76 lines
2.0 KiB
Markdown
76 lines
2.0 KiB
Markdown
# AtoCore
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Personal context engine that enriches LLM interactions with durable memory, structured context, and project knowledge.
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## Quick Start
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```bash
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pip install -e .
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uvicorn src.atocore.main:app --port 8100
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```
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## Usage
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```bash
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# Ingest markdown files
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curl -X POST http://localhost:8100/ingest \
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-H "Content-Type: application/json" \
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-d '{"path": "/path/to/notes"}'
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# Build enriched context for a prompt
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curl -X POST http://localhost:8100/context/build \
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-H "Content-Type: application/json" \
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-d '{"prompt": "What is the project status?", "project": "myproject"}'
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# CLI ingestion
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python scripts/ingest_folder.py --path /path/to/notes
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```
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## API Endpoints
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| Method | Path | Description |
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|--------|------|-------------|
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| POST | /ingest | Ingest markdown file or folder |
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| POST | /query | Retrieve relevant chunks |
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| POST | /context/build | Build full context pack |
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| GET | /health | Health check |
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| GET | /debug/context | Inspect last context pack |
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## Architecture
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```text
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FastAPI (port 8100)
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|- Ingestion: markdown -> parse -> chunk -> embed -> store
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|- Retrieval: query -> embed -> vector search -> rank
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|- Context Builder: retrieve -> boost -> budget -> format
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|- SQLite (documents, chunks, memories, projects, interactions)
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'- ChromaDB (vector embeddings)
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```
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## Configuration
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Set via environment variables (prefix `ATOCORE_`):
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| Variable | Default | Description |
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|----------|---------|-------------|
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| ATOCORE_DEBUG | false | Enable debug logging |
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| ATOCORE_PORT | 8100 | Server port |
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| ATOCORE_CHUNK_MAX_SIZE | 800 | Max chunk size (chars) |
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| ATOCORE_CONTEXT_BUDGET | 3000 | Context pack budget (chars) |
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| ATOCORE_EMBEDDING_MODEL | paraphrase-multilingual-MiniLM-L12-v2 | Embedding model |
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## Testing
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```bash
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pip install -e ".[dev]"
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pytest
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```
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## Architecture Notes
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Implementation-facing architecture notes live under `docs/architecture/`.
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Current additions:
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- `docs/architecture/engineering-knowledge-hybrid-architecture.md`
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- `docs/architecture/engineering-ontology-v1.md`
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