Top 10 Open-Source User Interfaces for LLMs

#opensource #llm #ai #userinterfaces

Open-source user interfaces for large language models (LLMs) are empowering developers, researchers, and businesses to interact with AI models locally and securely. These UIs offer everything from simple chat interfaces to advanced agent frameworks, supporting a wide range of models and deployment scenarios. In 2025, the landscape is richer than ever, with options tailored for privacy, customization, and rapid prototyping. This guide covers the 10 best open-source UIs for LLMs, their standout features, and direct links to their repositories.

1. Open WebUI

Open WebUI is a self-hosted, extensible AI interface that supports Ollama, OpenAI API, and various LLM runners. It features granular permissions, responsive design, full Markdown/LaTeX support, hands-free voice/video calls, native Python function calling, persistent artifact storage, local RAG integration, web search, image generation/editing, and enterprise authentication. It’s ideal for privacy-focused deployments, local model experimentation, and enterprise use cases.

GitHub Link: https://github.com/open-webui/open-webui

2. LobeChat

LobeChat is a modern, open-source ChatGPT-like UI with support for speech synthesis, multi-modal input, a plugin system, agent marketplace, and one-click deployment. It supports MCP (Model Context Protocol), smart internet search, chain of thought visualization, branching conversations, artifacts, file upload/knowledge base, multi-model providers, local LLMs (Ollama), visual recognition, TTS/STT, text-to-image generation, and custom themes. LobeChat excels in extensibility, user experience, and rapid deployment for both individuals and teams.

GitHub Link: https://github.com/lobehub/lobe-chat

3. Text Generation Web UI

Text Generation Web UI is a popular open-source platform for running and interacting with local LLMs. It supports a wide range of models, offers a clean interface, and includes advanced features like model presets, plugins, and community-driven enhancements. It’s favored by developers and researchers for local experimentation and model benchmarking.

GitHub Link: https://github.com/oobabooga/text-generation-webui

4. Chatbot UI

Chatbot UI is a Next.js-based, open-source chat interface that supports OpenAI and Azure APIs. It’s designed for easy self-hosting, customization, and rapid prototyping, making it a go-to choice for developers building custom chatbot experiences.

GitHub Link: https://github.com/mckaywrigley/chatbot-ui

5. LibreChat

LibreChat is an open-source, multi-provider chat UI with support for MCP, rich UI features, and a focus on privacy. It’s designed for users who want a versatile, self-hosted chat experience with advanced agent orchestration and workflow management.

GitHub Link: https://github.com/danny-avila/LibreChat

6. AnythingLLM

AnythingLLM is a multi-model, MCP-compatible UI that supports local and cloud deployment. It’s known for its flexibility, privacy, and ease of use, making it suitable for both personal and enterprise AI workflows.

GitHub Link: https://github.com/Mintplex-Labs/anything-llm

7. Flowise

Flowise is a visual builder for LangChain-based LLM applications. It enables users to create complex agent workflows and pipelines with drag-and-drop ease, ideal for developers and non-developers alike.

GitHub Link: https://github.com/FlowiseAI/Flowise

8. LangFlow

LangFlow is a visual pipeline builder for LangChain, allowing users to design, prototype, and deploy LLM-powered workflows. It’s perfect for rapid experimentation and building complex agent logic.

GitHub Link: https://github.com/logspace-ai/langflow

9. assistant-ui

assistant-ui is a React/TypeScript-based component library for building custom LLM chat interfaces. It’s highly modular and customizable, making it a favorite for developers building tailored agent experiences.

GitHub Link: https://github.com/assistant-ui/assistant-ui

10. Streamlit

Streamlit is a Python-based framework for quickly building and deploying interactive web apps, including LLM chat interfaces. It’s ideal for rapid prototyping, data science, and AI experimentation.

GitHub Link: https://github.com/streamlit/streamlit

How to Use These UIs

Most UIs can be self-hosted with Docker or via simple npm/pip installs.
They support local models (via Ollama, llama.cpp, etc.) and cloud APIs (OpenAI, Anthropic).
Many offer advanced features like RAG, agent orchestration, multimodal support, and MCP compatibility.

Conclusion

Open-source UIs for LLMs are essential tools for anyone building, experimenting, or deploying AI agents. From simple chat interfaces to full agent frameworks, these projects offer flexibility, privacy, and community-driven innovation. Whether you’re a developer, researcher, or entrepreneur, exploring these UIs can unlock new possibilities for your AI workflows in 2025 and beyond.