MLX Transcribe: A tool for transcribing audio files using MLX Whisper - Agno

Requirements: 1. ffmpeg - Install using: - macOS: brew install ffmpeg - Ubuntu: sudo apt-get install ffmpeg - Windows: Download from https://ffmpeg.org/download.html

"""
MLX Transcribe: A tool for transcribing audio files using MLX Whisper

Requirements:
1. ffmpeg - Install using:
   - macOS: `brew install ffmpeg`
   - Ubuntu: `sudo apt-get install ffmpeg`
   - Windows: Download from https://ffmpeg.org/download.html

2. mlx-whisper library:
   uv pip install mlx-whisper

Example Usage:
- Place your audio files in the 'storage/audio' directory
    Eg: download https://www.ted.com/talks/reid_hoffman_and_kevin_scott_the_evolution_of_ai_and_how_it_will_impact_human_creativity
- Run this script to transcribe audio files
- Supports various audio formats (mp3, mp4, wav, etc.)
"""

from pathlib import Path

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.mlx_transcribe import MLXTranscribeTools

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------


# Get audio files from storage/audio directory
agno_root_dir = Path(__file__).parent.parent.parent.resolve()
audio_storage_dir = agno_root_dir.joinpath("storage/audio")

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    if not audio_storage_dir.exists():
        audio_storage_dir.mkdir(exist_ok=True, parents=True)

    agent = Agent(
        name="Transcription Agent",
        model=OpenAIChat(id="gpt-4o"),
        tools=[MLXTranscribeTools(base_dir=audio_storage_dir)],
        instructions=[
            "To transcribe an audio file, use the `transcribe` tool with the name of the audio file as the argument.",
            "You can find all available audio files using the `read_files` tool.",
        ],
        markdown=True,
    )

    agent.print_response(
        "Summarize the reid hoffman ted talk, split into sections", stream=True
    )

Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/91_tools

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python mlx_transcribe_tools.py

⌘I