mantisai 0.1.4

A Python package for transcribing audio files, summarizing text, and extracting information using Gemini AI and Pydantic.

Mantis: Audio Processing with Large Language Models

Mantis is a Python package that makes it easy to transcribe audio files, generate summaries, and extract information using large language models. Built with Pydantic for robust data validation, it provides a simple and user-friendly API for processing both local audio files and YouTube content.

Key Features

• Audio Transcription: Convert audio files to text.
• Text Summarization: Generate concise summaries of your audio content.
• Information Extraction: Retrieve specific details from audio using custom prompts.
• Structured Data: Extract information in typed, validated formats using Pydantic models.
• YouTube Support: Automatically process YouTube URLs.
• Pydantic Validation: Ensure robust input/output handling.

Installation

Install Mantis with pip:

pip install mantisai

Quick Start

For Local Files

import mantis

# Transcribe a local audio file
print(mantis.transcribe("path/to/local/audio.mp3"))

# Summarize a local audio file
print(mantis.summarize("path/to/local/audio.mp3"))

# Extract information from a local audio file using a custom prompt
print(mantis.extract("path/to/local/audio.mp3", "Extract key details"))

For YouTube URLs

import mantis

# Transcribe a YouTube URL
print(mantis.transcribe("https://www.youtube.com/watch?v=example"))

# Summarize a YouTube URL
print(mantis.summarize("https://www.youtube.com/watch?v=example"))

# Extract information from a YouTube URL using a custom prompt
print(mantis.extract("https://www.youtube.com/watch?v=example", "Extract key details"))

Usage Notes

• Unified Interface: Whether you're passing a .mp3 file or a YouTube URL, the functions mantis.transcribe, mantis.summarize, and mantis.extract are used in the same way.
• Custom Prompts: For extraction, you can provide a custom prompt to guide the information retrieval.
• API Key: Ensure your Gemini AI API key is set in your environment (or in your code) as shown.
• Default Generative Model: Mantis uses Gemini 1.5 Flash by default.

Contributing

We welcome contributions! Here's how you can help:

1. Fork the repository.
2. Create a feature branch.
3. Make your changes.
4. Run the tests: python -m unittest discover tests
5. Submit a pull request.

License

This project is licensed under the Apache 2.0 License – see the LICENSE file for details.