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import gradio as gr |
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from config import VOICE_MODE_CLONE |
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from ..core.state import ( |
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generation_state_lock, |
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get_stop_generation_requested, |
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set_stop_generation_requested |
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) |
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from ..core.authentication import get_huggingface_token |
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from ..core.memory import ( |
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has_temporary_files_pending_cleanup, |
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cleanup_expired_temporary_files, |
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perform_memory_cleanup, |
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memory_cleanup, |
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trigger_background_cleanup_check |
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) |
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from ..tts.manager import text_to_speech_manager |
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from ..validation.text import validate_text_input |
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def check_if_generating(): |
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from ..core.state import is_currently_generating |
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with generation_state_lock: |
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return is_currently_generating |
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def request_generation_stop(): |
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set_stop_generation_requested(True) |
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return gr.update(interactive=False) |
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def perform_speech_generation( |
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text_input, |
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voice_mode_selection, |
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voice_preset_selection, |
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voice_clone_audio_file, |
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model_variant, |
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lsd_decode_steps, |
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temperature, |
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noise_clamp, |
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eos_threshold, |
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frames_after_eos, |
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enable_custom_frames |
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): |
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from ..core import state as global_state |
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if has_temporary_files_pending_cleanup(): |
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cleanup_expired_temporary_files() |
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perform_memory_cleanup() |
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is_valid, validation_result = validate_text_input(text_input) |
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if not is_valid: |
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if validation_result: |
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raise gr.Error(validation_result) |
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raise gr.Error("Please enter valid text to generate speech.") |
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if voice_mode_selection == VOICE_MODE_CLONE: |
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if not voice_clone_audio_file: |
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raise gr.Error("Please upload an audio file for voice cloning.") |
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if not get_huggingface_token(): |
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raise gr.Error("Voice cloning is not configured properly at the moment. Please try again later.") |
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with generation_state_lock: |
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if global_state.is_currently_generating: |
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raise gr.Error("A generation is already in progress. Please wait.") |
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global_state.is_currently_generating = True |
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global_state.stop_generation_requested = False |
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generated_audio_tensor = None |
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cloned_voice_state_tensor = None |
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try: |
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text_to_speech_manager.load_or_get_model( |
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model_variant, |
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temperature, |
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lsd_decode_steps, |
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noise_clamp, |
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eos_threshold |
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) |
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with generation_state_lock: |
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if global_state.stop_generation_requested: |
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return None |
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if voice_mode_selection == VOICE_MODE_CLONE: |
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cloned_voice_state_tensor = text_to_speech_manager.get_voice_state_for_clone(voice_clone_audio_file) |
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voice_state = cloned_voice_state_tensor |
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else: |
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voice_state = text_to_speech_manager.get_voice_state_for_preset(voice_preset_selection) |
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with generation_state_lock: |
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if global_state.stop_generation_requested: |
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return None |
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generated_audio_tensor = text_to_speech_manager.generate_audio( |
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validation_result, |
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voice_state, |
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frames_after_eos, |
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enable_custom_frames |
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) |
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with generation_state_lock: |
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if global_state.stop_generation_requested: |
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return None |
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output_file_path = text_to_speech_manager.save_audio_to_file(generated_audio_tensor) |
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return output_file_path |
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except gr.Error: |
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raise |
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except RuntimeError as runtime_error: |
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raise gr.Error(str(runtime_error)) |
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except Exception as generation_error: |
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raise gr.Error(f"Speech generation failed: {str(generation_error)}") |
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finally: |
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with generation_state_lock: |
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global_state.is_currently_generating = False |
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global_state.stop_generation_requested = False |
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if generated_audio_tensor is not None: |
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del generated_audio_tensor |
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generated_audio_tensor = None |
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if cloned_voice_state_tensor is not None: |
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del cloned_voice_state_tensor |
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cloned_voice_state_tensor = None |
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memory_cleanup() |
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trigger_background_cleanup_check() |
