refactor: 简化 AgentScope 运行时模块与 prompt 系统
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zl-q
@@ -1,202 +1,178 @@
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from __future__ import annotations
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from datetime import datetime, timedelta, timezone
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import base64
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from typing import Any
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from uuid import UUID
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from ag_ui.core import RunAgentInput
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from sqlalchemy import select
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from agentscope.message import Msg
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from core.agentscope.events import (
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AgentScopeAgUiCodec,
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AgentScopeEventPipeline,
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RedisStreamBus,
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SqlAlchemyEventStore,
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)
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from core.agentscope.schemas.agui_input import (
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extract_latest_tool_result,
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parse_run_input,
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)
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from core.agentscope.runtime.orchestrator import AgentScopeRuntimeOrchestrator
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from core.agentscope.schemas.agui_input import parse_run_input
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from core.agentscope.tools.tool_result_storage import create_tool_result_storage
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from core.auth.models import CurrentUser
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from core.config.settings import config
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from core.db.session import AsyncSessionLocal
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from core.logging import get_logger
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from core.taskiq.app import bulk_broker, critical_broker, default_broker
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from core.agentscope.tools.tool_result_storage import create_tool_result_storage
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from models.agent_chat_message import AgentChatMessage, AgentChatMessageRole
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from schemas.user import UserContext, parse_profile_settings
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from schemas.user import UserContext
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from services.base.redis import get_or_init_redis_client
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from services.base.supabase import supabase_service
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from v1.agent.dependencies import get_agent_service
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from v1.users.dependencies import get_user_service
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logger = get_logger("core.agentscope.runtime.tasks")
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AgentScopeRuntimeOrchestrator: type[Any] | None = None
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def _load_runtime() -> type[Any]:
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return AgentScopeRuntimeOrchestrator
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def _load_runtime_type() -> type[Any]:
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global AgentScopeRuntimeOrchestrator
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if AgentScopeRuntimeOrchestrator is None:
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from core.agentscope.runtime.orchestrator import (
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AgentScopeRuntimeOrchestrator as _ASRO,
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)
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AgentScopeRuntimeOrchestrator = _ASRO
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runtime_type = AgentScopeRuntimeOrchestrator
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if runtime_type is None:
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raise RuntimeError("failed to load AgentScopeRuntimeOrchestrator")
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return runtime_type
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def _build_user_context(*, owner_id: UUID, run_input: RunAgentInput) -> UserContext:
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forwarded = (
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run_input.forwarded_props if isinstance(run_input.forwarded_props, dict) else {}
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)
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username = str(forwarded.get("username", "user")).strip() or "user"
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bio_value = forwarded.get("bio")
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bio = str(bio_value).strip() if isinstance(bio_value, str) else None
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email_value = forwarded.get("email")
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email = str(email_value).strip() if isinstance(email_value, str) else None
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avatar_value = forwarded.get("avatarUrl")
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avatar_url = str(avatar_value).strip() if isinstance(avatar_value, str) else None
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profile_settings = forwarded.get("profileSettings")
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settings_raw = profile_settings if isinstance(profile_settings, dict) else None
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return UserContext(
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id=str(owner_id),
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username=username,
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email=email,
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avatar_url=avatar_url,
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bio=bio,
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settings=parse_profile_settings(settings_raw),
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)
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async def _build_user_context(
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*,
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owner_id: UUID,
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session: Any,
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) -> UserContext:
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current_user = CurrentUser(id=owner_id)
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user_service = get_user_service(session=session, user=current_user)
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return await user_service.get_me()
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async def _build_recent_context_messages(
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*,
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session: Any,
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thread_id: str,
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current_run_id: str,
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max_messages: int = 20,
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) -> list[dict[str, Any]]:
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try:
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session_uuid = UUID(thread_id)
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except ValueError:
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) -> list[Msg]:
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agent_service = get_agent_service(session)
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result = await agent_service.load_agent_input_messages(thread_id=thread_id)
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if not result:
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return []
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utc_now = datetime.now(timezone.utc)
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start_of_today = utc_now.replace(hour=0, minute=0, second=0, microsecond=0)
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start_of_yesterday = start_of_today - timedelta(days=1)
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raw_messages: list[dict[str, Any]] = result.get("messages") or []
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if not raw_messages:
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return []
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stmt = (
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select(AgentChatMessage)
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.where(AgentChatMessage.session_id == session_uuid)
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.where(AgentChatMessage.deleted_at.is_(None))
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.where(AgentChatMessage.created_at >= start_of_yesterday)
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.order_by(AgentChatMessage.seq.asc())
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)
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rows = (await session.execute(stmt)).scalars().all()
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converted: list[Msg] = []
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normalized: list[dict[str, Any]] = []
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for row in rows:
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metadata = row.metadata_json if isinstance(row.metadata_json, dict) else {}
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if metadata.get("run_id") == current_run_id:
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continue
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role = (
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row.role.value
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if isinstance(row.role, AgentChatMessageRole)
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else str(row.role)
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)
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if role not in {"user", "assistant"}:
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continue
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normalized.append(
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{
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"id": str(row.id),
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"role": role,
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"content": row.content,
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}
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for msg in raw_messages:
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role = msg.get("role")
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content = msg.get("content", "")
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metadata = msg.get("metadata")
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if role == "user" and metadata:
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attachments = metadata.get("user_message_attachments")
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if attachments:
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bucket = attachments.get("bucket")
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path = attachments.get("path")
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mime_type = attachments.get("mime_type")
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if bucket and path:
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try:
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image_bytes = await supabase_service.download_bytes(
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bucket=bucket,
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path=path,
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)
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b64_data = base64.b64encode(image_bytes).decode("utf-8")
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converted.append(
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Msg(
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name="user",
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role="user",
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content=[
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{"type": "text", "text": content},
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{
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"type": "image",
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"source": {
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"type": "base64",
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"media_type": mime_type or "image/png",
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"data": b64_data,
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},
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},
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],
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)
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)
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continue
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except Exception:
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pass
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if role == "tool":
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role = "assistant"
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converted.append(
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Msg(
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name=role or "user",
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role=role if role in ("user", "assistant", "system") else "user",
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content=content,
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)
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)
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if len(normalized) <= max_messages:
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return normalized
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return normalized[-max_messages:]
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return converted
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async def run_agentscope_task(command: dict[str, Any]) -> dict[str, object]:
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command_type = str(command.get("command", "run")).strip().lower()
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raw_run_input = command.get("run_input")
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raw_owner_id = command.get("owner_id")
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run_input_raw = command.get("run_input")
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if not isinstance(raw_run_input, dict):
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raise ValueError("run_input is required")
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if not isinstance(raw_owner_id, str) or not raw_owner_id.strip():
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raise ValueError("owner_id is required")
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if run_input_raw is None:
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raise ValueError("run_input is required")
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run_input = parse_run_input(run_input_raw)
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thread_id = run_input.thread_id
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run_id = run_input.run_id
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owner_id = UUID(raw_owner_id)
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if command_type not in {"run", "resume"}:
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if command_type != "run":
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raise ValueError("invalid command type")
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orchestrator_type = _load_runtime_type()
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parsed_run_input = parse_run_input(raw_run_input)
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if command_type == "resume":
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extract_latest_tool_result(parsed_run_input)
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user_context = _build_user_context(owner_id=owner_id, run_input=parsed_run_input)
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redis_client = await get_or_init_redis_client()
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bus = RedisStreamBus(
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client=redis_client,
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stream_prefix=config.agent_runtime.redis_stream_prefix,
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read_count=config.agent_runtime.redis_stream_read_count,
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block_ms=config.agent_runtime.redis_stream_block_ms,
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)
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pipeline = AgentScopeEventPipeline(
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codec=AgentScopeAgUiCodec(),
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store=SqlAlchemyEventStore(
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session_factory=AsyncSessionLocal,
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tool_result_storage=create_tool_result_storage(),
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tool_result_bucket=config.storage.bucket,
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),
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bus=bus,
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)
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runtime = orchestrator_type(
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pipeline=pipeline,
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)
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orchestrator = _load_runtime()
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async with AsyncSessionLocal() as session:
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user_context = await _build_user_context(owner_id=owner_id, session=session)
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redis_client = await get_or_init_redis_client()
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bus = RedisStreamBus(
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client=redis_client,
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stream_prefix=config.agent_runtime.redis_stream_prefix,
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read_count=config.agent_runtime.redis_stream_read_count,
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block_ms=config.agent_runtime.redis_stream_block_ms,
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)
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pipeline = AgentScopeEventPipeline(
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codec=AgentScopeAgUiCodec(),
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store=SqlAlchemyEventStore(
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session_factory=AsyncSessionLocal,
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tool_result_storage=create_tool_result_storage(),
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tool_result_bucket=config.storage.bucket,
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),
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bus=bus,
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)
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runtime = orchestrator(
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pipeline=pipeline,
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)
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context_messages = await _build_recent_context_messages(
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session=session,
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thread_id=parsed_run_input.thread_id,
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current_run_id=parsed_run_input.run_id,
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thread_id=thread_id,
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)
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if context_messages:
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parsed_run_input = parsed_run_input.model_copy(
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update={
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"messages": [
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*context_messages,
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*parsed_run_input.messages,
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]
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}
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)
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if command_type == "resume":
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await runtime.resume(
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command=parsed_run_input,
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owner_id=owner_id,
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user_context=user_context,
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session=session,
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)
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elif command_type == "run":
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await runtime.run(
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command=parsed_run_input,
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owner_id=owner_id,
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user_context=user_context,
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session=session,
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)
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await runtime.run(
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run_input=run_input,
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context_messages=context_messages,
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user_context=user_context,
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)
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logger.info(
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"agentscope runtime task completed",
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command_type=command_type,
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thread_id=parsed_run_input.thread_id,
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run_id=parsed_run_input.run_id,
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thread_id=thread_id,
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run_id=run_id,
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)
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return {
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"thread_id": parsed_run_input.thread_id,
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"run_id": parsed_run_input.run_id,
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"thread_id": thread_id,
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"run_id": run_id,
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"status": "completed",
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}
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