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

- 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- Mark #80 superseded by ADR-0013 (multi-agent orchestrator is the pipeline)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>

README.md

@@ -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+- [x] Generalized recommendation pipeline — superseded by ADR-0013; multi-agent orchestrator is the pipeline (#80)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)
 

infra/docker/docker-compose.yml

@@ -82,6 +82,46 @@ services:
       timeout: 5s
       retries: 5
 
+  # ── ai profile — Ollama + LiteLLM for local dev ──────────────────────────
+  # Start: docker compose --profile ai up
+  # Use when the Agap shared Ollama/LiteLLM services are not available locally.
+  # Set LITELLM_URL=http://localhost:4000 and OLLAMA_URL=http://localhost:11434
+  # in .env.local to point ml-serving at these containers instead of Agap.
+
+  ollama:
+    image: ollama/ollama:latest
+    profiles: [ai]
+    volumes:
+      - ollama-models:/root/.ollama
+    ports:
+      - "127.0.0.1:11434:11434"
+    healthcheck:
+      test: ["CMD", "curl", "-sf", "http://localhost:11434/api/tags"]
+      interval: 15s
+      timeout: 5s
+      retries: 10
+
+  litellm:
+    image: ghcr.io/berriai/litellm:main-latest
+    profiles: [ai]
+    environment:
+      LITELLM_MASTER_KEY: ${LITELLM_MASTER_KEY:-sk-local-dev}
+    command: >
+      --model ollama/qwen2.5:1.5b
+      --model ollama/nomic-embed-text
+      --api_base http://ollama:11434
+      --port 4000
+    ports:
+      - "127.0.0.1:4000:4000"
+    depends_on:
+      ollama:
+        condition: service_healthy
+    healthcheck:
+      test: ["CMD", "curl", "-sf", "http://localhost:4000/health"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
+
   # ── mlops profile — MLflow ────────────────────────────────────────────────
   # Start: docker compose --profile mlops up
   # MLflow UI:  http://localhost:5000  or  https://o.alogins.net/mlflow
@@ -129,3 +169,6 @@ services:
       interval: 10s
       timeout: 5s
       retries: 5
+
+volumes:
+  ollama-models: