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3.33 kB
| import base64 | |
| import os | |
| from boson_multimodal.data_types import ChatMLSample, Message, AudioContent | |
| def encode_base64_content_from_file(file_path: str) -> str: | |
| """Encode a content from a local file to base64 format.""" | |
| # Read the audio file as binary and encode it directly to Base64 | |
| with open(file_path, "rb") as audio_file: | |
| audio_base64 = base64.b64encode(audio_file.read()).decode("utf-8") | |
| return audio_base64 | |
| def get_interleaved_dialogue_input_sample(): | |
| system_prompt = ( | |
| "Generate audio following instruction.\n\n" | |
| "<|scene_desc_start|>\n" | |
| "SPEAKER0: vocal fry;moderate pitch;monotone;masculine;young adult;slightly fast\n" | |
| "SPEAKER1: masculine;moderate;moderate pitch;monotone;mature\n\n" | |
| "In this scene, a group of adventurers is debating whether to investigate a potentially dangerous situation.\n" | |
| "<|scene_desc_end|>" | |
| ) | |
| messages = [ | |
| Message( | |
| role="system", | |
| content=system_prompt, | |
| ), | |
| Message( | |
| role="user", | |
| content="<|generation_instruction_start|>\nGenerate interleaved transcript and audio that lasts for around 20 seconds.\n<|generation_instruction_end|>", | |
| ), | |
| ] | |
| chat_ml_sample = ChatMLSample(messages=messages) | |
| return chat_ml_sample | |
| def get_zero_shot_input_sample(): | |
| system_prompt = ( | |
| "Generate audio following instruction.\n\n<|scene_desc_start|>\nSPEAKER0: british accent\n<|scene_desc_end|>" | |
| ) | |
| messages = [ | |
| Message( | |
| role="system", | |
| content=system_prompt, | |
| ), | |
| Message( | |
| role="user", | |
| content="Hey, everyone! Welcome back to Tech Talk Tuesdays.\n" | |
| "It's your host, Alex, and today, we're diving into a topic that's become absolutely crucial in the tech world — deep learning.\n" | |
| "And let's be honest, if you've been even remotely connected to tech, AI, or machine learning lately, you know that deep learning is everywhere.", | |
| ), | |
| ] | |
| chat_ml_sample = ChatMLSample(messages=messages) | |
| return chat_ml_sample | |
| def get_voice_clone_input_sample(): | |
| reference_text = "I would imagine so. A wand with a dragon heartstring core is capable of dazzling magic." | |
| reference_audio = encode_base64_content_from_file( | |
| os.path.join(os.path.dirname(__file__), "voice_examples/old_man.wav") | |
| ) | |
| messages = [ | |
| Message( | |
| role="user", | |
| content=reference_text, | |
| ), | |
| Message( | |
| role="assistant", | |
| content=AudioContent(raw_audio=reference_audio, audio_url="placeholder"), | |
| ), | |
| Message( | |
| role="user", | |
| content="Hey, everyone! Welcome back to Tech Talk Tuesdays.\n" | |
| "It's your host, Alex, and today, we're diving into a topic that's become absolutely crucial in the tech world — deep learning.\n" | |
| "And let's be honest, if you've been even remotely connected to tech, AI, or machine learning lately, you know that deep learning is everywhere.", | |
| ), | |
| ] | |
| return ChatMLSample(messages=messages) | |
| INPUT_SAMPLES = { | |
| "interleaved_dialogue": get_interleaved_dialogue_input_sample, | |
| "zero_shot": get_zero_shot_input_sample, | |
| "voice_clone": get_voice_clone_input_sample, | |
| } | |