From acbd9ff2c91182d96c57ffb57bee6e9b3fcbcbd4 Mon Sep 17 00:00:00 2001
From: historia <historiavg@proton.me>
Date: Wed, 26 Aug 2026 01:43:41 -0400
Subject: refactor: split tts.py into per-backend packages

---
 app/converter/clients/transcribe.py | 54 +++++++++++++++++++++++++++++++++++++
 1 file changed, 54 insertions(+)
 create mode 100644 app/converter/clients/transcribe.py

(limited to 'app/converter/clients/transcribe.py')

diff --git a/app/converter/clients/transcribe.py b/app/converter/clients/transcribe.py
new file mode 100644
index 0000000..d2db9f1
--- /dev/null
+++ b/app/converter/clients/transcribe.py
@@ -0,0 +1,54 @@
+"""Optional local Whisper transcription of reference audio."""
+
+import logging
+from typing import Optional
+
+logger = logging.getLogger(__name__)
+
+
+def transcribe_reference_audio(audio_path: str, model_name: str = "base") -> Optional[str]:
+    """Transcribe reference audio locally using an optional Whisper backend.
+
+    The current qwen-tts demo does not expose a transcription endpoint, so
+    transcription is done client-side when a Whisper package is available.
+    Returns None if no backend is installed.
+    """
+    for backend in ("faster_whisper", "whisper"):
+        try:
+            if backend == "faster_whisper":
+                from faster_whisper import WhisperModel
+                model = WhisperModel(model_name, device="cpu", compute_type="int8")
+                segments, _ = model.transcribe(audio_path)
+                text = " ".join(seg.text.strip() for seg in segments).strip()
+            else:
+                import whisper
+                model = whisper.load_model(model_name)
+                result = model.transcribe(audio_path)
+                text = (result.get("text") or "").strip()
+            if text:
+                logger.info("Transcription complete via %s: %s", backend, text)
+                return text
+        except ImportError:
+            continue
+        except Exception as exc:
+            logger.warning("%s transcription failed: %s", backend, exc)
+    logger.warning("No Whisper backend available; transcription skipped.")
+    return None
+
+
+def whisper_backend_available() -> Optional[str]:
+    """Return the name of an importable Whisper backend, or None.
+
+    Checks faster_whisper first (preferred), then the openai-whisper
+    package, without importing the heavy model code: a bare import probe
+    is enough to tell whether the package is installed in the current
+    environment. Used by the make_audiocpp_server_json tool to warn when
+    neither is present (e.g. the wrong conda environment is active).
+    """
+    for backend in ("faster_whisper", "whisper"):
+        try:
+            __import__(backend)
+        except ImportError:
+            continue
+        return backend
+    return None
-- 
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