Refactor tool-speechtotext: extract sttlib shared library and add tests

Extract duplicated code (Whisper loading, audio recording, transcription,
VAD processing) into reusable sttlib/ package. Rewrite all 3 scripts as
thin wrappers. Add 24 unit tests with mocked hardware. Fix GPU fallback
bug in assistant.py and args.system assignment bug.

python/tool-speechtotext/tests/test_transcription.py

@@ -0,0 +1,78 @@
+from unittest.mock import MagicMock
+from sttlib.transcription import transcribe, is_hallucination
+
+
+# --- is_hallucination tests ---
+
+def test_known_hallucinations():
+    assert is_hallucination("Thank you")
+    assert is_hallucination("thanks for watching")
+    assert is_hallucination("Subscribe")
+    assert is_hallucination("the end")
+
+
+def test_short_text():
+    assert is_hallucination("hi")
+    assert is_hallucination("")
+    assert is_hallucination("a")
+
+
+def test_normal_text():
+    assert not is_hallucination("Hello how are you")
+    assert not is_hallucination("Please open the terminal")
+
+
+def test_case_insensitivity():
+    assert is_hallucination("THANK YOU")
+    assert is_hallucination("Thank You For Watching")
+
+
+def test_substring_match():
+    assert is_hallucination("I want to subscribe to your channel")
+
+
+def test_exactly_three_chars():
+    assert not is_hallucination("hey")
+
+
+# --- transcribe tests ---
+
+def _make_segment(text):
+    seg = MagicMock()
+    seg.text = text
+    return seg
+
+
+def test_transcribe_joins_segments():
+    model = MagicMock()
+    model.transcribe.return_value = (
+        [_make_segment("Hello "), _make_segment("world")],
+        None,
+    )
+    result = transcribe(model, MagicMock())
+    assert result == "Hello world"
+
+
+def test_transcribe_empty():
+    model = MagicMock()
+    model.transcribe.return_value = ([], None)
+    result = transcribe(model, MagicMock())
+    assert result == ""
+
+
+def test_transcribe_strips_whitespace():
+    model = MagicMock()
+    model.transcribe.return_value = (
+        [_make_segment("  hello  ")],
+        None,
+    )
+    result = transcribe(model, MagicMock())
+    assert result == "hello"
+
+
+def test_transcribe_passes_beam_size():
+    model = MagicMock()
+    model.transcribe.return_value = ([], None)
+    audio = MagicMock()
+    transcribe(model, audio)
+    model.transcribe.assert_called_once_with(audio, beam_size=5)