giles
1a74d811f7
Merges full history from art-dag/mono.git into the monorepo under the artdag/ directory. Contains: core (DAG engine), l1 (Celery rendering server), l2 (ActivityPub registry), common (shared templates/middleware), client (CLI), test (e2e). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> git-subtree-dir: artdag git-subtree-mainline:1a179de547git-subtree-split:4c2e716558
75 lines
2.8 KiB
Markdown
75 lines
2.8 KiB
Markdown
# Art DAG Monorepo
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Federated content-addressed DAG execution engine for distributed media processing with ActivityPub ownership and provenance tracking.
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## Project Structure
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```
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core/ # DAG engine (artdag package) - nodes, effects, analysis, planning
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l1/ # L1 Celery rendering server (FastAPI + Celery + Redis + PostgreSQL)
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l2/ # L2 ActivityPub registry (FastAPI + PostgreSQL)
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common/ # Shared templates, middleware, models (artdag_common package)
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client/ # CLI client
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test/ # Integration & e2e tests
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```
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## Tech Stack
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Python 3.11+, FastAPI, Celery, Redis, PostgreSQL (asyncpg for L1), SQLAlchemy, Pydantic, JAX (CPU/GPU), IPFS/Kubo, Docker Swarm, HTMX + Jinja2 for web UI.
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## Key Commands
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### Testing
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```bash
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cd l1 && pytest tests/ # L1 unit tests
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cd core && pytest tests/ # Core unit tests
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cd test && python run.py # Full integration pipeline
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```
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- pytest uses `asyncio_mode = "auto"` for async tests
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- Test files: `test_*.py`, fixtures in `conftest.py`
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### Linting & Type Checking (L1)
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```bash
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cd l1 && ruff check . # Lint (E, F, I, UP rules)
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cd l1 && mypy app/types.py app/routers/recipes.py tests/
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```
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- Line length: 100 chars (E501 ignored)
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- Mypy: strict on `app/types.py`, `app/routers/recipes.py`, `tests/`; gradual elsewhere
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- Mypy ignores imports for: celery, redis, artdag, artdag_common, ipfs_client
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### Docker
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```bash
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docker build -f l1/Dockerfile -t celery-l1-server:latest .
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docker build -f l1/Dockerfile.gpu -t celery-l1-gpu:latest .
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docker build -f l2/Dockerfile -t l2-server:latest .
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./deploy.sh # Build, push, deploy stacks
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```
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## Architecture Patterns
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- **3-Phase Execution**: Analyze -> Plan -> Execute (tasks in `l1/tasks/`)
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- **Content-Addressed**: All data identified by SHA3-256 hashes or IPFS CIDs
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- **Services Pattern**: Business logic in `app/services/`, API endpoints in `app/routers/`
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- **Types Module**: Pydantic models and TypedDicts in `app/types.py`
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- **Celery Tasks**: In `l1/tasks/`, decorated with `@app.task`
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- **S-Expression Effects**: Composable effect language in `l1/sexp_effects/`
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- **Storage**: Local filesystem, S3, or IPFS backends (`storage_providers.py`)
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## Auth
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- L1 <-> L2: scoped JWT tokens (no shared secrets)
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- L2: password + OAuth SSO, token revocation in Redis (30-day expiry)
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- Federation: ActivityPub RSA signatures (`core/artdag/activitypub/`)
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## Key Config Files
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- `l1/pyproject.toml` - mypy, pytest, ruff config for L1
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- `l1/celery_app.py` - Celery initialization
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- `l1/database.py` / `l2/db.py` - SQLAlchemy models
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- `l1/docker-compose.yml` / `l2/docker-compose.yml` - Swarm stacks
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## Tools
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- Use Context7 MCP for up-to-date library documentation
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- Playwright MCP is available for browser automation/testing
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