MCP Server Whisper

"""Constants and enumerations for the MCP Server Whisper.""" from enum import Enum from typing import Literal # Type Aliases SupportedChatWithAudioFormat = Literal["mp3", "wav"] AudioChatModel = Literal[ "gpt-4o-audio-preview", "gpt-4o-audio-preview-2024-10-01", "gpt-4o-audio-preview-2024-12-17", "gpt-4o-audio-preview-2025-06-03", "gpt-4o-mini-audio-preview", "gpt-4o-mini-audio-preview-2024-12-17", ] EnhancementType = Literal["detailed", "storytelling", "professional", "analytical"] TTSVoice = Literal["alloy", "ash", "ballad", "coral", "echo", "sage", "shimmer", "verse", "marin", "cedar"] # Supported Audio Formats TRANSCRIBE_AUDIO_FORMATS = { ".flac", # Added FLAC support ".mp3", ".mp4", ".mpeg", ".mpga", ".m4a", ".ogg", # Added OGG support ".wav", ".webm", } CHAT_WITH_AUDIO_FORMATS = {".mp3", ".wav"} # Enhancement Prompts ENHANCEMENT_PROMPTS: dict[EnhancementType, str] = { "detailed": "The following is a detailed transcript that includes all verbal and non-verbal elements. " "Background noises are noted in [brackets]. Speech characteristics like [pause], [laughs], and [sighs] " "are preserved. Filler words like 'um', 'uh', 'like', and 'you know' are included. " "Hello... [deep breath] Let me explain what I mean by that. [background noise] You know, it's like...", "storytelling": "The following is a natural conversation with proper punctuation and flow. " "Each speaker's words are captured in a new paragraph with emotional context preserved. " "Hello! I'm excited to share this story with you. It began on a warm summer morning...", "professional": "The following is a clear, professional transcript with proper capitalization and punctuation. " "Each sentence is complete and properly structured. Technical terms and acronyms are preserved exactly. " "Welcome to today's presentation on the Q4 financial results. Our KPIs show significant growth.", "analytical": "The following is a precise technical transcript that preserves speech patterns and terminology. " "Note changes in speaking pace, emphasis, and technical terms exactly as spoken. " "Preserve specialized vocabulary, acronyms, and technical jargon with high fidelity. " "Example: The API endpoint /v1/completions [spoken slowly] accepts JSON payloads " "with a maximum token count of 4096 [emphasis on numbers].", } class SortBy(str, Enum): """Sorting options for audio files.""" NAME = "name" SIZE = "size" DURATION = "duration" MODIFIED_TIME = "modified_time" FORMAT = "format" # Default Values DEFAULT_MAX_FILE_SIZE_MB = 25 DEFAULT_TTS_MAX_LENGTH = 4000 DEFAULT_TTS_SAMPLE_RATE = 11025