Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
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Route AutoGPT Platform self-hosting, backend, frontend, and legacy Classic agent work to focused operating guidance.
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설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Use this skill for the AutoGPT monorepo. Start by deciding whether the task is for the current AutoGPT Platform or the unsupported Classic suite. Platform is the maintained self-hosted product; Classic is retained for educational and historical use and has known dependency/security limitations.
| If the task involves | Read next |
|---|---|
Docker Compose, .env setup, local services, self-host upgrade, ports, or local LLM configuration | platform-stack |
| FastAPI routes, graph execution, blocks, integrations, Prisma, model catalog, backend CLI, or Python tests | platform-backend |
| Next.js pages, Builder/Copilot/Library/Marketplace UI, generated API hooks, Tailwind/design system, or frontend tests | platform-frontend |
autogpt/serve CLI, Forge, workspace permissions, or direct-benchmark | classic-agents |
For a backend endpoint plus a UI consumer, begin with platform-backend, then
use platform-frontend for the generated hook and screen work. For local
end-to-end validation, also read platform-stack before starting services.
autogpt, forge, and
direct_benchmark. Treat it as unsupported and avoid presenting it as the
recommended path for new production work.Read repository map for package boundaries and common change locations. Read contributor guidance when a task will modify code or documentation. Read cross-cutting troubleshooting for setup, secrets, service, and version failures.
Use the package-specific sub-skills for complete setup. Minimal public commands are:
cd autogpt_platform && make init-env && make start-core
cd autogpt_platform/backend && poetry install
cd autogpt_platform/frontend && corepack enable && pnpm install
cd classic && poetry install
Run only the commands needed for the chosen surface. Do not combine Platform backend and Classic dependencies into one Python environment unless a task explicitly asks for that experiment.
Run python scripts/autogpt_repo_probe.py --repo <checkout> to identify the
major AutoGPT surfaces and missing host tools without starting services or
editing the checkout. Use --json when another tool needs structured output.
This operating graph describes the checked source revision recorded in repo provenance. It does not provide secrets, managed-cloud access, external provider credentials, model downloads, or a promise that Classic dependencies are safe or maintained.
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Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
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Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
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Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
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Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.
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Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
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