Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
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Routes Cognee AI memory platform tasks across SDK memory APIs, graph/RAG retrieval, configuration, custom pipelines, session memory, CLI, API, MCP, and deployment workflows.
中文简介正在准备中。当前显示原文说明。
安装前可以查看交给 AI 代理的指令内容。
Use this skill when the user asks about Cognee, AI memory, persistent agent memory, graph RAG, Cognee SDK/CLI/API/MCP usage, Cognee configuration, custom graph extraction, session memory, or self-hosted Cognee services.
Cognee is a Python package and service stack for ingesting data, building a graph/vector-backed memory layer, and recalling knowledge for agents.
For a safe installed-package check:
python scripts/check_install.py --help
python scripts/check_install.py --json
Minimal package install:
python -m pip install "cognee"
python - <<'PY'
import cognee
print(cognee.__version__)
print(cognee.SearchType.GRAPH_COMPLETION)
PY
Do not assume provider credentials or optional databases are configured. Most real ingestion/search workflows need an LLM and embedding provider; backend-specific workflows need matching extras and services.
| User intent | Read |
|---|---|
| Store, build, recall, improve, or delete memory with SDK calls | sub-skills/core-memory/SKILL.md |
Choose SearchType, tune recall/search, handle empty results or invalid query knobs | sub-skills/search-retrieval/SKILL.md |
| Configure LLMs, embeddings, database/storage backends, optional extras, env vars, and paths | sub-skills/configuration-backends/SKILL.md |
| Define custom graph schemas, custom tasks/pipelines, ontology workflows, memify, migration, export, or visualization | sub-skills/advanced-graphs-pipelines/SKILL.md |
| Use session memory, feedback entries, agent memory decorators, agent identities, or multi-agent isolation | sub-skills/agent-session-memory/SKILL.md |
| Operate Cognee through CLI, FastAPI, MCP, Docker Compose, UI, cloud/local service connection, or push/sync | sub-skills/api-cli-services/SKILL.md |
remember/recall for memory-shaped user requests; prefer add/cognify/search for explicit pipeline control.--help, version, or check scripts unless the user asks to start them.还没有评价。欢迎分享你的使用感受。
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Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
中文简介正在准备中。当前显示原文说明。
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
中文简介正在准备中。当前显示原文说明。
Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
中文简介正在准备中。当前显示原文说明。
Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
中文简介正在准备中。当前显示原文说明。