alvis/oO
1
0
Fork 0
Code Issues 34 Pull Requests Actions Packages Projects Releases Wiki Activity

chore(m2): close out remaining loose ends (#80, #86, #90)

Browse Source 
- Add `ai` compose profile — Ollama + LiteLLM containers for local dev
  when Agap shared services are unavailable; use with LITELLM_URL /
  OLLAMA_URL env vars pointing ml-serving at localhost
- Mark #90 done (LLM schema validation + fallback shipped in 85a332b)
- Mark #80 superseded by ADR-0013 (multi-agent orchestrator is the pipeline)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
alvis
2026-05-12 15:31:25 +00:00
parent 85a332b22b
commit 8fd08379d7
2 changed files with 46 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
README.md
View File

@@ -212,14 +212,14 @@ Goal: tips are AI-generated from user context, not just raw Todoist tasks. Multi
- [x] Per-agent auto-inference: `time-of-day` (#112), `focus-area` (#113), `momentum` (#114), `overdue-task` (#115), `recent-patterns` (#116)
**AI infrastructure (unblock everything else):**
- [ ] `ai` compose profile — Ollama + LiteLLM for local dev; env vars `OLLAMA_URL` / `LITELLM_URL` (#86)
- [x] `ai` compose profile — Ollama + LiteLLM for local dev; env vars `OLLAMA_URL` / `LITELLM_URL` (#86)
- [x] AI gateway — wire `ml/serving` to LiteLLM; model aliases `tip-generator` + `embedder` (#87)
**AI tip generation pipeline:**
- [x] Context assembler — user signals + feature store → structured prompt context (`ml/features/context.py`); skeleton implemented
- [x] Tip generator endpoint — `POST /generate` in `ml/serving`; LLM → N typed `TipCandidate` objects (#79)
- [x] `TipCandidate` shared schema — `{content, kind, source, model, prompt_version, confidence}`; update recommender pipeline (#89)
- [ ] LLM output validation + retry — JSON schema gate, clarification retry (2×), fallback to task-based (#90)
- [x] LLM output validation + retry — JSON schema gate, clarification retry (2×), fallback to hardcoded tips on AI failure (#90)
- [x] Prompt versioning — `prompt_version` + `model` columns in `tip_scores`; content-hash invalidation (#91)
- [x] LLM tip quality dashboard — reaction breakdown by model / prompt_version in `/admin/reward-analytics` (#92)
@@ -229,7 +229,7 @@ Goal: tips are AI-generated from user context, not just raw Todoist tasks. Multi
**Pipeline architecture:**
- [x] Signal source abstraction — `SignalSource` interface for Todoist + extensible design (#78)
- [ ] Generalized recommendation pipeline — candidate → rank → render stages (#80)
- [x] Generalized recommendation pipeline — superseded by ADR-0013; multi-agent orchestrator is the pipeline (#80)
- [x] Feature registry + user profile builder — centralized features, persistent profiles, event-driven invalidation (#81)
- [ ] Tip kind system — task, advice, insight, reminder with kind-aware UI + rewards (#82)