alvis
305eeae38b
Each agent now exports a module-level MANIFEST declaring id, version, pref_schema, required_consents, ttl_sec, and silenced_in_contexts. The registry surfaces both the agent and its manifest, and rejects on mismatch so the two cannot drift. ml/serving exposes GET /agents/registry; services/api proxies it as GET /api/agents/registry with a 60s in-process cache so admin pageviews don't hammer upstream. Failures aren't cached. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
75 lines
2.7 KiB
Python
75 lines
2.7 KiB
Python
from __future__ import annotations
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from typing import ClassVar
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from .base import BaseAgent, AgentInput, AgentOutput
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from .manifest import AgentManifest
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MANIFEST = AgentManifest(
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id="momentum",
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version="1.0.0",
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description="Characterises the user's recent engagement trend from profile features.",
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pref_schema={
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"type": "object",
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"additionalProperties": False,
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"properties": {
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"low_engagement_threshold_pct": {
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"type": "integer",
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"minimum": 0,
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"maximum": 100,
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"default": 25,
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"description": "Completion rate below which momentum hints at low engagement.",
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},
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},
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},
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context_schema=["profile.features"],
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required_consents=["data:core", "agent:momentum"],
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output_contract={"type": "snippet", "format": "free_text"},
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ttl_sec=21_600,
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)
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class MomentumAgent(BaseAgent):
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"""Characterises the user's recent engagement trend from profile features."""
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agent_id: ClassVar[str] = MANIFEST.id
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ttl_seconds: ClassVar[int] = MANIFEST.ttl_sec
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version: ClassVar[str] = MANIFEST.version
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def compute(self, inp: AgentInput) -> AgentOutput:
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completion = inp.profile.get("completion_rate_30d")
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dismiss = inp.profile.get("dismiss_rate_30d")
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volume = inp.profile.get("tip_volume_30d")
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parts: list[str] = []
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if completion is not None:
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pct = round(completion * 100)
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if pct >= 50:
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parts.append(f"The user completes {pct}% of tips (strong engagement).")
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elif pct >= 25:
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parts.append(f"The user completes {pct}% of tips (moderate engagement).")
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else:
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parts.append(
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f"The user completes {pct}% of tips "
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f"(low engagement — prefer simple, immediately actionable tips)."
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)
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else:
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parts.append("No completion-rate data yet (new user).")
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if dismiss is not None:
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dpct = round(dismiss * 100)
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if dpct >= 40:
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parts.append(f"Dismiss rate is high ({dpct}%) — avoid repetitive or irrelevant tips.")
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elif dpct <= 10:
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parts.append(f"Dismiss rate is low ({dpct}%).")
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if volume is not None and int(volume) < 5:
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parts.append("Very few tips served so far — this is an early-stage user.")
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prompt = " ".join(parts) if parts else "No engagement data available yet."
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snapshot = {
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"completion_rate_30d": completion,
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"dismiss_rate_30d": dismiss,
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"tip_volume_30d": volume,
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}
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return self._make_output(inp, prompt, snapshot)
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