feat: #36 主控台/应用商店 — 模板一键执行与模板市场一键安装
- MainConsole.vue: 完全重写为应用商店主控台，支持分类筛选、参数表单、一键执行、进度轮询、结果下载 - TemplateMarket.vue: 新增"一键安装"和"快速执行"按钮，优化业务用户体验 - platform_templates.py: 新增模板执行API（POST execute + GET progress），支持Celery异步/同步回退 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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renjianbo
@@ -1,15 +1,19 @@
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"""
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场景模板 API（独立路由，避免与 /api/v1/agents/{agent_id} 在部分部署中的匹配顺序问题）。
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"""
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from fastapi import APIRouter, Depends, status
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from fastapi import APIRouter, Depends, status, HTTPException
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from pydantic import BaseModel, Field
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from sqlalchemy.orm import Session
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from typing import List
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from typing import Any, Dict, List, Optional
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import logging
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import uuid
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import json
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from app.core.database import get_db
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from app.api.auth import get_current_user
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from app.models.user import User
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from app.models.agent import Agent
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from app.models.execution import Execution
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from app.core.exceptions import ValidationError, ConflictError
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from app.services.workflow_validator import validate_workflow
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from app.services.scene_templates import build_workflow_for_template, list_scene_template_meta
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@@ -19,6 +23,27 @@ logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/v1/platform", tags=["platform-templates"])
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# ---------- 执行模板请求体 ----------
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class ExecuteTemplateRequest(BaseModel):
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message: str = Field(..., description="用户输入/任务描述")
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parameters: Optional[Dict[str, Any]] = Field(default_factory=dict, description="模板参数覆盖")
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class ExecuteTemplateResponse(BaseModel):
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execution_id: str
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status: str
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message: str
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# ---------- 执行进度响应 ----------
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class ExecutionProgressResponse(BaseModel):
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execution_id: str
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status: str
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progress_pct: int = 0
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output: Optional[str] = None
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error: Optional[str] = None
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execution_time_ms: Optional[int] = None
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@router.get("/scene-templates", response_model=List[SceneTemplateItem])
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async def list_scene_templates_v1(current_user: User = Depends(get_current_user)):
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@@ -70,3 +95,183 @@ async def create_agent_from_template_v1(
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f"用户 {current_user.username} 从模板 {body.template_id} 创建 Agent: {agent.name} ({agent.id})"
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)
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return agent
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@router.post("/templates/{template_id}/execute", response_model=ExecuteTemplateResponse)
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async def execute_template(
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template_id: str,
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body: ExecuteTemplateRequest,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""一键执行模板：生成工作流 → 创建 Execution → 触发异步执行 → 返回 execution_id 用于轮询进度。"""
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# 1. 根据模板 ID 和参数构建工作流
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try:
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workflow_config = build_workflow_for_template(
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template_id, body.parameters or {}
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)
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except ValueError as e:
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raise ValidationError(str(e))
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# 2. 校验工作流
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validation_result = validate_workflow(
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workflow_config.get("nodes", []), workflow_config.get("edges", [])
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)
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if not validation_result["valid"]:
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raise ValidationError(
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"工作流配置验证失败: " + ", ".join(validation_result["errors"])
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)
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# 3. 创建临时 Agent（内联，不持久化到 agents 表，避免污染列表）
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# 使用 name = f"平台模板执行-{template_id}" 作为标记
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agent_name = f"平台模板执行-{template_id}-{uuid.uuid4().hex[:8]}"
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temp_agent = Agent(
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name=agent_name,
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description=f"来自平台模板 {template_id} 的一次性执行",
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workflow_config=workflow_config,
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user_id=current_user.id,
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status="draft",
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)
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db.add(temp_agent)
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db.flush() # 获取 agent.id
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# 4. 创建 Execution 记录
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execution = Execution(
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agent_id=temp_agent.id,
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input_data={
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"USER_INPUT": body.message,
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"query": body.message,
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"message": body.message,
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"template_id": template_id,
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"parameters": body.parameters or {},
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},
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status="pending",
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)
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db.add(execution)
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db.flush()
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execution_id = str(execution.id)
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agent_id_str = str(temp_agent.id)
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# 5. 触发异步执行
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try:
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from app.tasks.agent_tasks import execute_agent_task
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task = execute_agent_task.delay(
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agent_id_str,
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{
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"USER_INPUT": body.message,
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"query": body.message,
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"message": body.message,
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},
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execution_id=execution_id,
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)
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execution.task_id = task.id
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execution.status = "running"
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db.commit()
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logger.info(
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f"模板执行已触发: template={template_id} execution={execution_id} "
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f"task={task.id} user={current_user.username}"
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)
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except Exception as e:
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# Celery 不可用时，回退到同步执行
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logger.warning(f"Celery 不可用，回退同步执行: {e}")
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execution.status = "running"
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db.commit()
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_run_template_sync(db, temp_agent, execution, body.message)
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return ExecuteTemplateResponse(
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execution_id=execution_id,
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status=execution.status,
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message="模板执行已触发，请通过 execution_id 轮询进度",
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)
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def _run_template_sync(db: Session, agent: Agent, execution: Execution, message: str):
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"""同步执行模板（Celery 不可用时的回退方案）。"""
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import asyncio
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from app.agent_runtime.core import AgentRuntime
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from app.agent_runtime.schemas import AgentConfig, AgentLLMConfig, AgentToolConfig, AgentMemoryConfig
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wf = agent.workflow_config or {}
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nodes = wf.get("nodes", [])
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system_prompt = "你是一个有用的AI助手。"
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model = "deepseek-v4-flash"
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provider = "deepseek"
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temperature = 0.7
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max_iterations = 10
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for n in nodes:
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cfg = n.get("data", {}) if isinstance(n, dict) else {}
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if n.get("type") in ("agent", "llm", "template"):
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system_prompt = cfg.get("system_prompt", "") or cfg.get("prompt", "") or system_prompt
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model = cfg.get("model", model)
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provider = cfg.get("provider", provider)
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temperature = float(cfg.get("temperature", temperature))
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max_iterations = int(cfg.get("max_iterations", max_iterations))
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break
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async def _run():
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config = AgentConfig(
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name=agent.name,
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system_prompt=system_prompt,
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llm=AgentLLMConfig(model=model, provider=provider, temperature=temperature, max_iterations=max_iterations),
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tools=AgentToolConfig(),
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memory=AgentMemoryConfig(),
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)
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runtime = AgentRuntime(config=config)
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return await runtime.run(message)
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try:
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loop = asyncio.get_event_loop()
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if loop.is_running():
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import nest_asyncio
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nest_asyncio.apply()
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result = asyncio.run(_run())
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except RuntimeError:
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result = asyncio.run(_run())
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import time
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execution.output_data = {"result": result.content, "iterations": result.iterations_used}
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execution.status = "completed" if result.success else "failed"
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execution.execution_time = 0
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if not result.success:
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execution.error_message = result.error
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db.commit()
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@router.get("/templates/executions/{execution_id}/progress", response_model=ExecutionProgressResponse)
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async def get_execution_progress(
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execution_id: str,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""查询模板执行进度。"""
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execution = db.query(Execution).filter(Execution.id == execution_id).first()
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if not execution:
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raise HTTPException(status_code=404, detail="执行记录不存在")
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progress_pct = 0
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if execution.status == "running":
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progress_pct = 50
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elif execution.status == "completed":
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progress_pct = 100
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elif execution.status == "failed":
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progress_pct = 100
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output = None
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if execution.output_data:
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if isinstance(execution.output_data, dict):
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output = execution.output_data.get("result") or execution.output_data.get("output") or json.dumps(execution.output_data, ensure_ascii=False)
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elif isinstance(execution.output_data, str):
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output = execution.output_data
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return ExecutionProgressResponse(
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execution_id=execution_id,
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status=execution.status,
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progress_pct=progress_pct,
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output=output,
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error=execution.error_message,
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execution_time_ms=execution.execution_time,
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)
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