1a8fdf42259ae850e4986af9a3592d98a250c9ac
Two fixes from the 2026-04-09 first real restore drill on Dalidou,
plus the long-overdue doc consolidation I should have done when I
added the drill runbook instead of creating a duplicate.
## Chroma restore bind-mount bug (drill finding)
src/atocore/ops/backup.py: restore_runtime_backup() used to call
shutil.rmtree(dst_chroma) before copying the snapshot back. In the
Dockerized Dalidou deployment the chroma dir is a bind-mounted
volume — you can't unlink a mount point, rmtree raises
OSError [Errno 16] Device or resource busy
and the restore silently fails to touch Chroma. This bit the first
real drill; the operator worked around it with --no-chroma plus a
manual cp -a.
Fix: clear the destination's CONTENTS (iterdir + rmtree/unlink per
child) and use copytree(dirs_exist_ok=True) so the mount point
itself is never touched. Equivalent semantics, bind-mount-safe.
Regression test:
tests/test_backup.py::test_restore_chroma_does_not_unlink_destination_directory
captures Path.stat().st_ino of the dest dir before and after
restore and asserts they match. That's the same invariant a
bind-mounted chroma dir enforces — if the inode changed, the
mount would have failed. 11/11 backup tests now pass.
## Doc consolidation
docs/backup-restore-drill.md existed as a duplicate of the
authoritative docs/backup-restore-procedure.md. When I added the
drill runbook in commit 3362080 I wrote it from scratch instead of
updating the existing procedure — bad doc hygiene on a project
that's literally about being a context engine.
- Deleted docs/backup-restore-drill.md
- Folded its contents into docs/backup-restore-procedure.md:
- Replaced the manual sudo cp restore sequence with the new
`python -m atocore.ops.backup restore <STAMP>
--confirm-service-stopped` CLI
- Added the one-shot docker compose run pattern for running
restore inside a container that reuses the live volume mounts
- Documented the --no-pre-snapshot / --no-chroma / --chroma flags
- New "Chroma restore and bind-mounted volumes" subsection
explaining the bug and the regression test that protects the fix
- New "Restore drill" subsection with three levels (unit tests,
module round-trip, live Dalidou drill) and the cadence list
- Failure-mode table gained four entries: restored_integrity_ok,
Device-or-resource-busy, drill marker still present,
chroma_snapshot_missing
- "Open follow-ups" struck the restore_runtime_backup item (done)
and added a "Done (historical)" note referencing 2026-04-09
- Quickstart cheat sheet now has a full drill one-liner using
memory_type=episodic (the 2026-04-09 drill found the runbook's
memory_type=note was invalid — the valid set is identity,
preference, project, episodic, knowledge, adaptation)
## Status doc sync
Long overdue — I've been landing code without updating the
project's narrative state docs.
docs/current-state.md:
- "Reliability Baseline" now reflects: restore_runtime_backup is
real with CLI, pre-restore safety snapshot, WAL cleanup,
integrity check; live drill on 2026-04-09 surfaced and fixed
Chroma bind-mount bug; deploy provenance via /health build_sha;
deploy.sh self-update re-exec guard
- "Immediate Next Focus" reshuffled: drill re-run (priority 1) and
auto-capture (priority 2) are now ahead of retrieval quality work,
reflecting the updated unblock sequence
docs/next-steps.md:
- New item 1: re-run the drill with chroma working end-to-end
- New item 2: auto-capture conservative mode (Stop hook)
- Old item 7 rewritten as item 9 listing what's DONE
(create/list/validate/restore, admin/backup endpoint with
include_chroma, /health provenance, self-update guard,
procedure doc with failure modes) and what's still pending
(retention cleanup, off-Dalidou target, auto-validation)
## Test count
226 passing (was 225 + 1 new inode-stability regression test).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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.pyprovides a live API client for project refresh, project-state inspection, and retrieval-quality audits.docs/operations.mdcaptures 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 modeldocs/architecture/engineering-ontology-v1.md— V1 object and relationship inventorydocs/architecture/engineering-query-catalog.md— 20 v1-required queriesdocs/architecture/memory-vs-entities.md— canonical home splitdocs/architecture/promotion-rules.md— Layer 0 to Layer 2 pipelinedocs/architecture/conflict-model.md— contradictory facts detection and resolution
Description
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