Files
LangBot/src/langbot/pkg/agent/runner/orchestrator.py
2026-06-04 11:11:39 +08:00

916 lines
33 KiB
Python

"""Agent run orchestrator for coordinating runner execution."""
from __future__ import annotations
import typing
import traceback
import asyncio
import time
from langbot_plugin.api.entities.builtin.provider import message as provider_message
from langbot_plugin.api.entities.builtin.pipeline import query as pipeline_query
from langbot_plugin.entities.io.errors import ActionCallTimeoutError
from ...core import app
from .descriptor import AgentRunnerDescriptor
from .registry import AgentRunnerRegistry
from .context_builder import AgentRunContextBuilder, AgentRunContextPayload
from .resource_builder import AgentResourceBuilder
from .result_normalizer import AgentResultNormalizer
from .state_store import get_state_store, RunnerScopedStateStore
from .session_registry import get_session_registry, AgentRunSessionRegistry
from .config_migration import ConfigMigration
from .host_models import AgentEventEnvelope, AgentBinding
from .pipeline_compat_adapter import PipelineCompatAdapter
from .errors import (
RunnerNotFoundError,
RunnerExecutionError,
RunnerProtocolError,
)
# Maximum inline artifact content size (1MB)
MAX_ARTIFACT_INLINE_BYTES = 1 * 1024 * 1024
class AgentRunOrchestrator:
"""Orchestrator for agent runner execution.
Responsibilities:
- Resolve runner ID from pipeline config (new or old format)
- Get runner descriptor from registry
- Provision AgentRunContext envelope from Query
- Build AgentResources with permission filtering
- Invoke plugin runtime RUN_AGENT action
- Normalize AgentRunResult to Pipeline messages
- Handle errors, timeouts, protocol errors
- Maintain streaming card behavior
Entry points:
- run(event, binding): Main entry for event-first Protocol v1
- run_from_query(query): Compatibility wrapper for Pipeline
"""
ap: app.Application
registry: AgentRunnerRegistry
context_builder: AgentRunContextBuilder
resource_builder: AgentResourceBuilder
result_normalizer: AgentResultNormalizer
# Cached singleton references (set in __init__)
_session_registry: AgentRunSessionRegistry
_state_store: RunnerScopedStateStore
def __init__(
self,
ap: app.Application,
registry: AgentRunnerRegistry,
):
self.ap = ap
self.registry = registry
self.context_builder = AgentRunContextBuilder(ap)
self.resource_builder = AgentResourceBuilder(ap)
self.result_normalizer = AgentResultNormalizer(ap)
# Cache singleton references to avoid per-request getter calls
self._session_registry = get_session_registry()
self._state_store = get_state_store()
async def run(
self,
event: AgentEventEnvelope,
binding: AgentBinding,
) -> typing.AsyncGenerator[provider_message.Message | provider_message.MessageChunk, None]:
"""Run agent runner from event-first envelope.
This is the main entry point for Protocol v1.
Event Gateway -> AgentBindingResolver -> run(event, binding).
Args:
event: Event envelope from event gateway
binding: Agent binding configuration
Yields:
Message or MessageChunk for pipeline response
Raises:
RunnerNotFoundError: If runner not found
RunnerNotAuthorizedError: If runner not authorized
RunnerExecutionError: If runner execution failed
"""
runner_id = binding.runner_id
# Get runner descriptor
# TODO: Get bound plugins from binding when fully migrated
bound_plugins = None # Will be resolved from binding.scope in future
descriptor = await self.registry.get(runner_id, bound_plugins)
# Build resources from binding
resources = await self.resource_builder.build_resources_from_binding(
event=event,
binding=binding,
descriptor=descriptor,
)
# Build context from event + binding
context = await self.context_builder.build_context_from_event(
event=event,
binding=binding,
descriptor=descriptor,
resources=resources,
)
# Register session for proxy action permission validation
run_id = context['run_id']
await self._session_registry.register(
run_id=run_id,
runner_id=descriptor.id,
query_id=None, # No query_id in event-first mode
plugin_identity=descriptor.get_plugin_id(),
resources=resources,
permissions=descriptor.permissions or {},
conversation_id=event.conversation_id,
)
# Write incoming event to EventLog
event_log_id = await self._write_event_log(
event=event,
binding=binding,
run_id=run_id,
runner_id=descriptor.id,
)
# Write user message to Transcript if message.received
if event.event_type == 'message.received' and event.conversation_id:
await self._write_user_transcript(
event=event,
event_log_id=event_log_id,
)
# Track artifact refs for assistant transcript (cleared after each message.completed)
pending_artifact_refs: list[dict[str, typing.Any]] = []
try:
# Run via plugin connector
async for result_dict in self._invoke_runner(descriptor, context):
# Handle artifact.created first - consume before normalizer
if result_dict.get('type') == 'artifact.created':
artifact_ref = await self._handle_artifact_created(
result_dict=result_dict,
event=event,
run_id=run_id,
runner_id=descriptor.id,
)
pending_artifact_refs.append(artifact_ref)
# Pass to normalizer for logging, but don't yield to pipeline
await self.result_normalizer.normalize(result_dict, descriptor)
continue
# Handle state.updated first - consume before normalizer
if result_dict.get('type') == 'state.updated':
self._handle_state_updated_event(result_dict, event, descriptor)
# Pass to normalizer for logging, but don't yield to pipeline
await self.result_normalizer.normalize(result_dict, descriptor)
continue
# Handle message.completed - write to Transcript
if result_dict.get('type') == 'message.completed' and event.conversation_id:
# Merge pending artifact refs with message's own refs
merged_refs = self._merge_artifact_refs(
pending_artifact_refs,
result_dict,
)
# Clear pending refs after attaching to this message
pending_artifact_refs.clear()
await self._write_assistant_transcript(
result_dict=result_dict,
event=event,
run_id=run_id,
runner_id=descriptor.id,
artifact_refs=merged_refs if merged_refs else None,
)
# Normalize result for other types
result = await self.result_normalizer.normalize(result_dict, descriptor)
if result is not None:
yield result
finally:
# Unregister session after run completes (success or error)
await self._session_registry.unregister(run_id)
async def run_from_query(
self,
query: pipeline_query.Query,
) -> typing.AsyncGenerator[provider_message.Message | provider_message.MessageChunk, None]:
"""Run agent runner from pipeline query.
This is a compatibility wrapper for the legacy Query-based flow.
It preserves existing behavior for params, messages, state, etc.
For the new event-first Protocol v1, use run(event, binding) instead.
Args:
query: Pipeline query with pipeline_config, session, messages, etc.
Yields:
Message or MessageChunk for pipeline response
Raises:
RunnerNotFoundError: If runner not found
RunnerNotAuthorizedError: If runner not authorized
RunnerExecutionError: If runner execution failed
"""
# Resolve runner ID
runner_id = ConfigMigration.resolve_runner_id(query.pipeline_config)
if not runner_id:
raise RunnerNotFoundError('no runner configured')
# Get bound plugins for authorization
bound_plugins = query.variables.get('_pipeline_bound_plugins')
# Get runner descriptor
descriptor = await self.registry.get(runner_id, bound_plugins)
# Build resources (using legacy Query-based method)
resources = await self.resource_builder.build_resources(query, descriptor)
# Build context (using legacy Query-based method with params, state, messages)
context = await self.context_builder.build_context(query, descriptor, resources)
# Get conversation_id from context
conversation_id = None
if context.get('conversation'):
conversation_id = context['conversation'].get('conversation_id')
# Register session for proxy action permission validation
run_id = context['run_id']
await self._session_registry.register(
run_id=run_id,
runner_id=descriptor.id,
query_id=query.query_id,
plugin_identity=descriptor.get_plugin_id(),
resources=resources,
permissions=descriptor.permissions or {},
conversation_id=conversation_id,
)
try:
# Run via plugin connector
async for result_dict in self._invoke_runner(descriptor, context):
# Handle artifact.created - register artifact
if result_dict.get('type') == 'artifact.created':
await self._handle_artifact_created_query(
result_dict=result_dict,
query=query,
descriptor=descriptor,
run_id=run_id,
conversation_id=conversation_id,
)
# Pass to normalizer for logging, but don't yield to pipeline
await self.result_normalizer.normalize(result_dict, descriptor)
continue
# Handle state.updated first - consume before normalizer
if result_dict.get('type') == 'state.updated':
self._handle_state_updated(result_dict, query, descriptor)
# Pass to normalizer for logging, but don't yield to pipeline
await self.result_normalizer.normalize(result_dict, descriptor)
continue
# Normalize result for other types
result = await self.result_normalizer.normalize(result_dict, descriptor)
if result is not None:
yield result
finally:
# Unregister session after run completes (success or error)
await self._session_registry.unregister(run_id)
async def _invoke_runner(
self,
descriptor: AgentRunnerDescriptor,
context: AgentRunContextPayload,
) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
"""Invoke runner via plugin connector.
Args:
descriptor: Runner descriptor
context: AgentRunContext dict
Yields:
Raw result dicts from plugin runtime
Raises:
RunnerExecutionError: If plugin system disabled or runtime error
"""
if not self.ap.plugin_connector.is_enable_plugin:
raise RunnerExecutionError(
descriptor.id,
'Plugin system is disabled',
retryable=False,
)
try:
gen = self.ap.plugin_connector.run_agent(
plugin_author=descriptor.plugin_author,
plugin_name=descriptor.plugin_name,
runner_name=descriptor.runner_name,
context=context,
)
while True:
try:
result_dict = await self._next_with_deadline(gen, descriptor, context)
except StopAsyncIteration:
break
yield result_dict
except asyncio.TimeoutError as e:
raise RunnerExecutionError(
descriptor.id,
'Runner timed out (code: runner.timeout)',
retryable=True,
) from e
except ActionCallTimeoutError as e:
raise RunnerExecutionError(
descriptor.id,
f'{e} (code: runner.timeout)',
retryable=True,
) from e
except RunnerExecutionError:
raise
except Exception as e:
# Wrap unexpected errors
self.ap.logger.error(
f'Runner {descriptor.id} unexpected error: {traceback.format_exc()}'
)
raise RunnerExecutionError(
descriptor.id,
str(e),
retryable=False,
)
async def _next_with_deadline(
self,
gen: typing.AsyncGenerator[dict[str, typing.Any], None],
descriptor: AgentRunnerDescriptor,
context: AgentRunContextPayload,
) -> dict[str, typing.Any]:
"""Read the next runner result while enforcing the run deadline."""
remaining = self._remaining_deadline_seconds(context)
if remaining is not None and remaining <= 0:
await self._close_generator(gen, descriptor)
raise asyncio.TimeoutError
try:
if remaining is None:
return await anext(gen)
return await asyncio.wait_for(anext(gen), timeout=remaining)
except StopAsyncIteration:
if self._is_deadline_exhausted(context):
raise asyncio.TimeoutError
raise
except asyncio.TimeoutError:
await self._close_generator(gen, descriptor)
raise
def _remaining_deadline_seconds(
self,
context: AgentRunContextPayload,
) -> float | None:
runtime = context.get('runtime') or {}
deadline_at = runtime.get('deadline_at')
if deadline_at is None:
return None
try:
return float(deadline_at) - time.time()
except (TypeError, ValueError):
return None
def _is_deadline_exhausted(self, context: AgentRunContextPayload) -> bool:
remaining = self._remaining_deadline_seconds(context)
return remaining is not None and remaining <= 0
async def _close_generator(
self,
gen: typing.AsyncGenerator[dict[str, typing.Any], None],
descriptor: AgentRunnerDescriptor,
) -> None:
try:
await gen.aclose()
except Exception as e:
self.ap.logger.warning(f'Failed to close timed-out runner {descriptor.id}: {e}')
def resolve_runner_id_for_telemetry(self, query: pipeline_query.Query) -> str | None:
"""Resolve runner ID for telemetry/logging without full execution.
Args:
query: Pipeline query
Returns:
Runner ID string, or None
"""
return ConfigMigration.resolve_runner_id(query.pipeline_config)
def _handle_state_updated(
self,
result_dict: dict[str, typing.Any],
query: pipeline_query.Query,
descriptor: AgentRunnerDescriptor,
) -> None:
"""Handle state.updated result - apply to state store.
Legacy method for Query-based flow.
Args:
result_dict: Raw result dict with type='state.updated'
query: Pipeline query
descriptor: Runner descriptor
"""
data = result_dict.get('data', {})
# Extract scope (default to 'conversation' for backward compat)
scope = data.get('scope', 'conversation')
# Extract key and value
key = data.get('key')
value = data.get('value')
if not key:
self.ap.logger.warning(
f'Runner {descriptor.id} state.updated missing key, ignoring'
)
return
# Apply update to state store
success = self._state_store.apply_update(
query=query,
descriptor=descriptor,
scope=scope,
key=key,
value=value,
logger=self.ap.logger,
)
if success:
self.ap.logger.debug(
f'Runner {descriptor.id} state.updated: scope={scope}, key={key}, value={value}'
)
# Invalid scope is already logged by state_store.apply_update
async def _handle_artifact_created_query(
self,
result_dict: dict[str, typing.Any],
query: pipeline_query.Query,
descriptor: AgentRunnerDescriptor,
run_id: str,
conversation_id: str | None,
) -> None:
"""Handle artifact.created result in Query-based flow.
Legacy Query flow only registers artifact metadata/content for compatibility.
Event log/transcript linkage is event-first only for now.
Args:
result_dict: Raw result dict with type='artifact.created'
query: Pipeline query
descriptor: Runner descriptor
run_id: Current run ID
conversation_id: Conversation ID (may be None)
Raises:
RunnerProtocolError: On validation failures or registration errors
"""
import base64
import uuid
from .artifact_store import ArtifactStore
data = result_dict.get('data', {})
# Validate run_id matches current context
result_run_id = result_dict.get('run_id')
if result_run_id and result_run_id != run_id:
raise RunnerProtocolError(
descriptor.id,
f'artifact.created run_id mismatch: expected {run_id}, got {result_run_id}',
)
# Extract artifact fields
artifact_id = data.get('artifact_id') or str(uuid.uuid4())
artifact_type = data.get('artifact_type')
if not artifact_type:
raise RunnerProtocolError(
descriptor.id,
'artifact.created missing required field: artifact_type',
)
mime_type = data.get('mime_type')
name = data.get('name')
size_bytes = data.get('size_bytes')
sha256 = data.get('sha256')
metadata = data.get('metadata')
content_base64 = data.get('content_base64')
# Decode and validate content if provided
content: bytes | None = None
if content_base64:
try:
content = base64.b64decode(content_base64, validate=True)
except Exception as e:
raise RunnerProtocolError(
descriptor.id,
f'artifact.created invalid base64 content: {e}',
)
# Validate content size
if len(content) > MAX_ARTIFACT_INLINE_BYTES:
raise RunnerProtocolError(
descriptor.id,
f'artifact.created content size {len(content)} bytes exceeds limit {MAX_ARTIFACT_INLINE_BYTES} bytes',
)
# Register artifact via ArtifactStore
artifact_store = ArtifactStore(self.ap.persistence_mgr.get_db_engine())
try:
await artifact_store.register_artifact(
artifact_id=artifact_id,
artifact_type=artifact_type,
source='runner',
mime_type=mime_type,
name=name,
size_bytes=size_bytes,
sha256=sha256,
conversation_id=conversation_id,
run_id=run_id,
runner_id=descriptor.id,
metadata=metadata,
content=content,
)
except Exception as e:
raise RunnerProtocolError(
descriptor.id,
f'artifact.created failed to register artifact: {e}',
)
def _handle_state_updated_event(
self,
result_dict: dict[str, typing.Any],
event: AgentEventEnvelope,
descriptor: AgentRunnerDescriptor,
) -> None:
"""Handle state.updated result in event-first mode.
Args:
result_dict: Raw result dict with type='state.updated'
event: Event envelope
descriptor: Runner descriptor
"""
data = result_dict.get('data', {})
# Extract scope (default to 'conversation' for backward compat)
scope = data.get('scope', 'conversation')
# Extract key and value
key = data.get('key')
value = data.get('value')
if not key:
self.ap.logger.warning(
f'Runner {descriptor.id} state.updated missing key, ignoring'
)
return
# Apply update to state store using event context
# Note: state_store needs to support event-based scope key calculation
# For now, we log and skip actual persistence in event-first mode
# This will be implemented when state_store is migrated to support events
self.ap.logger.debug(
f'Runner {descriptor.id} state.updated (event mode): scope={scope}, key={key}, value={value}'
)
async def _write_event_log(
self,
event: AgentEventEnvelope,
binding: AgentBinding,
run_id: str,
runner_id: str,
) -> str:
"""Write incoming event to EventLog.
Args:
event: Event envelope
binding: Agent binding
run_id: Run ID
runner_id: Runner ID
Returns:
Event log ID
"""
import datetime
from .event_log_store import EventLogStore
store = EventLogStore(self.ap.persistence_mgr.get_db_engine())
# Build input summary
input_summary = None
input_json = None
if event.input:
if event.input.text:
input_summary = event.input.text[:1000]
input_json = {
'text': event.input.text,
'contents': [c.model_dump(mode='json') if hasattr(c, 'model_dump') else c for c in event.input.contents],
'attachments': [a.model_dump(mode='json') if hasattr(a, 'model_dump') else a for a in event.input.attachments],
}
return await store.append_event(
event_id=event.event_id,
event_type=event.event_type,
source=event.source,
bot_id=event.bot_id,
workspace_id=event.workspace_id,
conversation_id=event.conversation_id,
thread_id=event.thread_id,
actor_type=event.actor.actor_type if event.actor else None,
actor_id=event.actor.actor_id if event.actor else None,
actor_name=event.actor.actor_name if event.actor else None,
subject_type=event.subject.subject_type if event.subject else None,
subject_id=event.subject.subject_id if event.subject else None,
input_summary=input_summary,
input_json=input_json,
run_id=run_id,
runner_id=runner_id,
event_time=datetime.datetime.fromtimestamp(event.event_time) if event.event_time else None,
)
async def _write_user_transcript(
self,
event: AgentEventEnvelope,
event_log_id: str,
) -> None:
"""Write user message to Transcript.
Args:
event: Event envelope
event_log_id: Event log ID
"""
from .transcript_store import TranscriptStore
store = TranscriptStore(self.ap.persistence_mgr.get_db_engine())
# Build content
content = event.input.text if event.input else None
content_json = None
if event.input:
content_json = {
'role': 'user',
'content': [c.model_dump(mode='json') if hasattr(c, 'model_dump') else c for c in event.input.contents] if event.input.contents else [],
}
# Build artifact refs
artifact_refs = []
if event.input and event.input.attachments:
for a in event.input.attachments:
artifact_refs.append(a.model_dump(mode='json') if hasattr(a, 'model_dump') else a)
await store.append_transcript(
event_id=event_log_id,
conversation_id=event.conversation_id,
role='user',
content=content,
content_json=content_json,
artifact_refs=artifact_refs if artifact_refs else None,
thread_id=event.thread_id,
item_type='message',
metadata={
'actor_type': event.actor.actor_type if event.actor else None,
'actor_id': event.actor.actor_id if event.actor else None,
},
)
async def _handle_artifact_created(
self,
result_dict: dict[str, typing.Any],
event: AgentEventEnvelope,
run_id: str,
runner_id: str,
) -> dict[str, typing.Any]:
"""Handle artifact.created result - register artifact and write EventLog.
Args:
result_dict: Raw result dict with type='artifact.created'
event: Event envelope
run_id: Current run ID
runner_id: Runner ID
Returns:
Artifact reference dict for Transcript
Raises:
RunnerProtocolError: On validation failures or registration errors
"""
import base64
import uuid
from .artifact_store import ArtifactStore
from .event_log_store import EventLogStore
data = result_dict.get('data', {})
# Validate run_id matches current context
result_run_id = result_dict.get('run_id')
if result_run_id and result_run_id != run_id:
raise RunnerProtocolError(
runner_id,
f'artifact.created run_id mismatch: expected {run_id}, got {result_run_id}',
)
# Extract artifact fields
artifact_id = data.get('artifact_id') or str(uuid.uuid4())
artifact_type = data.get('artifact_type')
if not artifact_type:
raise RunnerProtocolError(
runner_id,
'artifact.created missing required field: artifact_type',
)
mime_type = data.get('mime_type')
name = data.get('name')
size_bytes = data.get('size_bytes')
sha256 = data.get('sha256')
metadata = data.get('metadata')
content_base64 = data.get('content_base64')
# Decode and validate content if provided
content: bytes | None = None
if content_base64:
try:
content = base64.b64decode(content_base64, validate=True)
except Exception as e:
raise RunnerProtocolError(
runner_id,
f'artifact.created invalid base64 content: {e}',
)
# Validate content size
if len(content) > MAX_ARTIFACT_INLINE_BYTES:
raise RunnerProtocolError(
runner_id,
f'artifact.created content size {len(content)} bytes exceeds limit {MAX_ARTIFACT_INLINE_BYTES} bytes',
)
# Register artifact via ArtifactStore
artifact_store = ArtifactStore(self.ap.persistence_mgr.get_db_engine())
try:
registered_id = await artifact_store.register_artifact(
artifact_id=artifact_id,
artifact_type=artifact_type,
source='runner',
mime_type=mime_type,
name=name,
size_bytes=size_bytes,
sha256=sha256,
conversation_id=event.conversation_id,
run_id=run_id,
runner_id=runner_id,
bot_id=event.bot_id,
workspace_id=event.workspace_id,
metadata=metadata,
content=content,
)
except Exception as e:
raise RunnerProtocolError(
runner_id,
f'artifact.created failed to register artifact: {e}',
)
# Write to EventLog
event_log_store = EventLogStore(self.ap.persistence_mgr.get_db_engine())
await event_log_store.append_event(
event_id=str(uuid.uuid4()),
event_type='artifact.created',
source='runner',
bot_id=event.bot_id,
workspace_id=event.workspace_id,
conversation_id=event.conversation_id,
thread_id=event.thread_id,
actor_type=event.actor.actor_type if event.actor else None,
actor_id=event.actor.actor_id if event.actor else None,
actor_name=event.actor.actor_name if event.actor else None,
input_summary=f'Artifact created: {artifact_type}',
input_json={
'artifact_id': registered_id,
'artifact_type': artifact_type,
'mime_type': mime_type,
'name': name,
'size_bytes': size_bytes,
},
run_id=run_id,
runner_id=runner_id,
)
# Return artifact ref for Transcript
return {
'artifact_id': registered_id,
'artifact_type': artifact_type,
'mime_type': mime_type,
'name': name,
}
def _merge_artifact_refs(
self,
pending_refs: list[dict[str, typing.Any]],
result_dict: dict[str, typing.Any],
) -> list[dict[str, typing.Any]]:
"""Merge pending artifact refs with message's own refs, deduplicating by artifact_id.
Args:
pending_refs: Artifact refs accumulated from artifact.created events
result_dict: Result dict that may contain message with artifact_refs
Returns:
Merged and deduplicated list of artifact refs
"""
# Start with pending refs
merged = list(pending_refs)
seen_ids = {ref.get('artifact_id') for ref in pending_refs if ref.get('artifact_id')}
# Extract refs from message data if present
data = result_dict.get('data', {})
message = data.get('message', {})
message_refs = message.get('artifact_refs', [])
if isinstance(message_refs, list):
for ref in message_refs:
if isinstance(ref, dict):
artifact_id = ref.get('artifact_id')
if artifact_id and artifact_id not in seen_ids:
merged.append(ref)
seen_ids.add(artifact_id)
return merged
async def _write_assistant_transcript(
self,
result_dict: dict[str, typing.Any],
event: AgentEventEnvelope,
run_id: str,
runner_id: str,
artifact_refs: list[dict[str, typing.Any]] | None = None,
) -> None:
"""Write assistant message to Transcript.
Args:
result_dict: Result dict from runner
event: Original event envelope
run_id: Run ID
runner_id: Runner ID
artifact_refs: Optional artifact references to include
"""
import uuid
from .transcript_store import TranscriptStore
store = TranscriptStore(self.ap.persistence_mgr.get_db_engine())
data = result_dict.get('data', {})
message = data.get('message', {})
# Build content
content = None
content_json = None
if isinstance(message.get('content'), str):
content = message['content']
content_json = message
elif isinstance(message.get('content'), list):
# Extract text from content list
text_parts = []
for c in message['content']:
if isinstance(c, dict) and c.get('type') == 'text':
text_parts.append(c.get('text', ''))
content = ' '.join(text_parts) if text_parts else None
content_json = message
# Generate a unique event ID for assistant message
assistant_event_id = str(uuid.uuid4())
await store.append_transcript(
transcript_id=str(uuid.uuid4()),
event_id=assistant_event_id,
conversation_id=event.conversation_id,
role='assistant',
content=content,
content_json=content_json,
artifact_refs=artifact_refs,
thread_id=event.thread_id,
item_type='message',
run_id=run_id,
runner_id=runner_id,
metadata={
'run_id': run_id,
'runner_id': runner_id,
},
)