ADK: Build Production AI Agents at Scale
Google's open-source ADK framework enables building reliable AI agents in Python, TypeScript, Go, Java with structured context management, multi-model support, evaluation tools, and seamless Google Cloud deployment.
Define Agents with Minimal Code for Immediate Use
Create functional LLM agents using a single class instantiation across languages, specifying name, model (e.g., gemini-flash-latest), instruction, and tools like google_search. In Python: from google.adk import Agent; agent = Agent(name="researcher", model="gemini-flash-latest", instruction="You help users research topics thoroughly.", tools=[google_search]). TypeScript uses LlmAgent constructor similarly; Go uses agent.New with options; Java uses LlmAgent.builder(). Install via pip install google-adk, npm install @google/adk, go get google.golang.org/adk, or Maven com.google.adk:google-adk. This approach scales from simple tool-calling agents to multi-agent systems, workflow agents (sequential, loop, parallel), and custom agents without initial complexity.
Manage Context Like Source Code for Efficiency
ADK structures context from sessions, memory, tool outputs, and artifacts, filtering irrelevant events, summarizing old turns, lazy-loading artifacts, and tracking tokens to avoid overflow and keep agents fast. Customize via caching, compression, and compaction. Sessions support rewind and migration; state and memory persist across runs. Use callbacks for event interception, artifacts for generated content, and events for observability. This prevents the common pitfall of concatenating strings until failure, ensuring reliability in long-running tasks.
Evaluate, Deploy, and Integrate for Production
Test agents with visual debugging, user/environment simulation, custom metrics, and optimization loops. Deploy via containerization anywhere or one-command to Google Cloud's Agent Engine (inherits auth, tracing, security), Cloud Run, or GKE without code changes. Run via web UI, CLI, API server, or resume interrupted sessions. Supports models like Gemini, Gemma, Claude, Vertex AI, Ollama, vLLM, LiteLLM; tools including function, MCP, OpenAPI; integrations for apps, plugins, grounding (Google/Vertex Search), and A2A protocol for agent-to-agent communication. Build multi-agent teams, graph-based workflows (routes, data handling, human input), and streaming with Gemini Live API Toolkit handling audio/images/video.