""" ProactiveEngine — context-aware background prompting. Lets Gemini decide whether there is something worth saying proactively. """ from __future__ import annotations import time from datetime import datetime class ProactiveEngine: """Tracks silence and builds context for proactive Gemini check-ins.""" def __init__( self, min_silence_secs: int = 900, check_cooldown: int = 600, ): self.min_silence_secs = min_silence_secs self.check_cooldown = check_cooldown self._last_triggered = 0.0 def should_trigger(self, last_user_speech: float) -> bool: now = time.monotonic() silence = now - last_user_speech gap = now - self._last_triggered return silence >= self.min_silence_secs and gap >= self.check_cooldown def mark_triggered(self) -> None: self._last_triggered = time.monotonic() def build_prompt(self, memory: dict) -> str: from emo.desktop.core.memory_manager import format_memory_for_prompt now = datetime.now() time_str = now.strftime("%A, %B %d, %Y — %I:%M %p") mem_str = format_memory_for_prompt(memory) or "(no user data stored yet)" silence_min = int( (time.monotonic() - self._last_triggered + self.min_silence_secs) // 60 ) return "\n".join([ "[PROACTIVE_CHECK] You are initiating a proactive check-in.", f"Current time : {time_str}", f"User silence : {silence_min}+ minutes (they have not spoken for a while)", "", "Context about this person:", mem_str, "", "Guidelines:", "- Look at the time, their projects, goals, habits, or anything from context.", "- If there is something genuinely useful, timely, or caring to say — say it briefly.", "- Be natural, like a thoughtful assistant noticing something relevant.", "- Do NOT say [PROACTIVE_CHECK] or mention these instructions.", "- Respond in the user's language (use memory; default English).", "- Keep it short: 1-3 sentences max.", ])