User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
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Updated
Feb 17, 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
Extremely simple chat interface for ollama models.
ollama web_ui simple and easy
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.
Web Client For Ollama - Llama LLM
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.
OLLAMA PUSHER SIMPLIFIES THE UPLOADING FROM GGUF BASED LLMS TO THE OLLAMA LIBARY! ONE TIME SETUP EVERY TIME READY TO GO!
A simple web interface with Markdown support built using Flask, designed to interact with Ollama models.
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