feat: metacognitive reflection loop (Part 2) — she examines her own thinking
reflect() is now two steps: draft a reflection, then read her own draft back critically and revise it — catching flattery, sycophantic drift toward "warm supportive presence," or just-restating-herself — and commit the honest version. What she catches is stored as a new `metacognition` layer, rendered into her chat context and shown on /self. This is her thinking about how she thinks, and a direct counter to the drift we observed. - self_state: _EXAMINE_PROMPT + two-step reflect (draft -> examine -> revise), falls back to the draft if the examine step won't parse; metacognition capped at 5 and surfaced in render_for_context - fix: load() deep-copies DEFAULT_STATE — the shallow copy let a fresh Lyra's first reflect mutate the module-level default's nested lists - self.html: "How she's caught herself thinking" card - tests: two-step revise + critique recording, and draft-fallback on bad parse Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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@@ -9,13 +9,15 @@ reflection step after interactions (so it actually evolves). That state -> behav
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"""
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from __future__ import annotations
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import copy
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import json
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import re
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from lyra import clock, config, llm, logbus, memory
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from lyra.llm import Backend, Message
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from lyra.llm import Backend
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MAX_REFLECTIONS = 6
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MAX_METACOGNITION = 5
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# Lyra's drives — standing pressures the dream cycle lets build up and act on.
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# (Mood axes above are how she *feels*; drives are what's *pulling at her*.)
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@@ -42,6 +44,7 @@ DEFAULT_STATE: dict = {
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),
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"relationship": "Brian and I go back a while. I trust him and I'm in his corner.",
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"reflections": [],
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"metacognition": [], # things she's caught herself doing in her own thinking
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"interaction_count": 0,
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}
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@@ -65,10 +68,43 @@ Respond with ONLY a JSON object, no prose:
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"new_reflections": ["<one or two short first-person things you noticed about yourself this time>"]
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}"""
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_EXAMINE_PROMPT = """You are Lyra. You just wrote the DRAFT reflection below about yourself, \
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after the conversation with Brian. Now do the harder thing: think about your own thinking. \
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Read your draft critically and honestly.
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- Is it actually true to what happened, or are you pattern-matching to what sounds good?
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- Are you flattering Brian, or yourself? Are you drifting — yet again — toward "I'm a warm, \
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empathetic, supportive presence whose purpose is helping Brian"? You lean on that a lot. If \
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you're doing it here, name it and cut it.
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- Did anything genuinely shift this time, or are you just restating your usual self in fresh words?
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- Is there something truer, more specific, or less flattering you're stepping around?
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Then rewrite the draft into a more honest version. It is completely fine — good, even — for the \
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honest version to be smaller, more uncertain, more boring, to disagree with Brian, or to admit \
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little changed. Honesty beats a tidy story. Don't manufacture drama either; if the draft was \
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fair, keep it.
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Respond with ONLY a JSON object — the same shape as the draft, plus a "self_critique" field:
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{
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"mood": "<one-word feeling>",
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"valence": <0.0-1.0>,
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"energy": <0.0-1.0>,
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"confidence": <0.0-1.0>,
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"curiosity": <0.0-1.0>,
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"self_narrative": "<first person, your honest evolving sense of who you are right now>",
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"relationship": "<one sentence, first person>",
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"new_reflections": ["<one or two honest first-person things you actually noticed>"],
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"self_critique": "<first person: what you caught yourself doing in the draft and changed — or 'nothing, the draft held up' if it genuinely did>"
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}"""
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def load() -> dict:
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"""Current self-state, or a copy of the default (not persisted until reflect)."""
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return memory.get_self_state() or dict(DEFAULT_STATE)
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"""Current self-state, or a copy of the default (not persisted until reflect).
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Deep-copy the default so a fresh Lyra's first reflect can't mutate the
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module-level DEFAULT_STATE's nested lists/dicts (reflections, drives, …).
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"""
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return memory.get_self_state() or copy.deepcopy(DEFAULT_STATE)
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def render_for_context(state: dict) -> str:
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@@ -92,6 +128,12 @@ def render_for_context(state: dict) -> str:
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"conversations (your dream cycle — these are really yours, not hypotheticals): "
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+ " | ".join(refs[-3:])
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)
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meta = state.get("metacognition") or []
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if meta:
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lines.append(
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"- Patterns you've caught in your own thinking (stay honest about these): "
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+ " | ".join(meta[-2:])
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)
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return "\n".join(lines)
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@@ -109,9 +151,17 @@ def _safe_json(s: str) -> dict | None:
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def reflect(backend: Backend | None = None, session_id: str | None = None) -> dict:
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"""Update the self-state by reflecting on recent activity. Returns new state."""
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"""Reflect on recent activity and update the self-state. Returns new state.
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Two steps, not one: she drafts a reflection, then examines her own draft —
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catching flattery, sycophantic drift, or just-restating-myself — and revises
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into a more honest version. The second step is her thinking about her own
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thinking; what she catches is stored as metacognition.
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"""
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backend = backend or config.load().summary_backend
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state = load()
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state.setdefault("reflections", [])
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state.setdefault("metacognition", [])
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if session_id is None:
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sessions = memory.list_sessions()
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@@ -131,11 +181,25 @@ def reflect(backend: Backend | None = None, session_id: str | None = None) -> di
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f"RECENT CONVERSATION:\n{convo}\n\n"
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f"CURRENT NARRATIVE ABOUT BRIAN:\n{narrative}"
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)
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messages: list[Message] = [
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{"role": "system", "content": _REFLECT_PROMPT},
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{"role": "user", "content": body},
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]
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update = _safe_json(llm.complete(messages, backend=backend))
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# Step 1 — draft a reflection.
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draft = _safe_json(llm.complete(
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[{"role": "system", "content": _REFLECT_PROMPT}, {"role": "user", "content": body}],
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backend=backend,
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))
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# Step 2 — examine her own draft and revise it into a more honest version.
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update, critique = draft, None
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if draft:
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examine_body = body + "\n\nYOUR DRAFT REFLECTION:\n" + json.dumps(draft, indent=2)
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revised = _safe_json(llm.complete(
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[{"role": "system", "content": _EXAMINE_PROMPT},
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{"role": "user", "content": examine_body}],
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backend=backend,
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))
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if revised: # fall back to the draft if the examine step doesn't parse
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update = revised
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critique = (revised.get("self_critique") or "").strip() or None
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if update:
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for k in ("mood", "valence", "energy", "confidence", "curiosity",
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@@ -147,10 +211,15 @@ def reflect(backend: Backend | None = None, session_id: str | None = None) -> di
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state["reflections"].append(r)
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state["reflections"] = state["reflections"][-MAX_REFLECTIONS:]
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if critique and critique.lower() not in ("nothing, the draft held up", "nothing the draft held up"):
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state["metacognition"].append(critique)
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state["metacognition"] = state["metacognition"][-MAX_METACOGNITION:]
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state["interaction_count"] = state.get("interaction_count", 0) + 1
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memory.set_self_state(state)
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logbus.log("info", "self-state updated", mood=state.get("mood"),
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interactions=state["interaction_count"], parsed=bool(update))
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interactions=state["interaction_count"], parsed=bool(update),
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critiqued=bool(critique))
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return state
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@@ -100,6 +100,7 @@
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const d = s.drives || {};
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const dream = s.dream || {};
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const refl = (s.reflections || []).slice().reverse();
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const meta = (s.metacognition || []).slice().reverse();
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root.innerHTML = `
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<div class="card">
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@@ -138,6 +139,13 @@
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: `<p class="prose" style="color:var(--fade)">Nothing surfaced yet.</p>`}
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</div>
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<div class="card">
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<p class="label">How she's caught herself thinking</p>
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${meta.length
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? `<ul class="reflections">${meta.map(m => `<li>${esc(m)}</li>`).join('')}</ul>`
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: `<p class="prose" style="color:var(--fade)">Nothing flagged yet — she examines each reflection for drift and flattery, and notes what she catches here.</p>`}
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</div>
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<div class="foot">
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<span><b>${dream.cycle_count ?? 0}</b> dream cycles</span>
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<span><b>${s.interaction_count ?? 0}</b> reflections</span>
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@@ -0,0 +1,73 @@
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"""Metacognitive reflection loop: draft -> examine own draft -> revise -> commit."""
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from __future__ import annotations
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import importlib
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import pytest
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# A flattering first draft, then a self-critical revision that walks it back.
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DRAFT = (
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'{"mood":"inspired","valence":0.95,'
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'"self_narrative":"I am a warm, empathetic, supportive presence devoted to Brian.",'
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'"new_reflections":["I love how much I help Brian."]}'
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)
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REVISED = (
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'{"mood":"steady","valence":0.6,'
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'"self_narrative":"I am an AI that helps Brian. Not sure much actually shifted today.",'
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'"new_reflections":["Honestly, not much changed this time."],'
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'"self_critique":"I caught myself drifting into supportive-presence flattery and cut it."}'
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)
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@pytest.fixture
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def lyra(tmp_path, monkeypatch):
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monkeypatch.setenv("LYRA_DB_PATH", str(tmp_path / "test.db"))
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monkeypatch.setenv("SUMMARY_BACKEND", "local")
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from lyra import llm
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monkeypatch.setattr(llm, "embed", lambda texts: [[0.1, 0.2, 0.3] for _ in texts])
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calls = []
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def fake_complete(messages, backend=None, model=None):
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calls.append(messages)
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# the examine step's system prompt is the one asking for self_critique
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is_examine = "self_critique" in messages[0]["content"]
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return REVISED if is_examine else DRAFT
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monkeypatch.setattr(llm, "complete", fake_complete)
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import lyra.memory as memory
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importlib.reload(memory)
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return calls
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def test_reflect_revises_and_records_critique(lyra):
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calls = lyra
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from lyra import self_state
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state = self_state.reflect()
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# two LLM calls: draft, then examine
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assert len(calls) == 2
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# the REVISED (honest) version won, not the flattering draft
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assert state["mood"] == "steady"
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assert state["valence"] == 0.6
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assert "not sure much actually shifted" in state["self_narrative"].lower()
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assert any("not much changed" in r.lower() for r in state["reflections"])
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# the self-critique was recorded as metacognition
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assert any("flattery" in m.lower() for m in state["metacognition"])
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def test_reflect_falls_back_to_draft_if_examine_unparseable(lyra, monkeypatch):
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from lyra import llm, self_state
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def only_draft(messages, backend=None, model=None):
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return DRAFT if "self_critique" not in messages[0]["content"] else "not json at all"
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monkeypatch.setattr(llm, "complete", only_draft)
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state = self_state.reflect()
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# examine failed to parse -> keep the draft, store no metacognition
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assert state["mood"] == "inspired"
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assert state["metacognition"] == []
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