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https://github.com/EvolutionAPI/adk-python.git
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Agent Development Kit(ADK)
An easy-to-use and powerful framework to build AI agents.
This commit is contained in:
456
src/google/adk/runners.py
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456
src/google/adk/runners.py
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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import annotations
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import asyncio
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import logging
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import queue
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import threading
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from typing import AsyncGenerator
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from typing import Generator
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from typing import Optional
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from deprecated import deprecated
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from google.genai import types
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from .agents.active_streaming_tool import ActiveStreamingTool
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from .agents.base_agent import BaseAgent
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from .agents.invocation_context import InvocationContext
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from .agents.invocation_context import new_invocation_context_id
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from .agents.live_request_queue import LiveRequestQueue
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from .agents.llm_agent import LlmAgent
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from .agents.run_config import RunConfig
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from .agents.run_config import StreamingMode
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from .artifacts.base_artifact_service import BaseArtifactService
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from .artifacts.in_memory_artifact_service import InMemoryArtifactService
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from .events.event import Event
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from .memory.base_memory_service import BaseMemoryService
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from .memory.in_memory_memory_service import InMemoryMemoryService
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from .sessions.base_session_service import BaseSessionService
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from .sessions.in_memory_session_service import InMemorySessionService
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from .sessions.session import Session
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from .telemetry import tracer
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from .tools.built_in_code_execution_tool import built_in_code_execution
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logger = logging.getLogger(__name__)
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class Runner:
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"""The Runner class is used to run agents.
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It manages the execution of an agent within a session, handling message
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processing, event generation, and interaction with various services like
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artifact storage, session management, and memory.
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Attributes:
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app_name: The application name of the runner.
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agent: The root agent to run.
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artifact_service: The artifact service for the runner.
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session_service: The session service for the runner.
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memory_service: The memory service for the runner.
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"""
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app_name: str
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"""The app name of the runner."""
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agent: BaseAgent
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"""The root agent to run."""
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artifact_service: Optional[BaseArtifactService] = None
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"""The artifact service for the runner."""
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session_service: BaseSessionService
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"""The session service for the runner."""
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memory_service: Optional[BaseMemoryService] = None
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"""The memory service for the runner."""
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def __init__(
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self,
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*,
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app_name: str,
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agent: BaseAgent,
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artifact_service: Optional[BaseArtifactService] = None,
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session_service: BaseSessionService,
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memory_service: Optional[BaseMemoryService] = None,
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):
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"""Initializes the Runner.
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Args:
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app_name: The application name of the runner.
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agent: The root agent to run.
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artifact_service: The artifact service for the runner.
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session_service: The session service for the runner.
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memory_service: The memory service for the runner.
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"""
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self.app_name = app_name
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self.agent = agent
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self.artifact_service = artifact_service
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self.session_service = session_service
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self.memory_service = memory_service
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def run(
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self,
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*,
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user_id: str,
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session_id: str,
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new_message: types.Content,
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run_config: RunConfig = RunConfig(),
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) -> Generator[Event, None, None]:
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"""Runs the agent.
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NOTE: This sync interface is only for local testing and convenience purpose.
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Consider to use `run_async` for production usage.
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Args:
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user_id: The user ID of the session.
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session_id: The session ID of the session.
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new_message: A new message to append to the session.
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run_config: The run config for the agent.
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Yields:
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The events generated by the agent.
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"""
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event_queue = queue.Queue()
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async def _invoke_run_async():
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try:
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async for event in self.run_async(
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user_id=user_id,
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session_id=session_id,
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new_message=new_message,
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run_config=run_config,
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):
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event_queue.put(event)
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finally:
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event_queue.put(None)
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def _asyncio_thread_main():
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try:
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asyncio.run(_invoke_run_async())
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finally:
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event_queue.put(None)
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thread = threading.Thread(target=_asyncio_thread_main)
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thread.start()
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# consumes and re-yield the events from background thread.
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while True:
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event = event_queue.get()
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if event is None:
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break
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else:
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yield event
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thread.join()
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async def run_async(
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self,
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*,
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user_id: str,
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session_id: str,
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new_message: types.Content,
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run_config: RunConfig = RunConfig(),
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) -> AsyncGenerator[Event, None]:
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"""Main entry method to run the agent in this runner.
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Args:
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user_id: The user ID of the session.
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session_id: The session ID of the session.
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new_message: A new message to append to the session.
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run_config: The run config for the agent.
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Yields:
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The events generated by the agent.
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"""
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with tracer.start_as_current_span('invocation'):
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session = self.session_service.get_session(
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app_name=self.app_name, user_id=user_id, session_id=session_id
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)
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if not session:
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raise ValueError(f'Session not found: {session_id}')
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invocation_context = self._new_invocation_context(
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session,
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new_message=new_message,
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run_config=run_config,
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)
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root_agent = self.agent
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if new_message:
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self._append_new_message_to_session(
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session,
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new_message,
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invocation_context,
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run_config.save_input_blobs_as_artifacts,
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)
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invocation_context.agent = self._find_agent_to_run(session, root_agent)
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async for event in invocation_context.agent.run_async(invocation_context):
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if not event.partial:
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self.session_service.append_event(session=session, event=event)
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yield event
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def _append_new_message_to_session(
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self,
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session: Session,
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new_message: types.Content,
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invocation_context: InvocationContext,
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save_input_blobs_as_artifacts: bool = False,
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):
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"""Appends a new message to the session.
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Args:
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session: The session to append the message to.
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new_message: The new message to append.
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invocation_context: The invocation context for the message.
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save_input_blobs_as_artifacts: Whether to save input blobs as artifacts.
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"""
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if not new_message.parts:
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raise ValueError('No parts in the new_message.')
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if self.artifact_service and save_input_blobs_as_artifacts:
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# The runner directly saves the artifacts (if applicable) in the
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# user message and replaces the artifact data with a file name
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# placeholder.
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for i, part in enumerate(new_message.parts):
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if part.inline_data is None:
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continue
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file_name = f'artifact_{invocation_context.invocation_id}_{i}'
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self.artifact_service.save_artifact(
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app_name=self.app_name,
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user_id=session.user_id,
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session_id=session.id,
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filename=file_name,
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artifact=part,
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)
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new_message.parts[i] = types.Part(
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text=f'Uploaded file: {file_name}. It is saved into artifacts'
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)
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# Appends only. We do not yield the event because it's not from the model.
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event = Event(
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invocation_id=invocation_context.invocation_id,
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author='user',
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content=new_message,
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)
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self.session_service.append_event(session=session, event=event)
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async def run_live(
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self,
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*,
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session: Session,
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live_request_queue: LiveRequestQueue,
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run_config: RunConfig = RunConfig(),
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) -> AsyncGenerator[Event, None]:
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"""Runs the agent in live mode (experimental feature).
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Args:
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session: The session to use.
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live_request_queue: The queue for live requests.
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run_config: The run config for the agent.
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Yields:
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The events generated by the agent.
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"""
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# TODO: right now, only works for a single audio agent without FC.
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invocation_context = self._new_invocation_context_for_live(
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session,
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live_request_queue=live_request_queue,
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run_config=run_config,
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)
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root_agent = self.agent
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invocation_context.agent = self._find_agent_to_run(session, root_agent)
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invocation_context.active_streaming_tools = {}
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# TODO(hangfei): switch to use canonical_tools.
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for tool in invocation_context.agent.tools:
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# replicate a LiveRequestQueue for streaming tools that relis on
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# LiveRequestQueue
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from typing import get_type_hints
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type_hints = get_type_hints(tool)
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for arg_type in type_hints.values():
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if arg_type is LiveRequestQueue:
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if not invocation_context.active_streaming_tools:
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invocation_context.active_streaming_tools = {}
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active_streaming_tools = ActiveStreamingTool(
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stream=LiveRequestQueue()
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)
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invocation_context.active_streaming_tools[tool.__name__] = (
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active_streaming_tools
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)
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async for event in invocation_context.agent.run_live(invocation_context):
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self.session_service.append_event(session=session, event=event)
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yield event
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def close_session(self, session: Session):
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"""Closes a session and adds it to the memory service (experimental feature).
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Args:
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session: The session to close.
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"""
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if self.memory_service:
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self.memory_service.add_session_to_memory(session)
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self.session_service.close_session(session=session)
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def _find_agent_to_run(
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self, session: Session, root_agent: BaseAgent
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) -> BaseAgent:
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"""Finds the agent to run to continue the session.
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A qualified agent must be either of:
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- The root agent;
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- An LlmAgent who replied last and is capable to transfer to any other agent
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in the agent hierarchy.
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Args:
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session: The session to find the agent for.
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root_agent: The root agent of the runner.
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Returns:
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The agent of the last message in the session or the root agent.
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"""
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for event in filter(lambda e: e.author != 'user', reversed(session.events)):
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if event.author == root_agent.name:
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# Found root agent.
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return root_agent
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if not (agent := root_agent.find_sub_agent(event.author)):
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# Agent not found, continue looking.
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logger.warning(
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'Event from an unknown agent: %s, event id: %s',
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event.author,
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event.id,
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)
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continue
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if self._is_transferable_across_agent_tree(agent):
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return agent
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# Falls back to root agent if no suitable agents are found in the session.
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return root_agent
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def _is_transferable_across_agent_tree(self, agent_to_run: BaseAgent) -> bool:
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"""Whether the agent to run can transfer to any other agent in the agent tree.
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This typically means all agent_to_run's parent through root agent can
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transfer to their parent_agent.
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Args:
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agent_to_run: The agent to check for transferability.
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Returns:
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True if the agent can transfer, False otherwise.
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"""
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agent = agent_to_run
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while agent:
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if not isinstance(agent, LlmAgent):
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# Only LLM-based Agent can provider agent transfer capability.
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return False
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if agent.disallow_transfer_to_parent:
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return False
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agent = agent.parent_agent
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return True
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def _new_invocation_context(
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self,
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session: Session,
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*,
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new_message: Optional[types.Content] = None,
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live_request_queue: Optional[LiveRequestQueue] = None,
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run_config: RunConfig = RunConfig(),
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) -> InvocationContext:
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"""Creates a new invocation context.
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Args:
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session: The session for the context.
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new_message: The new message for the context.
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live_request_queue: The live request queue for the context.
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run_config: The run config for the context.
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Returns:
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The new invocation context.
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"""
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invocation_id = new_invocation_context_id()
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if run_config.support_cfc and isinstance(self.agent, LlmAgent):
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model_name = self.agent.canonical_model.model
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if not model_name.startswith('gemini-2'):
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raise ValueError(
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f'CFC is not supported for model: {model_name} in agent:'
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f' {self.agent.name}'
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)
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if built_in_code_execution not in self.agent.canonical_tools:
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self.agent.tools.append(built_in_code_execution)
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return InvocationContext(
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artifact_service=self.artifact_service,
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session_service=self.session_service,
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memory_service=self.memory_service,
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invocation_id=invocation_id,
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agent=self.agent,
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session=session,
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user_content=new_message,
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live_request_queue=live_request_queue,
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run_config=run_config,
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)
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def _new_invocation_context_for_live(
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self,
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session: Session,
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*,
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live_request_queue: Optional[LiveRequestQueue] = None,
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run_config: RunConfig = RunConfig(),
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) -> InvocationContext:
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"""Creates a new invocation context for live multi-agent."""
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# For live multi-agent, we need model's text transcription as context for
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# next agent.
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if self.agent.sub_agents and live_request_queue:
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if not run_config.response_modalities:
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# default
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run_config.response_modalities = ['AUDIO', 'TEXT']
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elif 'TEXT' not in run_config.response_modalities:
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run_config.response_modalities.append('TEXT')
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return self._new_invocation_context(
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session,
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live_request_queue=live_request_queue,
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run_config=run_config,
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)
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class InMemoryRunner(Runner):
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"""An in-memory Runner for testing and development.
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This runner uses in-memory implementations for artifact, session, and memory
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services, providing a lightweight and self-contained environment for agent
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execution.
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Attributes:
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agent: The root agent to run.
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app_name: The application name of the runner. Defaults to
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'InMemoryRunner'.
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"""
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def __init__(self, agent: LlmAgent, *, app_name: str = 'InMemoryRunner'):
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"""Initializes the InMemoryRunner.
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Args:
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agent: The root agent to run.
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app_name: The application name of the runner. Defaults to
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'InMemoryRunner'.
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"""
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super().__init__(
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app_name=app_name,
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agent=agent,
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artifact_service=InMemoryArtifactService(),
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session_service=InMemorySessionService(),
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memory_service=InMemoryMemoryService(),
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)
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Block a user