is True
mock_emit.assert_called_once()
data = mock_emit.call_args[1]["data"]
assert data["merged"] is True
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_bot_pr_close_without_merge_filtered(self, mock_emit):
"""Bot PR close (not merge) should be filtered."""
payload = _pr_payload(actor="manus", action="closed", merged=False)
result = await handle_webhook("pull_request", payload)
assert result is False
mock_emit.assert_not_called()
@patch("timmy.adapters.gitea_adapter.emit", new_callable=AsyncMock)
async def test_owner_activity_always_emitted(self, mock_emit):
result = await handle_webhook("push", _push_payload(actor="rockachopa"))
assert result is True
mock_emit.assert_called_once()

View File

@@ -0,0 +1,146 @@
"""Tests for the time adapter — circadian awareness."""
from datetime import UTC, datetime
from unittest.mock import AsyncMock, patch
import pytest
from timmy.adapters.time_adapter import TimeAdapter, classify_period
# ---------- classify_period ----------
@pytest.mark.parametrize(
"hour, expected",
[
(6, "morning"),
(7, "morning"),
(8, "morning"),
(9, None),
(12, "afternoon"),
(13, "afternoon"),
(14, None),
(18, "evening"),
(19, "evening"),
(20, None),
(23, "late_night"),
(0, "late_night"),
(2, "late_night"),
(3, None),
(10, None),
(16, None),
],
)
def test_classify_period(hour: int, expected: str | None) -> None:
assert classify_period(hour) == expected
# ---------- record_interaction / time_since ----------
def test_time_since_last_interaction_none() -> None:
adapter = TimeAdapter()
assert adapter.time_since_last_interaction() is None
def test_time_since_last_interaction() -> None:
adapter = TimeAdapter()
t0 = datetime(2026, 3, 18, 10, 0, 0, tzinfo=UTC)
t1 = datetime(2026, 3, 18, 10, 5, 0, tzinfo=UTC)
adapter.record_interaction(now=t0)
assert adapter.time_since_last_interaction(now=t1) == 300.0
# ---------- tick — circadian events ----------
@pytest.mark.asyncio
async def test_tick_emits_morning() -> None:
adapter = TimeAdapter()
now = datetime(2026, 3, 18, 7, 0, 0, tzinfo=UTC)
with patch("timmy.adapters.time_adapter.emit", new_callable=AsyncMock) as mock_emit:
emitted = await adapter.tick(now=now)
assert "time.morning" in emitted
mock_emit.assert_any_call(
"time.morning",
source="time_adapter",
data={"hour": 7, "period": "morning"},
)
@pytest.mark.asyncio
async def test_tick_emits_late_night() -> None:
adapter = TimeAdapter()
now = datetime(2026, 3, 19, 1, 0, 0, tzinfo=UTC)
with patch("timmy.adapters.time_adapter.emit", new_callable=AsyncMock) as mock_emit:
emitted = await adapter.tick(now=now)
assert "time.late_night" in emitted
mock_emit.assert_any_call(
"time.late_night",
source="time_adapter",
data={"hour": 1, "period": "late_night"},
)
@pytest.mark.asyncio
async def test_tick_no_duplicate_period() -> None:
"""Same period on consecutive ticks should not re-emit."""
adapter = TimeAdapter()
t1 = datetime(2026, 3, 18, 7, 0, 0, tzinfo=UTC)
t2 = datetime(2026, 3, 18, 7, 30, 0, tzinfo=UTC)
with patch("timmy.adapters.time_adapter.emit", new_callable=AsyncMock):
await adapter.tick(now=t1)
emitted = await adapter.tick(now=t2)
assert emitted == []
@pytest.mark.asyncio
async def test_tick_no_event_outside_periods() -> None:
adapter = TimeAdapter()
now = datetime(2026, 3, 18, 10, 0, 0, tzinfo=UTC)
with patch("timmy.adapters.time_adapter.emit", new_callable=AsyncMock) as mock_emit:
emitted = await adapter.tick(now=now)
assert emitted == []
mock_emit.assert_not_called()
# ---------- tick — new_day ----------
@pytest.mark.asyncio
async def test_tick_emits_new_day() -> None:
adapter = TimeAdapter()
day1 = datetime(2026, 3, 18, 23, 30, 0, tzinfo=UTC)
day2 = datetime(2026, 3, 19, 0, 30, 0, tzinfo=UTC)
with patch("timmy.adapters.time_adapter.emit", new_callable=AsyncMock) as mock_emit:
await adapter.tick(now=day1)
emitted = await adapter.tick(now=day2)
assert "time.new_day" in emitted
mock_emit.assert_any_call(
"time.new_day",
source="time_adapter",
data={"date": "2026-03-19"},
)
@pytest.mark.asyncio
async def test_tick_no_new_day_same_date() -> None:
adapter = TimeAdapter()
t1 = datetime(2026, 3, 18, 10, 0, 0, tzinfo=UTC)
t2 = datetime(2026, 3, 18, 15, 0, 0, tzinfo=UTC)
with patch("timmy.adapters.time_adapter.emit", new_callable=AsyncMock):
await adapter.tick(now=t1)
emitted = await adapter.tick(now=t2)
assert "time.new_day" not in emitted

View File

View File

@@ -0,0 +1,393 @@
"""Unit tests for timmy.agents.loader — YAML-driven agent factory."""
from __future__ import annotations
from unittest.mock import MagicMock, patch
import pytest
import timmy.agents.loader as loader
# ── Fixtures ──────────────────────────────────────────────────────────────────
MINIMAL_YAML = """
defaults:
model: test-model
prompt_tier: lite
max_history: 5
tools: []
routing:
method: pattern
patterns:
coder:
- code
- fix bug
writer:
- write
- draft
agents:
helper:
name: Helper
role: general
prompt: "You are a helpful agent."
coder:
name: Forge
role: code
model: big-model
prompt_tier: full
max_history: 15
tools:
- python
- shell
prompt: "You are a coding agent."
"""
@pytest.fixture(autouse=True)
def _reset_loader_cache():
"""Reset module-level caches before each test."""
loader._agents = None
loader._config = None
yield
loader._agents = None
loader._config = None
@pytest.fixture()
def mock_yaml_config(tmp_path):
"""Write a minimal agents.yaml and patch settings.repo_root to point at it."""
config_dir = tmp_path / "config"
config_dir.mkdir()
(config_dir / "agents.yaml").write_text(MINIMAL_YAML)
with patch.object(loader.settings, "repo_root", str(tmp_path)):
yield tmp_path
# ── _find_config_path ─────────────────────────────────────────────────────────
def test_find_config_path_returns_path(mock_yaml_config):
path = loader._find_config_path()
assert path.exists()
assert path.name == "agents.yaml"
def test_find_config_path_raises_when_missing(tmp_path):
with patch.object(loader.settings, "repo_root", str(tmp_path)):
with pytest.raises(FileNotFoundError, match="Agent config not found"):
loader._find_config_path()
# ── _load_config ──────────────────────────────────────────────────────────────
def test_load_config_parses_yaml(mock_yaml_config):
config = loader._load_config()
assert "defaults" in config
assert "agents" in config
assert "routing" in config
def test_load_config_caches(mock_yaml_config):
cfg1 = loader._load_config()
cfg2 = loader._load_config()
assert cfg1 is cfg2
def test_load_config_force_reload(mock_yaml_config):
cfg1 = loader._load_config()
cfg2 = loader._load_config(force_reload=True)
assert cfg1 is not cfg2
assert cfg1 == cfg2
# ── _resolve_model ────────────────────────────────────────────────────────────
def test_resolve_model_agent_specific():
assert loader._resolve_model("custom-model", {"model": "default-model"}) == "custom-model"
def test_resolve_model_defaults_fallback():
assert loader._resolve_model(None, {"model": "default-model"}) == "default-model"
def test_resolve_model_settings_fallback():
with patch.object(loader.settings, "ollama_model", "settings-model"):
assert loader._resolve_model(None, {}) == "settings-model"
# ── _resolve_prompt_tier ──────────────────────────────────────────────────────
def test_resolve_prompt_tier_agent_specific():
assert loader._resolve_prompt_tier("full", {"prompt_tier": "lite"}) == "full"
def test_resolve_prompt_tier_defaults_fallback():
assert loader._resolve_prompt_tier(None, {"prompt_tier": "full"}) == "full"
def test_resolve_prompt_tier_default_is_lite():
assert loader._resolve_prompt_tier(None, {}) == "lite"
# ── _build_system_prompt ──────────────────────────────────────────────────────
def test_build_system_prompt_full_tier():
with patch("timmy.prompts.get_system_prompt", return_value="BASE") as mock_gsp:
result = loader._build_system_prompt({"prompt": "Custom."}, "full")
mock_gsp.assert_called_once_with(tools_enabled=True)
assert result == "Custom.\n\nBASE"
def test_build_system_prompt_lite_tier():
with patch("timmy.prompts.get_system_prompt", return_value="BASE") as mock_gsp:
result = loader._build_system_prompt({"prompt": "Custom."}, "lite")
mock_gsp.assert_called_once_with(tools_enabled=False)
assert result == "Custom.\n\nBASE"
def test_build_system_prompt_no_custom():
with patch("timmy.prompts.get_system_prompt", return_value="BASE"):
result = loader._build_system_prompt({}, "lite")
assert result == "BASE"
def test_build_system_prompt_empty_custom():
with patch("timmy.prompts.get_system_prompt", return_value="BASE"):
result = loader._build_system_prompt({"prompt": " "}, "lite")
assert result == "BASE"
# ── load_agents ───────────────────────────────────────────────────────────────
def test_load_agents_creates_subagents(mock_yaml_config):
with (
patch("timmy.agents.base.SubAgent") as MockSubAgent,
patch("timmy.prompts.get_system_prompt", return_value="BASE"),
):
MockSubAgent.side_effect = lambda **kw: MagicMock(**kw)
agents = loader.load_agents()
assert len(agents) == 2
assert "helper" in agents
assert "coder" in agents
def test_load_agents_passes_correct_params(mock_yaml_config):
with (
patch("timmy.agents.base.SubAgent") as MockSubAgent,
patch("timmy.prompts.get_system_prompt", return_value="BASE"),
):
MockSubAgent.side_effect = lambda **kw: MagicMock(**kw)
loader.load_agents()
calls = {c.kwargs["agent_id"]: c.kwargs for c in MockSubAgent.call_args_list}
coder_kw = calls["coder"]
assert coder_kw["name"] == "Forge"
assert coder_kw["role"] == "code"
assert coder_kw["model"] == "big-model"
assert coder_kw["max_history"] == 15
assert coder_kw["tools"] == ["python", "shell"]
def test_load_agents_uses_defaults(mock_yaml_config):
with (
patch("timmy.agents.base.SubAgent") as MockSubAgent,
patch("timmy.prompts.get_system_prompt", return_value="BASE"),
):
MockSubAgent.side_effect = lambda **kw: MagicMock(**kw)
loader.load_agents()
calls = {c.kwargs["agent_id"]: c.kwargs for c in MockSubAgent.call_args_list}
helper_kw = calls["helper"]
assert helper_kw["model"] == "test-model"
assert helper_kw["max_history"] == 5
assert helper_kw["tools"] == []
def test_load_agents_caches(mock_yaml_config):
with (
patch("timmy.agents.base.SubAgent") as MockSubAgent,
patch("timmy.prompts.get_system_prompt", return_value="BASE"),
):
MockSubAgent.side_effect = lambda **kw: MagicMock(**kw)
a1 = loader.load_agents()
a2 = loader.load_agents()
assert a1 is a2
def test_load_agents_force_reload(mock_yaml_config):
with (
patch("timmy.agents.base.SubAgent") as MockSubAgent,
patch("timmy.prompts.get_system_prompt", return_value="BASE"),
):
MockSubAgent.side_effect = lambda **kw: MagicMock(**kw)
a1 = loader.load_agents()
a2 = loader.load_agents(force_reload=True)
assert a1 is not a2
# ── get_agent ─────────────────────────────────────────────────────────────────
def test_get_agent_returns_agent(mock_yaml_config):
with (
patch("timmy.agents.base.SubAgent") as MockSubAgent,
patch("timmy.prompts.get_system_prompt", return_value="BASE"),
):
MockSubAgent.side_effect = lambda **kw: MagicMock(agent_id=kw["agent_id"])
agent = loader.get_agent("helper")
assert agent.agent_id == "helper"
def test_get_agent_raises_for_unknown(mock_yaml_config):
with (
patch("timmy.agents.base.SubAgent") as MockSubAgent,
patch("timmy.prompts.get_system_prompt", return_value="BASE"),
):
MockSubAgent.side_effect = lambda **kw: MagicMock(**kw)
with pytest.raises(KeyError, match="Unknown agent.*nope"):
loader.get_agent("nope")
# ── list_agents ───────────────────────────────────────────────────────────────
def test_list_agents_returns_metadata(mock_yaml_config):
result = loader.list_agents()
assert len(result) == 2
ids = {a["id"] for a in result}
assert ids == {"helper", "coder"}
def test_list_agents_includes_model_and_tools(mock_yaml_config):
result = loader.list_agents()
coder = next(a for a in result if a["id"] == "coder")
assert coder["model"] == "big-model"
assert coder["tools"] == ["python", "shell"]
assert coder["status"] == "available"
def test_list_agents_uses_defaults_for_name_and_role(mock_yaml_config):
result = loader.list_agents()
helper = next(a for a in result if a["id"] == "helper")
assert helper["name"] == "Helper"
assert helper["role"] == "general"
# ── get_routing_config ────────────────────────────────────────────────────────
def test_get_routing_config(mock_yaml_config):
routing = loader.get_routing_config()
assert routing["method"] == "pattern"
assert "coder" in routing["patterns"]
def test_get_routing_config_default_when_missing(tmp_path):
"""When no routing section exists, returns a sensible default."""
config_dir = tmp_path / "config"
config_dir.mkdir()
(config_dir / "agents.yaml").write_text("defaults: {}\nagents: {}\n")
with patch.object(loader.settings, "repo_root", str(tmp_path)):
routing = loader.get_routing_config()
assert routing == {"method": "pattern", "patterns": {}}
# ── _matches_pattern ──────────────────────────────────────────────────────────
class TestMatchesPattern:
def test_single_word_match(self):
assert loader._matches_pattern("code", "please code this")
def test_single_word_no_partial(self):
assert not loader._matches_pattern("code", "barcode scanner")
def test_multi_word_all_present(self):
assert loader._matches_pattern("fix bug", "can you fix this bug?")
def test_multi_word_any_order(self):
assert loader._matches_pattern("fix bug", "there is a bug, please fix it")
def test_multi_word_missing_one(self):
assert not loader._matches_pattern("fix bug", "fix the typo")
def test_case_insensitive(self):
assert loader._matches_pattern("Code", "CODE this")
def test_word_boundary(self):
assert not loader._matches_pattern("test", "testing in progress")
# ── route_request ─────────────────────────────────────────────────────────────
def test_route_request_matches_coder(mock_yaml_config):
assert loader.route_request("please code this feature") == "coder"
def test_route_request_matches_writer(mock_yaml_config):
assert loader.route_request("write a summary") == "writer"
def test_route_request_returns_none_when_no_match(mock_yaml_config):
assert loader.route_request("hello there") is None
def test_route_request_non_pattern_method(mock_yaml_config):
"""When routing method is not 'pattern', always returns None."""
loader._load_config()
loader._config["routing"]["method"] = "llm"
assert loader.route_request("code this") is None
# ── route_request_with_match ──────────────────────────────────────────────────
def test_route_request_with_match_returns_tuple(mock_yaml_config):
agent_id, pattern = loader.route_request_with_match("fix this bug please")
assert agent_id == "coder"
assert pattern == "fix bug"
def test_route_request_with_match_no_match(mock_yaml_config):
agent_id, pattern = loader.route_request_with_match("hello")
assert agent_id is None
assert pattern is None
def test_route_request_with_match_non_pattern_method(mock_yaml_config):
loader._load_config()
loader._config["routing"]["method"] = "llm"
agent_id, pattern = loader.route_request_with_match("code this")
assert agent_id is None
assert pattern is None
# ── reload_agents ─────────────────────────────────────────────────────────────
def test_reload_agents_clears_caches(mock_yaml_config):
with (
patch("timmy.agents.base.SubAgent") as MockSubAgent,
patch("timmy.prompts.get_system_prompt", return_value="BASE"),
):
MockSubAgent.side_effect = lambda **kw: MagicMock(**kw)
loader.load_agents()
assert loader._agents is not None
assert loader._config is not None
loader.reload_agents()
assert loader._agents is not None
assert MockSubAgent.call_count == 4 # 2 agents * 2 loads

View File

@@ -81,7 +81,6 @@ def test_create_timmy_respects_custom_ollama_url():
mock_settings.ollama_url = custom_url
mock_settings.ollama_num_ctx = 4096
mock_settings.timmy_model_backend = "ollama"
mock_settings.airllm_model_size = "70b"
from timmy.agent import create_timmy
@@ -91,33 +90,6 @@ def test_create_timmy_respects_custom_ollama_url():
assert kwargs["host"] == custom_url
# ── AirLLM path ──────────────────────────────────────────────────────────────
def test_create_timmy_airllm_returns_airllm_agent():
"""backend='airllm' must return a TimmyAirLLMAgent, not an Agno Agent."""
with patch("timmy.backends.is_apple_silicon", return_value=False):
from timmy.agent import create_timmy
from timmy.backends import TimmyAirLLMAgent
result = create_timmy(backend="airllm", model_size="8b")
assert isinstance(result, TimmyAirLLMAgent)
def test_create_timmy_airllm_does_not_call_agno_agent():
"""When using the airllm backend, Agno Agent should never be instantiated."""
with (
patch("timmy.agent.Agent") as MockAgent,
patch("timmy.backends.is_apple_silicon", return_value=False),
):
from timmy.agent import create_timmy
create_timmy(backend="airllm", model_size="8b")
MockAgent.assert_not_called()
def test_create_timmy_explicit_ollama_ignores_autodetect():
"""backend='ollama' must always use Ollama, even on Apple Silicon."""
with (
@@ -141,7 +113,6 @@ def test_create_timmy_explicit_ollama_ignores_autodetect():
def test_resolve_backend_explicit_takes_priority():
from timmy.agent import _resolve_backend
assert _resolve_backend("airllm") == "airllm"
assert _resolve_backend("ollama") == "ollama"
@@ -152,39 +123,6 @@ def test_resolve_backend_defaults_to_ollama_without_config():
assert _resolve_backend(None) == "ollama"
def test_resolve_backend_auto_uses_airllm_on_apple_silicon():
"""'auto' on Apple Silicon with airllm stubbed → 'airllm'."""
with (
patch("timmy.backends.is_apple_silicon", return_value=True),
patch("timmy.agent.settings") as mock_settings,
):
mock_settings.timmy_model_backend = "auto"
mock_settings.airllm_model_size = "70b"
mock_settings.ollama_model = "llama3.2"
from timmy.agent import _resolve_backend
assert _resolve_backend(None) == "airllm"
def test_resolve_backend_auto_falls_back_on_non_apple():
"""'auto' on non-Apple Silicon → 'ollama'."""
with (
patch("timmy.backends.is_apple_silicon", return_value=False),
patch("timmy.agent.settings") as mock_settings,
):
mock_settings.timmy_model_backend = "auto"
mock_settings.airllm_model_size = "70b"
mock_settings.ollama_model = "llama3.2"
from timmy.agent import _resolve_backend
assert _resolve_backend(None) == "ollama"
# ── _model_supports_tools ────────────────────────────────────────────────────
def test_model_supports_tools_llama32_returns_false():
"""llama3.2 (3B) is too small for reliable tool calling."""
from timmy.agent import _model_supports_tools
@@ -259,7 +197,6 @@ def test_create_timmy_includes_tools_for_large_model():
mock_settings.ollama_url = "http://localhost:11434"
mock_settings.ollama_num_ctx = 4096
mock_settings.timmy_model_backend = "ollama"
mock_settings.airllm_model_size = "70b"
mock_settings.telemetry_enabled = False
from timmy.agent import create_timmy
@@ -444,6 +381,150 @@ def test_get_effective_ollama_model_walks_fallback_chain():
assert result == "fb-2"
# ── _build_tools_list ─────────────────────────────────────────────────────
def test_build_tools_list_empty_when_tools_disabled():
"""Small models get an empty tools list."""
from timmy.agent import _build_tools_list
result = _build_tools_list(use_tools=False, skip_mcp=False, model_name="llama3.2")
assert result == []
def test_build_tools_list_includes_toolkit_when_enabled():
"""Tool-capable models get the full toolkit."""
mock_toolkit = MagicMock()
with patch("timmy.agent.create_full_toolkit", return_value=mock_toolkit):
from timmy.agent import _build_tools_list
result = _build_tools_list(use_tools=True, skip_mcp=True, model_name="llama3.1")
assert mock_toolkit in result
def test_build_tools_list_skips_mcp_when_flagged():
"""skip_mcp=True must not call MCP factories."""
mock_toolkit = MagicMock()
with (
patch("timmy.agent.create_full_toolkit", return_value=mock_toolkit),
patch("timmy.mcp_tools.create_gitea_mcp_tools") as mock_gitea,
patch("timmy.mcp_tools.create_filesystem_mcp_tools") as mock_fs,
):
from timmy.agent import _build_tools_list
_build_tools_list(use_tools=True, skip_mcp=True, model_name="llama3.1")
mock_gitea.assert_not_called()
mock_fs.assert_not_called()
def test_build_tools_list_includes_mcp_when_not_skipped():
"""skip_mcp=False should attempt MCP tool creation."""
mock_toolkit = MagicMock()
with (
patch("timmy.agent.create_full_toolkit", return_value=mock_toolkit),
patch("timmy.mcp_tools.create_gitea_mcp_tools", return_value=None) as mock_gitea,
patch("timmy.mcp_tools.create_filesystem_mcp_tools", return_value=None) as mock_fs,
):
from timmy.agent import _build_tools_list
_build_tools_list(use_tools=True, skip_mcp=False, model_name="llama3.1")
mock_gitea.assert_called_once()
mock_fs.assert_called_once()
# ── _build_prompt ─────────────────────────────────────────────────────────
def test_build_prompt_includes_base_prompt():
"""Prompt should always contain the base system prompt."""
from timmy.agent import _build_prompt
result = _build_prompt(use_tools=False, session_id="test")
assert "Timmy" in result
def test_build_prompt_appends_memory_context():
"""Memory context should be appended when available."""
mock_memory = MagicMock()
mock_memory.get_system_context.return_value = "User prefers dark mode."
with patch("timmy.memory_system.memory_system", mock_memory):
from timmy.agent import _build_prompt
result = _build_prompt(use_tools=True, session_id="test")
assert "GROUNDED CONTEXT" in result
assert "dark mode" in result
def test_build_prompt_truncates_long_memory():
"""Long memory context should be truncated."""
mock_memory = MagicMock()
mock_memory.get_system_context.return_value = "x" * 10000
with patch("timmy.memory_system.memory_system", mock_memory):
from timmy.agent import _build_prompt
result = _build_prompt(use_tools=False, session_id="test")
assert "[truncated]" in result
def test_build_prompt_survives_memory_failure():
"""Prompt should fall back to base when memory fails."""
mock_memory = MagicMock()
mock_memory.get_system_context.side_effect = RuntimeError("db locked")
with patch("timmy.memory_system.memory_system", mock_memory):
from timmy.agent import _build_prompt
result = _build_prompt(use_tools=True, session_id="test")
assert "Timmy" in result
# Memory context should NOT be appended (the db locked error was caught)
assert "db locked" not in result
# ── _create_ollama_agent ──────────────────────────────────────────────────
def test_create_ollama_agent_passes_correct_kwargs():
"""_create_ollama_agent must pass the expected kwargs to Agent."""
with (
patch("timmy.agent.Agent") as MockAgent,
patch("timmy.agent.Ollama"),
patch("timmy.agent.SqliteDb"),
patch("timmy.agent._warmup_model", return_value=True),
):
from timmy.agent import _create_ollama_agent
_create_ollama_agent(
db_file="test.db",
model_name="llama3.1",
tools_list=[MagicMock()],
full_prompt="test prompt",
use_tools=True,
)
kwargs = MockAgent.call_args.kwargs
assert kwargs["description"] == "test prompt"
assert kwargs["markdown"] is False
def test_create_ollama_agent_none_tools_when_empty():
"""Empty tools_list should pass tools=None to Agent."""
with (
patch("timmy.agent.Agent") as MockAgent,
patch("timmy.agent.Ollama"),
patch("timmy.agent.SqliteDb"),
patch("timmy.agent._warmup_model", return_value=True),
):
from timmy.agent import _create_ollama_agent
_create_ollama_agent(
db_file="test.db",
model_name="llama3.2",
tools_list=[],
full_prompt="test prompt",
use_tools=False,
)
kwargs = MockAgent.call_args.kwargs
assert kwargs["tools"] is None
def test_no_hardcoded_fallback_constants_in_agent():
"""agent.py must not define module-level DEFAULT_MODEL_FALLBACKS."""
import timmy.agent as agent_mod

View File

@@ -0,0 +1,386 @@
"""Tests for timmy.agentic_loop — multi-step task execution engine."""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from timmy.agentic_loop import (
AgenticResult,
AgenticStep,
_parse_steps,
)
# ---------------------------------------------------------------------------
# Data structures
# ---------------------------------------------------------------------------
class TestAgenticStep:
"""Unit tests for the AgenticStep dataclass."""
def test_creation(self):
step = AgenticStep(
step_num=1,
description="Do thing",
result="Done",
status="completed",
duration_ms=42,
)
assert step.step_num == 1
assert step.description == "Do thing"
assert step.result == "Done"
assert step.status == "completed"
assert step.duration_ms == 42
def test_failed_status(self):
step = AgenticStep(
step_num=2, description="Bad step", result="Error", status="failed", duration_ms=10
)
assert step.status == "failed"
def test_adapted_status(self):
step = AgenticStep(
step_num=3, description="Retried", result="OK", status="adapted", duration_ms=100
)
assert step.status == "adapted"
class TestAgenticResult:
"""Unit tests for the AgenticResult dataclass."""
def test_defaults(self):
result = AgenticResult(task_id="abc", task="Test", summary="Done")
assert result.steps == []
assert result.status == "completed"
assert result.total_duration_ms == 0
def test_with_steps(self):
s = AgenticStep(step_num=1, description="A", result="B", status="completed", duration_ms=5)
result = AgenticResult(task_id="x", task="T", summary="S", steps=[s])
assert len(result.steps) == 1
# ---------------------------------------------------------------------------
# _parse_steps — pure function, highly testable
# ---------------------------------------------------------------------------
class TestParseSteps:
"""Unit tests for the plan parser."""
def test_numbered_with_dots(self):
text = "1. First step\n2. Second step\n3. Third step"
steps = _parse_steps(text)
assert steps == ["First step", "Second step", "Third step"]
def test_numbered_with_parens(self):
text = "1) Do this\n2) Do that"
steps = _parse_steps(text)
assert steps == ["Do this", "Do that"]
def test_mixed_numbering(self):
text = "1. Step one\n2) Step two\n3. Step three"
steps = _parse_steps(text)
assert len(steps) == 3
def test_indented_steps(self):
text = " 1. Indented step\n 2. Also indented"
steps = _parse_steps(text)
assert len(steps) == 2
assert steps[0] == "Indented step"
def test_no_numbered_steps_fallback(self):
text = "Do this first\nThen do that\nFinally wrap up"
steps = _parse_steps(text)
assert len(steps) == 3
assert steps[0] == "Do this first"
def test_empty_string(self):
steps = _parse_steps("")
assert steps == []
def test_blank_lines_ignored_in_fallback(self):
text = "Step A\n\n\nStep B\n"
steps = _parse_steps(text)
assert steps == ["Step A", "Step B"]
def test_strips_whitespace(self):
text = "1. Lots of space \n2. Also spaced "
steps = _parse_steps(text)
assert steps[0] == "Lots of space"
assert steps[1] == "Also spaced"
def test_preamble_ignored_when_numbered(self):
text = "Here is the plan:\n1. Step one\n2. Step two"
steps = _parse_steps(text)
assert steps == ["Step one", "Step two"]
# ---------------------------------------------------------------------------
# _get_loop_agent — singleton pattern
# ---------------------------------------------------------------------------
class TestGetLoopAgent:
"""Tests for the agent singleton."""
def test_creates_agent_once(self):
import timmy.agentic_loop as mod
mod._loop_agent = None
mock_agent = MagicMock()
with patch("timmy.agent.create_timmy", return_value=mock_agent) as mock_create:
agent = mod._get_loop_agent()
assert agent is mock_agent
mock_create.assert_called_once()
# Second call should reuse singleton
agent2 = mod._get_loop_agent()
assert agent2 is mock_agent
mock_create.assert_called_once()
mod._loop_agent = None # cleanup
def test_reuses_existing(self):
import timmy.agentic_loop as mod
sentinel = MagicMock()
mod._loop_agent = sentinel
assert mod._get_loop_agent() is sentinel
mod._loop_agent = None # cleanup
# ---------------------------------------------------------------------------
# _broadcast_progress — best-effort WebSocket broadcast
# ---------------------------------------------------------------------------
class TestBroadcastProgress:
"""Tests for the WebSocket broadcast helper."""
@pytest.mark.asyncio
async def test_successful_broadcast(self):
from timmy.agentic_loop import _broadcast_progress
mock_ws = MagicMock()
mock_ws.broadcast = AsyncMock()
mock_module = MagicMock()
mock_module.ws_manager = mock_ws
with patch.dict("sys.modules", {"infrastructure.ws_manager.handler": mock_module}):
await _broadcast_progress("test.event", {"key": "value"})
mock_ws.broadcast.assert_awaited_once_with("test.event", {"key": "value"})
@pytest.mark.asyncio
async def test_import_error_swallowed(self):
"""When ws_manager import fails, broadcast silently succeeds."""
import sys
from timmy.agentic_loop import _broadcast_progress
# Remove the module so import fails
saved = sys.modules.pop("infrastructure.ws_manager.handler", None)
try:
with patch.dict("sys.modules", {"infrastructure": None}):
# Should not raise — errors are swallowed
await _broadcast_progress("fail.event", {})
finally:
if saved is not None:
sys.modules["infrastructure.ws_manager.handler"] = saved
# ---------------------------------------------------------------------------
# run_agentic_loop — integration-style tests with mocked agent
# ---------------------------------------------------------------------------
class TestRunAgenticLoop:
"""Tests for the main agentic loop."""
@pytest.fixture(autouse=True)
def _reset_agent(self):
import timmy.agentic_loop as mod
mod._loop_agent = None
yield
mod._loop_agent = None
def _mock_agent(self, responses):
"""Create a mock agent that returns responses in sequence."""
agent = MagicMock()
run_results = []
for r in responses:
mock_result = MagicMock()
mock_result.content = r
run_results.append(mock_result)
agent.run = MagicMock(side_effect=run_results)
return agent
@pytest.mark.asyncio
async def test_successful_two_step_task(self):
from timmy.agentic_loop import run_agentic_loop
agent = self._mock_agent(
[
"1. Step one\n2. Step two", # planning
"Step one done", # execution step 1
"Step two done", # execution step 2
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
patch("timmy.session._clean_response", side_effect=lambda x: x),
):
result = await run_agentic_loop("Test task", max_steps=5)
assert result.status == "completed"
assert len(result.steps) == 2
assert result.steps[0].status == "completed"
assert result.steps[1].status == "completed"
assert result.total_duration_ms >= 0
@pytest.mark.asyncio
async def test_planning_failure(self):
from timmy.agentic_loop import run_agentic_loop
agent = MagicMock()
agent.run = MagicMock(side_effect=RuntimeError("LLM down"))
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
result = await run_agentic_loop("Broken task", max_steps=3)
assert result.status == "failed"
assert "Planning failed" in result.summary
@pytest.mark.asyncio
async def test_empty_plan(self):
from timmy.agentic_loop import run_agentic_loop
agent = self._mock_agent([""]) # empty plan
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
):
result = await run_agentic_loop("Empty plan task", max_steps=3)
assert result.status == "failed"
assert "no steps" in result.summary.lower()
@pytest.mark.asyncio
async def test_step_failure_triggers_adaptation(self):
from timmy.agentic_loop import run_agentic_loop
agent = MagicMock()
call_count = 0
def mock_run(prompt, **kwargs):
nonlocal call_count
call_count += 1
result = MagicMock()
if call_count == 1:
result.content = "1. Only step"
elif call_count == 2:
raise RuntimeError("Step failed")
else:
result.content = "Adapted successfully"
return result
agent.run = mock_run
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
patch("timmy.session._clean_response", side_effect=lambda x: x),
):
result = await run_agentic_loop("Failing task", max_steps=5)
assert len(result.steps) == 1
assert result.steps[0].status == "adapted"
assert "[Adapted]" in result.steps[0].description
@pytest.mark.asyncio
async def test_max_steps_truncation(self):
from timmy.agentic_loop import run_agentic_loop
agent = self._mock_agent(
[
"1. A\n2. B\n3. C\n4. D\n5. E", # 5 steps planned
"Done A",
"Done B",
]
)
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
patch("timmy.session._clean_response", side_effect=lambda x: x),
):
result = await run_agentic_loop("Big task", max_steps=2)
assert result.status == "partial" # was truncated
assert len(result.steps) == 2
@pytest.mark.asyncio
async def test_on_progress_callback(self):
from timmy.agentic_loop import run_agentic_loop
agent = self._mock_agent(
[
"1. Only step",
"Step done",
]
)
progress_calls = []
async def track_progress(desc, step_num, total):
progress_calls.append((desc, step_num, total))
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
patch("timmy.session._clean_response", side_effect=lambda x: x),
):
await run_agentic_loop("Callback task", max_steps=5, on_progress=track_progress)
assert len(progress_calls) == 1
assert progress_calls[0][1] == 1 # step_num
@pytest.mark.asyncio
async def test_default_max_steps_from_settings(self):
from timmy.agentic_loop import run_agentic_loop
agent = self._mock_agent(["1. Step one", "Done"])
mock_settings = MagicMock()
mock_settings.max_agent_steps = 7
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
patch("timmy.session._clean_response", side_effect=lambda x: x),
patch("config.settings", mock_settings),
):
result = await run_agentic_loop("Settings task")
assert result.status == "completed"
@pytest.mark.asyncio
async def test_task_id_generated(self):
from timmy.agentic_loop import run_agentic_loop
agent = self._mock_agent(["1. Step", "OK"])
with (
patch("timmy.agentic_loop._get_loop_agent", return_value=agent),
patch("timmy.agentic_loop._broadcast_progress", new_callable=AsyncMock),
patch("timmy.session._clean_response", side_effect=lambda x: x),
):
result = await run_agentic_loop("ID task", max_steps=5)
assert result.task_id # non-empty
assert len(result.task_id) == 8 # uuid[:8]

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@@ -0,0 +1,532 @@
"""Tests for timmy.agents.base — BaseAgent and SubAgent.
Covers:
- Initialization and default values
- Tool registry integration
- Event bus connection and subscription
- run() with retry logic (transient + fatal errors)
- Event emission on successful run
- get_capabilities / get_status
- SubAgent.execute_task delegation
"""
from unittest.mock import AsyncMock, MagicMock, patch
import httpx
import pytest
# ── helpers ──────────────────────────────────────────────────────────────────
def _mock_settings(**overrides):
"""Create a settings mock with sensible defaults."""
s = MagicMock()
s.ollama_model = "qwen3:30b"
s.ollama_url = "http://localhost:11434"
s.ollama_num_ctx = 0
s.telemetry_enabled = False
for k, v in overrides.items():
setattr(s, k, v)
return s
def _make_agent_class():
"""Import after patches are in place."""
from timmy.agents.base import SubAgent
return SubAgent
def _make_base_class():
from timmy.agents.base import BaseAgent
return BaseAgent
# ── patch context ────────────────────────────────────────────────────────────
# All tests patch Agno's Agent so we never touch Ollama.
_AGENT_PATCH = "timmy.agents.base.Agent"
_OLLAMA_PATCH = "timmy.agents.base.Ollama"
_SETTINGS_PATCH = "timmy.agents.base.settings"
_REGISTRY_PATCH = "timmy.agents.base.tool_registry"
# ── Initialization ───────────────────────────────────────────────────────────
class TestBaseAgentInit:
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_defaults(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(
agent_id="test-1",
name="TestBot",
role="tester",
system_prompt="You are a test agent.",
)
assert agent.agent_id == "test-1"
assert agent.name == "TestBot"
assert agent.role == "tester"
assert agent.tools == []
assert agent.model == "qwen3:30b"
assert agent.max_history == 10
assert agent.event_bus is None
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_custom_model(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(
agent_id="a",
name="A",
role="r",
system_prompt="p",
model="llama3:8b",
)
assert agent.model == "llama3:8b"
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_custom_max_history(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p", max_history=5)
assert agent.max_history == 5
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_tools_list_stored(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(
agent_id="a",
name="A",
role="r",
system_prompt="p",
tools=["calculator", "search"],
)
assert agent.tools == ["calculator", "search"]
# ── _create_agent internals ──────────────────────────────────────────────────
class TestCreateAgent:
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings(ollama_num_ctx=4096))
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_num_ctx_passed_when_set(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
# Ollama should have been called with options
_, kwargs = mock_ollama.call_args
assert kwargs.get("options") == {"num_ctx": 4096}
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings(ollama_num_ctx=0))
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_num_ctx_omitted_when_zero(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
_, kwargs = mock_ollama.call_args
assert "options" not in kwargs
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_tool_registry_lookup(self, mock_agent_cls, mock_ollama):
mock_registry = MagicMock()
handler1 = MagicMock()
handler2 = None # Simulate missing tool
mock_registry.get_handler.side_effect = [handler1, handler2]
with patch(_REGISTRY_PATCH, mock_registry):
SubAgent = _make_agent_class()
SubAgent(
agent_id="a",
name="A",
role="r",
system_prompt="p",
tools=["calc", "missing"],
)
assert mock_registry.get_handler.call_count == 2
# Agent should have been created with just the one handler
_, kwargs = mock_agent_cls.call_args
assert kwargs["tools"] == [handler1]
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_no_tools_passes_none(self, mock_agent_cls, mock_ollama):
with patch(_REGISTRY_PATCH, None):
SubAgent = _make_agent_class()
SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
_, kwargs = mock_agent_cls.call_args
assert kwargs["tools"] is None
# ── Event bus ────────────────────────────────────────────────────────────────
class TestEventBus:
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_connect_event_bus(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="bot-1", name="B", role="r", system_prompt="p")
bus = MagicMock()
bus.subscribe.return_value = lambda fn: fn # decorator pattern
agent.connect_event_bus(bus)
assert agent.event_bus is bus
assert bus.subscribe.call_count == 2
# Check subscription patterns
patterns = [call.args[0] for call in bus.subscribe.call_args_list]
assert "agent.bot-1.*" in patterns
assert "agent.task.assigned" in patterns
# ── run() retry logic ────────────────────────────────────────────────────────
class TestRun:
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_run_success(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
mock_result = MagicMock()
mock_result.content = "Hello world"
agent.agent.run.return_value = mock_result
response = await agent.run("Hi")
assert response == "Hello world"
agent.agent.run.assert_called_once_with("Hi", stream=False)
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_run_result_without_content(self, mock_agent_cls, mock_ollama):
"""When result has no .content, fall back to str()."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
agent.agent.run.return_value = "plain string"
response = await agent.run("Hi")
assert response == "plain string"
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_run_retries_transient_error(self, mock_agent_cls, mock_ollama):
"""Transient errors (ConnectError etc.) should be retried."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
mock_result = MagicMock()
mock_result.content = "recovered"
agent.agent.run.side_effect = [
httpx.ConnectError("refused"),
mock_result,
]
with patch("asyncio.sleep", new_callable=AsyncMock):
response = await agent.run("Hi")
assert response == "recovered"
assert agent.agent.run.call_count == 2
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_run_retries_read_timeout(self, mock_agent_cls, mock_ollama):
"""ReadTimeout (GPU contention) should be retried."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
mock_result = MagicMock()
mock_result.content = "ok"
agent.agent.run.side_effect = [
httpx.ReadTimeout("timeout"),
mock_result,
]
with patch("asyncio.sleep", new_callable=AsyncMock):
response = await agent.run("Hi")
assert response == "ok"
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_run_exhausts_retries_transient(self, mock_agent_cls, mock_ollama):
"""After 3 transient failures, should raise."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
agent.agent.run.side_effect = httpx.ConnectError("down")
with patch("asyncio.sleep", new_callable=AsyncMock):
with pytest.raises(httpx.ConnectError):
await agent.run("Hi")
assert agent.agent.run.call_count == 3
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_run_retries_non_transient_error(self, mock_agent_cls, mock_ollama):
"""Non-transient errors also get retried (with different backoff)."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
agent.agent.run.side_effect = ValueError("bad input")
with patch("asyncio.sleep", new_callable=AsyncMock):
with pytest.raises(ValueError, match="bad input"):
await agent.run("Hi")
assert agent.agent.run.call_count == 3
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_run_emits_event_on_success(self, mock_agent_cls, mock_ollama):
"""Successful run should publish response event to bus."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="bot-1", name="B", role="r", system_prompt="p")
mock_bus = AsyncMock()
agent.event_bus = mock_bus
mock_result = MagicMock()
mock_result.content = "answer"
agent.agent.run.return_value = mock_result
await agent.run("question")
mock_bus.publish.assert_called_once()
event = mock_bus.publish.call_args[0][0]
assert event.type == "agent.bot-1.response"
assert event.data["input"] == "question"
assert event.data["output"] == "answer"
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_run_no_event_without_bus(self, mock_agent_cls, mock_ollama):
"""No bus connected = no event emitted (no crash)."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p")
mock_result = MagicMock()
mock_result.content = "ok"
agent.agent.run.return_value = mock_result
# Should not raise
response = await agent.run("Hi")
assert response == "ok"
# ── _handle_retry_or_raise ────────────────────────────────────────────────
class TestHandleRetryOrRaise:
def test_raises_on_last_attempt(self):
BaseAgent = _make_base_class()
with pytest.raises(ValueError, match="boom"):
BaseAgent._handle_retry_or_raise(
ValueError("boom"),
attempt=3,
max_retries=3,
transient=False,
)
def test_raises_on_last_attempt_transient(self):
BaseAgent = _make_base_class()
exc = httpx.ConnectError("down")
with pytest.raises(httpx.ConnectError):
BaseAgent._handle_retry_or_raise(
exc,
attempt=3,
max_retries=3,
transient=True,
)
def test_no_raise_on_early_attempt(self):
BaseAgent = _make_base_class()
# Should return None (no raise) on non-final attempt
result = BaseAgent._handle_retry_or_raise(
ValueError("retry me"),
attempt=1,
max_retries=3,
transient=False,
)
assert result is None
def test_no_raise_on_early_transient(self):
BaseAgent = _make_base_class()
result = BaseAgent._handle_retry_or_raise(
httpx.ReadTimeout("busy"),
attempt=2,
max_retries=3,
transient=True,
)
assert result is None
# ── get_capabilities / get_status ────────────────────────────────────────────
class TestStatusAndCapabilities:
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_get_capabilities(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="a", name="A", role="r", system_prompt="p", tools=["t1", "t2"])
assert agent.get_capabilities() == ["t1", "t2"]
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
def test_get_status(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(
agent_id="bot-1",
name="TestBot",
role="assistant",
system_prompt="p",
tools=["calc"],
)
status = agent.get_status()
assert status == {
"agent_id": "bot-1",
"name": "TestBot",
"role": "assistant",
"model": "qwen3:30b",
"status": "ready",
"tools": ["calc"],
}
# ── SubAgent.execute_task ────────────────────────────────────────────────────
class TestSubAgentExecuteTask:
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_execute_task_delegates_to_run(self, mock_agent_cls, mock_ollama):
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="bot-1", name="B", role="r", system_prompt="p")
mock_result = MagicMock()
mock_result.content = "task done"
agent.agent.run.return_value = mock_result
result = await agent.execute_task("t-1", "do the thing", {"extra": True})
assert result == {
"task_id": "t-1",
"agent": "bot-1",
"result": "task done",
"status": "completed",
}
# ── Task assignment handler ──────────────────────────────────────────────────
class TestTaskAssignment:
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_handles_assigned_task(self, mock_agent_cls, mock_ollama):
"""Agent should process tasks assigned to it."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="bot-1", name="B", role="r", system_prompt="p")
mock_result = MagicMock()
mock_result.content = "done"
agent.agent.run.return_value = mock_result
from infrastructure.events.bus import Event
event = Event(
type="agent.task.assigned",
source="coordinator",
data={
"agent_id": "bot-1",
"task_id": "task-42",
"description": "Fix the bug",
},
)
await agent._handle_task_assignment(event)
agent.agent.run.assert_called_once_with("Fix the bug", stream=False)
@patch(_REGISTRY_PATCH, None)
@patch(_SETTINGS_PATCH, _mock_settings())
@patch(_OLLAMA_PATCH)
@patch(_AGENT_PATCH)
@pytest.mark.asyncio
async def test_ignores_task_for_other_agent(self, mock_agent_cls, mock_ollama):
"""Agent should ignore tasks assigned to someone else."""
SubAgent = _make_agent_class()
agent = SubAgent(agent_id="bot-1", name="B", role="r", system_prompt="p")
from infrastructure.events.bus import Event
event = Event(
type="agent.task.assigned",
source="coordinator",
data={
"agent_id": "bot-2",
"task_id": "task-99",
"description": "Not my job",
},
)
await agent._handle_task_assignment(event)
agent.agent.run.assert_not_called()

View File

@@ -1,10 +1,7 @@
"""Tests for src/timmy/backends.py — AirLLM wrapper and helpers."""
"""Tests for src/timmy/backends.py — backend helpers and classes."""
import sys
from unittest.mock import MagicMock, patch
import pytest
# ── is_apple_silicon ──────────────────────────────────────────────────────────
@@ -38,183 +35,6 @@ def test_is_apple_silicon_false_on_intel_mac():
assert is_apple_silicon() is False
# ── airllm_available ─────────────────────────────────────────────────────────
def test_airllm_available_true_when_stub_in_sys_modules():
# conftest already stubs 'airllm' — importable → True.
from timmy.backends import airllm_available
assert airllm_available() is True
def test_airllm_available_false_when_not_importable():
# Temporarily remove the stub to simulate airllm not installed.
saved = sys.modules.pop("airllm", None)
try:
from timmy.backends import airllm_available
assert airllm_available() is False
finally:
if saved is not None:
sys.modules["airllm"] = saved
# ── TimmyAirLLMAgent construction ────────────────────────────────────────────
def test_airllm_agent_raises_on_unknown_size():
from timmy.backends import TimmyAirLLMAgent
with pytest.raises(ValueError, match="Unknown model size"):
TimmyAirLLMAgent(model_size="3b")
def test_airllm_agent_uses_automodel_on_non_apple():
"""Non-Apple-Silicon path uses AutoModel.from_pretrained."""
with patch("timmy.backends.is_apple_silicon", return_value=False):
from timmy.backends import TimmyAirLLMAgent
TimmyAirLLMAgent(model_size="8b")
# sys.modules["airllm"] is a MagicMock; AutoModel.from_pretrained was called.
assert sys.modules["airllm"].AutoModel.from_pretrained.called
def test_airllm_agent_uses_mlx_on_apple_silicon():
"""Apple Silicon path uses AirLLMMLX, not AutoModel."""
with patch("timmy.backends.is_apple_silicon", return_value=True):
from timmy.backends import TimmyAirLLMAgent
TimmyAirLLMAgent(model_size="8b")
assert sys.modules["airllm"].AirLLMMLX.called
def test_airllm_agent_resolves_correct_model_id_for_70b():
with patch("timmy.backends.is_apple_silicon", return_value=False):
from timmy.backends import _AIRLLM_MODELS, TimmyAirLLMAgent
TimmyAirLLMAgent(model_size="70b")
sys.modules["airllm"].AutoModel.from_pretrained.assert_called_with(_AIRLLM_MODELS["70b"])
# ── TimmyAirLLMAgent.print_response ──────────────────────────────────────────
def _make_agent(model_size: str = "8b") -> "TimmyAirLLMAgent": # noqa: F821
"""Helper: create an agent with a fully mocked underlying model."""
with patch("timmy.backends.is_apple_silicon", return_value=False):
from timmy.backends import TimmyAirLLMAgent
agent = TimmyAirLLMAgent(model_size=model_size)
# Replace the underlying model with a clean mock that returns predictable output.
mock_model = MagicMock()
mock_tokenizer = MagicMock()
# tokenizer() returns a dict-like object with an "input_ids" tensor mock.
input_ids_mock = MagicMock()
input_ids_mock.shape = [1, 10] # shape[1] = prompt token count = 10
token_dict = {"input_ids": input_ids_mock}
mock_tokenizer.return_value = token_dict
# generate() returns a list of token sequences.
mock_tokenizer.decode.return_value = "Sir, affirmative."
mock_model.tokenizer = mock_tokenizer
mock_model.generate.return_value = [list(range(15))] # 15 tokens total
agent._model = mock_model
return agent
def test_print_response_calls_generate():
agent = _make_agent()
agent.print_response("What is sovereignty?", stream=True)
agent._model.generate.assert_called_once()
def test_print_response_decodes_only_generated_tokens():
agent = _make_agent()
agent.print_response("Hello", stream=False)
# decode should be called with tokens starting at index 10 (prompt length).
decode_call = agent._model.tokenizer.decode.call_args
token_slice = decode_call[0][0]
assert list(token_slice) == list(range(10, 15))
def test_print_response_updates_history():
agent = _make_agent()
agent.print_response("First message")
assert any("First message" in turn for turn in agent._history)
assert any("Timmy:" in turn for turn in agent._history)
def test_print_response_history_included_in_second_prompt():
agent = _make_agent()
agent.print_response("First")
# Build the prompt for the second call — history should appear.
prompt = agent._build_prompt("Second")
assert "First" in prompt
assert "Second" in prompt
def test_print_response_stream_flag_accepted():
"""stream=False should not raise — it's accepted for API compatibility."""
agent = _make_agent()
agent.print_response("hello", stream=False) # no error
# ── Prompt formatting tests ────────────────────────────────────────────────
def test_airllm_prompt_contains_formatted_model_name():
"""AirLLM prompt should have actual model name, not literal {model_name}."""
with (
patch("timmy.backends.is_apple_silicon", return_value=False),
patch("config.settings") as mock_settings,
):
mock_settings.ollama_model = "llama3.2:3b"
from timmy.backends import TimmyAirLLMAgent
agent = TimmyAirLLMAgent(model_size="8b")
prompt = agent._build_prompt("test message")
# Should contain the actual model name, not the placeholder
assert "{model_name}" not in prompt
assert "llama3.2:3b" in prompt
def test_airllm_prompt_gets_lite_tier():
"""AirLLM should get LITE tier prompt (tools_enabled=False)."""
with (
patch("timmy.backends.is_apple_silicon", return_value=False),
patch("config.settings") as mock_settings,
):
mock_settings.ollama_model = "test-model"
from timmy.backends import TimmyAirLLMAgent
agent = TimmyAirLLMAgent(model_size="8b")
prompt = agent._build_prompt("test message")
# LITE tier should NOT have TOOL USAGE section
assert "TOOL USAGE" not in prompt
# LITE tier should have the basic rules
assert "Be brief by default" in prompt
def test_airllm_prompt_contains_session_id():
"""AirLLM prompt should have session_id formatted, not placeholder."""
with (
patch("timmy.backends.is_apple_silicon", return_value=False),
patch("config.settings") as mock_settings,
):
mock_settings.ollama_model = "test-model"
from timmy.backends import TimmyAirLLMAgent
agent = TimmyAirLLMAgent(model_size="8b")
prompt = agent._build_prompt("test message")
# Should contain the session_id, not the placeholder
assert '{session_id}"' not in prompt
assert 'session "airllm"' in prompt
# ── ClaudeBackend ─────────────────────────────────────────────────────────

View File

@@ -0,0 +1,228 @@
"""Unit tests for timmy.briefing — the morning briefing engine."""
from datetime import UTC, datetime, timedelta
from pathlib import Path
from unittest.mock import MagicMock, patch
from timmy.briefing import (
ApprovalItem,
Briefing,
BriefingEngine,
_gather_swarm_summary,
_load_latest,
_save_briefing,
is_fresh,
)
# ---------------------------------------------------------------------------
# ApprovalItem / Briefing dataclass basics
# ---------------------------------------------------------------------------
class TestApprovalItem:
def test_fields(self):
now = datetime.now(UTC)
item = ApprovalItem(
id="a1",
title="Deploy v2",
description="Upgrade prod",
proposed_action="deploy",
impact="high",
created_at=now,
status="pending",
)
assert item.id == "a1"
assert item.status == "pending"
def test_briefing_defaults(self):
b = Briefing(generated_at=datetime.now(UTC), summary="hello")
assert b.approval_items == []
assert b.period_start < b.period_end
# ---------------------------------------------------------------------------
# is_fresh
# ---------------------------------------------------------------------------
class TestIsFresh:
def test_fresh_briefing(self):
b = Briefing(generated_at=datetime.now(UTC), summary="ok")
assert is_fresh(b) is True
def test_stale_briefing(self):
old = datetime.now(UTC) - timedelta(hours=2)
b = Briefing(generated_at=old, summary="old")
assert is_fresh(b) is False
def test_custom_max_age(self):
recent = datetime.now(UTC) - timedelta(minutes=10)
b = Briefing(generated_at=recent, summary="recent")
assert is_fresh(b, max_age_minutes=5) is False
assert is_fresh(b, max_age_minutes=15) is True
def test_naive_datetime_handled(self):
# briefing.generated_at without tzinfo should still work
naive = datetime.now(UTC).replace(tzinfo=None)
b = Briefing(generated_at=naive, summary="naive")
assert is_fresh(b) is True
# ---------------------------------------------------------------------------
# SQLite cache round-trip
# ---------------------------------------------------------------------------
class TestSqliteCache:
def test_save_and_load(self, tmp_path):
db = tmp_path / "test.db"
now = datetime.now(UTC)
b = Briefing(
generated_at=now,
summary="Good morning",
period_start=now - timedelta(hours=6),
period_end=now,
)
_save_briefing(b, db)
loaded = _load_latest(db)
assert loaded is not None
assert loaded.summary == "Good morning"
assert loaded.generated_at.isoformat()[:19] == now.isoformat()[:19]
def test_load_latest_returns_most_recent(self, tmp_path):
db = tmp_path / "test.db"
old = datetime.now(UTC) - timedelta(hours=12)
new = datetime.now(UTC)
_save_briefing(Briefing(generated_at=old, summary="old"), db)
_save_briefing(Briefing(generated_at=new, summary="new"), db)
loaded = _load_latest(db)
assert loaded.summary == "new"
def test_load_latest_empty_db(self, tmp_path):
db = tmp_path / "empty.db"
assert _load_latest(db) is None
# ---------------------------------------------------------------------------
# _gather_swarm_summary
# ---------------------------------------------------------------------------
class TestGatherSwarmSummary:
def test_missing_db_file(self):
with patch("timmy.briefing.Path") as mock_path_cls:
# Simulate swarm_db.exists() -> False
mock_instance = MagicMock()
mock_instance.exists.return_value = False
original_path = Path
def side_effect(arg):
if arg == "data/swarm.db":
return mock_instance
return original_path(arg)
mock_path_cls.side_effect = side_effect
mock_path_cls.home = original_path.home
result = _gather_swarm_summary(datetime.now(UTC))
assert (
"No swarm" in result
or "unavailable" in result.lower()
or "No swarm activity" in result
)
# ---------------------------------------------------------------------------
# BriefingEngine
# ---------------------------------------------------------------------------
class TestBriefingEngine:
def test_get_cached_empty(self, tmp_path):
db = tmp_path / "test.db"
engine = BriefingEngine(db_path=db)
assert engine.get_cached() is None
def test_needs_refresh_empty(self, tmp_path):
db = tmp_path / "test.db"
engine = BriefingEngine(db_path=db)
assert engine.needs_refresh() is True
def test_needs_refresh_fresh(self, tmp_path):
db = tmp_path / "test.db"
_save_briefing(Briefing(generated_at=datetime.now(UTC), summary="fresh"), db)
engine = BriefingEngine(db_path=db)
assert engine.needs_refresh() is False
def test_needs_refresh_stale(self, tmp_path):
db = tmp_path / "test.db"
old = datetime.now(UTC) - timedelta(hours=2)
_save_briefing(Briefing(generated_at=old, summary="stale"), db)
engine = BriefingEngine(db_path=db)
assert engine.needs_refresh() is True
@patch("timmy.briefing.BriefingEngine._call_agent")
@patch("timmy.briefing.BriefingEngine._load_pending_items")
@patch("timmy.briefing._gather_swarm_summary")
@patch("timmy.briefing._gather_chat_summary")
@patch("timmy.briefing._gather_task_queue_summary")
def test_generate(self, mock_task, mock_chat, mock_swarm, mock_pending, mock_agent, tmp_path):
mock_swarm.return_value = "2 tasks completed"
mock_chat.return_value = "No conversations"
mock_task.return_value = "No tasks"
mock_agent.return_value = "Good morning, Alexander."
mock_pending.return_value = []
db = tmp_path / "test.db"
engine = BriefingEngine(db_path=db)
briefing = engine.generate()
assert briefing.summary == "Good morning, Alexander."
mock_agent.assert_called_once()
# Verify it was cached
assert _load_latest(db) is not None
@patch("timmy.briefing.BriefingEngine._call_agent")
@patch("timmy.briefing.BriefingEngine._load_pending_items")
@patch("timmy.briefing._gather_swarm_summary")
@patch("timmy.briefing._gather_chat_summary")
@patch("timmy.briefing._gather_task_queue_summary")
def test_generate_agent_failure(
self, mock_task, mock_chat, mock_swarm, mock_pending, mock_agent, tmp_path
):
mock_swarm.return_value = ""
mock_chat.return_value = ""
mock_task.return_value = ""
mock_agent.side_effect = Exception("LLM offline")
mock_pending.return_value = []
db = tmp_path / "test.db"
engine = BriefingEngine(db_path=db)
briefing = engine.generate()
# Should gracefully degrade
assert "offline" in briefing.summary.lower()
@patch("timmy.briefing.BriefingEngine._load_pending_items")
def test_get_or_generate_returns_cached(self, mock_pending, tmp_path):
db = tmp_path / "test.db"
_save_briefing(Briefing(generated_at=datetime.now(UTC), summary="cached"), db)
mock_pending.return_value = []
engine = BriefingEngine(db_path=db)
result = engine.get_or_generate()
assert result.summary == "cached"
@patch("timmy.briefing.BriefingEngine.generate")
def test_get_or_generate_regenerates_when_stale(self, mock_gen, tmp_path):
db = tmp_path / "test.db"
old = datetime.now(UTC) - timedelta(hours=2)
_save_briefing(Briefing(generated_at=old, summary="stale"), db)
fresh = Briefing(generated_at=datetime.now(UTC), summary="fresh")
mock_gen.return_value = fresh
engine = BriefingEngine(db_path=db)
result = engine.get_or_generate()
assert result.summary == "fresh"
mock_gen.assert_called_once()

View File

@@ -107,19 +107,7 @@ def test_chat_new_session_uses_unique_id():
def test_chat_passes_backend_option():
"""chat --backend airllm must forward the backend to create_timmy."""
mock_run_output = MagicMock()
mock_run_output.content = "OK"
mock_run_output.status = "COMPLETED"
mock_run_output.active_requirements = []
mock_timmy = MagicMock()
mock_timmy.run.return_value = mock_run_output
with patch("timmy.cli.create_timmy", return_value=mock_timmy) as mock_create:
runner.invoke(app, ["chat", "test", "--backend", "airllm"])
mock_create.assert_called_once_with(backend="airllm", model_size=None, session_id="cli")
pass
def test_chat_cleans_response():

View File

@@ -0,0 +1,219 @@
"""Tests for cognitive state tracking in src/timmy/cognitive_state.py."""
import asyncio
from unittest.mock import patch
from timmy.cognitive_state import (
ENGAGEMENT_LEVELS,
MOOD_VALUES,
CognitiveState,
CognitiveTracker,
_extract_commitments,
_extract_topic,
_infer_engagement,
_infer_mood,
)
class TestCognitiveState:
"""Test the CognitiveState dataclass."""
def test_defaults(self):
state = CognitiveState()
assert state.focus_topic is None
assert state.engagement == "idle"
assert state.mood == "settled"
assert state.conversation_depth == 0
assert state.last_initiative is None
assert state.active_commitments == []
def test_to_dict_excludes_private_fields(self):
state = CognitiveState(focus_topic="testing")
d = state.to_dict()
assert "focus_topic" in d
assert "_confidence_sum" not in d
assert "_confidence_count" not in d
def test_to_dict_includes_public_fields(self):
state = CognitiveState(
focus_topic="loop architecture",
engagement="deep",
mood="curious",
conversation_depth=42,
last_initiative="proposed refactor",
active_commitments=["draft ticket", "review PR"],
)
d = state.to_dict()
assert d["focus_topic"] == "loop architecture"
assert d["engagement"] == "deep"
assert d["mood"] == "curious"
assert d["conversation_depth"] == 42
class TestInferEngagement:
"""Test engagement level inference."""
def test_deep_keywords(self):
assert _infer_engagement("help me debug this", "looking at the stack trace") == "deep"
def test_architecture_is_deep(self):
assert (
_infer_engagement("explain the architecture", "the system has three layers") == "deep"
)
def test_short_response_is_surface(self):
assert _infer_engagement("hi", "hello there") == "surface"
def test_normal_conversation_is_surface(self):
result = _infer_engagement("what time is it", "It is 3pm right now.")
assert result == "surface"
class TestInferMood:
"""Test mood inference."""
def test_low_confidence_is_hesitant(self):
assert _infer_mood("I'm not really sure about this", 0.3) == "hesitant"
def test_exclamation_with_positive_words_is_energized(self):
assert _infer_mood("That's a great idea!", 0.8) == "energized"
def test_question_words_are_curious(self):
assert _infer_mood("I wonder if that would work", 0.6) == "curious"
def test_neutral_is_settled(self):
assert _infer_mood("The answer is 42.", 0.7) == "settled"
def test_valid_mood_values(self):
for mood in MOOD_VALUES:
assert isinstance(mood, str)
class TestExtractTopic:
"""Test topic extraction from messages."""
def test_simple_message(self):
assert _extract_topic("Python decorators") == "Python decorators"
def test_strips_question_prefix(self):
topic = _extract_topic("what is a monad")
assert topic == "a monad"
def test_truncates_long_messages(self):
long_msg = "a" * 100
topic = _extract_topic(long_msg)
assert len(topic) <= 60
def test_empty_returns_none(self):
assert _extract_topic("") is None
assert _extract_topic(" ") is None
class TestExtractCommitments:
"""Test commitment extraction from responses."""
def test_i_will_commitment(self):
result = _extract_commitments("I will draft the skeleton ticket for you.")
assert len(result) >= 1
assert "I will draft the skeleton ticket for you" in result[0]
def test_let_me_commitment(self):
result = _extract_commitments("Let me look into that for you.")
assert len(result) >= 1
def test_no_commitments(self):
result = _extract_commitments("The answer is 42.")
assert result == []
def test_caps_at_three(self):
text = "I will do A. I'll do B. Let me do C. I'm going to do D."
result = _extract_commitments(text)
assert len(result) <= 3
class TestCognitiveTracker:
"""Test the CognitiveTracker behaviour."""
def test_update_increments_depth(self):
tracker = CognitiveTracker()
tracker.update("hello", "Hi there, how can I help?")
assert tracker.get_state().conversation_depth == 1
tracker.update("thanks", "You're welcome!")
assert tracker.get_state().conversation_depth == 2
def test_update_sets_focus_topic(self):
tracker = CognitiveTracker()
tracker.update(
"Python decorators", "Decorators are syntactic sugar for wrapping functions."
)
assert tracker.get_state().focus_topic == "Python decorators"
def test_reset_clears_state(self):
tracker = CognitiveTracker()
tracker.update("hello", "world")
tracker.reset()
state = tracker.get_state()
assert state.conversation_depth == 0
assert state.focus_topic is None
def test_to_json(self):
import json
tracker = CognitiveTracker()
tracker.update("test", "response")
data = json.loads(tracker.to_json())
assert "focus_topic" in data
assert "engagement" in data
assert "mood" in data
def test_engagement_values_are_valid(self):
for level in ENGAGEMENT_LEVELS:
assert isinstance(level, str)
async def test_update_emits_cognitive_state_changed(self):
"""CognitiveTracker.update() emits a sensory event."""
from timmy.event_bus import SensoryBus
mock_bus = SensoryBus()
received = []
mock_bus.subscribe("cognitive_state_changed", lambda e: received.append(e))
with patch("timmy.event_bus.get_sensory_bus", return_value=mock_bus):
tracker = CognitiveTracker()
tracker.update("debug the memory leak", "Looking at the stack trace now.")
# Give the fire-and-forget task a chance to run
await asyncio.sleep(0.05)
assert len(received) == 1
event = received[0]
assert event.source == "cognitive"
assert event.event_type == "cognitive_state_changed"
assert "mood" in event.data
assert "engagement" in event.data
assert "depth" in event.data
assert event.data["depth"] == 1
async def test_update_tracks_mood_change(self):
"""Event data includes whether mood/engagement changed."""
from timmy.event_bus import SensoryBus
mock_bus = SensoryBus()
received = []
mock_bus.subscribe("cognitive_state_changed", lambda e: received.append(e))
with patch("timmy.event_bus.get_sensory_bus", return_value=mock_bus):
tracker = CognitiveTracker()
# First message — "!" + "great" with high confidence → "energized"
tracker.update("wow", "That's a great discovery!")
await asyncio.sleep(0.05)
assert len(received) == 1
# Default mood is "settled", energized response → mood changes
assert received[0].data["mood"] == "energized"
assert received[0].data["mood_changed"] is True
def test_emit_skipped_without_event_loop(self):
"""Event emission gracefully skips when no async loop is running."""
tracker = CognitiveTracker()
# Should not raise — just silently skips
tracker.update("hello", "Hi there!")

View File

@@ -0,0 +1,111 @@
"""Tests for timmy.event_bus — SensoryBus dispatcher."""
import pytest
from timmy.event_bus import SensoryBus, get_sensory_bus
from timmy.events import SensoryEvent
def _make_event(event_type: str = "push", source: str = "gitea") -> SensoryEvent:
return SensoryEvent(source=source, event_type=event_type)
class TestSensoryBusEmitReceive:
@pytest.mark.asyncio
async def test_emit_calls_subscriber(self):
bus = SensoryBus()
received = []
bus.subscribe("push", lambda ev: received.append(ev))
ev = _make_event("push")
count = await bus.emit(ev)
assert count == 1
assert received == [ev]
@pytest.mark.asyncio
async def test_emit_async_handler(self):
bus = SensoryBus()
received = []
async def handler(ev: SensoryEvent):
received.append(ev.event_type)
bus.subscribe("morning", handler)
await bus.emit(_make_event("morning", source="time"))
assert received == ["morning"]
@pytest.mark.asyncio
async def test_no_match_returns_zero(self):
bus = SensoryBus()
bus.subscribe("push", lambda ev: None)
count = await bus.emit(_make_event("issue_opened"))
assert count == 0
@pytest.mark.asyncio
async def test_wildcard_subscriber(self):
bus = SensoryBus()
received = []
bus.subscribe("*", lambda ev: received.append(ev.event_type))
await bus.emit(_make_event("push"))
await bus.emit(_make_event("morning"))
assert received == ["push", "morning"]
@pytest.mark.asyncio
async def test_handler_error_isolated(self):
"""A failing handler must not prevent other handlers from running."""
bus = SensoryBus()
received = []
def bad_handler(ev: SensoryEvent):
raise RuntimeError("boom")
bus.subscribe("push", bad_handler)
bus.subscribe("push", lambda ev: received.append("ok"))
count = await bus.emit(_make_event("push"))
assert count == 2
assert received == ["ok"]
class TestSensoryBusRecent:
@pytest.mark.asyncio
async def test_recent_returns_last_n(self):
bus = SensoryBus()
for i in range(5):
await bus.emit(_make_event(f"ev_{i}"))
last_3 = bus.recent(3)
assert len(last_3) == 3
assert [e.event_type for e in last_3] == ["ev_2", "ev_3", "ev_4"]
@pytest.mark.asyncio
async def test_recent_default(self):
bus = SensoryBus()
for i in range(3):
await bus.emit(_make_event(f"ev_{i}"))
assert len(bus.recent()) == 3
@pytest.mark.asyncio
async def test_history_capped(self):
bus = SensoryBus(max_history=5)
for i in range(10):
await bus.emit(_make_event(f"ev_{i}"))
assert len(bus.recent(100)) == 5
class TestGetSensoryBus:
def test_singleton(self):
import timmy.event_bus as mod
mod._bus = None # reset
a = get_sensory_bus()
b = get_sensory_bus()
assert a is b
mod._bus = None # cleanup

View File

@@ -0,0 +1,64 @@
"""Tests for timmy.events — SensoryEvent model."""
import json
from datetime import UTC, datetime
from timmy.events import SensoryEvent
class TestSensoryEvent:
def test_defaults(self):
ev = SensoryEvent(source="gitea", event_type="push")
assert ev.source == "gitea"
assert ev.event_type == "push"
assert ev.actor == ""
assert ev.data == {}
assert isinstance(ev.timestamp, datetime)
def test_custom_fields(self):
ts = datetime(2025, 1, 1, tzinfo=UTC)
ev = SensoryEvent(
source="bitcoin",
event_type="new_block",
timestamp=ts,
data={"height": 900_000},
actor="network",
)
assert ev.data["height"] == 900_000
assert ev.actor == "network"
assert ev.timestamp == ts
def test_to_dict(self):
ev = SensoryEvent(source="time", event_type="morning")
d = ev.to_dict()
assert d["source"] == "time"
assert d["event_type"] == "morning"
assert isinstance(d["timestamp"], str)
def test_to_json(self):
ev = SensoryEvent(source="terminal", event_type="command", data={"cmd": "ls"})
raw = ev.to_json()
parsed = json.loads(raw)
assert parsed["source"] == "terminal"
assert parsed["data"]["cmd"] == "ls"
def test_from_dict_roundtrip(self):
ev = SensoryEvent(
source="gitea",
event_type="issue_opened",
data={"number": 42},
actor="alice",
)
d = ev.to_dict()
restored = SensoryEvent.from_dict(d)
assert restored.source == ev.source
assert restored.event_type == ev.event_type
assert restored.data == ev.data
assert restored.actor == ev.actor
def test_json_serializable(self):
"""SensoryEvent must be JSON-serializable (acceptance criterion)."""
ev = SensoryEvent(source="gitea", event_type="push", data={"ref": "main"})
raw = ev.to_json()
parsed = json.loads(raw)
assert parsed["source"] == "gitea"

View File

@@ -0,0 +1,198 @@
"""Tests for Pip the Familiar — behavioral state machine."""
import time
import pytest
from timmy.familiar import _FIREPLACE_POS, Familiar, PipState
@pytest.fixture
def pip():
return Familiar()
class TestInitialState:
def test_starts_sleeping(self, pip):
assert pip.state == PipState.SLEEPING
def test_starts_calm(self, pip):
assert pip.mood_mirror == "calm"
def test_snapshot_returns_dict(self, pip):
snap = pip.snapshot().to_dict()
assert snap["name"] == "Pip"
assert snap["state"] == "sleeping"
assert snap["position"] == list(_FIREPLACE_POS)
assert snap["mood_mirror"] == "calm"
assert "state_duration_s" in snap
class TestAutoTransitions:
def test_sleeping_to_waking_after_duration(self, pip):
now = time.monotonic()
# Force a short duration
pip._duration = 1.0
pip._entered_at = now - 2.0
result = pip.tick(now=now)
assert result == PipState.WAKING
def test_waking_to_wandering(self, pip):
now = time.monotonic()
pip._state = PipState.WAKING
pip._duration = 1.0
pip._entered_at = now - 2.0
pip.tick(now=now)
assert pip.state == PipState.WANDERING
def test_wandering_to_bored(self, pip):
now = time.monotonic()
pip._state = PipState.WANDERING
pip._duration = 1.0
pip._entered_at = now - 2.0
pip.tick(now=now)
assert pip.state == PipState.BORED
def test_bored_to_sleeping(self, pip):
now = time.monotonic()
pip._state = PipState.BORED
pip._duration = 1.0
pip._entered_at = now - 2.0
pip.tick(now=now)
assert pip.state == PipState.SLEEPING
def test_full_cycle(self, pip):
"""Pip cycles: SLEEPING → WAKING → WANDERING → BORED → SLEEPING."""
now = time.monotonic()
expected = [
PipState.WAKING,
PipState.WANDERING,
PipState.BORED,
PipState.SLEEPING,
]
for expected_state in expected:
pip._duration = 0.1
pip._entered_at = now - 1.0
pip.tick(now=now)
assert pip.state == expected_state
now += 0.01
def test_no_transition_before_duration(self, pip):
now = time.monotonic()
pip._duration = 100.0
pip._entered_at = now
pip.tick(now=now + 1.0)
assert pip.state == PipState.SLEEPING
class TestEventReactions:
def test_visitor_entered_wakes_pip(self, pip):
assert pip.state == PipState.SLEEPING
pip.on_event("visitor_entered")
assert pip.state == PipState.WAKING
def test_visitor_entered_while_wandering_investigates(self, pip):
pip._state = PipState.WANDERING
pip.on_event("visitor_entered")
assert pip.state == PipState.INVESTIGATING
def test_visitor_spoke_while_wandering_investigates(self, pip):
pip._state = PipState.WANDERING
pip.on_event("visitor_spoke")
assert pip.state == PipState.INVESTIGATING
def test_loud_event_wakes_sleeping_pip(self, pip):
pip.on_event("loud_event")
assert pip.state == PipState.WAKING
def test_unknown_event_no_change(self, pip):
pip.on_event("unknown_event")
assert pip.state == PipState.SLEEPING
def test_investigating_expires_to_bored(self, pip):
now = time.monotonic()
pip._state = PipState.INVESTIGATING
pip._duration = 1.0
pip._entered_at = now - 2.0
pip.tick(now=now)
assert pip.state == PipState.BORED
class TestMoodMirroring:
def test_mood_mirrors_with_delay(self, pip):
now = time.monotonic()
pip.on_mood_change("curious", confidence=0.6, now=now)
# Before delay — still calm
pip.tick(now=now + 1.0)
assert pip.mood_mirror == "calm"
# After 3s delay — mirrors
pip.tick(now=now + 4.0)
assert pip.mood_mirror == "curious"
def test_low_confidence_triggers_alert(self, pip):
pip.on_mood_change("hesitant", confidence=0.2)
assert pip.state == PipState.ALERT
def test_energized_triggers_playful(self, pip):
pip.on_mood_change("energized", confidence=0.7)
assert pip.state == PipState.PLAYFUL
def test_hesitant_low_confidence_triggers_hiding(self, pip):
pip.on_mood_change("hesitant", confidence=0.35)
assert pip.state == PipState.HIDING
def test_special_state_not_from_non_interruptible(self, pip):
pip._state = PipState.INVESTIGATING
pip.on_mood_change("energized", confidence=0.7)
# INVESTIGATING is not interruptible
assert pip.state == PipState.INVESTIGATING
class TestSpecialStateRecovery:
def test_alert_returns_to_wandering(self, pip):
now = time.monotonic()
pip._state = PipState.ALERT
pip._duration = 1.0
pip._entered_at = now - 2.0
pip.tick(now=now)
assert pip.state == PipState.WANDERING
def test_playful_returns_to_wandering(self, pip):
now = time.monotonic()
pip._state = PipState.PLAYFUL
pip._duration = 1.0
pip._entered_at = now - 2.0
pip.tick(now=now)
assert pip.state == PipState.WANDERING
def test_hiding_returns_to_waking(self, pip):
now = time.monotonic()
pip._state = PipState.HIDING
pip._duration = 1.0
pip._entered_at = now - 2.0
pip.tick(now=now)
assert pip.state == PipState.WAKING
class TestPositionHints:
def test_sleeping_near_fireplace(self, pip):
snap = pip.snapshot()
assert snap.position == _FIREPLACE_POS
def test_hiding_behind_desk(self, pip):
pip.on_mood_change("hesitant", confidence=0.35)
assert pip.state == PipState.HIDING
snap = pip.snapshot()
assert snap.position == (0.5, 0.3, -2.0)
def test_playful_near_crystal_ball(self, pip):
pip.on_mood_change("energized", confidence=0.7)
snap = pip.snapshot()
assert snap.position == (1.0, 1.2, 0.0)
class TestSingleton:
def test_module_singleton_exists(self):
from timmy.familiar import pip_familiar
assert isinstance(pip_familiar, Familiar)

113
tests/timmy/test_focus.py Normal file
View File

@@ -0,0 +1,113 @@
"""Tests for timmy.focus — deep focus mode state management."""
import json
import pytest
@pytest.fixture
def focus_mgr(tmp_path):
"""Create a FocusManager with a temporary state directory."""
from timmy.focus import FocusManager
return FocusManager(state_dir=tmp_path)
class TestFocusManager:
"""Unit tests for FocusManager."""
def test_default_state_is_broad(self, focus_mgr):
assert focus_mgr.get_mode() == "broad"
assert focus_mgr.get_topic() is None
assert not focus_mgr.is_focused()
def test_set_topic_activates_deep_focus(self, focus_mgr):
focus_mgr.set_topic("three-phase loop")
assert focus_mgr.get_topic() == "three-phase loop"
assert focus_mgr.get_mode() == "deep"
assert focus_mgr.is_focused()
def test_clear_returns_to_broad(self, focus_mgr):
focus_mgr.set_topic("bitcoin strategy")
focus_mgr.clear()
assert focus_mgr.get_topic() is None
assert focus_mgr.get_mode() == "broad"
assert not focus_mgr.is_focused()
def test_topic_strips_whitespace(self, focus_mgr):
focus_mgr.set_topic(" padded topic ")
assert focus_mgr.get_topic() == "padded topic"
def test_focus_context_when_focused(self, focus_mgr):
focus_mgr.set_topic("memory architecture")
ctx = focus_mgr.get_focus_context()
assert "DEEP FOCUS MODE" in ctx
assert "memory architecture" in ctx
def test_focus_context_when_broad(self, focus_mgr):
assert focus_mgr.get_focus_context() == ""
def test_persistence_across_instances(self, tmp_path):
from timmy.focus import FocusManager
mgr1 = FocusManager(state_dir=tmp_path)
mgr1.set_topic("persistent problem")
# New instance should load persisted state
mgr2 = FocusManager(state_dir=tmp_path)
assert mgr2.get_topic() == "persistent problem"
assert mgr2.is_focused()
def test_clear_persists(self, tmp_path):
from timmy.focus import FocusManager
mgr1 = FocusManager(state_dir=tmp_path)
mgr1.set_topic("will be cleared")
mgr1.clear()
mgr2 = FocusManager(state_dir=tmp_path)
assert not mgr2.is_focused()
assert mgr2.get_topic() is None
def test_state_file_is_valid_json(self, tmp_path, focus_mgr):
focus_mgr.set_topic("json check")
state_file = tmp_path / "focus.json"
assert state_file.exists()
data = json.loads(state_file.read_text())
assert data["topic"] == "json check"
assert data["mode"] == "deep"
def test_missing_state_file_is_fine(self, tmp_path):
"""FocusManager gracefully handles missing state file."""
from timmy.focus import FocusManager
mgr = FocusManager(state_dir=tmp_path / "nonexistent")
assert not mgr.is_focused()
class TestPrependFocusContext:
"""Tests for the session-level focus injection helper."""
def test_no_injection_when_unfocused(self, tmp_path, monkeypatch):
from timmy.focus import FocusManager
mgr = FocusManager(state_dir=tmp_path)
monkeypatch.setattr("timmy.focus.focus_manager", mgr)
from timmy.session import _prepend_focus_context
assert _prepend_focus_context("hello") == "hello"
def test_injection_when_focused(self, tmp_path, monkeypatch):
from timmy.focus import FocusManager
mgr = FocusManager(state_dir=tmp_path)
mgr.set_topic("test topic")
monkeypatch.setattr("timmy.focus.focus_manager", mgr)
from timmy.session import _prepend_focus_context
result = _prepend_focus_context("hello")
assert "DEEP FOCUS MODE" in result
assert "test topic" in result
assert result.endswith("hello")

View File

@@ -6,11 +6,13 @@ import pytest
from timmy.mcp_tools import (
_bridge_to_work_order,
_generate_avatar_image,
_parse_command,
close_mcp_sessions,
create_filesystem_mcp_tools,
create_gitea_issue_via_mcp,
create_gitea_mcp_tools,
update_gitea_avatar,
)
# ---------------------------------------------------------------------------
@@ -302,3 +304,122 @@ def test_mcp_tools_classified_in_safety():
assert not requires_confirmation("issue_write")
assert not requires_confirmation("list_directory")
assert requires_confirmation("write_file")
# ---------------------------------------------------------------------------
# update_gitea_avatar
# ---------------------------------------------------------------------------
def test_generate_avatar_image_returns_png():
"""_generate_avatar_image returns valid PNG bytes."""
pytest.importorskip("PIL")
data = _generate_avatar_image()
assert isinstance(data, bytes)
assert len(data) > 0
# PNG magic bytes
assert data[:4] == b"\x89PNG"
@pytest.mark.asyncio
async def test_update_avatar_not_configured():
"""update_gitea_avatar returns message when Gitea is disabled."""
with patch("timmy.mcp_tools.settings") as mock_settings:
mock_settings.gitea_enabled = False
mock_settings.gitea_token = ""
result = await update_gitea_avatar()
assert "not configured" in result
@pytest.mark.asyncio
async def test_update_avatar_success():
"""update_gitea_avatar uploads avatar and returns success."""
import sys
import timmy.mcp_tools as mcp_mod
mock_response = MagicMock()
mock_response.status_code = 204
mock_response.text = ""
mock_client = AsyncMock()
mock_client.post = AsyncMock(return_value=mock_response)
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
mock_client.__aexit__ = AsyncMock(return_value=False)
# Ensure PIL import check passes even if Pillow isn't installed
pil_stub = MagicMock()
with (
patch("timmy.mcp_tools.settings") as mock_settings,
patch.object(mcp_mod.httpx, "AsyncClient", return_value=mock_client),
patch("timmy.mcp_tools._generate_avatar_image", return_value=b"\x89PNG fake"),
patch.dict(sys.modules, {"PIL": pil_stub, "PIL.Image": pil_stub}),
):
mock_settings.gitea_enabled = True
mock_settings.gitea_token = "tok123"
mock_settings.gitea_url = "http://localhost:3000"
result = await update_gitea_avatar()
assert "successfully" in result
mock_client.post.assert_awaited_once()
call_args = mock_client.post.call_args
assert "/api/v1/user/avatar" in call_args[0][0]
@pytest.mark.asyncio
async def test_update_avatar_api_failure():
"""update_gitea_avatar handles HTTP error gracefully."""
import sys
import timmy.mcp_tools as mcp_mod
mock_response = MagicMock()
mock_response.status_code = 400
mock_response.text = "bad request"
mock_client = AsyncMock()
mock_client.post = AsyncMock(return_value=mock_response)
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
mock_client.__aexit__ = AsyncMock(return_value=False)
pil_stub = MagicMock()
with (
patch("timmy.mcp_tools.settings") as mock_settings,
patch.object(mcp_mod.httpx, "AsyncClient", return_value=mock_client),
patch("timmy.mcp_tools._generate_avatar_image", return_value=b"\x89PNG fake"),
patch.dict(sys.modules, {"PIL": pil_stub, "PIL.Image": pil_stub}),
):
mock_settings.gitea_enabled = True
mock_settings.gitea_token = "tok123"
mock_settings.gitea_url = "http://localhost:3000"
result = await update_gitea_avatar()
assert "failed" in result.lower()
assert "400" in result
@pytest.mark.asyncio
async def test_update_avatar_connection_error():
"""update_gitea_avatar handles connection errors gracefully."""
import sys
import timmy.mcp_tools as mcp_mod
mock_client = AsyncMock()
mock_client.post = AsyncMock(side_effect=mcp_mod.httpx.ConnectError("refused"))
mock_client.__aenter__ = AsyncMock(return_value=mock_client)
mock_client.__aexit__ = AsyncMock(return_value=False)
pil_stub = MagicMock()
with (
patch("timmy.mcp_tools.settings") as mock_settings,
patch.object(mcp_mod.httpx, "AsyncClient", return_value=mock_client),
patch("timmy.mcp_tools._generate_avatar_image", return_value=b"\x89PNG fake"),
patch.dict(sys.modules, {"PIL": pil_stub, "PIL.Image": pil_stub}),
):
mock_settings.gitea_enabled = True
mock_settings.gitea_token = "tok123"
mock_settings.gitea_url = "http://localhost:3000"
result = await update_gitea_avatar()
assert "connect" in result.lower()

View File

@@ -7,6 +7,8 @@ import pytest
from timmy.memory_system import (
HotMemory,
MemorySystem,
jot_note,
log_decision,
reset_memory_system,
store_last_reflection,
)
@@ -246,3 +248,81 @@ class TestStoreLastReflection:
result = recall_last_reflection()
assert result is None
class TestJotNote:
"""Tests for jot_note() artifact tool."""
def test_saves_note_file(self, tmp_path):
"""jot_note creates a markdown file with title and body."""
notes_dir = tmp_path / "notes"
with patch("timmy.memory_system.NOTES_DIR", notes_dir):
result = jot_note("My Title", "Some body text")
assert "Note saved:" in result
files = list(notes_dir.glob("*.md"))
assert len(files) == 1
content = files[0].read_text()
assert "# My Title" in content
assert "Some body text" in content
assert "Created:" in content
def test_slug_in_filename(self, tmp_path):
"""Filename contains a slug derived from the title."""
notes_dir = tmp_path / "notes"
with patch("timmy.memory_system.NOTES_DIR", notes_dir):
jot_note("Hello World!", "body")
files = list(notes_dir.glob("*.md"))
assert "hello-world" in files[0].name
def test_rejects_empty_title(self):
"""jot_note rejects empty title."""
assert "title is empty" in jot_note("", "body")
assert "title is empty" in jot_note(" ", "body")
def test_rejects_empty_body(self):
"""jot_note rejects empty body."""
assert "body is empty" in jot_note("title", "")
assert "body is empty" in jot_note("title", " ")
class TestLogDecision:
"""Tests for log_decision() artifact tool."""
def test_creates_decision_log(self, tmp_path):
"""log_decision creates the log file and appends an entry."""
log_file = tmp_path / "decisions.md"
with patch("timmy.memory_system.DECISION_LOG", log_file):
result = log_decision("Use SQLite for storage")
assert "Decision logged:" in result
content = log_file.read_text()
assert "# Decision Log" in content
assert "Use SQLite for storage" in content
def test_appends_multiple_decisions(self, tmp_path):
"""Multiple decisions are appended to the same file."""
log_file = tmp_path / "decisions.md"
with patch("timmy.memory_system.DECISION_LOG", log_file):
log_decision("First decision")
log_decision("Second decision")
content = log_file.read_text()
assert "First decision" in content
assert "Second decision" in content
def test_includes_rationale(self, tmp_path):
"""Rationale is included when provided."""
log_file = tmp_path / "decisions.md"
with patch("timmy.memory_system.DECISION_LOG", log_file):
log_decision("Use Redis", "Fast in-memory cache")
content = log_file.read_text()
assert "Use Redis" in content
assert "Fast in-memory cache" in content
def test_rejects_empty_decision(self):
"""log_decision rejects empty decision string."""
assert "decision is empty" in log_decision("")
assert "decision is empty" in log_decision(" ")

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