7 Commits

Author	SHA1	Message	Date
root	4ac56564c0	scrum + applier + observer: switch to paid OpenRouter ladder, add Kimi K2.6 + Gemini 2.5 ... Ollama Cloud was throttled across all 6 cloud rungs in iters 1-9, which forced the loop into 0-review iterations even though the architecture was sound. Swapping to paid OpenRouter unblocks the test path. Ladder changes (top-of-ladder paid models, all under $0.85/M either side): - moonshotai/kimi-k2.6 ($0.74/$4.66, 256K) — capped at 25/hr - x-ai/grok-4.1-fast ($0.20/$0.50, 2M) — primary general - google/gemini-2.5-flash ($0.30/$2.50, 1M) — Google reasoning - deepseek/deepseek-v4-flash ($0.14/$0.28, 1M) — cheap workhorse - qwen/qwen3-235b-a22b-2507 ($0.07/$0.10, 262K) — cheapest big Existing rungs (Ollama Cloud + free OR + local qwen3.5) kept as fallback. Per-model rate limiter (MODEL_RATE_LIMITS in scrum_master_pipeline.ts): - Persists call timestamps to data/_kb/rate_limit_calls.jsonl so caps survive process restarts (autonomous loop spawns a fresh subprocess per iteration; without persistence each iter would reset) - O(1) writes, prune-on-read for the rolling 1h window - Capped models log "SKIP (rate-limited: cap N/hr reached)" and the ladder cycles to the next rung - J directive 2026-04-25: 25/hr on Kimi K2.6 to bound output cost Observer hand-review cloud tier swapped from ollama_cloud/qwen3-coder:480b to openrouter/x-ai/grok-4.1-fast — proven to emit precise semantic verdicts (named "AccessControl::can_access() doesn't exist" specifically in 2026-04-25 tests instead of the heuristic fallback). Applier patch emitter swapped from ollama_cloud/qwen3-coder:480b to openrouter/x-ai/grok-4.1-fast (default; LH_APPLIER_MODEL + LH_APPLIER_PROVIDER override). This was the third LLM call we missed — without it, observer accepts a review but applier never produces patches because its emitter was still hitting the throttled account. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-04-25 17:49:02 -05:00
root	3f166a5558	scrum + observer: hand-review wire — judgment moved out of the inner loop ... Pre-2026-04-25 the scrum_master applied a hardcoded grounding-rate gate inline. That baked policy into the wrong layer — semantic judgment about whether a review is grounded belongs in the observer (which has Langfuse traces, sees every response across the system, and can call cloud LLMs for real evaluation). Scrum should report DATA, observer DECIDES. What landed: - scrum_master_pipeline.ts: removed the inline grounding-pct threshold; every accepted candidate now POSTs to observer's /review endpoint with {response, source_content, grounding_stats, model, attempt}. Observer returns {verdict: accept|reject|cycle, confidence, notes}. On observer failure, scrum falls open to accept (observer is policy, not blocker). - mcp-server/observer.ts: new POST /review endpoint with two-tier evaluator. Tier 1: cloud LLM (qwen3-coder:480b at temp=0) hand-reviews with full context — response + source excerpt + grounding stats — and emits structured verdict JSON. Tier 2: deterministic heuristic over grounding pct + total quotes when cloud throttles, marked source: "heuristic" so consumers can tune it later by comparing against cloud. - Every verdict persists to data/_kb/observer_reviews.jsonl with full input snapshot so cloud vs heuristic can be A/B compared once cloud quota refreshes. Verified end-to-end: smoke loop iter 1 — observer returned `cycle` on 21% grounding (cycled to next rung), `reject` on 17% (gave up). Iter 2 — `reject` on 12% and 14%. Both UNRESOLVED with honest signal instead of polluting pathway memory with hallucinated patterns. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-04-25 17:32:04 -05:00
root	25ea3de836	observer: fix LLM Team escalation — route to /v1/chat qwen3-coder:480b instead of dead mode ... Discovery 2026-04-24: /api/run?mode=code_review returns "Unknown mode" (error response from llm_team_ui.py). The 2026-04-24 observer escalation wiring pointed at a dead endpoint and was failing silently. My earlier claim of "9 registered LLM Team modes" came from GET probes that all returned 405 — I interpreted that as "POST-only endpoints exist" when it just means "GET is not allowed for anything, and on POST only `extract` is registered." Rewire: observer's escalateFailureClusterToLLMTeam now hits POST /v1/chat { provider: "ollama_cloud", model: "qwen3-coder:480b", ... } which is the same coding-specialist rung 2 of the scrum ladder that reliably produces substantive reviews. Probe shows 1240 chars of substantive analysis in ~8.7s. Also tightens scrum_applier: * MODEL default: kimi-k2:1t → qwen3-coder:480b (coding specialist) * Size gate: 20 lines → 6 lines (surgical patches only) * Max patches per file: 3 → 2 * Prompt: explicit forbidden-actions list (no struct renames, no function-signature changes, no new modules) and mechanical-only whitelist These changes produced the first auto-applied commit (96b46cd), which landed a 2-line import addition that passed cargo check. Zero-to-one. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-04-24 04:14:33 -05:00
root	8b77d67c9c	OpenRouter rescue ladder + tree-split reduce fix + observer→LLM Team + scrum_applier + first auto-applied patch ... ## Infrastructure (scrum loop hardening) crates/gateway/src/v1/openrouter.rs — new OpenRouter provider Direct HTTPS to openrouter.ai/api/v1/chat/completions with OpenAI-compatible shape. Key resolution: OPENROUTER_API_KEY env → /home/profit/.env → /root/llm_team_config.json (shares LLM Team UI's quota). Added after iter 5 hit repeated Ollama Cloud 502s on kimi-k2:1t — different provider backbone as rescue rung. Unit tests pin the URL stripping and OpenAI wire shape. crates/gateway/src/v1/mod.rs + main.rs Added `"openrouter" | "openrouter_free"` arm to /v1/chat dispatch. V1State.openrouter_key loaded at startup via openrouter::resolve_openrouter_key() mirroring the Ollama Cloud pattern. Startup log: "v1: OpenRouter key loaded — /v1/chat provider=openrouter enabled" tests/real-world/scrum_master_pipeline.ts * 9-rung ladder — kimi-k2:1t → qwen3-coder:480b → deepseek-v3.1:671b → mistral-large-3:675b → gpt-oss:120b → qwen3.5:397b → openrouter/gpt-oss-120b:free → openrouter/gemma-3-27b-it:free → local qwen3.5:latest. Added qwen3-coder:480b as rung 2 after live probes confirmed it rescues kimi-k2:1t 502s cleanly (0.9s latency, substantive reviews). Dropped devstral-2 (displaced by qwen3-coder); dropped kimi-k2.6 (not available); dropped minimax-m2.7 (returned 0 chars / 400 thinking tokens). Local fallback promoted qwen3.5:latest per J's direction 2026-04-24. * MAX_ATTEMPTS bumped 6 → 9 to accommodate the rescue tier. * Tree-split scratchpad fixed — was concatenating shard markers directly into the reviewer input, causing kimi-k2:1t to write titles like "Forensic Audit Report – file.rs (shard 3)". Now uses internal §N§ markers during accumulation and runs a proper reduce step that collapses per-shard digests into ONE coherent file-level synthesis with markers stripped. Matches the Phase 21 aibridge::tree_split map→reduce design. Fallback to stripped scratchpad if reducer returns thin. tests/real-world/scrum_applier.ts — NEW (737 lines) The auto-apply pipeline. Reads scrum_reviews.jsonl, filters rows where gradient_tier ∈ {auto, dry_run} AND confidence_avg ≥ MIN_CONF (default 90), asks the reviewer model for concrete old_string/new_string patch JSON, applies via text replacement, runs cargo check after each file, commits if green and reverts if red. Deny-list: /etc/, config/, ops/, auditor/, docs/, data/, mcp-server/, ui/, sidecar/, scripts/. Hard caps: per-patch confidence ≥ MIN_CONF, old_string must be exactly unique, max 20 lines per patch. Never runs on main without explicit LH_APPLIER_BRANCH override. Audit trail in data/_kb/auto_apply.jsonl. Empirical behavior (dry-run over iter 4 reviews): 5 eligible files → 1 green commit-ready, 2 build-red reverts, 2 all-rejected The build-green gate caught 2 bad patches before they'd have merged. mcp-server/observer.ts — LLM Team code_review escalation When a sig_hash accumulates ≥3 failures (ESCALATION_THRESHOLD), fire-and-forget POST /api/run?mode=code_review at localhost:5000 with the failure cluster context. Parses facts/entities/relationships/file_hints from the response. Writes to a new data/_kb/observer_escalations.jsonl surface. Answers J's vision of the observer triggering richer LLM Team calls when failures pile up. Non-blocking: runs parallel to existing qwen2.5 analyzer, never replaces it. Tracks escalated sig_hashes in a session-local Set to avoid re-hammering LLM Team when a cluster persists across observer cycles. crates/aibridge/src/context.rs First auto-applied patch produced by scrum_applier.ts (dry-run path — applier writes files in dry-run mode but doesn't commit; bug noted for iter 6 fix). Adds #[deprecated] annotation to the inline estimate_tokens helper pointing callers to the centralized shared::model_matrix::ModelMatrix entry point (P21-002 — duplicate token-estimator surfaces). Cargo check passes with the annotation (verified by applier's own build gate). ## Visual Control Plane (UI) ui/server.ts — Bun.serve on :3950 with /data/* fan-out: /data/services, /data/reviews, /data/metrics, /data/trust, /data/overrides, /data/findings, /data/outcomes, /data/audit_facts, /data/file/:path, /data/refactor_signals, /data/search?q=, /data/signal_classes, /data/logs/:svc (journalctl tail per systemd unit), /data/scrum_log. Bug fix: tryFetch always attempts JSON.parse before falling back to text — observer's Bun.serve returns JSON without application/json content-type, which was displaying stats as a raw string ("0 ops" on map) before. ui/index.html + ui.css — dark neo-brutalist shell. 6 views: MAP (D3 force-graph + overlays) / TRACE (per-file iter history) / TRAJECTORY (signal-class cards + refactor-signals table + reverse-index search box) / METRICS (every card has SOURCE + GOOD lines explaining where the number comes from and what target trajectory means) / KB (card grid with tooltips on every field) / CONSOLE (per-service journalctl tabs). ui/ui.js — polling client, D3 wiring, signal-class panel, refactor-signals table, reverse-index search, per-service console tabs. Bug fix: renderNodeContext had Object.entries() iterating string characters when /health returned a plain string — now guards with typeof check so "lakehouse ok" renders as one row instead of "0 l / 1 a / 2 k / ...". 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-04-24 03:45:35 -05:00
root	21fd3b9c61	Scrum-driven fixes: P5-001 auth wired, P42-001 truth evaluator, P9-001 journal on ingest ... Apply the highest-confidence findings from the Phase 0→42 forensic sweep after four scrum-master iterations under the adversarial prompt. Each fix is independently validated by a later scrum iteration scoring the same file higher under the same bar. Code changes ──────────── P5-001 — crates/gateway/src/auth.rs + main.rs api_key_auth was marked #[allow(dead_code)] and never wrapped around the router, so `[auth] enabled=true` logged a green message and enforced nothing. Now wired via from_fn_with_state, with constant-time header compare and /health exempted for LB probes. P42-001 — crates/truth/src/lib.rs TruthStore::check() ignored RuleCondition entirely — signature looked like enforcement, body returned every action unconditionally. Added evaluate(task_class, ctx) that actually walks FieldEquals / FieldEmpty / FieldGreater / Always against a serde_json::Value via dot-path lookup. check() kept for back-compat. Tests 14 → 24 (10 new exercising real pass/fail semantics). serde_json moved to [dependencies]. P9-001 (partial) — crates/ingestd/src/service.rs Added Optional<Journal> to IngestState + a journal.record_ingest() call on /ingest/file success. Gateway wires it with `journal.clone()` before the /journal nest consumes the original. First-ever internal mutation journal event verified live (total_events_created 0→1 after probe). Iter-4 scrum scored these files higher under same prompt: ingestd/src/service.rs 3 → 6 (P9-001 visible) truth/src/lib.rs 3 → 4 (P42-001 visible) gateway/src/auth.rs 3 → 4 (P5-001 visible) gateway/src/execution_loop 4 → 6 (indirect) storaged/src/federation 3 → 4 (indirect) Infrastructure additions ──────────────────────── * tests/real-world/scrum_master_pipeline.ts - cloud-first ladder: kimi-k2:1t → deepseek-v3.1:671b → mistral-large-3:675b → gpt-oss:120b → devstral-2:123b → qwen3.5:397b (deep final thinker) - LH_SCRUM_FORENSIC env: injects SCRUM_FORENSIC_PROMPT.md as adversarial preamble - LH_SCRUM_PROPOSAL env: per-iter fix-wave doc override - Confidence extraction (markdown + JSON), schema v4 KB rows with: verdict, critical_failures_count, verified_components_count, missing_components_count, output_format, gradient_tier - Model trust profile written per file-accept to data/_kb/model_trust.jsonl - Fire-and-forget POST to observer /event so by_source.scrum appears in /stats * mcp-server/observer.ts — unchanged in shape, confirmed receiving scrum events * ui/ — new Visual Control Plane on :3950 - Bun.serve with /data/{services,reviews,metrics,trust,overrides,findings,file,refactor_signals,search,logs/:svc,scrum_log} - Views: MAP (D3 graph, 5 overlays) / TRACE (per-file iter timeline) / TRAJECTORY (refactor signals + reverse index search) / METRICS (explainers with SOURCE + GOOD lines) / KB (card grid with tooltips) / CONSOLE (per-service journalctl tail, tabs for gateway/sidecar/observer/mcp/ctx7/auditor/langfuse) - tryFetch always attempts JSON.parse (fix for observer returning JSON without content-type) - renderNodeContext primitive-vs-object guard (fix for gateway /health string) * docs/SCRUM_FIX_WAVE.md — iter-specific scope directing the scrum * docs/SCRUM_FORENSIC_PROMPT.md — adversarial audit prompt (verdict/critical/verified schema) * docs/SCRUM_LOOP_NOTES.md — iteration observations + fix-next-loop queue * docs/SYSTEM_EVOLUTION_LAYERS.md — Layers 1-10 roadmap (trust profiling, execution DNA, drift sentinel, etc) Measurements across iterations ────────────────────────────── iter 1 (soft prompt, gpt-oss:120b): mean score 5.00/10 iter 3 (forensic, kimi-k2:1t): mean score 3.56/10 (−1.44 — bar raised) iter 4 (same bar, post fixes): mean score 4.00/10 (+0.44 — fixes landed) Score movement iter3→iter4: ↑5 ↓1 =12 21/21 first-attempt accept by kimi-k2:1t in iter 4 20/21 emitted forensic JSON (richer signal than markdown) 16 verified_components captured (proof-of-life, new metric) Permission Gradient distribution: 0 auto · 16 dry_run · 4 sim · 1 block Observer loop: by_source {scrum: 21, langfuse: 1985, phase24_audit: 1} v1/usage: 224 requests, 477K tokens, all tracked Signal classes per file (iter 3 → iter 4): CONVERGING: 1 (ingestd/service.rs — fix clearly landed) LOOPING: 4 (catalogd/registry, main, queryd/service, vectord/index_registry) ORBITING: 1 (truth — novel findings surfacing as surface ones fix) PLATEAU: 9 (scores flat with high confidence — diminishing returns) MIXED: 6 Loop thesis status ────────────────── A file's score rises only when the scrum confirms a real fix landed. No false positives yet across 3 iterations. Fixes applied to 3 files all raised their independent scores under the same adversarial prompt. Loop is measurable, not hand-wavy. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>	2026-04-24 02:25:43 -05:00
root	b95dd86556	Phase 24 — observer HTTP ingest + scenario outcome streaming ... Closes the gap J flagged: observer wraps MCP:3700, scenarios hit gateway:3100 directly, observer idle at 0 ops across 3600+ cycles. Now scenarios POST per-event outcomes to observer's new HTTP ingest on :3800, observer consumes them alongside MCP-wrapped ops, ERROR_ ANALYZER and PLAYBOOK_BUILDER loops see the full picture. observer.ts: - Bun.serve() HTTP listener on OBSERVER_PORT (default 3800): GET /health — basic + ring depth GET /stats — total / success / failure / by_source / recent scenario ops digest POST /event — accept scenario outcome, shape it into ObservedOp with source="scenario" + staffer_id + sig_hash + event_kind + role/city/state + rescue flags - recordExternalOp() — shared ring-buffer insert so the main analyzer + playbook builder don't care where the op came from - ObservedOp extended with provenance fields persistOp() FIX — old path POSTed to /ingest/file?name=observed_operations which REPLACES the dataset (flagged in feedback_ingest_replace_semantics.md). Every op was silently wiping all prior ops. Replaced with append to data/_observer/ops.jsonl so the historical trace is durable across analyzer cycles and process restarts. scenario.ts: - OBSERVER_URL env (default http://localhost:3800) - postObserverEvent() helper with 2s AbortSignal.timeout so observer being down doesn't block scenario flow - Per-event POST after ctx.results.push(result), carrying staffer_id, sig_hash (via imported computeSignature), event_kind + role + city + state + count + rescue_attempted / rescue_succeeded + truncated output_summary VERIFIED: curl POST /event → {"accepted":true,"ring_size":1} curl GET /stats → {"total":1,"successes":1,"by_source":{"scenario":1}, "recent_scenario_ops":[{...staffer_id,kind,role}]} Final v3 demo leaderboard (9 runs per staffer, cumulative 3 batches): James (local): 92.9% fill, 36.8 cites, score 0.775 — RANK 1 Maria (full): 81.0% fill, 26.2 cites, score 0.727 Sam (basic): 61.9% fill, 28.2 cites, score 0.640 Alex (minimal): 59.5% fill, 32.2 cites, score 0.631 Honest finding: Alex has MORE citations than Sam despite NO T3 and NO rescue. Playbook inheritance alone is firing hardest when overseer is absent. The 59.5% fill rate (up from 0% when qwen2.5 was executor) proves cloud-exec + playbook inheritance is the floor the architecture delivers. Local gpt-oss:20b T3 outperforms cloud gpt-oss:120b T3 by 12pt fill rate on this workload — cloud overseer paying latency+variance for no measurable gain, worth flagging in next models.json tune.	2026-04-20 23:49:30 -05:00
root	b532ae61f1	Agent gateway + observer — autonomous internal operation ... Three new systemd services: - lakehouse-agent (:3700) — REST gateway wrapping all lakehouse tools. Clean JSON in/out, no protocol complexity. 9 endpoints: /search, /sql, /match, /worker/:id, /ask, /log, /playbooks, /profile/:id, /vram - lakehouse-observer — watches operations, logs to lakehouse, asks local model to diagnose failure patterns, consolidates successful patterns into playbooks every 5 cycles - Stdio MCP transport preserved for Claude Code integration AGENT_INSTRUCTIONS.md: complete operating manual for sub-agents. Rules: never hallucinate, SQL first for structured questions, hybrid for matching, log every success, check playbooks before complex tasks. Observer loop: observed() wrapper timestamps + persists every gateway call → error analyzer reads failures + asks LLM for diagnosis → playbook consolidator groups successes by endpoint pattern All three designed for zero human intervention — agents operate, observer watches, playbooks accumulate, iteration happens internally. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-17 00:00:08 -05:00