"""Tests for interruptibility (TASK-03-05) + branch classifier (TASK-03-06)."""

from __future__ import annotations

import asyncio
from types import SimpleNamespace

import pytest

from server.interruptibility import pipeline_allows_interruptions
from server.scenarios.classifier import (
    classify_branch,
    classify_branch_sync_heuristic,
    _parse_branch,
)
from server.scenarios.loader import load


# ─── TASK-03-05: interruptibility ────────────────────────────────────────────


def test_pipeline_allows_interruptions_flag():
    """The pipeline task must be configured with allow_interruptions=True (D-008)."""
    task = SimpleNamespace(params=SimpleNamespace(allow_interruptions=True))
    assert pipeline_allows_interruptions(task) is True


def test_pipeline_allows_interruptions_false_flag():
    task = SimpleNamespace(params=SimpleNamespace(allow_interruptions=False))
    assert pipeline_allows_interruptions(task) is False


def test_pipeline_allows_interruptions_missing_params():
    task = SimpleNamespace()
    assert pipeline_allows_interruptions(task) is False


# ─── TASK-03-06: branch classifier ───────────────────────────────────────────


def test_heuristic_classifier_accept():
    """A scripted empathetic transcript → accept_resolution."""
    scenario = load("customer_service_refund_ca_v01")
    turns = [
        "I'm really sorry you're frustrated. I can offer a full refund right now.",
        "Let me confirm the next steps for you.",
    ]
    branch_id = classify_branch_sync_heuristic(scenario, turns)
    assert branch_id == "accept_resolution"


def test_heuristic_classifier_escalate():
    """A scripted defensive transcript → escalate."""
    scenario = load("customer_service_refund_ca_v01")
    turns = [
        "Well, our policy says we don't do refunds after 30 days.",
        "That's just how it works, I can't help you.",
    ]
    branch_id = classify_branch_sync_heuristic(scenario, turns)
    assert branch_id == "escalate"


def test_parse_branch_valid_json():
    scenario = load("customer_service_refund_ca_v01")
    text = '{"branch_id": "accept_resolution", "reason": "empathy shown"}'
    bid, reason = _parse_branch(text, scenario)
    assert bid == "accept_resolution"
    assert "empathy" in reason


def test_parse_branch_code_fenced_json():
    scenario = load("customer_service_refund_ca_v01")
    text = '```json\n{"branch_id": "escalate", "reason": "defensive"}\n```'
    bid, reason = _parse_branch(text, scenario)
    assert bid == "escalate"


def test_parse_branch_unknown_id_falls_back():
    scenario = load("customer_service_refund_ca_v01")
    text = '{"branch_id": "not_real", "reason": "x"}'
    bid, reason = _parse_branch(text, scenario)
    # Falls back to the first branch.
    assert bid in scenario.branch_ids()
    assert "fallback" in reason


def test_parse_branch_malformed_json_scans_for_id():
    scenario = load("customer_service_refund_ca_v01")
    text = "The learner matches the escalate branch."
    bid, reason = _parse_branch(text, scenario)
    assert bid == "escalate"
    assert "fallback" in reason


class _FakeLLM:
    """A fake LLMProvider for the classifier test (no real API call)."""

    debrief_model = "deepseek-v4-flash:cloud"
    roleplay_model = "gemma4:cloud"

    async def chat_full(self, messages, *, model=None, no_think=False):
        return (
            '{"branch_id": "accept_resolution", "reason": "empathy + concrete_resolution"}',
            {"output_tokens": 10},
        )


def test_classify_branch_with_fake_llm():
    """The async classifier returns the LLM's branch verdict (R7, offline)."""
    scenario = load("customer_service_refund_ca_v01")
    turns = ["I'm sorry, I can offer a refund."]
    bid, reason = asyncio.run(classify_branch(_FakeLLM(), scenario, turns))
    assert bid == "accept_resolution"
    assert "empathy" in reason


def test_classifier_runs_offline_from_voice_loop():
    """D-P1-05: the classifier is a one-shot end-of-session call, not per-turn."""
    # This is a structural assertion: classify_branch takes the full turns list,
    # not a single turn — confirming it runs at session end, not on the
    # latency-critical voice path.
    scenario = load("customer_service_refund_ca_v01")
    turns = ["turn 1", "turn 2", "turn 3"]
    bid = classify_branch_sync_heuristic(scenario, turns)
    assert bid in scenario.branch_ids()