Sessions, Artifacts, and Memory

Where data lives beyond a single node: the session store, binary artifacts, and long-term memory.

State key scopes

A prefix on the key decides how far the value travels and how long it lives.

Key form	Scope
`key`	This session
`app:key`	The whole app — shared across every session and user
`user:key`	This user, across their sessions
`temp:key`	This invocation only; never persisted

A state_schema on a node validates writes, but prefixed keys bypass that validation.

Mutate, do not rebind — state['key'] = value records a delta, whereas state = {'key': value} just rebinds a local name and is lost.

python

def my_tool(tool_context: ToolContext):
  tool_context.state['user_name'] = 'Alice'
  tool_context.state['app:feature_flag'] = True

In parallel branches, two nodes writing the same key race. Give each branch its own key, or write to a shared app:-scoped key deliberately.

Session services

Service	Use for	Import
`InMemorySessionService`	local development and tests	`from google.adk.sessions import InMemorySessionService`
`DatabaseSessionService`	production on SQLite or PostgreSQL	`from google.adk.sessions import DatabaseSessionService`
`VertexAiSessionService`	Vertex AI Agent Engine	`from google.adk.sessions import VertexAiSessionService`

python

from google.adk import Runner
from google.adk.sessions import InMemorySessionService

runner = Runner(
    agent=root_agent,
    app_name='my_app',
    session_service=InMemorySessionService(),
)

DatabaseSessionService needs the db extra (pip install "google-adk[db]"). It also serializes everything you put in state and in a JoinNode's parked inputs, so a non-JSON-serializable value that works in memory fails here.

Artifacts

Artifacts hold bytes — images, files, generated documents — keyed by filename and versioned per session.

python

from google.genai import types


async def save_chart(tool_context: ToolContext):
  part = types.Part.from_bytes(data=generate_chart(), mime_type='image/png')
  version = await tool_context.save_artifact('chart.png', part)


async def get_chart(tool_context: ToolContext):
  part = await tool_context.load_artifact('chart.png')
  return part.inline_data.data

Memory

Memory is recall across sessions, as opposed to state, which is recall within one.

python

from google.adk.memory.in_memory_memory_service import InMemoryMemoryService

runner = Runner(
    agent=root_agent,
    app_name='my_app',
    session_service=InMemorySessionService(),
    memory_service=InMemoryMemoryService(),
)

Agents reach it through the load_memory and preload_memory tools, or directly with await ctx.search_memory(query).