Dabis Content Manager

Desktop tool for content creators – upload, schedule and optimize videos with local AI.

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📋 Overview

Dabis Content Manager is a Windows desktop application that streamlines the upload workflow for YouTube videos. Instead of juggling multiple browser tabs, you handle everything in one app – from selecting the video file to scheduling the upload with thumbnail and playlist assignment.

The app runs in portable mode by default – all data stays in the application folder, so you can run it from a USB drive or any location without installation.

Optionally, a local AI model helps you create titles, descriptions, tags and even chapter timestamps. The AI runs entirely on your machine, so no data is sent to external servers.

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✨ Features

Feature	Description
Portable mode	Run from any folder – no installation required
YouTube upload	Upload videos directly from the app, including thumbnail
Scheduled publishing	Set date and time for the release with visual picker
Chapter generation	Automatic timestamps/chapters from transcription
Transcription	Local speech-to-text with Whisper (offline)
AI suggestions	Generate titles, descriptions and tags (local, offline)
Presets	Save and reuse upload configurations
Templates	Reusable description templates with placeholders
Multi-upload	Queue multiple videos with fast-fill workflow
Channel profile	Store language, tone and target audience for better AI suggestions
Upload history	Overview of all uploads with status and direct link
Encrypted credentials	OAuth tokens encrypted with Windows DPAPI

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🖼️ Screenshots

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🚀 Installation

Requirements

• Windows 10/11
• .NET 9 Runtime (download)

Download

1. Download the latest release from the Releases page
2. Extract the archive to a folder of your choice
3. Start DCM.App.exe

The app runs in portable mode – all settings and data are stored in the application folder.

Build from source

git clone https://github.com/dabinuss/Dabis-Content-Manager.git
cd Dabis-Content-Manager
dotnet build -c Release

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⚙️ Setup

🔑 YouTube API (included)

The release comes with YouTube API credentials included – no setup required. Just connect your account in the app.

Use your own API credentials (optional)

1. Go to the Google Cloud Console
2. Create a new project or select an existing one
3. Enable YouTube Data API v3
4. Create OAuth 2.0 credentials (Desktop application)
5. Download the JSON file
6. Rename it to youtube_client_secrets.json
7. Place it in the DabisContentManager folder next to the app

🎙️ Set up transcription (optional)

The app can transcribe your videos locally using Whisper.

1. In the app, go to Settings → General
2. Select a Whisper model size (small recommended for most users)
3. The model downloads automatically on first use

🤖 Set up local AI (optional)

The AI features require a GGUF model running locally on your machine.

1. Download a compatible GGUF model (e.g. from Hugging Face)
2. In the app, open Settings → AI / LLM
3. Select mode: Local (GGUF)
4. Set the path to the model file
5. Save the settings

Note: AI suggestions work best with a transcript. Without one, rule-based fallback suggestions are used.

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📖 Usage

First start

1. Connect your account: Accounts tab → Connect to YouTube
2. Select a video: New Upload tab → choose video file
3. Enter metadata: title, description, tags, visibility
4. Optional: add thumbnail, choose playlist, schedule publishing
5. Start upload: click Start Upload

Using presets

1. Configure your upload settings (visibility, playlist, tags, etc.)
2. Save as preset for quick reuse
3. Set a default preset to auto-apply on new uploads

Using templates

1. Go to the Templates tab → create a new template
2. Use placeholders such as:
   • {{TITLE}} – video title
   • {{TAGS}} – tags as comma-separated list
   • {{HASHTAGS}} – tags as hashtags
   • {{DATE}} – planned publication date
   • {{PLAYLIST}} – playlist name
   • {{VISIBILITY}} – visibility
   • {{YEAR}}, {{MONTH}}, {{DAY}} – current date
3. Apply a template during upload to auto-fill the description

Transcription & AI suggestions

1. Add a video and click Transcribe to generate a transcript locally
2. Click Suggest for title, description, tags or chapters
3. Review, edit and accept the suggestions

Tip: Use the chapter generation feature to automatically create timestamps from your transcript.

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🛠️ Tech stack

• Framework: .NET 9, WPF
• YouTube API: Google.Apis.YouTube.v3
• Transcription: Whisper.net (local, offline)
• Local AI: LLamaSharp with Vulkan backend
• Persistence: JSON files in the application folder (portable)

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👤 Author

dabinuss – @dabinuss

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⭐ Support

If you find this project useful, consider leaving a star on GitHub!

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📄 License

This project is licensed under the MIT License.