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Align branding, prompts, and deployment tooling

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This commit is contained in:
cillin
2026-03-28 22:16:56 +08:00
parent 4aa69650e8
commit 4295293a21
90 changed files with 1320 additions and 2044 deletions
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165
backend/agents/factory.py
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@@ -21,22 +21,6 @@ class ModelConfig:
max_tokens: int = 4096
@dataclass
class RoleConfig:
"""Role configuration for an agent."""
name: str
description: str = ""
focus_areas: List[str] = None
constraints: List[str] = None
def __post_init__(self):
if self.focus_areas is None:
self.focus_areas = []
if self.constraints is None:
self.constraints = []
class AgentConfig:
"""Represents a configured agent instance (data class)."""
@@ -47,14 +31,12 @@ class AgentConfig:
workspace_id: str,
config_path: Path,
model_config: Optional[ModelConfig] = None,
role_config: Optional[RoleConfig] = None,
):
self.agent_id = agent_id
self.agent_type = agent_type
self.workspace_id = workspace_id
self.config_path = config_path
self.model_config = model_config or ModelConfig()
self.role_config = role_config
self.agent_dir = config_path.parent
def to_dict(self) -> Dict[str, Any]:
@@ -70,103 +52,12 @@ class AgentConfig:
"temperature": self.model_config.temperature,
"max_tokens": self.model_config.max_tokens,
},
"role_config": self.role_config.__dict__ if self.role_config else None,
}
class AgentFactory:
"""Factory for creating, cloning, and managing agents."""
# Default role templates by agent type
ROLE_TEMPLATES = {
"technical_analyst": {
"name": "Technical Analyst",
"description": "Analyze price patterns, trends, and technical indicators.",
"focus_areas": [
"Price action and chart patterns",
"Support and resistance levels",
"Technical indicators (RSI, MACD, Moving Averages)",
"Volume analysis",
],
"constraints": [
"State clear signal, confidence, and invalidation conditions",
"Use available technical analysis tools",
],
},
"fundamentals_analyst": {
"name": "Fundamentals Analyst",
"description": "Analyze company financials, earnings, and business metrics.",
"focus_areas": [
"Financial statements analysis",
"Earnings reports and guidance",
"Valuation metrics",
"Business model and competitive position",
],
"constraints": [
"State clear signal, confidence, and invalidation conditions",
"Use available fundamental analysis tools",
],
},
"sentiment_analyst": {
"name": "Sentiment Analyst",
"description": "Analyze market sentiment, news, and social signals.",
"focus_areas": [
"News sentiment analysis",
"Social media sentiment",
"Analyst ratings and price targets",
"Insider activity",
],
"constraints": [
"State clear signal, confidence, and invalidation conditions",
"Use available sentiment analysis tools",
],
},
"valuation_analyst": {
"name": "Valuation Analyst",
"description": "Perform valuation analysis and price target calculations.",
"focus_areas": [
"DCF and comparable valuation",
"Price target derivation",
"Margin of safety assessment",
"Risk-adjusted return expectations",
],
"constraints": [
"State clear signal, confidence, and invalidation conditions",
"Use available valuation tools",
],
},
"risk_manager": {
"name": "Risk Manager",
"description": "Quantify concentration, leverage, liquidity, and volatility risk.",
"focus_areas": [
"Portfolio concentration risk",
"Leverage and margin analysis",
"Liquidity assessment",
"Volatility and drawdown risk",
],
"constraints": [
"Prioritize highest-severity risk first",
"State concrete limits and recommendations",
"Use available risk tools before issuing final memo",
],
},
"portfolio_manager": {
"name": "Portfolio Manager",
"description": "Synthesize analyst and risk inputs into portfolio decisions.",
"focus_areas": [
"Position sizing and allocation",
"Risk-adjusted portfolio construction",
"Trade execution timing",
"Portfolio rebalancing",
],
"constraints": [
"Be concise, capital-aware, and explicit about sizing rationale",
"Respect cash, margin, and concentration constraints",
"Consider all analyst inputs before decisions",
],
},
}
def __init__(self, project_root: Optional[Path] = None):
"""Initialize the agent factory.
@@ -183,7 +74,6 @@ class AgentFactory:
agent_type: str,
workspace_id: str,
model_config: Optional[ModelConfig] = None,
role_config: Optional[RoleConfig] = None,
clone_from: Optional[str] = None,
) -> AgentConfig:
"""Create a new agent.
@@ -193,7 +83,6 @@ class AgentFactory:
agent_type: Type of agent (e.g., "technical_analyst")
workspace_id: ID of the workspace to create agent in
model_config: Model configuration
role_config: Role configuration (auto-generated if None)
clone_from: Path to existing agent to clone from (optional)
Returns:
@@ -223,13 +112,6 @@ class AgentFactory:
else:
self._copy_template(agent_dir, agent_id, agent_type)
# Generate role config if not provided
if role_config is None:
role_config = self._generate_role_config(agent_type)
# Generate ROLE.md
self._generate_role_md(agent_dir, role_config)
# Write agent.yaml
config_path = agent_dir / "agent.yaml"
self._write_agent_yaml(config_path, agent_id, agent_type, model_config)
@@ -240,7 +122,6 @@ class AgentFactory:
workspace_id=workspace_id,
config_path=config_path,
model_config=model_config,
role_config=role_config,
)
def delete_agent(self, agent_id: str, workspace_id: str) -> bool:
@@ -369,9 +250,7 @@ class AgentFactory:
"SOUL.md": f"# Soul\n\nDescribe {agent_id}'s temperament, reasoning posture, and voice.\n\n",
"PROFILE.md": f"# Profile\n\nTrack {agent_id}'s long-lived investment style, preferences, and strengths.\n\n",
"MEMORY.md": f"# Memory\n\nStore durable lessons, heuristics, and reminders for {agent_id}.\n\n",
"HEARTBEAT.md": f"# Heartbeat\n\nOptional checklist for periodic review or self-reflection.\n\n",
"POLICY.md": f"# Policy\n\nOptional run-scoped constraints, limits, or strategy policy.\n\n",
"STYLE.md": f"# Style\n\nOptional run-scoped communication or reasoning style.\n\n",
}
for filename, content in default_files.items():
@@ -411,50 +290,6 @@ class AgentFactory:
if skill_file.is_file():
shutil.copy2(skill_file, target_skills / skill_file.name)
def _generate_role_config(self, agent_type: str) -> RoleConfig:
"""Generate role configuration for an agent type.
Args:
agent_type: Type of agent
Returns:
RoleConfig instance
"""
template = self.ROLE_TEMPLATES.get(agent_type, {})
return RoleConfig(
name=template.get("name", agent_type.replace("_", " ").title()),
description=template.get("description", ""),
focus_areas=template.get("focus_areas", []),
constraints=template.get("constraints", []),
)
def _generate_role_md(self, agent_dir: Path, role_config: RoleConfig) -> None:
"""Generate ROLE.md file.
Args:
agent_dir: Agent directory
role_config: Role configuration
"""
lines = [f"# {role_config.name}", ""]
if role_config.description:
lines.extend([role_config.description, ""])
if role_config.focus_areas:
lines.extend(["## Focus Areas", ""])
for area in role_config.focus_areas:
lines.append(f"- {area}")
lines.append("")
if role_config.constraints:
lines.extend(["## Constraints", ""])
for constraint in role_config.constraints:
lines.append(f"- {constraint}")
lines.append("")
content = "\n".join(lines)
(agent_dir / "ROLE.md").write_text(content, encoding="utf-8")
def _write_agent_yaml(
self,
config_path: Path,