ALog is an AI-powered audio diary application designed for users who want to record and reflect on their daily experiences using voice. It leverages AI to process audio entries, offering a convenient way to maintain a personal journal.

How It Works

The project utilizes an AI model, likely from OpenAI, to transcribe and analyze audio recordings. The backend is deployed as a Cloudflare Worker, handling audio processing and AI interactions. Client-side code, presumably Swift for iOS, communicates with this worker to send audio data and receive processed diary entries.

Quick Start & Requirements

• Installation: Clone the repository, install xcodegen via Homebrew, install Ruby gems with bundle install, copy .env.example to .env and update keys, generate the Arkana package (bundle exec bin/arkana), and finally generate the project (xcodegen).
• Prerequisites: Ruby, Homebrew, xcodegen, an OpenAI API key.
• Deployment: Requires creating a Cloudflare worker, pasting Server/src/worker.js into the editor, and setting environment variables (OPENAI_KEY, HMAC_KEY, AI_MODEL). The client-side Constants.swift must be updated with the worker's URL.
• Resources: Setup involves standard development tools; no specific hardware requirements are listed beyond typical development machine capabilities.

Highlighted Details

• AI-powered audio transcription and analysis for diary entries.
• Backend deployed as a Cloudflare Worker for serverless processing.
• Client-side application likely built with Swift for iOS.
• Supports OpenAI API for AI model integration.

Maintenance & Community

The project credits @onenewbite for inspiration. No other community channels or active maintenance indicators are present in the README.

Licensing & Compatibility

Distributed under the GNU General Public License v2.0. The license explicitly states that renaming and repackaging for distribution is permitted, but submission to the App Store under these conditions violates their guidelines.

Limitations & Caveats

The project's primary limitation is its strict adherence to GPLv2, which may impact commercial use or integration into closed-source applications. The README also warns against App Store submission of repackaged versions due to guideline violations.