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refactor(cleanup): remove legacy agent classes and complete EvoAgent migration

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Remove deprecated AnalystAgent, PMAgent, and RiskAgent classes.
All agent creation now goes through UnifiedAgentFactory creating EvoAgent instances.

- Delete backend/agents/analyst.py (169 lines)
- Delete backend/agents/portfolio_manager.py (420 lines)
- Delete backend/agents/risk_manager.py (139 lines)
- Update all imports to use EvoAgent exclusively
- Clean up unused imports across 25 files
- Update tests to work with simplified agent structure

Constraint: EvoAgent is now the single source of truth for all agent roles
Constraint: UnifiedAgentFactory handles runtime agent creation
Rejected: Keep legacy aliases | creates maintenance burden
Confidence: high
Scope-risk: moderate (affects agent instantiation paths)
Directive: All new agent features must be added to EvoAgent, not legacy classes
Not-tested: Kubernetes sandbox executor (marked with TODO)
This commit is contained in:
cillin
2026-04-02 10:51:14 +08:00
parent 49d704c363
commit 45c3996434
34 changed files with 201 additions and 1534 deletions
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66
backend/core/pipeline.py
View File

@@ -26,7 +26,7 @@ from backend.agents.team_pipeline_config import (
resolve_active_analysts,
update_active_analysts,
)
from backend.agents import AnalystAgent, EvoAgent
from backend.agents import EvoAgent
from backend.agents.agent_workspace import load_agent_workspace_config
from backend.agents.toolkit_factory import create_agent_toolkit
from backend.agents.workspace_manager import WorkspaceManager
@@ -1586,46 +1586,30 @@ class TradingPipeline:
),
)
# Determine whether to use EvoAgent based on EVO_AGENT_IDS
use_evo_agent = analyst_type in _resolve_evo_agent_ids()
if use_evo_agent:
from backend.agents.skills_manager import SkillsManager
skills_manager = SkillsManager(project_root=project_root)
workspace_dir = skills_manager.get_agent_asset_dir(
config_name,
agent_id,
)
agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
agent = EvoAgent(
agent_id=agent_id,
config_name=config_name,
workspace_dir=workspace_dir,
model=get_agent_model(analyst_type),
formatter=get_agent_formatter(analyst_type),
prompt_files=agent_config.prompt_files,
)
agent.toolkit = create_agent_toolkit(
agent_id=agent_id,
config_name=config_name,
active_skill_dirs=[],
)
setattr(agent, "run_id", config_name)
# Keep workspace_id for backward compatibility
setattr(agent, "workspace_id", config_name)
else:
agent = AnalystAgent(
analyst_type=analyst_type,
toolkit=create_agent_toolkit(
agent_id=agent_id,
config_name=config_name,
active_skill_dirs=[],
),
model=get_agent_model(analyst_type),
formatter=get_agent_formatter(analyst_type),
agent_id=agent_id,
config={"config_name": config_name},
)
# Create EvoAgent with workspace-driven configuration
from backend.agents.skills_manager import SkillsManager
skills_manager = SkillsManager(project_root=project_root)
workspace_dir = skills_manager.get_agent_asset_dir(
config_name,
agent_id,
)
agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
agent = EvoAgent(
agent_id=agent_id,
config_name=config_name,
workspace_dir=workspace_dir,
model=get_agent_model(analyst_type),
formatter=get_agent_formatter(analyst_type),
prompt_files=agent_config.prompt_files,
)
agent.toolkit = create_agent_toolkit(
agent_id=agent_id,
config_name=config_name,
active_skill_dirs=[],
)
setattr(agent, "run_id", config_name)
# Keep workspace_id for backward compatibility
setattr(agent, "workspace_id", config_name)
self._dynamic_analysts[agent_id] = agent
update_active_analysts(
project_root=project_root,

39
backend/core/pipeline_runner.py
View File

@@ -14,7 +14,7 @@ from contextlib import AsyncExitStack
from pathlib import Path
from typing import Any, Dict, List, Optional, Callable
from backend.agents import AnalystAgent, EvoAgent, PMAgent, RiskAgent
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
@@ -235,34 +235,21 @@ def _create_analyst_agent(
active_skill_dirs=active_skill_dirs,
)
use_evo_agent = analyst_type in _resolve_evo_agent_ids()
if use_evo_agent:
workspace_dir = skills_manager.get_agent_asset_dir(run_id, analyst_type)
agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
agent = EvoAgent(
agent_id=analyst_type,
config_name=run_id,
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, "workspace_id", run_id)
return agent
return AnalystAgent(
analyst_type=analyst_type,
toolkit=toolkit,
workspace_dir = skills_manager.get_agent_asset_dir(run_id, analyst_type)
agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
agent = EvoAgent(
agent_id=analyst_type,
config_name=run_id,
workspace_dir=workspace_dir,
model=model,
formatter=formatter,
agent_id=analyst_type,
config={"config_name": run_id},
skills_manager=skills_manager,
prompt_files=agent_config.prompt_files,
long_term_memory=long_term_memory,
)
agent.toolkit = toolkit
setattr(agent, "workspace_id", run_id)
return agent
def _create_risk_manager_agent(
@@ -607,7 +594,7 @@ async def run_pipeline(
trading_calendar="NYSE",
delay_between_days=0.5,
)
trading_dates = backtest_scheduler.get_trading_dates()
backtest_scheduler.get_trading_dates()
async def scheduler_callback_fn(callback):
await backtest_scheduler.start(callback)