alvis
1d9a395591
Adds four InferredParams (all TTL=24h, min_history=50 except preferred_hour=10):
- quiet_start / quiet_end: longest contiguous below-baseline hour run (HH:MM)
- peak_hours: top-quartile done-event hours, sorted ascending
- tz: cold-start only ("UTC"); populated from auth provider, no inference function
compute() updated:
- in_quiet check (quiet window) takes precedence over peak hours
- in_peak emits "peak productivity hour" language when current hour is in peak_hours
- approaching peak (within 2h) surfaces for orchestrator timing
- tz surfaced in snippet header when not UTC
- snapshot adds peak_hours, in_quiet, in_peak, tz
- Agent bumped to v1.2.0
- 21 new tests: night-owl, early-bird, shift-worker, quiet/peak snippet rendering
- Fixed test_snapshot_keys in test_agents.py to include new snapshot fields
Closes #112
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
121 lines
4.8 KiB
Python
121 lines
4.8 KiB
Python
"""Tests for the inference framework and time-of-day #112 proof."""
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from __future__ import annotations
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import sys, os
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", ".."))
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import pytest
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from datetime import datetime, timezone
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from ml.agents.inference.history import FeedbackEvent, UserHistory
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from ml.agents.inference.framework import run_inference
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from ml.agents.time_of_day import TimeOfDayAgent, MANIFEST as TOD_MANIFEST, MANIFEST
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from ml.agents.base import AgentInput
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_NOW = datetime(2026, 5, 1, 14, 0, 0, tzinfo=timezone.utc) # Thursday 14:00
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def _inp(**kwargs) -> AgentInput:
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defaults = dict(user_id="u1", tasks=[], profile={}, now=_NOW, agent_prefs={})
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defaults.update(kwargs)
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return AgentInput(**defaults)
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def _event(action: str, hour: int) -> FeedbackEvent:
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ts = f"2026-05-01T{hour:02d}:00:00+00:00"
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return FeedbackEvent(action=action, dwell_ms=60_000 if action == "done" else 500, created_at=ts)
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class TestRunInference:
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def test_cold_start_when_below_min_history(self):
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history = UserHistory(user_id="u1", events=[_event("done", 9)] * 5) # only 5 < 10
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result = run_inference(TOD_MANIFEST, history)
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assert result["preferred_hour"] is None # cold_start_default
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def test_infers_preferred_hour_as_mode(self):
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# 7 events at 09:00, 3 at 17:00 → preferred_hour should be 9
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events = [_event("done", 9)] * 7 + [_event("done", 17)] * 3
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history = UserHistory(user_id="u1", events=events)
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result = run_inference(TOD_MANIFEST, history)
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assert result["preferred_hour"] == 9
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def test_infers_preferred_hour_from_majority_hour(self):
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events = [_event("done", 20)] * 6 + [_event("done", 8)] * 4
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history = UserHistory(user_id="u1", events=events)
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result = run_inference(TOD_MANIFEST, history)
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assert result["preferred_hour"] == 20
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def test_no_inferred_params_returns_empty(self):
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from ml.agents.manifest import AgentManifest
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bare = AgentManifest(
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id="bare", version="1.0.0", description="", pref_schema={},
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context_schema=[], required_consents=[], output_contract={}, ttl_sec=300,
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)
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history = UserHistory(user_id="u1", events=[_event("done", 9)] * 20)
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result = run_inference(bare, history)
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assert result == {}
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def test_cold_start_fallback_on_infer_error(self):
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"""infer() raising should fall back to cold_start_default, not crash."""
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from ml.agents.manifest import InferredParam, AgentManifest
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def _bad_infer(h):
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raise RuntimeError("oops")
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m = AgentManifest(
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id="boom", version="1.0.0", description="", pref_schema={},
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context_schema=[], required_consents=[], output_contract={}, ttl_sec=300,
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inferred_params=[InferredParam(key="x", ttl_sec=60, cold_start_default=42, min_history=1, infer=_bad_infer)],
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)
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history = UserHistory(user_id="u1", events=[_event("done", 9)] * 5)
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result = run_inference(m, history)
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assert result["x"] == 42
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class TestTimeOfDayAgentWithInference:
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agent = TimeOfDayAgent()
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def test_uses_preferred_hour_from_agent_prefs(self):
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inp = _inp(agent_prefs={"preferred_hour": 9}, now=datetime(2026, 5, 1, 9, 0, 0, tzinfo=timezone.utc))
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out = self.agent.compute(inp)
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assert "peak productivity hour" in out.prompt_text.lower() or "peak" in out.prompt_text
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def test_quiet_window_noon_suppressed(self):
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inp = _inp(
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agent_prefs={"quiet_start": "22:00", "quiet_end": "07:00"},
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now=datetime(2026, 5, 1, 23, 0, 0, tzinfo=timezone.utc),
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)
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out = self.agent.compute(inp)
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assert "quiet window" in out.prompt_text
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def test_quiet_window_not_in_window(self):
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inp = _inp(
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agent_prefs={"quiet_start": "22:00", "quiet_end": "07:00"},
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now=datetime(2026, 5, 1, 14, 0, 0, tzinfo=timezone.utc),
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)
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out = self.agent.compute(inp)
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assert "quiet window" not in out.prompt_text
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def test_agent_prefs_override_profile(self):
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# agent_prefs.preferred_hour wins over profile.preferred_hour
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inp = _inp(
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profile={"preferred_hour": 8},
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agent_prefs={"preferred_hour": 14},
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now=datetime(2026, 5, 1, 14, 0, 0, tzinfo=timezone.utc),
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)
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out = self.agent.compute(inp)
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assert "peak productivity hour (14:00)" in out.prompt_text
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def test_no_prefs_falls_back_to_profile(self):
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inp = _inp(profile={"preferred_hour": 10}, now=datetime(2026, 5, 1, 10, 0, 0, tzinfo=timezone.utc))
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out = self.agent.compute(inp)
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assert "peak" in out.prompt_text
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def test_version_bumped(self):
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assert MANIFEST.version == "1.2.0"
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def test_manifest_has_preferred_hour_param(self):
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keys = {p.key for p in MANIFEST.inferred_params}
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assert "preferred_hour" in keys
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