Deploy public LiteLLM on US DC1 with preserved HK routes
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"""Scoped Vertex dictation settings; ordinary transcription calls stay unchanged."""
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import json
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from pathlib import Path
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VOCABULARY = Path('/credentials/personal-vocabulary.json')
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def vocabulary(path=VOCABULARY):
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words = json.loads(path.read_text())
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if not isinstance(words, list) or not 1 <= len(words) <= 100:
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raise ValueError('Personal vocabulary must contain 1-100 terms')
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if any(not isinstance(word, str) or not word.strip() or len(word) > 100 for word in words):
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raise ValueError('Invalid personal vocabulary term')
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return list(dict.fromkeys(word.strip() for word in words))
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def install():
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from litellm.llms.vertex_ai.audio_transcription.gemini_transcribe_transformation import (
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VertexGeminiAudioTranscriptionConfig,
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)
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original = VertexGeminiAudioTranscriptionConfig.transform_audio_transcription_request
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if getattr(original, '_personal_dictation_patch', False):
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return
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def transform(self, model, audio_file, optional_params, litellm_params):
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if optional_params.get('personal_dictation') is not True:
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return original(self, model, audio_file, optional_params, litellm_params)
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if model.removeprefix('vertex_ai/') != 'gemini-3.5-transcribe':
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raise ValueError('Personal dictation is restricted to Vertex Gemini 3.5 Transcribe')
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if optional_params.get('timestamp_granularities') or optional_params.get('response_format') not in (None, 'json', 'text'):
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raise ValueError('Personal dictation supports json/text without timestamps')
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clean = {key: val for key, val in optional_params.items() if key != 'personal_dictation'}
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result = original(self, model, audio_file, clean, litellm_params)
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config = result.data.setdefault('generationConfig', {}).setdefault('audioTranscriptionConfig', {})
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if set(config) - {'mode', 'languageCodes'} or config.get('mode') not in (None, 'VERBATIM'):
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raise ValueError('Unexpected Vertex transcription defaults; review adapter compatibility')
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config['mode'] = 'SMART'
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config['customVocabulary'] = vocabulary()
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return result
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transform._personal_dictation_patch = True
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VertexGeminiAudioTranscriptionConfig.transform_audio_transcription_request = transform
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if __name__ == '__main__':
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import sys
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from litellm import run_server
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from zenmux_transcription import install as install_zenmux_asr
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from bailian_transcription import install as install_bailian_asr
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install_zenmux_asr()
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install_bailian_asr()
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install()
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sys.argv[0] = 'litellm'
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sys.exit(run_server())
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