docs(P01): complete minimal-voice-loop phase

---ci---
phase: 1
milestone: v0.1
status: complete
requirements:
  covered: [REQ-VOICE-01, REQ-VOICE-02, REQ-VOICE-03, REQ-VOICE-04, REQ-SCEN-01, REQ-STATE-01, REQ-LLM-01, REQ-LLM-02, REQ-DEBRIEF-01, REQ-ORCH-01, REQ-ORCH-02, REQ-SCEN-FMT-01, REQ-NFR-LAT-01, REQ-NFR-SAFE-01, REQ-NFR-COST-01]
  partial: []
---/ci---

tests/test_classifier.py

@@ -0,0 +1,125 @@
+"""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()