alvis
b3cf588f2f
Adds ml/agents/ — five specialised sub-agents (overdue_task, momentum, time_of_day, recent_patterns, focus_area) each producing a prompt snippet from user signals. A registry wires them up; the orchestrator prompt in ml/serving/prompts.py synthesises their outputs into one tip via LiteLLM. Also wires /api/agents route in the API and updates the Dockerfile to copy the full ml/ tree with PYTHONPATH=/app so agent imports resolve correctly. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
5 lines
178 B
Python
5 lines
178 B
Python
from .base import BaseAgent, AgentInput, AgentOutput
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from .registry import get_agent, all_agents
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__all__ = ["BaseAgent", "AgentInput", "AgentOutput", "get_agent", "all_agents"]
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