Transcribe audio using the Groq.com Whisper API
Project description
llm-groq-whisper
Transcribe audio using the Groq.com Whisper API
Installation
Install this plugin in the same environment as LLM.
llm install llm-groq-whisper
Usage
Run transcripts using:
llm groq-whisper audio.mp3
llm groq-whisper --help
Usage: llm groq-whisper [OPTIONS] AUDIO_FILE
Run transcriptions or translations using the Groq Whisper API
Usage: llm groq-whisper audio.mp3 > output.txt cat audio.mp3 | llm
groq-whisper - > output.txt
Examples: # Basic transcription llm groq-whisper audio.mp3
# Translation to English llm groq-whisper --translate audio.mp3
# Transcription with specific model and language llm groq-whisper
--model whisper-large-v3 --language fr audio.mp3
# Detailed JSON output with timestamps llm groq-whisper --response-
format verbose_json audio.mp3
Options:
--key TEXT Groq API key to use
--model [whisper-large-v3-turbo|distil-whisper-large-v3-en|whisper-large-v3]
Whisper model to use
--response-format [json|verbose_json|text]
Response format
--language TEXT Language code (e.g., 'en' for English). Only
for whisper-large-v3-turbo and whisper-
large-v3
--temperature FLOAT Temperature between 0 and 1
--prompt TEXT Optional context or spelling guidance (max 224
tokens)
--translate Use translation endpoint instead of
transcription
--help Show this message and exit.
Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd llm-groq-whisper
python -m venv venv
source venv/bin/activate
Now install the dependencies and test dependencies:
llm install -e '.[test]'
To run the tests:
python -m pytest
Project details
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