ik xddlmZddlmZmZddlmZddlm Z ddl Z ddl m Z mZmZdZdddd d d d d dddddd Zde j$dedede j$fdZeeedej,fdededej.fdZ d#deeefded ede j4fd!Z d#deeefded ede j4fd"Zy)$)Path)OptionalUnionN)base_load_modelget_model_path load_configi> cohere_asr fireredasr2glmasr sensevoicevoxtralvoxtral_realtime vibevoice_asr qwen3_asrcanary moonshinemmsgranite_speech qwen2_audio) r r glmr r r vibevoicerrrrrraudioorig_sr target_srreturnc|ddlm}tj||}||z}||z}|j |||d}|S)Nr)signaledge)padtype)scipyrnpgcd resample_poly)rrrrr"updown resampleds h/Volumes/fast/ai/experiments/voice-extract-mac/.venv/lib/python3.12/site-packages/mlx_audio/stt/utils.pyresample_audior(sG &&) $C c B c>D$$UBf$EI Ffilesrdtypecddlm}||d\}}||k7r t|||}tj||j dS)a? Open an audio file and read as mono waveform, resampling as necessary Parameters ---------- file: str The audio file to open sr: int The sample rate to resample the audio if necessary Returns ------- A NumPy array containing the audio waveform, in float32 dtype. r)readT) always_2d)r,)axis)mlx_audio.audio_ior.r(mxarraymean)r*r+ from_stdinr, audio_readr sample_rates r' load_audior9'sM*6#DD9E;buk26 88E ' , ,! , 44r) model_pathlazystrictc ,td|dt||d|S)a Load and initialize an STT model from a given path. Args: model_path: The path or HuggingFace repo to load the model from. lazy: If False, evaluate model parameters immediately. strict: If True, raise an error if any weights are missing. **kwargs: Additional keyword arguments (revision, force_download). Returns: nn.Module: The loaded and initialized model. stt)r:categorymodel_remappingr;r<)rMODEL_REMAPPINGr:r;r<kwargss r' load_modelrEDs/  '      r)c t|f||d|S)aY Load a speech-to-text model from a local path or HuggingFace repository. This is the main entry point for loading STT models. It automatically detects the model type and initializes the appropriate model class. Args: model_path: The local path or HuggingFace repo ID to load from. lazy: If False, evaluate model parameters immediately. strict: If True, raise an error if any weights are missing. **kwargs: Additional keyword arguments: - revision (str): HuggingFace revision/branch to use - force_download (bool): Force re-download of model files Returns: nn.Module: The loaded and initialized model. Example: >>> from mlx_audio.stt import load >>> model = load("mlx-community/whisper-tiny-asr-fp16") >>> result = model.generate(audio) )r;r<)rErCs r'loadrG]s2 j EtF Ef EEr))FF)pathlibrtypingrrmlx.corecorer3mlx.nnnnnumpyr!mlx_audio.utilsrrr SAMPLE_RATErBndarrayintr(strfloat32Dtyper9boolModulerErGrAr)r'rXs("HH  *  & ""**ssrzz jj 5 5 5 88 5<FKc4i (,>BYY4FKFc4i F(,F>BFYYFr)