Anto01 88f2f7c4e1 feat: Phase 4 V1 — Robustness Hardening
Adds the observability + safety layer that turns AtoCore from
"works until something silently breaks" into "every mutation is
traceable, drift is detected, failures raise alerts."

1. Audit log (memory_audit table):
   - New table with id, memory_id, action, actor, before/after JSON,
     note, timestamp; 3 indexes for memory_id/timestamp/action
   - _audit_memory() helper called from every mutation:
     create_memory, update_memory, promote_memory,
     reject_candidate_memory, invalidate_memory, supersede_memory,
     reinforce_memory, auto_promote_reinforced, expire_stale_candidates
   - Action verb auto-selected: promoted/rejected/invalidated/
     superseded/updated based on state transition
   - "actor" threaded through: api-http, human-triage, phase10-auto-
     promote, candidate-expiry, reinforcement, etc.
   - Fail-open: audit write failure logs but never breaks the mutation
   - GET /memory/{id}/audit: full history for one memory
   - GET /admin/audit/recent: last 50 mutations across the system

2. Alerts framework (src/atocore/observability/alerts.py):
   - emit_alert(severity, title, message, context) fans out to:
     - structlog logger (always)
     - ~/atocore-logs/alerts.log append (configurable via
       ATOCORE_ALERT_LOG)
     - project_state atocore/alert/last_{severity} (dashboard surface)
     - ATOCORE_ALERT_WEBHOOK POST if set (auto-detects Discord webhook
       format for nice embeds; generic JSON otherwise)
   - Every sink fail-open — one failure doesn't prevent the others
   - Pipeline alert step in nightly cron: harness < 85% → warning;
     candidate queue > 200 → warning

3. Integrity checks (scripts/integrity_check.py):
   - Nightly scan for drift:
     - Memories → missing source_chunk_id references
     - Duplicate active memories (same type+content+project)
     - project_state → missing projects
     - Orphaned source_chunks (no parent document)
   - Results persisted to atocore/status/integrity_check_result
   - Any finding emits a warning alert
   - Added as Step G in deploy/dalidou/batch-extract.sh nightly cron

4. Dashboard surfaces it all:
   - integrity (findings + details)
   - alerts (last info/warning/critical per severity)
   - recent_audit (last 10 mutations with actor + action + preview)

Tests: 308 → 317 (9 new):
  - test_audit_create_logs_entry
  - test_audit_promote_logs_entry
  - test_audit_reject_logs_entry
  - test_audit_update_captures_before_after
  - test_audit_reinforce_logs_entry
  - test_recent_audit_returns_cross_memory_entries
  - test_emit_alert_writes_log_file
  - test_emit_alert_invalid_severity_falls_back_to_info
  - test_emit_alert_fails_open_on_log_write_error

Deferred: formal migration framework with rollback (current additive
pattern is fine for V1); memory detail wiki page with audit view
(quick follow-up).

To enable Discord alerts: set ATOCORE_ALERT_WEBHOOK to a Discord
webhook URL in Dalidou's environment. Default = log-only.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-16 21:54:10 -04:00

AtoCore

Personal context engine that enriches LLM interactions with durable memory, structured context, and project knowledge.

Quick Start

pip install -e .
uvicorn src.atocore.main:app --port 8100

Usage

# Ingest markdown files
curl -X POST http://localhost:8100/ingest \
  -H "Content-Type: application/json" \
  -d '{"path": "/path/to/notes"}'

# Build enriched context for a prompt
curl -X POST http://localhost:8100/context/build \
  -H "Content-Type: application/json" \
  -d '{"prompt": "What is the project status?", "project": "myproject"}'

# CLI ingestion
python scripts/ingest_folder.py --path /path/to/notes

# Live operator client
python scripts/atocore_client.py health
python scripts/atocore_client.py audit-query "gigabit" 5

API Endpoints

Method Path Description
POST /ingest Ingest markdown file or folder
POST /query Retrieve relevant chunks
POST /context/build Build full context pack
GET /health Health check
GET /debug/context Inspect last context pack

Architecture

FastAPI (port 8100)
  |- Ingestion: markdown -> parse -> chunk -> embed -> store
  |- Retrieval: query -> embed -> vector search -> rank
  |- Context Builder: retrieve -> boost -> budget -> format
  |- SQLite (documents, chunks, memories, projects, interactions)
  '- ChromaDB (vector embeddings)

Configuration

Set via environment variables (prefix ATOCORE_):

Variable Default Description
ATOCORE_DEBUG false Enable debug logging
ATOCORE_PORT 8100 Server port
ATOCORE_CHUNK_MAX_SIZE 800 Max chunk size (chars)
ATOCORE_CONTEXT_BUDGET 3000 Context pack budget (chars)
ATOCORE_EMBEDDING_MODEL paraphrase-multilingual-MiniLM-L12-v2 Embedding model

Testing

pip install -e ".[dev]"
pytest

Operations

  • scripts/atocore_client.py provides a live API client for project refresh, project-state inspection, and retrieval-quality audits.
  • docs/operations.md captures the current operational priority order: retrieval quality, Wave 2 trusted-operational ingestion, AtoDrive scoping, and restore validation.

Architecture Notes

Implementation-facing architecture notes live under docs/architecture/.

Current additions:

  • docs/architecture/engineering-knowledge-hybrid-architecture.md — 5-layer hybrid model
  • docs/architecture/engineering-ontology-v1.md — V1 object and relationship inventory
  • docs/architecture/engineering-query-catalog.md — 20 v1-required queries
  • docs/architecture/memory-vs-entities.md — canonical home split
  • docs/architecture/promotion-rules.md — Layer 0 to Layer 2 pipeline
  • docs/architecture/conflict-model.md — contradictory facts detection and resolution
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