Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
日本語の概要は準備中です。原文の説明を表示しています。
Use Google ADK Python to build agents, Workflow graphs, tools, runtime services, CLI apps, evaluations, deployments, and ADK repository changes.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Use this repo skill when a task involves Google Agent Development Kit for Python (google-adk / google.adk), ADK 2.0 Agent and Workflow APIs, ADK CLI commands, tool integrations, runtime services, evaluation/debugging, or modifying the ADK Python repository itself.
pip install google-adk on Python 3.10+.all by default, such as google-adk[db], google-adk[mcp], google-adk[eval], google-adk[gcp], or google-adk[extensions].python -c "import google.adk; print(google.adk.__version__)" and adk --help.Agent/LlmAgent, instructions, model settings, callbacks, schemas, task/single-turn modes, sub-agents, and multi-agent delegation.Workflow, BaseNode, function nodes, graph edges, JoinNode, dynamic nodes, parallel worker, HITL, retry, checkpoint/resume, and event flow.FunctionTool, ToolContext, toolsets, confirmation/long-running tools, auth, MCP, OpenAPI, Google API/cloud integrations, A2A, and optional extras.Runner, App, sessions, memory, artifacts, plugins, telemetry, code executors, environments, event persistence, and service lifecycles.adk run, adk web, adk api_server, adk test, adk eval, adk deploy, app discovery, YAML config, service URIs, and safe CLI/schema inspection.adk test, adk eval, event summaries, traces, session inspection, flaky evals, and assertion design.repo-skills-router during import.--help, and dry-run diagnostics before starting servers, deployments, cloud calls, model-backed evals, or database migrations.google-adk; diagnose missing modules and install only what the selected workflow requires.Create a simple agent:
from google.adk import Agent
root_agent = Agent(
name="greeter",
model="gemini-2.5-flash",
instruction="Greet the user and answer briefly.",
)
Create a simple workflow:
from google.adk import Workflow
root_agent = Workflow(
name="fruit_flow",
edges=[("START", pick_fruit, explain_benefit)],
)
Run local checks:
python scripts/check_adk_install.py --json
adk --help
adk run path/to/my_agent --help
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
日本語の概要は準備中です。原文の説明を表示しています。
Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
日本語の概要は準備中です。原文の説明を表示しています。
Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
日本語の概要は準備中です。原文の説明を表示しています。