ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter6/controllable-tts/test_fish_s1.py

@@ -0,0 +1,91 @@
+import json
+import subprocess
+
+import pytest
+
+from evaluate_audio_quality import DIMENSIONS, OUTPUTS, PERMUTATIONS, aggregate, validate_response
+from markup import parse
+from tts import concat_mp3, make_silence
+from voice_library import EMOTIONS, SPEEDS, STYLES, load_voice_library
+
+
+def test_native_s1_nonverbal_events_not_onomatopoeia():
+    segments = parse("[THINKING]好吧，[SIGH][LAUGH:small][BREATH]继续。")
+    texts = [s["text"] for s in segments if s["type"] == "speech"]
+    assert "(uncertain)嗯……" in texts
+    assert "(sighing)" in texts
+    assert "(chuckling)" in texts
+    assert "(gasping)" in texts
+    assert "哈哈，" not in texts and "唉——" not in texts
+
+
+@pytest.mark.parametrize(
+    "directory_name",
+    ["speaker clips", "speaker's clips", "d'angelo's clips"],
+)
+def test_concat_handles_apostrophe_in_output_directory(tmp_path, directory_name):
+    """FFconcat must preserve ordinary, single-quote, and multi-quote paths."""
+    output_dir = tmp_path / directory_name
+    output_dir.mkdir()
+    parts = [output_dir / "first.mp3", output_dir / "second.mp3"]
+    for part in parts:
+        make_silence(100, part)
+
+    output = output_dir / "joined.mp3"
+    concat_mp3(parts, output)
+
+    duration = float(subprocess.check_output([
+        "ffprobe", "-v", "error", "-show_entries", "format=duration",
+        "-of", "default=noprint_wrappers=1:nokey=1", str(output),
+    ], text=True).strip())
+    assert output.is_file()
+    assert duration >= 0.18
+
+
+def test_library_requires_exact_cartesian_product(tmp_path):
+    manifest = tmp_path / "manifest.json"
+    manifest.write_text(json.dumps({"profiles": {}}))
+    with pytest.raises(ValueError, match="24"):
+        load_voice_library(manifest)
+
+
+def test_dimensions_are_4_by_3_by_2():
+    assert len(EMOTIONS) * len(SPEEDS) * len(STYLES) == 24
+
+
+def _judge_response(scores):
+    return {
+        "clips": {
+            alias: {
+                dimension: {"score": scores[alias], "reason": f"audible evidence for {alias}"}
+                for dimension in DIMENSIONS
+            }
+            for alias in ("X", "Y", "Z")
+        },
+        "ranking": sorted(("X", "Y", "Z"), key=scores.get, reverse=True),
+        "ranking_reason": "audible comparison",
+    }
+
+
+def test_quality_response_rejects_bare_scores_without_audible_evidence():
+    response = _judge_response({"X": 1, "Y": 2, "Z": 3})
+    response["clips"]["X"]["naturalness"]["reason"] = ""
+    with pytest.raises(ValueError, match="audible evidence"):
+        validate_response(response)
+
+
+def test_position_balanced_aggregate_maps_aliases_back_to_configurations():
+    # Each pass gives C=5, B=4, A=2 regardless of its anonymous position.
+    passes = []
+    score_by_name = {
+        "A_no_control_markers": 2,
+        "B_single_reference": 4,
+        "C_24_reference_library": 5,
+    }
+    for permutation in PERMUTATIONS:
+        mapping = dict(zip(("X", "Y", "Z"), permutation))
+        scores = {alias: score_by_name[name] for alias, name in mapping.items()}
+        passes.append({"alias_to_configuration": mapping, "response": _judge_response(scores)})
+    result = aggregate(passes)
+    assert result["aggregate_ranking"] == list(reversed(list(OUTPUTS)))
+    assert result["manuscript_quality_claim_reproduced"] is True