chore: remove legacy startup paths

backend/api/agents.py

@@ -1,46 +1,18 @@
 # -*- coding: utf-8 -*-
-"""
-Agent API Routes
-
-Provides REST API endpoints for both:
-
-- design-time agent management under `workspaces/`
-- run-scoped agent asset access under `runs/<run_id>/`
-"""
+"""Agent API routes for design-time workspace registry CRUD only."""
 import logging
-import os
-import tempfile
 from pathlib import Path
 from typing import Any, Dict, List, Optional
 
-from fastapi import APIRouter, HTTPException, Depends, Body, UploadFile, File, Form
+from fastapi import APIRouter, HTTPException, Depends
 from pydantic import BaseModel, Field
 
 from backend.agents import AgentFactory, get_registry
-from backend.agents.workspace_manager import RunWorkspaceManager
-from backend.agents.agent_workspace import load_agent_workspace_config
-from backend.agents.skills_manager import SkillsManager
-from backend.agents.toolkit_factory import load_agent_profiles
-from backend.config.bootstrap_config import get_bootstrap_config_for_run
-from backend.llm.models import get_agent_model_info
 
 logger = logging.getLogger(__name__)
 
 router = APIRouter(prefix="/api/workspaces/{workspace_id}/agents", tags=["agents"])
 DESIGN_SCOPE = "design_workspace"
-RUNTIME_SCOPE = "runtime_run"
-RUNTIME_SCOPE_NOTE = (
-    "For profile, skills, and editable agent files, `workspace_id` is treated "
-    "as the active run id under `runs/<run_id>/`, not as the design-time "
-    "`workspaces/` registry."
-)
-
-
-def _runtime_scope_fields() -> dict[str, str]:
-    return {
-        "scope_type": RUNTIME_SCOPE,
-        "scope_note": RUNTIME_SCOPE_NOTE,
-    }
 
 
 def _design_scope_fields() -> dict[str, str]:
@@ -65,26 +37,9 @@ class CreateAgentRequest(BaseModel):
 
 
 class UpdateAgentRequest(BaseModel):
-    """Request to update an agent."""
+    """Request to update design-time agent metadata."""
     name: Optional[str] = None
     description: Optional[str] = None
-    enabled_skills: Optional[List[str]] = None
-    disabled_skills: Optional[List[str]] = None
-
-
-class InstallExternalSkillRequest(BaseModel):
-    """Request to install an external skill for one agent."""
-    source: str = Field(..., description="Directory path, zip path, or http(s) zip URL")
-    name: Optional[str] = Field(None, description="Optional override skill name")
-    activate: bool = Field(True, description="Whether to enable skill immediately")
-
-
-class LocalSkillRequest(BaseModel):
-    skill_name: str = Field(..., description="Local skill name")
-
-
-class LocalSkillContentRequest(BaseModel):
-    content: str = Field(..., description="Updated SKILL.md content")
 
 
 class AgentResponse(BaseModel):
@@ -99,54 +54,12 @@ class AgentResponse(BaseModel):
     scope_note: Optional[str] = None
 
 
-class AgentFileResponse(BaseModel):
-    """Agent file content response."""
-    filename: str
-    content: str
-    scope_type: str = RUNTIME_SCOPE
-    scope_note: Optional[str] = None
-
-
-class AgentProfileResponse(BaseModel):
-    agent_id: str
-    workspace_id: str
-    profile: Dict[str, Any]
-    scope_type: str = RUNTIME_SCOPE
-    scope_note: Optional[str] = None
-
-
-class AgentSkillsResponse(BaseModel):
-    agent_id: str
-    workspace_id: str
-    skills: List[Dict[str, Any]]
-    scope_type: str = RUNTIME_SCOPE
-    scope_note: Optional[str] = None
-
-
-class SkillDetailResponse(BaseModel):
-    agent_id: str
-    workspace_id: str
-    skill: Dict[str, Any]
-    scope_type: str = RUNTIME_SCOPE
-    scope_note: Optional[str] = None
-
-
 # Dependencies
 def get_agent_factory():
     """Get AgentFactory instance."""
     return AgentFactory()
 
 
-def get_workspace_manager():
-    """Get run-scoped asset manager for one runtime workspace/run id."""
-    return RunWorkspaceManager()
-
-
-def get_skills_manager():
-    """Get SkillsManager instance."""
-    return SkillsManager()
-
-
 # Routes
 @router.post("", response_model=AgentResponse)
 async def create_agent(
@@ -270,119 +183,6 @@ async def get_agent(
     )
 
 
-@router.get("/{agent_id}/profile", response_model=AgentProfileResponse)
-async def get_agent_profile(
-    workspace_id: str,
-    agent_id: str,
-    skills_manager: SkillsManager = Depends(get_skills_manager),
-):
-    asset_dir = skills_manager.get_agent_asset_dir(workspace_id, agent_id)
-    agent_config = load_agent_workspace_config(asset_dir / "agent.yaml")
-    profiles = load_agent_profiles()
-    profile = profiles.get(agent_id, {})
-    bootstrap = get_bootstrap_config_for_run(skills_manager.project_root, workspace_id)
-    override = bootstrap.agent_override(agent_id)
-    active_tool_groups = override.get("active_tool_groups", agent_config.active_tool_groups or profile.get("active_tool_groups", []))
-    if not isinstance(active_tool_groups, list):
-        active_tool_groups = []
-    disabled_tool_groups = agent_config.disabled_tool_groups
-    if disabled_tool_groups:
-        disabled_set = set(disabled_tool_groups)
-        active_tool_groups = [group_name for group_name in active_tool_groups if group_name not in disabled_set]
-
-    default_skills = profile.get("skills", [])
-    if not isinstance(default_skills, list):
-        default_skills = []
-    resolved_skills = skills_manager.resolve_agent_skill_names(
-        config_name=workspace_id,
-        agent_id=agent_id,
-        default_skills=default_skills,
-    )
-    prompt_files = agent_config.prompt_files or ["SOUL.md", "PROFILE.md", "AGENTS.md", "POLICY.md", "MEMORY.md"]
-    model_name, model_provider = get_agent_model_info(agent_id)
-
-    return AgentProfileResponse(
-        agent_id=agent_id,
-        workspace_id=workspace_id,
-        profile={
-            "model_name": model_name,
-            "model_provider": model_provider,
-            "prompt_files": prompt_files,
-            "default_skills": default_skills,
-            "resolved_skills": resolved_skills,
-            "active_tool_groups": active_tool_groups,
-            "disabled_tool_groups": disabled_tool_groups,
-            "enabled_skills": agent_config.enabled_skills,
-            "disabled_skills": agent_config.disabled_skills,
-        },
-        **_runtime_scope_fields(),
-    )
-
-
-@router.get("/{agent_id}/skills", response_model=AgentSkillsResponse)
-async def get_agent_skills(
-    workspace_id: str,
-    agent_id: str,
-    skills_manager: SkillsManager = Depends(get_skills_manager),
-):
-    agent_asset_dir = skills_manager.get_agent_asset_dir(workspace_id, agent_id)
-    agent_config = load_agent_workspace_config(agent_asset_dir / "agent.yaml")
-    resolved_skills = set(skills_manager.resolve_agent_skill_names(config_name=workspace_id, agent_id=agent_id, default_skills=[]))
-    enabled = set(agent_config.enabled_skills)
-    disabled = set(agent_config.disabled_skills)
-
-    payload = []
-    for item in skills_manager.list_agent_skill_catalog(workspace_id, agent_id):
-        if item.skill_name in disabled:
-            status = "disabled"
-        elif item.skill_name in enabled:
-            status = "enabled"
-        elif item.skill_name in resolved_skills:
-            status = "active"
-        else:
-            status = "available"
-        payload.append({
-            "skill_name": item.skill_name,
-            "name": item.name,
-            "description": item.description,
-            "version": item.version,
-            "source": item.source,
-            "tools": item.tools,
-            "status": status,
-        })
-
-    return AgentSkillsResponse(
-        agent_id=agent_id,
-        workspace_id=workspace_id,
-        skills=payload,
-        **_runtime_scope_fields(),
-    )
-
-
-@router.get("/{agent_id}/skills/{skill_name}", response_model=SkillDetailResponse)
-async def get_agent_skill_detail(
-    workspace_id: str,
-    agent_id: str,
-    skill_name: str,
-    skills_manager: SkillsManager = Depends(get_skills_manager),
-):
-    try:
-        detail = skills_manager.load_agent_skill_document(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            skill_name=skill_name,
-        )
-    except FileNotFoundError:
-        raise HTTPException(status_code=404, detail=f"Unknown skill: {skill_name}")
-
-    return SkillDetailResponse(
-        agent_id=agent_id,
-        workspace_id=workspace_id,
-        skill=detail,
-        **_runtime_scope_fields(),
-    )
-
-
 @router.delete("/{agent_id}")
 async def delete_agent(
     workspace_id: str,
@@ -448,16 +248,6 @@ async def update_agent(
     if metadata_updates:
         registry.update_metadata(agent_id, metadata_updates)
 
-    # Update skills if provided
-    if request.enabled_skills or request.disabled_skills:
-        skills_manager = SkillsManager()
-        skills_manager.update_agent_skill_overrides(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            enable=request.enabled_skills or [],
-            disable=request.disabled_skills or [],
-        )
-
     # Get updated info
     agent_info = registry.get(agent_id)
     return AgentResponse(
@@ -469,301 +259,3 @@ async def update_agent(
         status=agent_info.status,
         **_design_scope_fields(),
     )
-
-
-@router.post("/{agent_id}/skills/{skill_name}/enable")
-async def enable_skill(
-    workspace_id: str,
-    agent_id: str,
-    skill_name: str,
-    registry = Depends(get_registry),
-):
-    """
-    Enable a skill for an agent.
-
-    Args:
-        workspace_id: Workspace identifier
-        agent_id: Agent identifier
-        skill_name: Skill name to enable
-
-    Returns:
-        Success message
-    """
-    agent_info = registry.get(agent_id)
-    if not agent_info or agent_info.workspace_id != workspace_id:
-        raise HTTPException(status_code=404, detail=f"Agent '{agent_id}' not found")
-
-    skills_manager = SkillsManager()
-    result = skills_manager.update_agent_skill_overrides(
-        config_name=workspace_id,
-        agent_id=agent_id,
-        enable=[skill_name],
-    )
-
-    return {
-        "message": f"Skill '{skill_name}' enabled for agent '{agent_id}'",
-        "enabled_skills": result["enabled_skills"],
-    }
-
-
-@router.post("/{agent_id}/skills/{skill_name}/disable")
-async def disable_skill(
-    workspace_id: str,
-    agent_id: str,
-    skill_name: str,
-    registry = Depends(get_registry),
-):
-    """
-    Disable a skill for an agent.
-
-    Args:
-        workspace_id: Workspace identifier
-        agent_id: Agent identifier
-        skill_name: Skill name to disable
-
-    Returns:
-        Success message
-    """
-    agent_info = registry.get(agent_id)
-    if not agent_info or agent_info.workspace_id != workspace_id:
-        raise HTTPException(status_code=404, detail=f"Agent '{agent_id}' not found")
-
-    skills_manager = SkillsManager()
-    result = skills_manager.update_agent_skill_overrides(
-        config_name=workspace_id,
-        agent_id=agent_id,
-        disable=[skill_name],
-    )
-
-    return {
-        "message": f"Skill '{skill_name}' disabled for agent '{agent_id}'",
-        "disabled_skills": result["disabled_skills"],
-    }
-
-
-@router.post("/{agent_id}/skills/install")
-async def install_external_skill(
-    workspace_id: str,
-    agent_id: str,
-    request: InstallExternalSkillRequest,
-    registry=Depends(get_registry),
-):
-    """Install an external skill into one agent's local skills."""
-    agent_info = registry.get(agent_id)
-    if not agent_info or agent_info.workspace_id != workspace_id:
-        raise HTTPException(status_code=404, detail=f"Agent '{agent_id}' not found")
-
-    skills_manager = SkillsManager()
-    try:
-        result = skills_manager.install_external_skill_for_agent(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            source=request.source,
-            skill_name=request.name,
-            activate=request.activate,
-        )
-    except (FileNotFoundError, ValueError) as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-    return {
-        "message": f"Installed external skill '{result['skill_name']}' for '{agent_id}'",
-        **result,
-    }
-
-
-@router.post("/{agent_id}/skills/local")
-async def create_local_skill(
-    workspace_id: str,
-    agent_id: str,
-    request: LocalSkillRequest,
-    registry=Depends(get_registry),
-):
-    agent_info = registry.get(agent_id)
-    if not agent_info or agent_info.workspace_id != workspace_id:
-        raise HTTPException(status_code=404, detail=f"Agent '{agent_id}' not found")
-
-    skills_manager = SkillsManager()
-    try:
-        skills_manager.create_agent_local_skill(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            skill_name=request.skill_name,
-        )
-    except (ValueError, FileExistsError) as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-    return {"message": f"Created local skill '{request.skill_name}' for '{agent_id}'"}
-
-
-@router.put("/{agent_id}/skills/local/{skill_name}")
-async def update_local_skill(
-    workspace_id: str,
-    agent_id: str,
-    skill_name: str,
-    request: LocalSkillContentRequest,
-    registry=Depends(get_registry),
-):
-    agent_info = registry.get(agent_id)
-    if not agent_info or agent_info.workspace_id != workspace_id:
-        raise HTTPException(status_code=404, detail=f"Agent '{agent_id}' not found")
-
-    skills_manager = SkillsManager()
-    try:
-        skills_manager.update_agent_local_skill(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            skill_name=skill_name,
-            content=request.content,
-        )
-    except (ValueError, FileNotFoundError) as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-    return {"message": f"Updated local skill '{skill_name}' for '{agent_id}'"}
-
-
-@router.delete("/{agent_id}/skills/local/{skill_name}")
-async def delete_local_skill(
-    workspace_id: str,
-    agent_id: str,
-    skill_name: str,
-    registry=Depends(get_registry),
-):
-    agent_info = registry.get(agent_id)
-    if not agent_info or agent_info.workspace_id != workspace_id:
-        raise HTTPException(status_code=404, detail=f"Agent '{agent_id}' not found")
-
-    skills_manager = SkillsManager()
-    try:
-        skills_manager.delete_agent_local_skill(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            skill_name=skill_name,
-        )
-        skills_manager.forget_agent_skill_overrides(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            skill_names=[skill_name],
-        )
-    except (ValueError, FileNotFoundError) as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-    return {"message": f"Deleted local skill '{skill_name}' for '{agent_id}'"}
-
-
-@router.post("/{agent_id}/skills/upload")
-async def upload_external_skill(
-    workspace_id: str,
-    agent_id: str,
-    file: UploadFile = File(...),
-    name: Optional[str] = Form(None),
-    activate: bool = Form(True),
-    registry=Depends(get_registry),
-):
-    """Upload a zip skill package from frontend and install for one agent."""
-    agent_info = registry.get(agent_id)
-    if not agent_info or agent_info.workspace_id != workspace_id:
-        raise HTTPException(status_code=404, detail=f"Agent '{agent_id}' not found")
-
-    original_name = (file.filename or "").strip()
-    if not original_name.lower().endswith(".zip"):
-        raise HTTPException(status_code=400, detail="Uploaded file must be a .zip archive")
-
-    suffix = Path(original_name).suffix or ".zip"
-    temp_path: Optional[str] = None
-    try:
-        with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
-            temp_path = tmp.name
-            content = await file.read()
-            tmp.write(content)
-
-        skills_manager = SkillsManager()
-        result = skills_manager.install_external_skill_for_agent(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            source=temp_path,
-            skill_name=name,
-            activate=activate,
-        )
-    except (FileNotFoundError, ValueError) as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-    finally:
-        try:
-            await file.close()
-        except Exception as e:
-            logger.warning(f"Failed to close uploaded file: {e}")
-        if temp_path and os.path.exists(temp_path):
-            os.remove(temp_path)
-
-    return {
-        "message": f"Uploaded and installed external skill '{result['skill_name']}' for '{agent_id}'",
-        **result,
-    }
-
-
-@router.get("/{agent_id}/files/{filename}", response_model=AgentFileResponse)
-async def get_agent_file(
-    workspace_id: str,
-    agent_id: str,
-    filename: str,
-    workspace_manager: RunWorkspaceManager = Depends(get_workspace_manager),
-):
-    """
-    Read an agent file from the run-scoped asset tree under `runs/<run_id>/`.
-
-    Args:
-        workspace_id: Workspace identifier
-        agent_id: Agent identifier
-        filename: File to read (e.g., SOUL.md, PROFILE.md)
-
-    Returns:
-        File content
-    """
-    try:
-        content = workspace_manager.load_agent_file(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            filename=filename,
-        )
-        return AgentFileResponse(
-            filename=filename,
-            content=content,
-            **_runtime_scope_fields(),
-        )
-    except FileNotFoundError:
-        raise HTTPException(status_code=404, detail=f"File '{filename}' not found")
-
-
-@router.put("/{agent_id}/files/{filename}", response_model=AgentFileResponse)
-async def update_agent_file(
-    workspace_id: str,
-    agent_id: str,
-    filename: str,
-    content: str = Body(..., media_type="text/plain"),
-    workspace_manager: RunWorkspaceManager = Depends(get_workspace_manager),
-):
-    """
-    Update an agent file in the run-scoped asset tree under `runs/<run_id>/`.
-
-    Args:
-        workspace_id: Workspace identifier
-        agent_id: Agent identifier
-        filename: File to update
-        content: New file content
-
-    Returns:
-        Updated file information
-    """
-    try:
-        workspace_manager.update_agent_file(
-            config_name=workspace_id,
-            agent_id=agent_id,
-            filename=filename,
-            content=content,
-        )
-        return AgentFileResponse(
-            filename=filename,
-            content=content,
-            **_runtime_scope_fields(),
-        )
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))

backend/api/runs.py

@@ -6,7 +6,7 @@ Provides REST API endpoints for runtime agent asset access under `runs/<run_id>/
 
 This module separates runtime concerns from design-time workspace management:
 - `/api/runs/{run_id}/agents/*` - Runtime agent assets and configuration
-- `/api/workspaces/{workspace_id}/agents/*` - Design-time workspace registry (deprecated)
+- design-time workspace registry CRUD lives under `/api/workspaces/{workspace_id}/...`
 """
 import logging
 import os

backend/api/runtime.py

@@ -29,6 +29,17 @@ router = APIRouter(prefix="/api/runtime", tags=["runtime"])
 PROJECT_ROOT = Path(__file__).resolve().parents[2]
 
 
+def _normalize_schedule_mode(value: Any) -> str:
+    """Normalize schedule mode to the current public vocabulary.
+
+    `intraday` is kept as a backward-compatible alias for `interval`.
+    """
+    mode = str(value or "daily").strip().lower()
+    if mode == "intraday":
+        return "interval"
+    return mode or "daily"
+
+
 class RuntimeState:
     """Thread-safe singleton for managing runtime state.
 
@@ -439,6 +450,11 @@ def _is_gateway_running() -> bool:
 
     Checks both the internally-managed gateway process and falls back to
     port availability (for externally-managed gateway processes).
+
+    The fallback matters because this codebase may still encounter two startup
+    shapes while historical artifacts remain in-tree:
+    1. runtime_service-managed Gateway subprocesses
+    2. externally started historical Gateway processes outside the supported dev flow
     """
     process = _runtime_state.gateway_process
     if process is not None and process.poll() is None:
@@ -481,7 +497,11 @@ def _start_gateway_process(
     bootstrap: Dict[str, Any],
     port: int
 ) -> subprocess.Popen:
-    """Start Gateway as a separate process."""
+    """Start Gateway as a runtime_service-managed subprocess.
+
+    This path is used when runtime lifecycle is driven through the runtime API.
+    It is not the only supported way a Gateway may exist in the current repo.
+    """
     # Validate configuration before starting
     validation_errors = _validate_gateway_config(bootstrap)
     if validation_errors:
@@ -592,9 +612,9 @@ def _validate_gateway_config(bootstrap: Dict[str, Any]) -> List[str]:
                 errors.append("Dates must be in YYYY-MM-DD format")
 
     # Validate schedule mode
-    schedule_mode = bootstrap.get("schedule_mode", "daily")
-    if schedule_mode not in ("daily", "intraday"):
-        errors.append(f"Invalid schedule_mode '{schedule_mode}': must be 'daily' or 'intraday'")
+    schedule_mode = _normalize_schedule_mode(bootstrap.get("schedule_mode", "daily"))
+    if schedule_mode not in ("daily", "interval"):
+        errors.append(f"Invalid schedule_mode '{schedule_mode}': must be 'daily' or 'interval'")
 
     return errors
 
@@ -778,7 +798,7 @@ async def get_runtime_mode() -> RuntimeModeResponse:
             mode=mode,
             is_backtest=mode == "backtest",
             run_id=context.get("config_name"),
-            schedule_mode=bootstrap.get("schedule_mode"),
+            schedule_mode=_normalize_schedule_mode(bootstrap.get("schedule_mode")),
             is_running=True,
         )
     except HTTPException:
@@ -909,7 +929,7 @@ def _resolve_runtime_response(run_id: str) -> RuntimeConfigResponse:
         project_root=PROJECT_ROOT,
         config_name=run_id,
         enable_memory=bool(bootstrap.get("enable_memory", False)),
-        schedule_mode=str(bootstrap.get("schedule_mode", "daily")),
+        schedule_mode=_normalize_schedule_mode(bootstrap.get("schedule_mode", "daily")),
         interval_minutes=int(bootstrap.get("interval_minutes", 60) or 60),
         trigger_time=str(bootstrap.get("trigger_time", "09:30") or "09:30"),
     )
@@ -929,11 +949,11 @@ def _normalize_runtime_config_updates(
     updates: Dict[str, Any] = {}
 
     if request.schedule_mode is not None:
-        schedule_mode = str(request.schedule_mode).strip().lower()
-        if schedule_mode not in {"daily", "intraday"}:
+        schedule_mode = _normalize_schedule_mode(request.schedule_mode)
+        if schedule_mode not in {"daily", "interval"}:
             raise HTTPException(
                 status_code=400,
-                detail="schedule_mode must be 'daily' or 'intraday'",
+                detail="schedule_mode must be 'daily' or 'interval'",
             )
         updates["schedule_mode"] = schedule_mode
 

backend/apps/agent_service.py

@@ -31,8 +31,7 @@ def _build_scope_payload(project_root: Path) -> dict[str, object]:
         },
         "agent_route_note": (
             "Runtime routes use `/api/runs/{run_id}/agents/...`. "
-            "Legacy `/api/workspaces/{workspace_id}/agents/...` routes are deprecated "
-            "but remain for backward compatibility."
+            "Design-time CRUD routes use `/api/workspaces/{workspace_id}/agents/...`."
         ),
     }
 

backend/core/pipeline_runner.py

@@ -4,6 +4,12 @@ Pipeline Runner - Independent trading pipeline execution
 
 This module provides functions to start/stop trading pipelines
 that can be called from the REST API.
+
+COMPATIBILITY_NOTE:
+This module still carries selected fallback creation paths used by managed
+runtime startup and compatibility flows. New runtime behavior should be judged
+against the run-scoped helpers and current pipeline selection rules rather than
+assuming every constructor here is the long-term default.
 """
 
 from __future__ import annotations
@@ -11,6 +17,7 @@ from __future__ import annotations
 import asyncio
 import os
 from contextlib import AsyncExitStack
+from dataclasses import dataclass
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Callable
 
@@ -22,7 +29,7 @@ from backend.agents.prompt_loader import get_prompt_loader
 from backend.agents.workspace_manager import WorkspaceManager
 from backend.config.constants import ANALYST_TYPES
 from backend.core.pipeline import TradingPipeline
-from backend.core.scheduler import BacktestScheduler, Scheduler
+from backend.core.scheduler import BacktestScheduler, Scheduler, normalize_schedule_mode
 from backend.llm.models import get_agent_formatter, get_agent_model
 from backend.runtime.manager import (
     TradingRuntimeManager,
@@ -46,6 +53,21 @@ _gateway_instance: Optional[Gateway] = None
 _long_term_memories: List[Any] = []
 
 
+@dataclass
+class GatewayRuntimeBundle:
+    """Assembled runtime components for a Gateway-backed execution path."""
+
+    runtime_manager: TradingRuntimeManager
+    market_service: MarketService
+    storage_service: StorageService
+    pipeline: TradingPipeline
+    gateway: Gateway
+    scheduler: Optional[Scheduler]
+    scheduler_callback: Optional[Callable]
+    long_term_memories: List[Any]
+    trading_dates: List[str]
+
+
 def _set_gateway(gateway: Optional[Gateway]) -> None:
     """Set global gateway reference."""
     global _gateway_instance
@@ -443,6 +465,151 @@ def create_agents(
     return analysts, risk_manager, portfolio_manager, long_term_memories
 
 
+def build_gateway_runtime_bundle(
+    *,
+    run_id: str,
+    run_dir: Path,
+    bootstrap: Dict[str, Any],
+    poll_interval: int = 10,
+) -> GatewayRuntimeBundle:
+    """Build the full Gateway runtime component graph for one run."""
+    tickers = bootstrap.get("tickers", ["AAPL", "MSFT", "GOOGL", "AMZN", "NVDA", "META", "TSLA", "AMD", "NFLX", "AVGO", "PLTR", "COIN"])
+    initial_cash = float(bootstrap.get("initial_cash", 100000.0))
+    margin_requirement = float(bootstrap.get("margin_requirement", 0.0))
+    max_comm_cycles = int(bootstrap.get("max_comm_cycles", 2))
+    schedule_mode = normalize_schedule_mode(bootstrap.get("schedule_mode", "daily"))
+    trigger_time = bootstrap.get("trigger_time", "09:30")
+    interval_minutes = int(bootstrap.get("interval_minutes", 60))
+    heartbeat_interval = int(bootstrap.get("heartbeat_interval", 0))
+    mode = bootstrap.get("mode", "live")
+    start_date = bootstrap.get("start_date")
+    end_date = bootstrap.get("end_date")
+    enable_memory = bootstrap.get("enable_memory", False)
+
+    is_backtest = mode == "backtest"
+
+    runtime_manager = TradingRuntimeManager(
+        config_name=run_id,
+        run_dir=run_dir,
+        bootstrap=bootstrap,
+    )
+    runtime_manager.prepare_run()
+
+    market_service = MarketService(
+        tickers=tickers,
+        poll_interval=poll_interval,
+        backtest_mode=is_backtest,
+        api_key=os.getenv("FINNHUB_API_KEY") if not is_backtest else None,
+        backtest_start_date=start_date if is_backtest else None,
+        backtest_end_date=end_date if is_backtest else None,
+    )
+
+    storage_service = StorageService(
+        dashboard_dir=run_dir / "team_dashboard",
+        initial_cash=initial_cash,
+        config_name=run_id,
+    )
+    if not storage_service.files["summary"].exists():
+        storage_service.initialize_empty_dashboard()
+    else:
+        storage_service.update_leaderboard_model_info()
+
+    analysts, risk_manager, pm, long_term_memories = create_agents(
+        run_id=run_id,
+        run_dir=run_dir,
+        initial_cash=initial_cash,
+        margin_requirement=margin_requirement,
+        enable_long_term_memory=enable_memory,
+    )
+    for agent in analysts + [risk_manager, pm]:
+        agent_id = getattr(agent, "agent_id", None) or getattr(agent, "name", None)
+        if agent_id:
+            runtime_manager.register_agent(agent_id)
+
+    portfolio_state = storage_service.load_portfolio_state()
+    pm.load_portfolio_state(portfolio_state)
+
+    settlement_coordinator = SettlementCoordinator(
+        storage=storage_service,
+        initial_capital=initial_cash,
+    )
+    pipeline = TradingPipeline(
+        analysts=analysts,
+        risk_manager=risk_manager,
+        portfolio_manager=pm,
+        settlement_coordinator=settlement_coordinator,
+        max_comm_cycles=max_comm_cycles,
+        runtime_manager=runtime_manager,
+    )
+
+    scheduler_callback = None
+    live_scheduler = None
+    trading_dates: List[str] = []
+
+    if is_backtest:
+        backtest_scheduler = BacktestScheduler(
+            start_date=start_date,
+            end_date=end_date,
+            trading_calendar="NYSE",
+            delay_between_days=0.5,
+        )
+        trading_dates = backtest_scheduler.get_trading_dates()
+
+        async def scheduler_callback_fn(callback):
+            await backtest_scheduler.start(callback)
+
+        scheduler_callback = scheduler_callback_fn
+    else:
+        live_scheduler = Scheduler(
+            mode=schedule_mode,
+            trigger_time=trigger_time,
+            interval_minutes=interval_minutes,
+            heartbeat_interval=heartbeat_interval if heartbeat_interval > 0 else None,
+            config={"config_name": run_id},
+        )
+
+        async def scheduler_callback_fn(callback):
+            await live_scheduler.start(callback)
+
+        scheduler_callback = scheduler_callback_fn
+
+    gateway = Gateway(
+        market_service=market_service,
+        storage_service=storage_service,
+        pipeline=pipeline,
+        scheduler_callback=scheduler_callback,
+        config={
+            "mode": mode,
+            "backtest_mode": is_backtest,
+            "tickers": tickers,
+            "config_name": run_id,
+            "schedule_mode": schedule_mode,
+            "interval_minutes": interval_minutes,
+            "trigger_time": trigger_time,
+            "heartbeat_interval": heartbeat_interval,
+            "initial_cash": initial_cash,
+            "margin_requirement": margin_requirement,
+            "max_comm_cycles": max_comm_cycles,
+            "enable_memory": enable_memory,
+        },
+        scheduler=live_scheduler,
+    )
+    if is_backtest:
+        gateway.set_backtest_dates(trading_dates)
+
+    return GatewayRuntimeBundle(
+        runtime_manager=runtime_manager,
+        market_service=market_service,
+        storage_service=storage_service,
+        pipeline=pipeline,
+        gateway=gateway,
+        scheduler=live_scheduler,
+        scheduler_callback=scheduler_callback,
+        long_term_memories=long_term_memories,
+        trading_dates=trading_dates,
+    )
+
+
 async def run_pipeline(
     run_id: str,
     run_dir: Path,
@@ -483,7 +650,7 @@ async def run_pipeline(
         initial_cash = float(bootstrap.get("initial_cash", 100000.0))
         margin_requirement = float(bootstrap.get("margin_requirement", 0.0))
         max_comm_cycles = int(bootstrap.get("max_comm_cycles", 2))
-        schedule_mode = bootstrap.get("schedule_mode", "daily")
+        schedule_mode = normalize_schedule_mode(bootstrap.get("schedule_mode", "daily"))
         trigger_time = bootstrap.get("trigger_time", "09:30")
         interval_minutes = int(bootstrap.get("interval_minutes", 60))
         heartbeat_interval = int(bootstrap.get("heartbeat_interval", 0))

backend/gateway_server.py

@@ -1,15 +1,14 @@
 # -*- coding: utf-8 -*-
-"""Gateway Server - Entry point for Gateway subprocess.
+"""Gateway Server - Entry point for the managed Gateway subprocess.
 
-This module is launched as a subprocess by the Control Plane (FastAPI)
-to run the Data Plane (Gateway + Pipeline).
+This module is launched by `runtime_service` when the runtime API is used to
+spawn a run-scoped Gateway process.
 """
 
 import argparse
 import asyncio
 import json
 import logging
-import os
 import sys
 from contextlib import AsyncExitStack
 from pathlib import Path
@@ -19,22 +18,13 @@ from dotenv import load_dotenv
 # Load environment variables
 load_dotenv()
 
-from backend.agents.prompt_loader import get_prompt_loader
-from backend.core.pipeline import TradingPipeline
-from backend.core.pipeline_runner import create_agents
-from backend.core.scheduler import BacktestScheduler, Scheduler
+from backend.core.pipeline_runner import build_gateway_runtime_bundle
 from backend.runtime.manager import (
-    TradingRuntimeManager,
     set_global_runtime_manager,
     clear_global_runtime_manager,
 )
-from backend.services.gateway import Gateway
-from backend.services.market import MarketService
-from backend.services.storage import StorageService
-from backend.utils.settlement import SettlementCoordinator
 
 logger = logging.getLogger(__name__)
-_prompt_loader = get_prompt_loader()
 
 
 INFO_LOGGER_PREFIXES = (
@@ -110,153 +100,24 @@ async def run_gateway(
     port: int
 ):
     """Run Gateway with Pipeline."""
-
-    # Extract config
-    tickers = bootstrap.get("tickers", ["AAPL", "MSFT", "GOOGL", "AMZN", "NVDA", "META", "TSLA", "AMD", "NFLX", "AVGO", "PLTR", "COIN"])
-    initial_cash = float(bootstrap.get("initial_cash", 100000.0))
-    margin_requirement = float(bootstrap.get("margin_requirement", 0.0))
-    max_comm_cycles = int(bootstrap.get("max_comm_cycles", 2))
-    schedule_mode = bootstrap.get("schedule_mode", "daily")
-    trigger_time = bootstrap.get("trigger_time", "09:30")
-    interval_minutes = int(bootstrap.get("interval_minutes", 60))
-    heartbeat_interval = int(bootstrap.get("heartbeat_interval", 0))  # 0 = disabled
-    mode = bootstrap.get("mode", "live")
-    start_date = bootstrap.get("start_date")
-    end_date = bootstrap.get("end_date")
-    enable_memory = bootstrap.get("enable_memory", False)
     poll_interval = int(bootstrap.get("poll_interval", 10))
 
-    is_backtest = mode == "backtest"
-
     logger.info(f"[Gateway Server] Starting run {run_id} on port {port}")
 
-    # Create runtime manager
-    runtime_manager = TradingRuntimeManager(
-        config_name=run_id,
-        run_dir=run_dir,
-        bootstrap=bootstrap,
-    )
-    runtime_manager.prepare_run()
-    set_global_runtime_manager(runtime_manager)
-
     try:
+        bundle = build_gateway_runtime_bundle(
+            run_id=run_id,
+            run_dir=run_dir,
+            bootstrap=bootstrap,
+            poll_interval=poll_interval,
+        )
+        set_global_runtime_manager(bundle.runtime_manager)
+
         async with AsyncExitStack() as stack:
-            # Create services
-            market_service = MarketService(
-                tickers=tickers,
-                poll_interval=poll_interval,
-                backtest_mode=is_backtest,
-                api_key=os.getenv("FINNHUB_API_KEY") if not is_backtest else None,
-                backtest_start_date=start_date if is_backtest else None,
-                backtest_end_date=end_date if is_backtest else None,
-            )
-
-            storage_service = StorageService(
-                dashboard_dir=run_dir / "team_dashboard",
-                initial_cash=initial_cash,
-                config_name=run_id,
-            )
-
-            if not storage_service.files["summary"].exists():
-                storage_service.initialize_empty_dashboard()
-            else:
-                storage_service.update_leaderboard_model_info()
-
-            # Create agents
-            analysts, risk_manager, pm, long_term_memories = create_agents(
-                run_id=run_id,
-                run_dir=run_dir,
-                initial_cash=initial_cash,
-                margin_requirement=margin_requirement,
-                enable_long_term_memory=enable_memory,
-            )
-
-            # Register agents
-            for agent in analysts + [risk_manager, pm]:
-                agent_id = getattr(agent, "agent_id", None) or getattr(agent, "name", None)
-                if agent_id:
-                    runtime_manager.register_agent(agent_id)
-
-            # Load portfolio state
-            portfolio_state = storage_service.load_portfolio_state()
-            pm.load_portfolio_state(portfolio_state)
-
-            # Create settlement coordinator
-            settlement_coordinator = SettlementCoordinator(
-                storage=storage_service,
-                initial_capital=initial_cash,
-            )
-
-            # Create pipeline
-            pipeline = TradingPipeline(
-                analysts=analysts,
-                risk_manager=risk_manager,
-                portfolio_manager=pm,
-                settlement_coordinator=settlement_coordinator,
-                max_comm_cycles=max_comm_cycles,
-                runtime_manager=runtime_manager,
-            )
-
-            # Create scheduler
-            scheduler_callback = None
-            live_scheduler = None
-
-            if is_backtest:
-                backtest_scheduler = BacktestScheduler(
-                    start_date=start_date,
-                    end_date=end_date,
-                    trading_calendar="NYSE",
-                    delay_between_days=0.5,
-                )
-
-                async def scheduler_callback_fn(callback):
-                    await backtest_scheduler.start(callback)
-
-                scheduler_callback = scheduler_callback_fn
-            else:
-                live_scheduler = Scheduler(
-                    mode=schedule_mode,
-                    trigger_time=trigger_time,
-                    interval_minutes=interval_minutes,
-                    heartbeat_interval=heartbeat_interval if heartbeat_interval > 0 else None,
-                    config={"config_name": run_id},
-                )
-
-                async def scheduler_callback_fn(callback):
-                    await live_scheduler.start(callback)
-
-                scheduler_callback = scheduler_callback_fn
-
-            # Enter long-term memory contexts
-            for memory in long_term_memories:
+            for memory in bundle.long_term_memories:
                 await stack.enter_async_context(memory)
-
-            # Create Gateway
-            gateway = Gateway(
-                market_service=market_service,
-                storage_service=storage_service,
-                pipeline=pipeline,
-                scheduler_callback=scheduler_callback,
-                config={
-                    "mode": mode,
-                    "backtest_mode": is_backtest,
-                    "tickers": tickers,
-                    "config_name": run_id,
-                    "schedule_mode": schedule_mode,
-                    "interval_minutes": interval_minutes,
-                    "trigger_time": trigger_time,
-                    "heartbeat_interval": heartbeat_interval,
-                    "initial_cash": initial_cash,
-                    "margin_requirement": margin_requirement,
-                    "max_comm_cycles": max_comm_cycles,
-                    "enable_memory": enable_memory,
-                },
-                scheduler=live_scheduler,
-            )
-
-            # Start Gateway (blocks until shutdown)
             logger.info(f"[Gateway Server] Gateway starting on port {port}")
-            await gateway.start(host="0.0.0.0", port=port)
+            await bundle.gateway.start(host="0.0.0.0", port=port)
 
     except asyncio.CancelledError:
         logger.info("[Gateway Server] Cancelled")

backend/main.py

@@ -1,596 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Main Entry Point
-Supports: backtest, live modes
-"""
-import argparse
-import asyncio
-import logging
-import os
-from contextlib import AsyncExitStack
-from pathlib import Path
-import loguru
-
-from dotenv import load_dotenv
-
-from backend.agents import EvoAgent
-from backend.agents.agent_workspace import load_agent_workspace_config
-from backend.agents.skills_manager import SkillsManager
-from backend.agents.toolkit_factory import create_agent_toolkit, load_agent_profiles
-from backend.agents.prompt_loader import get_prompt_loader
-# WorkspaceManager is RunWorkspaceManager - provides run-scoped asset management
-# All runtime state lives under runs/<run_id>/
-from backend.agents.workspace_manager import WorkspaceManager
-from backend.config.bootstrap_config import resolve_runtime_config
-from backend.config.constants import ANALYST_TYPES
-from backend.core.pipeline import TradingPipeline
-from backend.core.scheduler import BacktestScheduler, Scheduler
-from backend.llm.models import get_agent_formatter, get_agent_model
-from backend.api.runtime import unregister_runtime_manager
-from backend.runtime.manager import (
-    TradingRuntimeManager,
-    set_global_runtime_manager,
-    clear_global_runtime_manager,
-)
-from backend.gateway_server import configure_gateway_logging
-from backend.services.gateway import Gateway
-from backend.services.market import MarketService
-from backend.services.storage import StorageService
-from backend.utils.settlement import SettlementCoordinator
-
-load_dotenv()
-logger = logging.getLogger(__name__)
-loguru.logger.disable("flowllm")
-loguru.logger.disable("reme_ai")
-configure_gateway_logging(verbose=os.getenv("LOG_LEVEL", "").upper() == "DEBUG")
-_prompt_loader = get_prompt_loader()
-
-
-def _get_run_dir(config_name: str) -> Path:
-    """Return the canonical run-scoped directory for a config.
-
-    This is the authoritative path for runtime state under runs/<run_id>/.
-    All runtime assets, state, and exports are scoped to this directory.
-    """
-    project_root = Path(__file__).resolve().parents[1]
-    # Use RunWorkspaceManager for run-scoped path resolution
-    return WorkspaceManager(project_root=project_root).get_run_dir(config_name)
-
-
-def _resolve_runtime_config(args) -> dict:
-    """Merge env defaults with run-scoped bootstrap config."""
-    project_root = Path(__file__).resolve().parents[1]
-    return resolve_runtime_config(
-        project_root=project_root,
-        config_name=args.config_name,
-        enable_memory=args.enable_memory,
-        schedule_mode=args.schedule_mode,
-        interval_minutes=args.interval_minutes,
-        trigger_time=args.trigger_time,
-    )
-
-
-def create_long_term_memory(agent_name: str, config_name: str):
-    """
-    Create ReMeTaskLongTermMemory for an agent
-
-    Requires DASHSCOPE_API_KEY env var
-    """
-    from agentscope.memory import ReMeTaskLongTermMemory
-    from agentscope.model import DashScopeChatModel
-    from agentscope.embedding import DashScopeTextEmbedding
-
-    api_key = os.getenv("MEMORY_API_KEY")
-    if not api_key:
-        logger.warning("MEMORY_API_KEY not set, long-term memory disabled")
-        return None
-
-    memory_dir = str(_get_run_dir(config_name) / "memory")
-
-    return ReMeTaskLongTermMemory(
-        agent_name=agent_name,
-        user_name=agent_name,
-        model=DashScopeChatModel(
-            model_name=os.getenv("MEMORY_MODEL_NAME", "qwen3-max"),
-            api_key=api_key,
-            stream=False,
-        ),
-        embedding_model=DashScopeTextEmbedding(
-            model_name=os.getenv(
-                "MEMORY_EMBEDDING_MODEL",
-                "text-embedding-v4",
-            ),
-            api_key=api_key,
-            dimensions=1024,
-        ),
-        **{
-            "vector_store.default.backend": "local",
-            "vector_store.default.params.store_dir": memory_dir,
-        },
-    )
-
-
-def _resolve_evo_agent_ids() -> set[str]:
-    """Return agent ids selected to use EvoAgent.
-
-    By default, all supported roles use EvoAgent.
-    EVO_AGENT_IDS can be used to limit to specific roles (legacy behavior).
-    Set EVO_AGENT_LEGACY=1 to disable EvoAgent entirely.
-
-    Supported roles:
-    - analyst roles (fundamentals, technical, sentiment, valuation)
-    - risk_manager
-    - portfolio_manager
-
-    Example:
-        EVO_AGENT_IDS=fundamentals_analyst,risk_manager,portfolio_manager
-    """
-    from backend.config.constants import ANALYST_TYPES
-
-    all_supported = set(ANALYST_TYPES) | {"risk_manager", "portfolio_manager"}
-
-    raw = os.getenv("EVO_AGENT_IDS", "")
-    if not raw.strip():
-        # Default: all supported roles use EvoAgent
-        return all_supported
-
-    if raw.strip().lower() in ("legacy", "old", "none"):
-        return set()
-
-    requested = {
-        item.strip()
-        for item in raw.split(",")
-        if item.strip()
-    }
-    return {
-        agent_id
-        for agent_id in requested
-        if agent_id in ANALYST_TYPES or agent_id in {"risk_manager", "portfolio_manager"}
-    }
-
-
-def _create_analyst_agent(
-    *,
-    analyst_type: str,
-    config_name: str,
-    model,
-    formatter,
-    skills_manager: SkillsManager,
-    active_skill_map: dict[str, list[Path]],
-    long_term_memory=None,
-):
-    """Create one analyst agent, optionally using EvoAgent."""
-    active_skill_dirs = active_skill_map.get(analyst_type, [])
-    toolkit = create_agent_toolkit(
-        analyst_type,
-        config_name,
-        active_skill_dirs=active_skill_dirs,
-    )
-
-    workspace_dir = skills_manager.get_agent_asset_dir(config_name, analyst_type)
-    agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
-    agent = EvoAgent(
-        agent_id=analyst_type,
-        config_name=config_name,
-        workspace_dir=workspace_dir,
-        model=model,
-        formatter=formatter,
-        skills_manager=skills_manager,
-        prompt_files=agent_config.prompt_files,
-        long_term_memory=long_term_memory,
-    )
-    agent.toolkit = toolkit
-    setattr(agent, "run_id", config_name)
-    # Keep workspace_id for backward compatibility
-    setattr(agent, "workspace_id", config_name)
-    return agent
-
-
-def _create_risk_manager_agent(
-    *,
-    config_name: str,
-    model,
-    formatter,
-    skills_manager: SkillsManager,
-    active_skill_map: dict[str, list[Path]],
-    long_term_memory=None,
-):
-    """Create the risk manager, optionally using EvoAgent."""
-    active_skill_dirs = active_skill_map.get("risk_manager", [])
-    toolkit = create_agent_toolkit(
-        "risk_manager",
-        config_name,
-        active_skill_dirs=active_skill_dirs,
-    )
-
-    use_evo_agent = "risk_manager" in _resolve_evo_agent_ids()
-
-    if use_evo_agent:
-        workspace_dir = skills_manager.get_agent_asset_dir(config_name, "risk_manager")
-        agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
-        agent = EvoAgent(
-            agent_id="risk_manager",
-            config_name=config_name,
-            workspace_dir=workspace_dir,
-            model=model,
-            formatter=formatter,
-            skills_manager=skills_manager,
-            prompt_files=agent_config.prompt_files,
-            long_term_memory=long_term_memory,
-        )
-        agent.toolkit = toolkit
-        setattr(agent, "run_id", config_name)
-        # Keep workspace_id for backward compatibility
-        setattr(agent, "workspace_id", config_name)
-        return agent
-
-    return RiskAgent(
-        model=model,
-        formatter=formatter,
-        name="risk_manager",
-        config={"config_name": config_name},
-        long_term_memory=long_term_memory,
-        toolkit=toolkit,
-    )
-
-
-def _create_portfolio_manager_agent(
-    *,
-    config_name: str,
-    model,
-    formatter,
-    initial_cash: float,
-    margin_requirement: float,
-    skills_manager: SkillsManager,
-    active_skill_map: dict[str, list[Path]],
-    long_term_memory=None,
-):
-    """Create the portfolio manager, optionally using EvoAgent."""
-    active_skill_dirs = active_skill_map.get("portfolio_manager", [])
-    use_evo_agent = "portfolio_manager" in _resolve_evo_agent_ids()
-
-    if use_evo_agent:
-        workspace_dir = skills_manager.get_agent_asset_dir(
-            config_name,
-            "portfolio_manager",
-        )
-        agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
-        agent = EvoAgent(
-            agent_id="portfolio_manager",
-            config_name=config_name,
-            workspace_dir=workspace_dir,
-            model=model,
-            formatter=formatter,
-            skills_manager=skills_manager,
-            prompt_files=agent_config.prompt_files,
-            initial_cash=initial_cash,
-            margin_requirement=margin_requirement,
-            long_term_memory=long_term_memory,
-        )
-        agent.toolkit = create_agent_toolkit(
-            "portfolio_manager",
-            config_name,
-            owner=agent,
-            active_skill_dirs=active_skill_dirs,
-        )
-        setattr(agent, "run_id", config_name)
-        # Keep workspace_id for backward compatibility
-        setattr(agent, "workspace_id", config_name)
-        return agent
-
-    return PMAgent(
-        name="portfolio_manager",
-        model=model,
-        formatter=formatter,
-        initial_cash=initial_cash,
-        margin_requirement=margin_requirement,
-        config={"config_name": config_name},
-        long_term_memory=long_term_memory,
-        toolkit_factory=create_agent_toolkit,
-        toolkit_factory_kwargs={
-            "active_skill_dirs": active_skill_dirs,
-        },
-    )
-
-
-def create_agents(
-    config_name: str,
-    initial_cash: float,
-    margin_requirement: float,
-    enable_long_term_memory: bool = False,
-):
-    """Create all agents for the system
-
-    Returns:
-        tuple: (analysts, risk_manager, portfolio_manager, long_term_memories)
-        long_term_memories is a list of memory
-    """
-    analysts = []
-    long_term_memories = []
-    workspace_manager = WorkspaceManager()
-    workspace_manager.initialize_default_assets(
-        config_name=config_name,
-        agent_ids=list(ANALYST_TYPES.keys())
-        + ["risk_manager", "portfolio_manager"],
-        analyst_personas=_prompt_loader.load_yaml_config("analyst", "personas"),
-    )
-    profiles = load_agent_profiles()
-    skills_manager = SkillsManager()
-    active_skill_map = skills_manager.prepare_active_skills(
-        config_name=config_name,
-        agent_defaults={
-            agent_id: profile.get("skills", [])
-            for agent_id, profile in profiles.items()
-        },
-    )
-
-    for analyst_type in ANALYST_TYPES:
-        model = get_agent_model(analyst_type)
-        formatter = get_agent_formatter(analyst_type)
-
-        long_term_memory = None
-        if enable_long_term_memory:
-            long_term_memory = create_long_term_memory(
-                analyst_type,
-                config_name,
-            )
-            if long_term_memory:
-                long_term_memories.append(long_term_memory)
-
-        analyst = _create_analyst_agent(
-            analyst_type=analyst_type,
-            config_name=config_name,
-            model=model,
-            formatter=formatter,
-            skills_manager=skills_manager,
-            active_skill_map=active_skill_map,
-            long_term_memory=long_term_memory,
-        )
-        analysts.append(analyst)
-
-    risk_long_term_memory = None
-    if enable_long_term_memory:
-        risk_long_term_memory = create_long_term_memory(
-            "risk_manager",
-            config_name,
-        )
-        if risk_long_term_memory:
-            long_term_memories.append(risk_long_term_memory)
-
-    risk_manager = _create_risk_manager_agent(
-        config_name=config_name,
-        model=get_agent_model("risk_manager"),
-        formatter=get_agent_formatter("risk_manager"),
-        skills_manager=skills_manager,
-        active_skill_map=active_skill_map,
-        long_term_memory=risk_long_term_memory,
-    )
-
-    pm_long_term_memory = None
-    if enable_long_term_memory:
-        pm_long_term_memory = create_long_term_memory(
-            "portfolio_manager",
-            config_name,
-        )
-        if pm_long_term_memory:
-            long_term_memories.append(pm_long_term_memory)
-
-    portfolio_manager = _create_portfolio_manager_agent(
-        config_name=config_name,
-        model=get_agent_model("portfolio_manager"),
-        formatter=get_agent_formatter("portfolio_manager"),
-        initial_cash=initial_cash,
-        margin_requirement=margin_requirement,
-        skills_manager=skills_manager,
-        active_skill_map=active_skill_map,
-        long_term_memory=pm_long_term_memory,
-    )
-
-    return analysts, risk_manager, portfolio_manager, long_term_memories
-async def run_with_gateway(args):
-    """Run with WebSocket gateway"""
-    is_backtest = args.mode == "backtest"
-    runtime_config = _resolve_runtime_config(args)
-
-    config_name = args.config_name
-    tickers = runtime_config["tickers"]
-    initial_cash = runtime_config["initial_cash"]
-    margin_requirement = runtime_config["margin_requirement"]
-
-    runtime_manager = TradingRuntimeManager(
-        config_name=config_name,
-        run_dir=_get_run_dir(config_name),
-        bootstrap=runtime_config,
-    )
-    runtime_manager.prepare_run()
-    set_global_runtime_manager(runtime_manager)
-
-    # Create market service
-    market_service = MarketService(
-        tickers=tickers,
-        poll_interval=args.poll_interval,
-        backtest_mode=is_backtest,
-        api_key=os.getenv("FINNHUB_API_KEY") if not is_backtest else None,
-        backtest_start_date=args.start_date if is_backtest else None,
-        backtest_end_date=args.end_date if is_backtest else None,
-    )
-
-    # Create storage service
-    storage_service = StorageService(
-        dashboard_dir=_get_run_dir(config_name) / "team_dashboard",
-        initial_cash=initial_cash,
-        config_name=config_name,
-    )
-
-    if not storage_service.files["summary"].exists():
-        storage_service.initialize_empty_dashboard()
-    else:
-        storage_service.update_leaderboard_model_info()
-
-    # Create agents and pipeline
-    analysts, risk_manager, pm, long_term_memories = create_agents(
-        config_name=config_name,
-        initial_cash=initial_cash,
-        margin_requirement=margin_requirement,
-        enable_long_term_memory=runtime_config["enable_memory"],
-    )
-    for agent in analysts + [risk_manager, pm]:
-        agent_id = getattr(agent, "agent_id", None) or getattr(agent, "name", None)
-        if agent_id:
-            runtime_manager.register_agent(agent_id)
-    portfolio_state = storage_service.load_portfolio_state()
-    pm.load_portfolio_state(portfolio_state)
-
-    settlement_coordinator = SettlementCoordinator(
-        storage=storage_service,
-        initial_capital=initial_cash,
-    )
-
-    pipeline = TradingPipeline(
-        analysts=analysts,
-        risk_manager=risk_manager,
-        portfolio_manager=pm,
-        settlement_coordinator=settlement_coordinator,
-        max_comm_cycles=runtime_config["max_comm_cycles"],
-        runtime_manager=runtime_manager,
-    )
-
-    # Create scheduler callback
-    scheduler_callback = None
-    trading_dates = []
-    live_scheduler = None
-
-    if is_backtest:
-        backtest_scheduler = BacktestScheduler(
-            start_date=args.start_date,
-            end_date=args.end_date,
-            trading_calendar="NYSE",
-            delay_between_days=0.5,
-        )
-        trading_dates = backtest_scheduler.get_trading_dates()
-
-        async def scheduler_callback_fn(callback):
-            await backtest_scheduler.start(callback)
-
-        scheduler_callback = scheduler_callback_fn
-    else:
-        # Live mode: use daily or intraday scheduler with NYSE timezone
-        live_scheduler = Scheduler(
-            mode=runtime_config["schedule_mode"],
-            trigger_time=runtime_config["trigger_time"],
-            interval_minutes=runtime_config["interval_minutes"],
-            config={"config_name": config_name},
-        )
-
-        async def scheduler_callback_fn(callback):
-            await live_scheduler.start(callback)
-
-        scheduler_callback = scheduler_callback_fn
-
-    # Create gateway
-    gateway = Gateway(
-        market_service=market_service,
-        storage_service=storage_service,
-        pipeline=pipeline,
-        scheduler_callback=scheduler_callback,
-        config={
-            "mode": args.mode,
-            "backtest_mode": is_backtest,
-            "tickers": tickers,
-            "config_name": config_name,
-            "schedule_mode": runtime_config["schedule_mode"],
-            "interval_minutes": runtime_config["interval_minutes"],
-            "trigger_time": runtime_config["trigger_time"],
-            "initial_cash": initial_cash,
-            "margin_requirement": margin_requirement,
-            "max_comm_cycles": runtime_config["max_comm_cycles"],
-            "enable_memory": runtime_config["enable_memory"],
-        },
-        scheduler=live_scheduler if not is_backtest else None,
-    )
-
-    if is_backtest:
-        gateway.set_backtest_dates(trading_dates)
-
-    # Start long-term memory contexts and run gateway
-    async with AsyncExitStack() as stack:
-        try:
-            for memory in long_term_memories:
-                await stack.enter_async_context(memory)
-            await gateway.start(host=args.host, port=args.port)
-        finally:
-            # Persist long-term memories before cleanup
-            for memory in long_term_memories:
-                try:
-                    if hasattr(memory, 'save') and callable(getattr(memory, 'save')):
-                        await memory.save()
-                except Exception as e:
-                    logger.warning(f"Failed to persist memory: {e}")
-            unregister_runtime_manager()
-            clear_global_runtime_manager()
-
-
-def build_arg_parser() -> argparse.ArgumentParser:
-    """Build the CLI parser for the gateway runtime entrypoint."""
-    parser = argparse.ArgumentParser(description="Trading System")
-    parser.add_argument("--mode", choices=["live", "backtest"], default="live")
-    parser.add_argument(
-        "--config-name",
-        default="default_run",
-        help=(
-            "Run label under runs/<config_name>; not a special root-level "
-            "live/backtest/production directory."
-        ),
-    )
-    parser.add_argument("--host", default="0.0.0.0")
-    parser.add_argument("--port", type=int, default=8765)
-    parser.add_argument(
-        "--schedule-mode",
-        choices=["daily", "intraday"],
-        default="daily",
-    )
-    parser.add_argument("--trigger-time", default="09:30")  # NYSE market open
-    parser.add_argument("--interval-minutes", type=int, default=60)
-    parser.add_argument("--poll-interval", type=int, default=10)
-    parser.add_argument("--start-date")
-    parser.add_argument("--end-date")
-    parser.add_argument(
-        "--enable-memory",
-        action="store_true",
-        help="Enable ReMeTaskLongTermMemory for agents",
-    )
-    return parser
-
-
-def main():
-    """Main entry point"""
-    parser = build_arg_parser()
-
-    args = parser.parse_args()
-
-    # Load config from env for logging
-    runtime_config = _resolve_runtime_config(args)
-    tickers = runtime_config["tickers"]
-    initial_cash = runtime_config["initial_cash"]
-
-    logger.info("=" * 60)
-    logger.info(f"Mode: {args.mode}, Config: {args.config_name}")
-    logger.info(f"Tickers: {tickers}")
-    logger.info(f"Initial Cash: ${initial_cash:,.2f}")
-    logger.info(
-        "Long-term Memory: %s",
-        "enabled" if runtime_config["enable_memory"] else "disabled",
-    )
-    if args.mode == "backtest":
-        if not args.start_date or not args.end_date:
-            parser.error(
-                "--start-date and --end-date required for backtest mode",
-            )
-        logger.info(f"Backtest: {args.start_date} to {args.end_date}")
-    logger.info("=" * 60)
-
-    asyncio.run(run_with_gateway(args))
-
-
-if __name__ == "__main__":
-    main()

backend/tests/test_agent_service_app.py

@@ -5,7 +5,7 @@
 from fastapi.testclient import TestClient
 
 from backend.apps.agent_service import create_app
-from backend.api import agents as agents_module
+from backend.api import runs as runs_module
 
 
 def test_agent_service_routes_include_control_plane_endpoints(tmp_path):
@@ -73,10 +73,10 @@ def test_agent_service_read_routes(monkeypatch, tmp_path):
         def load_agent_file(self, config_name, agent_id, filename):
             return f"{config_name}:{agent_id}:{filename}"
 
-    monkeypatch.setattr(agents_module, "load_agent_profiles", lambda: {"portfolio_manager": {"skills": ["demo_skill"]}})
-    monkeypatch.setattr(agents_module, "get_agent_model_info", lambda agent_id: ("deepseek-v3.2", "DASHSCOPE"))
+    monkeypatch.setattr(runs_module, "load_agent_profiles", lambda: {"portfolio_manager": {"skills": ["demo_skill"]}})
+    monkeypatch.setattr(runs_module, "get_agent_model_info", lambda agent_id: ("deepseek-v3.2", "DASHSCOPE"))
     monkeypatch.setattr(
-        agents_module,
+        runs_module,
         "load_agent_workspace_config",
         lambda path: type(
             "Cfg",
@@ -91,20 +91,20 @@ def test_agent_service_read_routes(monkeypatch, tmp_path):
         )(),
     )
     monkeypatch.setattr(
-        agents_module,
+        runs_module,
         "get_bootstrap_config_for_run",
         lambda project_root, config_name: type("Bootstrap", (), {"agent_override": lambda self, agent_id: {}})(),
     )
 
     app = create_app(project_root=tmp_path)
-    app.dependency_overrides[agents_module.get_skills_manager] = lambda: _FakeSkillsManager()
-    app.dependency_overrides[agents_module.get_workspace_manager] = lambda: _FakeWorkspaceManager()
+    app.dependency_overrides[runs_module.get_skills_manager] = lambda: _FakeSkillsManager()
+    app.dependency_overrides[runs_module.get_workspace_manager] = lambda: _FakeWorkspaceManager()
 
     with TestClient(app) as client:
-        profile = client.get("/api/workspaces/demo/agents/portfolio_manager/profile")
-        skills = client.get("/api/workspaces/demo/agents/portfolio_manager/skills")
-        detail = client.get("/api/workspaces/demo/agents/portfolio_manager/skills/demo_skill")
-        workspace_file = client.get("/api/workspaces/demo/agents/portfolio_manager/files/MEMORY.md")
+        profile = client.get("/api/runs/demo/agents/portfolio_manager/profile")
+        skills = client.get("/api/runs/demo/agents/portfolio_manager/skills")
+        detail = client.get("/api/runs/demo/agents/portfolio_manager/skills/demo_skill")
+        workspace_file = client.get("/api/runs/demo/agents/portfolio_manager/files/MEMORY.md")
 
     assert profile.status_code == 200
     assert profile.json()["profile"]["model_name"] == "deepseek-v3.2"
@@ -118,4 +118,3 @@ def test_agent_service_read_routes(monkeypatch, tmp_path):
     assert workspace_file.status_code == 200
     assert workspace_file.json()["content"] == "demo:portfolio_manager:MEMORY.md"
     assert workspace_file.json()["scope_type"] == "runtime_run"
-    assert "runs/<run_id>" in workspace_file.json()["scope_note"]

backend/tests/test_evo_agent_selection.py

@@ -6,14 +6,14 @@ from pathlib import Path
 
 
 def test_main_resolve_evo_agent_ids_filters_unsupported_roles(monkeypatch):
-    from backend import main as main_module
+    from backend.core import pipeline_runner as runner_module
 
     monkeypatch.setenv(
         "EVO_AGENT_IDS",
         "fundamentals_analyst,portfolio_manager,unknown,technical_analyst",
     )
 
-    resolved = main_module._resolve_evo_agent_ids()
+    resolved = runner_module._resolve_evo_agent_ids()
 
     assert resolved == {"fundamentals_analyst", "portfolio_manager", "technical_analyst"}
 
@@ -29,7 +29,7 @@ def test_pipeline_runner_resolve_evo_agent_ids_keeps_supported_roles(monkeypatch
 
 
 def test_main_create_analyst_agent_can_build_evo_agent(monkeypatch, tmp_path):
-    from backend import main as main_module
+    from backend.core import pipeline_runner as runner_module
 
     created = {}
 
@@ -49,12 +49,12 @@ def test_main_create_analyst_agent_can_build_evo_agent(monkeypatch, tmp_path):
             self.toolkit = None
 
     monkeypatch.setenv("EVO_AGENT_IDS", "fundamentals_analyst")
-    monkeypatch.setattr(main_module, "EvoAgent", DummyEvoAgent)
-    monkeypatch.setattr(main_module, "create_agent_toolkit", lambda *args, **kwargs: "toolkit")
+    monkeypatch.setattr(runner_module, "EvoAgent", DummyEvoAgent)
+    monkeypatch.setattr(runner_module, "create_agent_toolkit", lambda *args, **kwargs: "toolkit")
 
-    agent = main_module._create_analyst_agent(
+    agent = runner_module._create_analyst_agent(
         analyst_type="fundamentals_analyst",
-        config_name="demo",
+        run_id="demo",
         model="model",
         formatter="formatter",
         skills_manager=DummySkillsManager(),
@@ -71,7 +71,7 @@ def test_main_create_analyst_agent_can_build_evo_agent(monkeypatch, tmp_path):
 
 
 def test_main_create_risk_manager_can_build_evo_agent(monkeypatch, tmp_path):
-    from backend import main as main_module
+    from backend.core import pipeline_runner as runner_module
 
     created = {}
 
@@ -91,11 +91,11 @@ def test_main_create_risk_manager_can_build_evo_agent(monkeypatch, tmp_path):
             self.toolkit = None
 
     monkeypatch.setenv("EVO_AGENT_IDS", "risk_manager")
-    monkeypatch.setattr(main_module, "EvoAgent", DummyEvoAgent)
-    monkeypatch.setattr(main_module, "create_agent_toolkit", lambda *args, **kwargs: "risk-toolkit")
+    monkeypatch.setattr(runner_module, "EvoAgent", DummyEvoAgent)
+    monkeypatch.setattr(runner_module, "create_agent_toolkit", lambda *args, **kwargs: "risk-toolkit")
 
-    agent = main_module._create_risk_manager_agent(
-        config_name="demo",
+    agent = runner_module._create_risk_manager_agent(
+        run_id="demo",
         model="model",
         formatter="formatter",
         skills_manager=DummySkillsManager(),
@@ -112,7 +112,7 @@ def test_main_create_risk_manager_can_build_evo_agent(monkeypatch, tmp_path):
 
 
 def test_main_create_portfolio_manager_can_build_evo_agent(monkeypatch, tmp_path):
-    from backend import main as main_module
+    from backend.core import pipeline_runner as runner_module
 
     created = {}
 
@@ -132,15 +132,15 @@ def test_main_create_portfolio_manager_can_build_evo_agent(monkeypatch, tmp_path
             self.toolkit = None
 
     monkeypatch.setenv("EVO_AGENT_IDS", "portfolio_manager")
-    monkeypatch.setattr(main_module, "EvoAgent", DummyEvoAgent)
+    monkeypatch.setattr(runner_module, "EvoAgent", DummyEvoAgent)
     monkeypatch.setattr(
-        main_module,
+        runner_module,
         "create_agent_toolkit",
         lambda *args, **kwargs: "pm-toolkit",
     )
 
-    agent = main_module._create_portfolio_manager_agent(
-        config_name="demo",
+    agent = runner_module._create_portfolio_manager_agent(
+        run_id="demo",
         model="model",
         formatter="formatter",
         initial_cash=12345.0,
@@ -372,13 +372,13 @@ def test_pipeline_create_runtime_analyst_uses_legacy_when_not_in_evo_ids(monkeyp
 
 def test_main_resolve_evo_agent_ids_returns_all_by_default(monkeypatch):
     """Test that _resolve_evo_agent_ids returns all supported roles by default."""
-    from backend import main as main_module
+    from backend.core import pipeline_runner as runner_module
     from backend.config.constants import ANALYST_TYPES
 
     # Unset EVO_AGENT_IDS to test default behavior
     monkeypatch.delenv("EVO_AGENT_IDS", raising=False)
 
-    resolved = main_module._resolve_evo_agent_ids()
+    resolved = runner_module._resolve_evo_agent_ids()
 
     expected = set(ANALYST_TYPES) | {"risk_manager", "portfolio_manager"}
     assert resolved == expected