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align=\"center\"\u003e\n\u003ch1 align=\"center\"\u003eGemini Ultra\u003c/h1\u003e\n\n![GitHub deployments](https://img.shields.io/github/deployments/Amery2010/TalkWithGemini/Production)\n![GitHub Release](https://img.shields.io/github/v/release/Amery2010/TalkWithGemini)\n![Docker Image Size (tag)](https://img.shields.io/docker/image-size/xiangfa/talk-with-gemini/latest)\n![Docker Pulls](https://img.shields.io/docker/pulls/xiangfa/talk-with-gemini)\n![GitHub License](https://img.shields.io/github/license/Amery2010/TalkWithGemini)\n\nDeploy 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.\n\n\n\n[web-url]: https://gemini-ultra-iota.vercel.app/\n\n\n\nA straightforward interface supporting image recognition and voice conversations.\n\n\n\n![Gemini 1.5 Flash](./public/screenshots/pc-screenshot-1.png)\n\nSupports Gemini 1.5 and Gemini 1.5 Flash multimodal models.\n\nA cross-platform application client with a persistent menu bar for enhanced productivity.\n\n\n\n\u003c/div\u003e\n\n\u003e Note: For troubleshooting during usage, refer to the known issues and solutions in the [FAQ](#FAQ) section.\n\n\n\n## Features\n\n- **One-Click Free Deployment** on Vercel in under 1 minute.\n- Lightweight (~4MB) cross-platform client (Windows/MacOS/Linux) that can reside in the menu bar for improved office efficiency.\n- Supports multimodal models capable of understanding images, videos, audios, and some text documents.\n- Talk mode: Directly converse with Gemini.\n- Visual recognition allows Gemini to interpret picture content.\n- Assistant market featuring hundreds of curated system commands.\n- Full Markdown support: LaTeX formulas, code highlighting, and more.\n- Automatic compression of contextual chat records for extended conversations while conserving tokens.\n- Privacy and security ensured with all data stored locally in the user's browser.\n- Progressive Web App (PWA) support for standalone application functionality.\n- Well-designed UI with responsive design and dark mode support.\n- Extremely fast initial screen load time with support for streaming responses.\n- Static deployment allows deployment on any service supporting static pages like GitHub Pages, Cloudflare, Vercel, etc.\n- Multilingual support: English, Hindi, Bengali, Simplified Chinese, Traditional Chinese, Japanese, Korean, Spanish, German, French, Portuguese, Russian, and Arabic.\n\n## Roadmap\n\n- [x] Topic square reconstruction and introduction of Prompt list.\n- [x] Use Tauri to package desktop applications.\n- [ ] Implementation based on functionCall plugin.\n- [ ] Support conversation list.\n\n## Get Started\n\n1. Obtain a [Gemini API Key](https://aistudio.google.com/app/apikey).\n2. Click on the button below to deploy:\n   ![Deploy with Vercel](https://vercel.com/button)\n3. Start using.\n\n## Access Password\n\nThis project implements limited access control. Add an environment variable named `ACCESS_PASSWORD` on the Vercel environment variables page.\n\nAfter adding or modifying this environment variable, redeploy the project for the changes to take effect.\n\n## Custom Model List\n\nSupports customization of model lists. Add an environment variable named `NEXT_PUBLIC_GEMINI_MODEL_LIST` in the `.env` file or on the environment variables page.\n\nThe default model list is represented by `all`, and multiple models are separated by `,`.\n\nFor 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`.\n\nTo 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.\n\nTo set a default model, use the `@` symbol followed by the model name, e.g., `all,@default-model-name`.\n\n## Environment Variables\n\nDetails about environment variables are provided in the sections of the README.\n\n## Requirements\n\nNodeJS \u003e= 18, Docker \u003e= 20\n\n## Development\n\nInstructions for development are detailed in the README.\n\n## Deployment\n\nDeployment methods are detailed in the README.\n\n## FAQ\n\nFrequently asked questions and their solutions are provided in the FAQ section of the README.\n\n## Star History\n\nView the star history of the project.\n\n---\n\nThis version focuses on describing the application features, deployment options, and customization capabilities without including installation instructions.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farnab-4%2Fgemini-ultra","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Farnab-4%2Fgemini-ultra","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Farnab-4%2Fgemini-ultra/lists"}