User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
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Updated
Feb 15, 2025 - JavaScript
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Free, high-quality text-to-speech API endpoint to replace OpenAI, Azure, or ElevenLabs
Belullama is a comprehensive AI application that bundles Ollama, Open WebUI, and Automatic1111 (Stable Diffusion WebUI) into a single, easy-to-use package.
This repository provides resources and guidelines to facilitate the integration of Open-WebUI and Langfuse, enabling seamless monitoring and management of AI model usage statistics.
A Docker Compose to run a local ChatGPT-like application using Ollama, Ollama Web UI, Mistral NeMo & DeepSeek R1.
Ollama with Let's Encrypt Using Docker Compose
An excellent localized AI chat client application, cross-platform, compatible with all large models compatible with Ollama and OpenAI API. Local deployment protects your data privacy and can be used as Ollama client and OpenAI client.
A modern web interface for [Ollama](https://ollama.ai/), with DeepSeek in next version.
Simple web UI for Ollama
Streamlined Ollama WebUI Setup: Automated Scripts, LLM Integration, and Desktop Shortcut Creation
Ollama Web UI is a simple yet powerful web-based interface for interacting with large language models. It offers chat history, voice commands, voice output, model download and management, conversation saving, terminal access, multi-model chat, and more—all in one streamlined platform.
ollama web_ui simple and easy
Extremely simple chat interface for ollama models.
Web Client For Ollama - Llama LLM
OLLAMA PUSHER SIMPLIFIES THE UPLOADING FROM GGUF BASED LLMS TO THE OLLAMA LIBARY! ONE TIME SETUP EVERY TIME READY TO GO!
AI Chat UI is a responsive, modern chat interface, designed for seamless interactions with local Large Language Models (LLMs) like Ollama. It features a clean design, light/dark themes, PWA support for offline use, real-time chat with streaming responses, and local storage for chat history.
A simple web interface with Markdown support built using Flask, designed to interact with Ollama models.
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