Anto01
90001c1956
Broke the dedup-watcher cron when I wrote memory_dedup.py in session
7A: imported atocore.memory.similarity, which transitively pulls
sentence-transformers + pydantic_settings onto host Python that
intentionally doesn't have them. Every UI-triggered + cron dedup scan
since 7A deployed was silently crashing with ModuleNotFoundError
(visible only in /home/papa/atocore-logs/dedup-ondemand-*.log).
I even documented this architecture rule in atocore.memory._llm_prompt
('This module MUST stay stdlib-only') then violated it one session
later. Shame.
Real fix — matches the extractor pattern:
- New endpoint POST /admin/memory/dedup-cluster on the server: takes
{project, similarity_threshold, max_clusters}, runs the embedding +
transitive-clustering inside the container where
sentence-transformers lives, returns cluster shape.
- scripts/memory_dedup.py now pure stdlib: pulls clusters via HTTP,
LLM-drafts merges via claude CLI, POSTs proposals back. No atocore
imports beyond the stdlib-only _dedup_prompt shared module.
- Regression test pins the rule: test_memory_dedup_script_is_stdlib_only
snapshots sys.modules before/after importing the script and asserts
no non-allowed atocore modules were pulled.
Also: similarity.py + cluster_by_threshold stay server-side, still
covered by the same tests that used to live in the host tier-helper
section.
Tests 459 → 458 (-1 via rewrite of obsolete host-tier helper tests,
+2 for the new stdlib-only regression + endpoint shape tests).
Co-Authored-By: Claude Opus 4.7 (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