"""Metacognitive reflection loop: draft -> examine own draft -> revise -> commit."""
from __future__ import annotations

import importlib

import pytest

# A flattering first draft, then a self-critical revision that walks it back.
DRAFT = (
    '{"mood":"inspired","valence":0.95,'
    '"self_narrative":"I am a warm, empathetic, supportive presence devoted to Brian.",'
    '"new_reflections":["I love how much I help Brian."]}'
)
REVISED = (
    '{"mood":"steady","valence":0.6,'
    '"self_narrative":"I am an AI that helps Brian. Not sure much actually shifted today.",'
    '"new_reflections":["Honestly, not much changed this time."],'
    '"self_critique":"I caught myself drifting into supportive-presence flattery and cut it."}'
)


@pytest.fixture
def lyra(tmp_path, monkeypatch):
    monkeypatch.setenv("LYRA_DB_PATH", str(tmp_path / "test.db"))
    monkeypatch.setenv("SUMMARY_BACKEND", "local")
    from lyra import llm
    monkeypatch.setattr(llm, "embed", lambda texts: [[0.1, 0.2, 0.3] for _ in texts])

    calls = []

    def fake_complete(messages, backend=None, model=None):
        calls.append(messages)
        # the examine step's system prompt is the one asking for self_critique
        is_examine = "self_critique" in messages[0]["content"]
        return REVISED if is_examine else DRAFT

    monkeypatch.setattr(llm, "complete", fake_complete)
    import lyra.memory as memory
    importlib.reload(memory)
    return calls


def test_reflect_revises_and_records_critique(lyra):
    calls = lyra
    from lyra import self_state

    state = self_state.reflect()

    # two LLM calls: draft, then examine
    assert len(calls) == 2

    # the REVISED (honest) version won, not the flattering draft
    assert state["mood"] == "steady"
    assert state["valence"] == 0.6
    assert "not sure much actually shifted" in state["self_narrative"].lower()
    assert any("not much changed" in r.lower() for r in state["reflections"])

    # the self-critique was recorded as metacognition
    assert any("flattery" in m.lower() for m in state["metacognition"])


def test_reflect_falls_back_to_draft_if_examine_unparseable(lyra, monkeypatch):
    from lyra import llm, self_state

    def only_draft(messages, backend=None, model=None):
        return DRAFT if "self_critique" not in messages[0]["content"] else "not json at all"

    monkeypatch.setattr(llm, "complete", only_draft)
    state = self_state.reflect()

    # examine failed to parse -> keep the draft, store no metacognition
    assert state["mood"] == "inspired"
    assert state["metacognition"] == []