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ALog: portable AI voice diary app with speech-to-text support.

General Introduction

ALog is an AI-based voice diary application designed to help users record their daily lives by voice. The project is developed by duxins and open-sourced on GitHub. Users can record diary through voice input, the application will automatically convert voice to text, and intelligent analysis and categorization. ALog supports multi-platform use, and provides a detailed installation and usage guide, so that users can get started quickly.

Deployment of the project consists of building the project and deploying the server-side code to Cloudflare. environment variables such as the OpenAI API key need to be set when configuring the worker on Cloudflare.


 

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Function List

  • Voice recording: Record diary contents by voice input
  • Speech to text: automatically converts speech to text
  • Intelligent analysis: Intelligent analysis and classification of diary content
  • Multi-platform support: iOS and Android platforms are supported.
  • Open source project: code open, users can freely modify and extend the function

 

Using Help

Installation process

  1. clone warehouse: First, clone ALog's GitHub repository.
    git clone https://github.com/duxins/alog
    

     

  2. Installation of dependencies: Install xcodegen with Homebrew.
    brew install xcodegen
    

     

  3. Installing Ruby gems: Run the following command in the project directory.
    bundle install
    

     

  4. Configuring Environment Variables: Reproduction .env.example file and rename it .env, and then update the keys in it as needed.
    cp .env.example .env
    

     

  5. Generate project files: Run xcodegen to generate the project file.
    xcodegen
    

     

Usage Process

  1. launch an application: Open the generated Xcode project file, compile and run the application.
  2. voice recording: Tap the Record button within the app to start voice recording the contents of your diary.
  3. speech-to-text: When the recording is finished, the app automatically converts the voice to text and displays it in the diary list.
  4. intelligent analysis (religion): The app intelligently analyzes and categorizes diary content, and users can view different types of diary entries through categorized tags.
  5. Multi-platform useALog supports both iOS and Android platforms, allowing users to synchronize their devices.

Deploying server-side code to Cloudflare

  1. Creating a Cloudflare Worker: After logging into Cloudflare, navigate to the "Workers & Pages" section and click "Create Application" → "Create Worker". Rename the worker as needed and click "Deploy".
  2. Configuring the Worker: Once deployed, click on the "Quick Edit" button to move the Server/src/worker.js Paste the contents of the file into the Cloudflare Worker editor and click "Save and deploy".
  3. Setting environment variables: Under the Worker's Settings tab, navigate to the Variables section and set the following variables:
    • OPENAI_KEY: Required, your OpenAI API key.
    • HMAC_KEY: Optional, consistent with the key used by the client.
    • AI_MODEL: Optional, default model.
  4. Updating the API base URL: Open Constants.swift file, which will api_base_url Constants are updated to the URL of the deployed Cloudflare Worker.
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