Shangjie Chen
1d89e0ff8d
Add granular developer guide for BaseRunner and InMemoryRunner covering session lifecycle resolution, RunConfig, and event streaming under docs/guides/runners/runner/index.md, and real-time bidirectional streaming with run_live and LiveRequestQueue under docs/guides/runners/runner/live.md. Co-authored-by: Shangjie Chen <deanchen@google.com> PiperOrigin-RevId: 968085075
ADK Developer Guides
This directory contains specific developer guides for the ADK Python implementation. For the official ADK documentation, visit adk.dev.
Index
Agents
- LiveRequestQueue - Streaming content, realtime audio, and stream control signals to live agents.
- LlmAgent Single-Turn Mode - Guide on using LlmAgent in single-turn mode.
- LlmAgent Task Mode - Guide on using LlmAgent in task mode.
- ManagedAgent - Guide on using ManagedAgent with server-side tools.
- RemoteA2aAgent Task Mode - Guide on using RemoteA2aAgent in task mode.
Apps
- App - The top-level container binding a root agent to app-wide plugins and configuration.
Artifacts
- BaseArtifactService - Storing binary payloads outside the conversation history, with versioning and user-scoped filenames.
Auth
- AuthConfig and authenticated tools - Declaring the credentials a tool needs, and the pause-for-consent handshake.
Code Executors
- BaseCodeExecutor - Executing model-generated code safely across local, container, GKE, and managed sandbox backends.
Events
- Event and NodeInfo - Understanding Event and NodeInfo in workflows.
- RequestInput - How to use RequestInput for human-in-the-loop interactions.
Memory
- BaseMemoryService - Storing finished sessions and recalling them from later conversations.
Models
- BaseLlm and LLMRegistry - The model interface, how a model name resolves to an implementation, and how to plug in your own.
Planners
- BasePlanner - Guiding model execution with structured planning instructions, thinking configurations, and Plan-Re-Act thought tagging.
Plugins
- ReflectAndRetryModelPlugin - Self-healing, concurrent-safe error recovery for model failures.
- ReflectAndRetryToolPlugin - Self-healing, concurrent-safe error recovery for tool failures.
Runners
- Runner and InMemoryRunner - Managing session lifecycles, state resolution, and streaming agent execution events.
- Runner Live Streaming - Real-time bidirectional audio/text streaming and non-blocking background tool execution with Gemini Multimodal Live API.
Sessions
- Session and BaseSessionService - The session lifecycle, state scoping, and choosing a session service.
- State - Session state and the app:, user:, and temp: prefixes that decide what is shared and what is stored.
Tools
- to_mcp_server - Expose an ADK agent as an MCP server so any MCP host can drive it as a single tool (the MCP counterpart of to_a2a).
Workflows
- Workflow - Graph-based orchestration of complex, multi-step agent interactions.
- Workflow Graphs - Understanding nodes, edges, and graph structures in workflows.
- Function Nodes - Wrapping Python functions and generators as workflow nodes.
- JoinNode - Synchronizing parallel execution paths in workflows.
- RetryConfig - Configuring retry policies for resilient workflow nodes.
- ParallelWorker - Processing lists of items concurrently in workflows.
- Dynamic Nodes - Scheduling and executing nodes dynamically at runtime.