Refactor code structure for improved readability and maintainability

2026-07-22 22:58:28 +05:30
parent d1308bf149
commit bc8bf2007d
99 changed files with 4784 additions and 111 deletions
@@ -0,0 +1,91 @@
+"""
+RunPod Serverless worker: Speech-to-Text (Whisper via faster-whisper).
+
+Chosen over Parakeet/NeMo because it has NO heavy dependencies (no NeMo, no
+torch — just ctranslate2), so it builds cleanly, AND it's multilingual (99
+languages incl. Hindi/regional + English) — a better fit for a mixed crew.
+
+Lets a worker speak instead of typing annotation text (image + video editors).
+
+Matches the app's transcribe contract:
+  {"input": {
+     "audio": "<base64 audio>",   # required (wav/mp3/m4a; any sample rate — resampled internally)
+     "language": "en",            # optional (e.g. "hi", "en"); omit = auto-detect
+     "timestamps": false          # optional — return per-segment start/end
+  }}
+Returns: {"transcript": "...", "language": "en", "segments"?: [{text,start_sec,end_sec}]}
+         (or {"error": "..."}).
+
+Tuning (env): WHISPER_MODEL (default large-v3; "medium"/"small" are faster),
+WHISPER_COMPUTE (default float16; "int8_float16" for less VRAM).
+"""
+
+import base64
+import os
+import tempfile
+
+_VOLUME = "/runpod-volume"
+if os.path.isdir(_VOLUME):
+    os.environ.setdefault("HF_HOME", os.path.join(_VOLUME, "huggingface"))
+
+import runpod  # noqa: E402
+from faster_whisper import WhisperModel  # noqa: E402
+
+MODEL_SIZE = os.environ.get("WHISPER_MODEL", "large-v3")
+DEVICE = os.environ.get("WHISPER_DEVICE", "cuda")
+COMPUTE = os.environ.get("WHISPER_COMPUTE", "float16")
+
+_model = None
+
+
+def _get_model():
+    global _model
+    if _model is None:
+        _model = WhisperModel(
+            MODEL_SIZE,
+            device=DEVICE,
+            compute_type=COMPUTE,
+            download_root=os.environ.get("HF_HOME"),
+        )
+    return _model
+
+
+def handler(event):
+    inp = (event or {}).get("input") or {}
+    audio_b64 = inp.get("audio")
+    if not audio_b64:
+        return {"error": "Missing 'audio' (base64)."}
+
+    language = inp.get("language") or None
+    want_ts = bool(inp.get("timestamps", False))
+
+    path = None
+    try:
+        data = audio_b64.split(",", 1)[1] if "," in audio_b64 else audio_b64
+        with tempfile.NamedTemporaryFile(suffix=".audio", delete=False) as f:
+            f.write(base64.b64decode(data))
+            path = f.name
+
+        segments, info = _get_model().transcribe(path, language=language, vad_filter=True)
+
+        parts = []
+        segs = []
+        for s in segments:
+            parts.append(s.text)
+            if want_ts:
+                segs.append(
+                    {"text": s.text.strip(), "start_sec": round(s.start, 2), "end_sec": round(s.end, 2)}
+                )
+
+        out = {"transcript": "".join(parts).strip(), "language": info.language}
+        if want_ts:
+            out["segments"] = segs
+        return out
+    except Exception as exc:
+        return {"error": f"{type(exc).__name__}: {exc}"}
+    finally:
+        if path and os.path.exists(path):
+            os.unlink(path)
+
+
+runpod.serverless.start({"handler": handler})