Revert transformers cap; catch torchcodec ASR failure with clear message

install.py: restore transformers>=5.0.0 (capping it would break other nodes).
generator.py: catch the torchcodec RuntimeError that fires when ref_text is
blank and transformers 5.x auto-transcription requires missing FFmpeg libs.
Raises a human-readable error telling the user to fill in ref_text manually.
Also updates the ref_text tooltip to recommend providing it explicitly.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

nodes/generator.py

@@ -60,7 +60,7 @@ class OmniVoiceGenerate:
                 }),
                 "ref_text": ("STRING", {
                     "default": "",
-                    "tooltip": "Transcription of ref_audio. Leave blank to auto-transcribe with Whisper.",
+                    "tooltip": "Transcription of ref_audio. Strongly recommended: type it manually. Auto-transcription requires FFmpeg shared libraries; if absent (e.g. some Docker images), generation will fail with a clear error message.",
                 }),
                 "instruct": ("STRING", {
                     "default": "",
@@ -115,7 +115,16 @@ class OmniVoiceGenerate:
                 kwargs["ref_audio"] = tmp_path
                 if ref_text:
                     kwargs["ref_text"] = ref_text
+                try:
                     audio_tensors = model.generate(**kwargs)
+                except RuntimeError as e:
+                    if "torchcodec" in str(e).lower() or "libtorchcodec" in str(e).lower():
+                        raise RuntimeError(
+                            "Auto-transcription of the reference audio failed because FFmpeg is not "
+                            "available in this environment (required by transformers 5.x for Whisper ASR). "
+                            "Fix: type the transcript of your reference audio into the ref_text field."
+                        ) from None
+                    raise
             finally:
                 try:
                     os.unlink(tmp_path)