11 Commits

Author SHA1 Message Date
root
86123fce4c gateway: /v1/validate endpoint — Phase 43 v3 part 2
Closes the Phase 43 PRD's "any caller can validate" surface. The
validator crate (FillValidator + EmailValidator + PlaybookValidator
+ WorkerLookup) is now reachable over HTTP at /v1/validate.

Request/response:
  POST /v1/validate
    {"kind":"fill"|"email"|"playbook", "artifact":{...}, "context":{...}?}
  → 200 + Report on success
  → 422 + ValidationError on validation failure
  → 400 on bad kind

Boot-time wiring (main.rs):
- Load workers_500k.parquet into a shared Arc<dyn WorkerLookup>
- Path overridable via LH_WORKERS_PARQUET env
- Missing file: warn + fall back to empty InMemoryWorkerLookup so the
  endpoint stays live (validators just fail Consistency on every
  worker-existence check, which is the correct behavior when the
  roster isn't configured)
- Boot log line: "workers parquet loaded from <path>" or
  "workers parquet at <path> not found"
- Live boot timing: 500K rows loaded in ~1.4s

V1State gains `validate_workers: Arc<dyn validator::WorkerLookup>`.
The `_context` JSON key is auto-injected from `request.context` so
callers can either embed `_context` directly in `artifact` or split
it cleanly via the `context` field.

Verified live (gateway + 500K worker snapshot):
  POST {kind:"fill", phantom W-FAKE-99999}    → 422 Consistency
                                                 ("does not exist in
                                                  worker roster")
  POST {kind:"fill", real W-1, "Anyone"}      → 200 OK + Warning
                                                 ("differs from
                                                  roster name 'Donald
                                                  Green'")
  POST {kind:"email", body has 123-45-6789}   → 422 Policy ("SSN-
                                                shaped sequence")
  POST {kind:"nonsense"}                       → 400 Bad Request

The "0→85% with iteration" thesis can now run end-to-end on real
staffing data: an executor emits a fill_proposal, posts to
/v1/validate, gets a structured ValidationError on phantom IDs or
inactive workers, observer-corrects, retries. Closure of that loop
in a scrum harness is the next commit (separate scope).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-27 07:40:27 -05:00
root
d277efbfd2 v1/mode: task_class → mode/model router (decision-only, phase 1)
Some checks failed
lakehouse/auditor 1 blocking issue: todo!() macro call in tests/real-world/scrum_master_pipeline.ts
HANDOVER §queued (2026-04-25): "Mode router — port LLM Team multi-model
patterns. Pick the right TOOL/MODE for each task class via the matrix,
not cascade through models."

Two-stage architecture:
  1. Decision (POST /v1/mode) — pure recommendation, no execution.
     Returns {mode, model, decision: {source, fallbacks, matrix_corpus,
     notes}} so callers see WHY this mode was picked.
  2. Execution (future POST /v1/mode/execute) — proxy to LLM Team
     /api/run for modes not yet ported to native Rust runners. Not
     wired in this phase.

Splitting decision from execution lets us A/B-test the routing logic
without committing to running every recommendation. The decision
function is pure enough for exhaustive unit tests (3 added).

config/modes.toml — initial map for 5 task_classes (scrum_review,
contract_analysis, staffing_inference, fact_extract, doc_drift_check)
+ a default. matrix_corpus per task is reserved for the future
matrix-informed routing pass.

VALID_MODES list (24 modes) is kept in sync manually with LLM Team's
/api/run handler at /root/llm_team_ui.py:10581. Adding a mode here
without adding it upstream returns 400 from a future proxy.

GET /v1/mode/list — operator introspection so a UI can render the
registry table without re-parsing TOML.

Live-tested: 5 task classes match, unknown classes fall through to
default, force_mode override works + validates, bogus modes return
400 with the valid_modes list.

Updates reference_llm_team_modes.md memory — earlier note claiming
"only extract is registered" was wrong (all 25 are registered).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-26 00:16:32 -05:00
root
21fd3b9c61 Scrum-driven fixes: P5-001 auth wired, P42-001 truth evaluator, P9-001 journal on ingest
Some checks failed
lakehouse/auditor 2 blocking issues: cloud: claim not backed — "| **P9-001** (partial) | `crates/ingestd/src/service.rs` | **3 → 6** ↑↑↑ | `journal.record_ing
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
profit
42a11d35cd Phase 39 (first slice): Ollama Cloud adapter on /v1/chat
Second provider wired. /v1/chat now routes by optional `provider`
field: default "ollama" hits local via sidecar, "ollama_cloud"
(or "cloud") hits ollama.com/api/generate directly with Bearer auth.
Key sourced at gateway startup from OLLAMA_CLOUD_KEY env, then
/root/llm_team_config.json (providers.ollama_cloud.api_key), then
OLLAMA_CLOUD_API_KEY env. Config source matches LLM Team convention.

Shape-identical to scenario.ts::generateCloud — same endpoint, same
body, same Bearer auth. Cloud path bypasses sidecar entirely (sidecar
is local-only by design, mirrors TS agent.ts).

Changes:
- crates/gateway/src/v1/ollama_cloud.rs (new, 130 LOC) — reqwest
  client, resolve_cloud_key(), chat() adapter, CloudGenerateBody /
  CloudGenerateResponse wire shapes
- crates/gateway/src/v1/ollama.rs — flatten_messages_public()
  re-export so sibling adapters reuse the shape collapse
- crates/gateway/src/v1/mod.rs — provider field on ChatRequest,
  dispatch match in chat() handler, ollama_cloud_key on V1State
- crates/gateway/src/main.rs — resolves cloud key at startup,
  logs which source provided it
- crates/gateway/Cargo.toml — reqwest 0.12 with rustls-tls

Verified end-to-end after restart:
- provider=ollama → qwen3.5:latest local (~400ms, Phase 38 unchanged)
- provider=ollama_cloud + model=gpt-oss:120b → real 225-word
  technical response in 5.4s, 313 tokens

Tests: 9/9 green (7 from Phase 38 + 2 new for cloud body serialization
and key resolver shape).

Not in this slice: trait extraction (full Phase 39 scope adds
ProviderAdapter trait + OpenRouter adapter + fallback chain logic).
These land next with Phase 40 routing engine on top.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-22 02:57:42 -05:00
root
6f0f92a9e4 Phase 12: Tool registry — governed business actions for AI agents
- ToolRegistry: named tools with parameter validation and audit logging
- 6 built-in staffing tools:
  search_candidates (skills, city, state, experience, availability)
  get_candidate (by ID)
  revenue_by_client (top N by billed revenue)
  recruiter_performance (placements, revenue per recruiter)
  cold_leads (called N+ times, never placed)
  open_jobs (by vertical, city)
- Each tool: name, description, params, permission level (read/write/admin)
- SQL template with validated parameter substitution
- Full audit trail: every invocation logged with agent, params, result
- Endpoints: GET /tools (list), GET /tools/{name} (schema),
  POST /tools/{name}/call (execute), GET /tools/audit (log)
- Per ADR-015: governed interface before raw SQL for agents

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 09:31:42 -05:00
root
bf7cf96911 Phase 9: Event journal — append-only mutation history
- journald crate: immutable event log for every data mutation
- Events: entity_type, entity_id, field, action, old_value, new_value,
  actor, source, workspace_id, timestamp
- In-memory buffer with configurable flush threshold (default 100 events)
- Flush writes events as Parquet to journal/ directory
- Query: GET /journal/history/{entity_id} — full history of any record
- Query: GET /journal/recent?limit=50 — latest events across all entities
- Convenience methods: record_insert, record_update, record_ingest
- Stats: GET /journal/stats — buffer size, persisted file count
- Manual flush: POST /journal/flush
- Per ADR-012: events are never modified or deleted

This is the single most important future-proofing decision.
Once history is lost, it's gone forever.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 09:09:33 -05:00
root
26fc98c885 Phase 7: Vector index + RAG pipeline
- vectord crate: chunk → embed → store → search → RAG
- chunker: configurable chunk size + overlap, sentence-boundary aware splitting
- store: embeddings as Parquet (binary blob f32 vectors), portable format
- search: brute-force cosine similarity (works up to ~100K vectors)
- rag: full pipeline — embed question → search index → retrieve context → LLM answer
- Endpoints: POST /vectors/index, /vectors/search, /vectors/rag
- Gateway wired with vectord service
- Tested: 200 candidate resumes indexed in 5.4s, semantic search + RAG working
- 20 unit tests passing (chunker, search, ingestd, shared)
- AI gives honest "no match found" when context doesn't support an answer

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 08:12:28 -05:00
root
bb05c4412e Phase 6: Ingest pipeline — CSV, JSON, PDF, text file support
- ingestd crate: detect file type → parse → schema detection → Parquet → catalog
- CSV: auto-detect column types (int, float, bool, string), handles $, %, commas
  Strips dollar signs from amounts, flexible row parsing, sanitized column names
- JSON: array or newline-delimited, nested object flattening (a.b.c → a_b_c)
- PDF: text extraction via lopdf, one row per page (source_file, page_number, text)
- Text/SMS: line-based ingestion with line numbers
- Dedup: SHA-256 content hash, re-ingest same file = no-op
- Gateway: POST /ingest/file multipart upload, 256MB body limit
- Schema detection per ADR-010: ambiguous types default to String
- 12 unit tests passing (CSV parsing, JSON flattening, type inference, dedup)
- Tested: messy CSV with missing data, dollar amounts, N/A values → queryable

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 08:07:31 -05:00
root
01373c0e45 Phase 5: hardening — gRPC, observability, auth, config
- proto: lakehouse.proto with CatalogService, QueryService, StorageService, AiService
- proto crate: tonic-build codegen from proto definitions
- catalogd: gRPC CatalogService implementation
- gateway: dual HTTP (:3100) + gRPC (:3101) servers
- gateway: OpenTelemetry tracing with stdout exporter
- gateway: API key auth middleware (toggleable)
- shared: TOML config system with typed structs and defaults
- lakehouse.toml config file
- ADR-006 and ADR-007 documented

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 06:37:07 -05:00
root
655b6c0b37 Phase 1: storage + catalog layer
- storaged: object_store backend (LocalFileSystem), PUT/GET/DELETE/LIST endpoints
- shared: arrow_helpers with Parquet roundtrip + schema fingerprinting (2 tests)
- catalogd: in-memory registry with write-ahead manifest persistence to object storage
- catalogd: POST/GET /datasets, GET /datasets/by-name/{name}
- gateway: wires storaged + catalogd with shared object_store state
- Phase tracker updated: Phase 0 + Phase 1 gates passed

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 05:15:27 -05:00
root
a52ca841c6 Phase 0: bootstrap Rust workspace
- Cargo workspace with 6 crates: shared, storaged, catalogd, queryd, aibridge, gateway
- shared: types (DatasetId, ObjectRef, SchemaFingerprint, DatasetManifest) + error enum
- gateway: Axum HTTP entrypoint with nested service routers + tracing
- All services expose /health stubs
- justfile with build/test/run recipes
- PRD, phase tracker, and ADR docs

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 04:59:05 -05:00