Deploy your private Gemini application for free with one click, supporting Gemini 1.5 Pro, Gemini 1.5 Flash, Gemini Pro, and Gemini Pro Vision models.
A straightforward interface supporting image recognition and voice conversations.
Supports Gemini 1.5 and Gemini 1.5 Flash multimodal models.
A cross-platform application client with a persistent menu bar for enhanced productivity.
Note: For troubleshooting during usage, refer to the known issues and solutions in the FAQ section.
- One-Click Free Deployment on Vercel in under 1 minute.
- Lightweight (~4MB) cross-platform client (Windows/MacOS/Linux) that can reside in the menu bar for improved office efficiency.
- Supports multimodal models capable of understanding images, videos, audios, and some text documents.
- Talk mode: Directly converse with Gemini.
- Visual recognition allows Gemini to interpret picture content.
- Assistant market featuring hundreds of curated system commands.
- Full Markdown support: LaTeX formulas, code highlighting, and more.
- Automatic compression of contextual chat records for extended conversations while conserving tokens.
- Privacy and security ensured with all data stored locally in the user's browser.
- Progressive Web App (PWA) support for standalone application functionality.
- Well-designed UI with responsive design and dark mode support.
- Extremely fast initial screen load time with support for streaming responses.
- Static deployment allows deployment on any service supporting static pages like GitHub Pages, Cloudflare, Vercel, etc.
- Multilingual support: English, Hindi, Bengali, Simplified Chinese, Traditional Chinese, Japanese, Korean, Spanish, German, French, Portuguese, Russian, and Arabic.
- Topic square reconstruction and introduction of Prompt list.
- Use Tauri to package desktop applications.
- Implementation based on functionCall plugin.
- Support conversation list.
- Obtain a Gemini API Key.
- Click on the button below to deploy:
- Start using.
This project implements limited access control. Add an environment variable named ACCESS_PASSWORD on the Vercel environment variables page.
After adding or modifying this environment variable, redeploy the project for the changes to take effect.
Supports customization of model lists. Add an environment variable named NEXT_PUBLIC_GEMINI_MODEL_LIST in the .env file or on the environment variables page.
The default model list is represented by all, and multiple models are separated by ,.
For adding a new model, either directly specify the model name all,new-model-name, or use the + symbol followed by the model name, e.g., all,+new-model-name.
To remove a model from the list, use the - symbol followed by the model name, e.g., all,-existing-model-name. Use -all to remove the default model list.
To set a default model, use the @ symbol followed by the model name, e.g., all,@default-model-name.
Details about environment variables are provided in the sections of the README.
NodeJS >= 18, Docker >= 20
Instructions for development are detailed in the README.
Deployment methods are detailed in the README.
Frequently asked questions and their solutions are provided in the FAQ section of the README.
View the star history of the project.
This version focuses on describing the application features, deployment options, and customization capabilities without including installation instructions.