[cursor] One-shot into pipelines plugin system - #852
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Refactor pipeline discovery to use Python entry points, enabling external pipelines to live in separate repositories and be installed as dependencies. Key changes: - Created pyproject.toml for ai-runner-base package with entry points - Refactored loader.py to discover pipelines via entry points (no hardcoded imports) - Added two entry point groups: ai_runner.pipeline and ai_runner.pipeline_params - Removed Params class attribute from Pipeline interface (params discovered via entry points) - Updated Dockerfiles to use pyproject.toml for dependency installation - Removed requirements.live-ai.txt (deps consolidated into pyproject.toml) - Updated all documentation with plugin system details - Added Docker image hierarchy documentation to AGENTS.md Benefits: - Pipelines can live in separate repos and be installed via pip/uv - No code changes needed in ai-runner when adding new pipelines - Params can be parsed without importing heavy dependencies (torch, etc.) - Works seamlessly with multiprocessing spawn context - Cleaner separation of concerns between runtime and pipeline implementations
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great inspiration, thanks claude
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even tho its good i can do much better than these agentic newbs 🙊 |
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