mirror of
https://github.com/langbot-app/LangBot.git
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feat(agent): add event debugging and streamline configuration
This commit is contained in:
huanghuoguoguo
@@ -1,15 +1,33 @@
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from __future__ import annotations
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import datetime
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import fnmatch
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import time
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import uuid
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import typing
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import sqlalchemy
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from langbot_plugin.api.entities.builtin.agent_runner.delivery import DeliveryContext
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from langbot_plugin.api.entities.builtin.agent_runner.event import (
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ActorContext,
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RawEventRef,
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SubjectContext,
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)
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from langbot_plugin.api.entities.builtin.agent_runner.input import AgentInput
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from ....core import app
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from ....agent.runner.config_resolver import RunnerConfigResolver
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from ....agent.runner.host_models import (
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AgentBinding,
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AgentEventEnvelope,
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BindingScope,
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DeliveryPolicy,
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StatePolicy,
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)
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from ....agent.runner.resource_policy import ResourcePolicyProjector
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from ....entity.persistence import agent as persistence_agent
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from ....workspace.errors import WorkspaceNotFoundError
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from ..context import ExecutionContext, RequestContext
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from .tenant import TenantContext, require_workspace_uuid, scope_statement
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@@ -78,6 +96,173 @@ class AgentService:
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return None
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async def debug_agent(
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self,
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context: RequestContext,
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agent_uuid: str,
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payload: dict[str, typing.Any],
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) -> dict[str, typing.Any]:
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"""Execute one synthetic event against a configured Agent.
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The debug surface uses a trusted Workspace execution context, never
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delivers outputs to a real platform, and supports both message and
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non-message event envelopes.
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"""
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agent = await self.get_agent(context, agent_uuid)
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if agent is None or agent.get('kind') != AGENT_KIND_AGENT:
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raise ValueError('Agent not found')
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event_type = str(payload.get('event_type') or 'message.received').strip()
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if not event_type or len(event_type) > 128:
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raise ValueError('Invalid event_type')
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if not self._supports_event_type(
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agent.get('supported_event_patterns'),
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event_type,
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):
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raise ValueError('Agent does not support this event type')
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text = str(payload.get('text') or '').strip()
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if len(text) > 20_000:
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raise ValueError('Debug input is too long')
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event_data = payload.get('data') or {}
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if not isinstance(event_data, dict):
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raise ValueError('Debug event data must be an object')
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config = agent.get('config')
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if not isinstance(config, dict):
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raise ValueError('Agent configuration is invalid')
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_, runner_id, runner_config = RunnerConfigResolver.resolve_agent_runner_config(config)
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if not runner_id:
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raise ValueError('Agent has no configured runner')
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conversation_id = str(payload.get('conversation_id') or f'debug:{agent_uuid}').strip()
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if not conversation_id or len(conversation_id) > 256:
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raise ValueError('Invalid debug conversation_id')
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actor_payload = payload.get('actor') or {
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'actor_type': 'user',
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'actor_id': 'debug-user',
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'actor_name': 'Debug User',
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}
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subject_payload = payload.get('subject') or {
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'subject_type': 'message' if event_type.startswith('message.') else event_type.split('.', 1)[0],
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'subject_id': 'debug-subject',
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'data': event_data,
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}
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if not isinstance(actor_payload, dict) or not isinstance(subject_payload, dict):
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raise ValueError('Debug actor and subject must be objects')
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event_id = f'debug:{agent_uuid}:{uuid.uuid4()}'
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event = AgentEventEnvelope(
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event_id=event_id,
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event_type=event_type,
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event_time=int(time.time()),
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source='webui',
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source_event_type=event_type,
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workspace_id=context.workspace_uuid,
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conversation_id=conversation_id,
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actor=ActorContext.model_validate(actor_payload),
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subject=SubjectContext.model_validate(subject_payload),
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input=AgentInput.model_validate(
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{
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'text': text or event_type,
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'contents': [
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{'type': 'text', 'text': text or event_type},
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],
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'attachments': [],
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}
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),
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delivery=DeliveryContext(
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surface='webui',
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reply_target=None,
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supports_streaming=False,
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supports_edit=False,
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supports_reaction=False,
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platform_capabilities={
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'event_type': event_type,
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'debug': True,
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},
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),
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raw_ref=RawEventRef(ref_id=event_id, storage_key=None),
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data=event_data,
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)
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binding = AgentBinding(
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binding_id=f'debug:{agent_uuid}:{runner_id}',
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scope=BindingScope(scope_type='agent', scope_id=agent_uuid),
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event_types=[event_type],
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runner_id=runner_id,
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runner_config=runner_config,
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resource_policy=ResourcePolicyProjector.from_runner_config(runner_config),
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state_policy=StatePolicy(
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state_scopes=['conversation', 'actor', 'subject', 'runner'],
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),
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delivery_policy=DeliveryPolicy(
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enable_streaming=False,
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enable_reply=False,
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enable_interactions=False,
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),
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enabled=True,
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agent_id=agent_uuid,
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processor_type='agent',
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processor_id=agent_uuid,
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)
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execution_context = ExecutionContext.from_request(
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context,
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query_uuid=event_id,
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)
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output_items: list[dict[str, typing.Any]] = []
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final_text = ''
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async for output in self.ap.agent_run_orchestrator.run(
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event,
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binding,
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adapter_context={'_execution_context': execution_context},
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):
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output_text = self._provider_output_to_text(output)
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if output_text:
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final_text = output_text
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output_items.append(
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{
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'kind': output.__class__.__name__,
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'role': str(getattr(output, 'role', '') or ''),
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'text': output_text,
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}
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)
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return {
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'event_id': event_id,
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'event_type': event_type,
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'conversation_id': conversation_id,
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'final_text': final_text,
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'outputs': output_items,
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}
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@staticmethod
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def _supports_event_type(patterns: typing.Any, event_type: str) -> bool:
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normalized = patterns if isinstance(patterns, list) else AGENT_DEFAULT_EVENT_PATTERNS
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return any(isinstance(pattern, str) and fnmatch.fnmatchcase(event_type, pattern) for pattern in normalized)
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@staticmethod
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def _provider_output_to_text(output: typing.Any) -> str:
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all_content = getattr(output, 'all_content', None)
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if all_content:
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return str(all_content)
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content = getattr(output, 'content', None)
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if content is None:
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return ''
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if isinstance(content, str):
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return content
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if isinstance(content, list):
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parts: list[str] = []
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for item in content:
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item_data = item.model_dump(mode='json') if hasattr(item, 'model_dump') else item
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if isinstance(item_data, dict) and item_data.get('text') is not None:
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parts.append(str(item_data['text']))
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elif item_data is not None and not isinstance(item_data, dict):
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parts.append(str(item_data))
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return ''.join(parts)
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return str(content)
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async def create_agent(self, context: TenantContext, agent_data: dict) -> dict[str, str]:
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workspace_uuid = require_workspace_uuid(context)
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kind = agent_data.get('kind') or AGENT_KIND_AGENT
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@@ -89,7 +274,7 @@ class AgentService:
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'description': agent_data.get('description') or '',
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'emoji': agent_data.get('emoji') or '⚙️',
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'config': {},
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}
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},
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)
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return {'uuid': pipeline_uuid, 'kind': AGENT_KIND_PIPELINE}
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