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evotraders/backend/agents/toolkit_factory.py

210 lines
7.1 KiB
Python

# -*- coding: utf-8 -*-
"""Toolkit factory following AgentScope's skill + tool group practices."""
from typing import Any, Dict, Iterable
from .agent_workspace import load_agent_workspace_config
from backend.config.bootstrap_config import get_bootstrap_config_for_run
import yaml
from .skills_manager import SkillsManager
def load_agent_profiles() -> Dict[str, Dict[str, Any]]:
config_path = SkillsManager().project_root / "backend" / "config" / "agent_profiles.yaml"
with open(config_path, "r", encoding="utf-8") as file:
return yaml.safe_load(file) or {}
def _register_analysis_tool_groups(toolkit: Any) -> None:
from backend.tools.analysis_tools import TOOL_REGISTRY
tool_groups = {
"fundamentals": {
"description": "Financial health, profitability, growth, and efficiency analysis tools.",
"active": False,
"notes": (
"Use these tools to validate business quality, financial resilience, "
"and earnings durability before making directional conclusions."
),
"tools": [
"analyze_profitability",
"analyze_growth",
"analyze_financial_health",
"analyze_efficiency_ratios",
"analyze_valuation_ratios",
"get_financial_metrics_tool",
],
},
"technical": {
"description": "Trend, momentum, mean reversion, and volatility analysis tools.",
"active": False,
"notes": (
"Use these tools to assess timing, price structure, and risk-reward in "
"the current market regime."
),
"tools": [
"analyze_trend_following",
"analyze_momentum",
"analyze_mean_reversion",
"analyze_volatility",
],
},
"sentiment": {
"description": "News sentiment and insider activity analysis tools.",
"active": False,
"notes": (
"Use these tools to capture short-horizon catalysts, sentiment shifts, "
"and behavioral signals around each ticker."
),
"tools": [
"analyze_news_sentiment",
"analyze_insider_trading",
],
},
"valuation": {
"description": "Intrinsic value and relative valuation analysis tools.",
"active": False,
"notes": (
"Use these tools when the task requires fair value estimation, margin of "
"safety analysis, or valuation scenario comparison."
),
"tools": [
"dcf_valuation_analysis",
"owner_earnings_valuation_analysis",
"ev_ebitda_valuation_analysis",
"residual_income_valuation_analysis",
],
},
}
for group_name, group_config in tool_groups.items():
toolkit.create_tool_group(
group_name=group_name,
description=group_config["description"],
active=group_config["active"],
notes=group_config["notes"],
)
for tool_name in group_config["tools"]:
tool_func = TOOL_REGISTRY.get(tool_name)
if tool_func:
toolkit.register_tool_function(
tool_func,
group_name=group_name,
)
def _register_portfolio_tool_groups(toolkit: Any, pm_agent: Any) -> None:
toolkit.create_tool_group(
group_name="portfolio_ops",
description="Portfolio decision recording tools.",
active=False,
notes=(
"Use portfolio tools only after synthesizing analyst and risk inputs. "
"Record one explicit decision per ticker."
),
)
toolkit.register_tool_function(
pm_agent._make_decision,
group_name="portfolio_ops",
)
def _register_risk_tool_groups(toolkit: Any) -> None:
from backend.tools.risk_tools import (
assess_margin_and_liquidity,
assess_position_concentration,
assess_volatility_exposure,
)
toolkit.create_tool_group(
group_name="risk_ops",
description="Risk diagnostics for concentration, leverage, and volatility.",
active=False,
notes=(
"Use risk tools to quantify concentration, margin pressure, and volatility "
"before writing the final risk memo."
),
)
toolkit.register_tool_function(
assess_position_concentration,
group_name="risk_ops",
)
toolkit.register_tool_function(
assess_margin_and_liquidity,
group_name="risk_ops",
)
toolkit.register_tool_function(
assess_volatility_exposure,
group_name="risk_ops",
)
def create_agent_toolkit(
agent_id: str,
config_name: str,
owner: Any = None,
active_skill_dirs: Iterable[str] | None = None,
) -> Any:
"""Create a Toolkit with agent skills and grouped tools."""
from agentscope.tool import Toolkit
profiles = load_agent_profiles()
profile = profiles.get(agent_id, {})
skills_manager = SkillsManager()
agent_config = load_agent_workspace_config(
skills_manager.get_agent_asset_dir(config_name, agent_id) / "agent.yaml",
)
bootstrap_config = get_bootstrap_config_for_run(
skills_manager.project_root,
config_name,
)
override = bootstrap_config.agent_override(agent_id)
active_groups = override.get(
"active_tool_groups",
agent_config.active_tool_groups
or profile.get("active_tool_groups", []),
)
disabled_groups = set(agent_config.disabled_tool_groups)
if disabled_groups:
active_groups = [
group_name
for group_name in active_groups
if group_name not in disabled_groups
]
toolkit = Toolkit(
agent_skill_instruction=(
"<system-info>You have access to project skills. Each skill lives in a "
"directory and is described by SKILL.md. Follow the skill instructions "
"when they are relevant to the current task.</system-info>"
),
agent_skill_template="- {name} (dir: {dir}): {description}",
)
if agent_id.endswith("_analyst"):
_register_analysis_tool_groups(toolkit)
elif agent_id == "portfolio_manager" and owner is not None:
_register_portfolio_tool_groups(toolkit, owner)
elif agent_id == "risk_manager":
_register_risk_tool_groups(toolkit)
if active_skill_dirs is None:
skill_names = skills_manager.resolve_agent_skill_names(
config_name=config_name,
agent_id=agent_id,
default_skills=profile.get("skills", []),
)
active_skill_dirs = [
skills_manager.get_agent_active_root(config_name, agent_id) / skill_name
for skill_name in skill_names
]
for skill_dir in active_skill_dirs:
toolkit.register_agent_skill(str(skill_dir))
if active_groups:
toolkit.update_tool_groups(group_names=active_groups, active=True)
return toolkit