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RecapAI

Recap

Open Source, Privacy-First, macOS-Native AI Meeting Summary

ApplicationsProductivitySwift
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创建于 2025-08-02 · 更新于 2026-10-12 · 今日第 14584 名
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rawandahmad698dennisimootleyden

RecapAI/Recap 排名第 14,584,有 719 个星标。

同类别比较

RecapAI/Recap 排名第 14,584,此处有 8 个同类条目;dtnewman/zev 排名第 14,576。

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关键参数与规格
关键参数与规格
参数值
语言Swift
类别Applications
子类别Productivity
关键词LocalAI, Speech-to-text, Summarization
星标数719
分叉数41
贡献者3
创建日期2025-08-02
更新日期2026-10-12
1 天星标数0
7 天星标数1
排名14,584
上次排名14,435
排名变化-149
7 天星标排名10,831
上次 7 天星标排名10,894
7 天星标排名变化63
总星标排名14,572
上次总星标排名14,543
总星标排名变化-29
README 摘录

Screenshots View Screenshots Recap Preview Previous Recaps General Settings Whisper Models Section Jump to: Why Recap? Features System Requirements How It Works Installation Usage Contributing Why Recap? Ever been in a meeting where you wanted to focus on your work but still catch the important bits? I found myself constantly torn between paying attention to meetings and getting actual work done. Sometimes I'd miss crucial decisions while coding, or I'd lose my flow state trying to take notes. I needed

something that could listen for me and give me the highlights afterward. But here's the thing - I didn't want my private conversations floating around on some company's servers. When you're discussing sensitive business matters, product roadmaps, or personal topics, that data should stay on YOUR machine. That's why Recap processes everything locally on your Mac using Apple's own technologies. Recap is broken in its current state, but since I use it daily myself, you can absolutely expect new features soon

! TIP] Recap is in an incomplete state and I suggest that it is not used for production and daily usage, but help in shaping it is greatly appreciated. Recap Recap is an open-source, privacy-focused, macOS-native project to help you summarize your meetings. You could summarize audio of any app, not just meetings. Features **Meeting Detection**: Automatically detects meetings in Microsoft Teams, Zoom, Google Meet, and more using macOS ScreenCaptureKit **Audio Recording**: Records system audio and optionally microphone

input **Local Processing**: Uses WhisperKit for transcription and Ollama/(optionally, OpenRouter) for summarization **Privacy First**: No data leaves your device unless you choose to share it **Open Source**: Fully transparent codebase for community contributions Under the hood Native Core Audio taps, AVAudioEngine, driver-free system audio capture WhisperKit (MLX) (local transcription), Ollama/OpenRouter (summarization) Swift + SwiftUI Roadmap: Working on the following features now: [ ] Meeting Detection (Teams, Zoom, Google etc) [ ] Custom Prompt Via Settings (PR In Progress) [ ] Live Transcription using Parakeet

V2 (PR In Progress) [ ] Background Audio Processing [ ] Auto Recording Stop [ ] Better Error Handling [ ] 85% or more test coverage Right now, Recap is more of a POC of what I am trying to make. It records system audio (Core Audio Taps) + with an optional microphone recording (your audio) and feeds it to Whisper for transcription and then uses Ollama for summarizing. 0 or later | | **Processor** | Apple M1 | Apple M2 or newer | | **RAM** | 8 GB | 16 GB or more | | **Storage** | 2 GB

free space | 5 GB free space | **Note**: Intel Macs are not supported. How It Works bash git clone cd recap open Recap. xcodeproj bash HF_TOKEN="your_huggingface_token_here" bash OPENROUTER_API_KEY="your_openrouter_api_key_here" bash ollama pull llama3 ` Whisper Models 1. **Download & Select a Model:** Open Recap and go to **Settings → Whisper Models** Download a Whisper model (recommended: **Large v3** for best accuracy) Wait for the download to complete before proceeding 2. **Configure LLM Provider

:** Go to **Settings → LLM Models** Choose your preferred provider (Ollama or OpenRouter) If using Ollama, ensure it's installed and running

常见问题

记录了多少星标和分叉?

RecapAI/Recap 有 719 个星标和 41 个分叉。

仓库排名是多少?

RecapAI/Recap 排名第 14,584。

记录的语言和类别是什么?

RecapAI/Recap 有 719 个星标,语言为 Swift,类别为 Applications。

哪个仓库排名最接近?

RecapAI/Recap 与 dtnewman/zev 比较,后者排名第 14,576,有 720 个星标。

README

Screenshots

View Screenshots

Recap Preview

Previous Recaps

General Settings

Whisper Models Section

Jump to:

Why Recap?

Ever been in a meeting where you wanted to focus on your work but still catch the important bits? That's exactly why I created Recap.

I found myself constantly torn between paying attention to meetings and getting actual work done. Sometimes I'd miss crucial decisions while coding, or I'd lose my flow state trying to take notes. I needed something that could listen for me and give me the highlights afterward.

But here's the thing - I didn't want my private conversations floating around on some company's servers. When you're discussing sensitive business matters, product roadmaps, or personal topics, that data should stay on YOUR machine. That's why Recap processes everything locally on your Mac using Apple's own technologies.

Recap is broken in its current state, but since I use it daily myself, you can absolutely expect new features soon!


[!TIP] Recap is in an incomplete state and I suggest that it is not used for production and daily usage, but help in shaping it is greatly appreciated.

Recap

Recap is an open-source, privacy-focused, macOS-native project to help you summarize your meetings. You could summarize audio of any app, not just meetings.

Features

  • Meeting Detection: Automatically detects meetings in Microsoft Teams, Zoom, Google Meet, and more using macOS ScreenCaptureKit
  • Audio Recording: Records system audio and optionally microphone input
  • Local Processing: Uses WhisperKit for transcription and Ollama/(optionally, OpenRouter) for summarization
  • Privacy First: No data leaves your device unless you choose to share it
  • Open Source: Fully transparent codebase for community contributions

Under the hood

  • Native Core Audio taps, AVAudioEngine, driver-free system audio capture
  • WhisperKit (MLX) (local transcription), Ollama/OpenRouter (summarization)
  • Swift + SwiftUI

Roadmap:

Working on the following features now:

  • [ ] Meeting Detection (Teams, Zoom, Google etc)
  • [ ] Custom Prompt Via Settings (PR In Progress)
  • [ ] Live Transcription using Parakeet V2 (PR In Progress)
  • [ ] Background Audio Processing
  • [ ] Auto Recording Stop
  • [ ] Better Error Handling
  • [ ] 85% or more test coverage

Right now, Recap is more of a POC of what I am trying to make. It records system audio (Core Audio Taps) + with an optional microphone recording (your audio) and feeds it to Whisper for transcription and then uses Ollama for summarizing.

LLM Options:

  • Ollama (recommended): Complete privacy - everything stays on your device
  • OpenRouter: Cloud-based option if you lack local compute capacity, but data leaves your device

System Requirements

Ollama (Local Processing)

Component Minimum Recommended
macOS 15.0 or later 15.0 or later
Processor Apple M1 Apple M2 Pro or newer
RAM 16 GB 32 GB or more
Storage 10 GB free space 50 GB free space

OpenRouter (Cloud Processing)

Component Minimum Recommended
macOS 15.0 or later 15.0 or later
Processor Apple M1 Apple M2 or newer
RAM 8 GB 16 GB or more
Storage 2 GB free space 5 GB free space

Note: Intel Macs are not supported. Use it at your own risk.

How It Works

                              ┌───────────────┐
                          ┌───┤ 1. App Start  │
                          │   └───────────────┘
                          ▼
                    ┌─────────────┐
                    │2.App Select │
                    └─────────────┘
                          │
                          ▼
               ┌────────────────────────┐
               │3. Start Recording      │
               │   • System Audio       │
               │   • Microphone (opt)   │
               └────────────────────────┘
                          │
                          ▼
               ┌────────────────────────┐
               │4. Stop Recording       │
               │   • Save Audio Files   │
               │   • Create DB Record   │
               └────────────────────────┘
                          │
                          ▼
               ┌────────────────────────┐
               │5. Background Process   │
               │   • Transcribe Audio   │
               │   • Generate Summary   │
               └────────────────────────┘
                          │
                          ▼
               ┌────────────────────────┐
               │6. Complete & Store     │
               │   • Update DB Record   │
               │   • Show Results       │
               └────────────────────────┘

Installation

Currently, Recap is only available through compilation from source. Pre-built releases will be available once core features are stabilized.

Compile from Source

  1. Prerequisites:

    • Ensure your system meets the requirements above
    • Install Xcode 15.0 or later from the Mac App Store
  2. Clone and Build:

    git clone https://github.com/rawandahmad698/recap.git
    cd recap
    open Recap.xcodeproj
    
  3. Build in Xcode:

    • Build and run (⌘+R)

Note: Distribution via Mac App Store and direct download will be available in future releases once the app reaches production readiness.

Usage

Required Environment Variables (Set Via Xcode Scheme Editor)

  • Support for Keychain-based token storage soon

Before using, you need to set up the following environment variables using Xcode Scheme Editor:

  • HF_TOKEN (Required): Hugging Face token for downloading Whisper models

    HF_TOKEN="your_huggingface_token_here"
    

Read Hugging Face documentation to get a token!

  • OPENROUTER_API_KEY (Optional): Only required if using OpenRouter for summarization

    OPENROUTER_API_KEY="your_openrouter_api_key_here"
    

Read OpenRouter documentation to get a key!

First-Time Setup

Ollama Setup

  1. Download Ollama here: Ollama

  2. Pull the latest models (i.e. Llama 3):

    ollama pull llama3
    

Whisper Models

  1. Download & Select a Model:

    • Open Recap and go to Settings → Whisper Models
    • Download a Whisper model (recommended: Large v3 for best accuracy)
    • Wait for the download to complete before proceeding
  2. Configure LLM Provider:

    • Go to Settings → LLM Models
    • Choose your preferred provider (Ollama or OpenRouter)
    • If using Ollama, ensure it's installed and running locally
  3. Start Recording:

    • Select an audio application from the dropdown
    • Click the record button to start capturing
    • Optionally enable microphone for dual-audio recording
    • Click stop when finished - processing will begin automatically

Contributing

I really need help finishing Recap! Any contribution is greatly welcomed.

Focus:

  • See Roadmap above for current focus areas

How to Contribute

  1. Fork the repository and create a feature branch
  2. Submit a pull request with clear description of changes

All skill levels welcome - from fixing typos to architecting new features. I really mean it!

Linter

Not using any linter right now, but I am planning to use SwiftLint/SwiftFormat in the future (PRs greatly welcomed).

Be notified of releases, watch the repo!

Star History

License

MIT License

Copyright © 2025 Rawand Ahmed Shaswar

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. What this means:

Any kind of usage allowed — personal, educational, or commercial use and modification is permitted. Redistribution allowed — you may freely redistribute the original or modified project.

Please see the LICENSE file for full details.

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