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Nextjs Ollama Llm UI

A Next.js-based web interface for Ollama LLMs, offering a ChatGPT-like experience for local and offline model interaction with easy setup.

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Next.js Ollama UI: Local & Feature-Rich LLM Interaction

This Next.js project provides a fully-featured web interface for Ollama Large Language Models, designed for ease of use and quick local setup. It offers a ChatGPT-inspired user experience, allowing you to interact with LLMs on your own machine, even offline. Chats are conveniently stored in localstorage, eliminating the need for a separate database, and the interface is fully responsive for use on any device.

Features:

  • Beautiful & Intuitive UI: Experience a ChatGPT-inspired interface for enhanced usability.
  • Fully Local Operation: Stores chats in localstorage, no database required.
  • Fully Responsive Design: Seamlessly chat on desktop or mobile devices.
  • Easy Setup: Clone the repository and get started quickly without complex configuration.
  • Code Syntax Highlighting: Code within messages is automatically highlighted for readability.
  • Easy Code Copying: Copy code blocks with a single click.
  • Model Management: Download, pull, and delete Ollama models directly from the UI.
  • Model Switching: Quickly switch between different LLM models.
  • Chat History: Access and manage your saved chat conversations.
  • Light & Dark Mode: Choose between light and dark visual themes.
  • Voice Input Support: Enables interaction with LLMs using voice commands.
  • Image Prompt Capability: Send images in prompts to utilize vision language models.
  • Response Regeneration: Easily regenerate model responses for variations.

Summary:

The Next.js Ollama LLM UI empowers developers and users to run and interact with Ollama's large language models locally through a user-friendly, ChatGPT-like web interface. It simplifies model management, chat history, and offers features like code highlighting and responsive design, all with a straightforward setup process. This makes it an accessible tool for exploring LLMs privately and offline.

Distribution:
opensource
GitHub:
1,253 Stars
297 Forks
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