Chats: A Unified Frontend and Gateway Solution Supporting 21+ Mainstream AI Model Providers

Introducing the Chats project—an open-source large language model frontend and AI gateway designed to address the pain points of integrating multiple model providers. It supports over 21 mainstream AI model providers, is built using C# and React, and offers features such as unified interfaces, conversation management, and cost monitoring, making it suitable for developers, enterprises, and multi-tenant scenarios.

In today's era of diverse LLMs, developers and enterprises face numerous integration challenges: varying API interfaces, different authentication methods, and scattered management interfaces, all of which increase the difficulty of technical integration. The Chats project was created to address this pain point, providing a unified interface and management experience.

Chats uses a separated frontend-backend architecture: the frontend is built on React, responsible for interaction and state maintenance; the backend is developed in C#, handling AI model access and request forwarding. As an AI gateway, it abstracts the API differences between different providers, exposes a unified interface to upstream users, and supports features like traffic management, cost monitoring, and security control.

Chats supports over 21 mainstream AI model providers, including OpenAI (GPT series), Anthropic Claude, Google Gemini, DeepSeek, Moonshot, ChatGLM, Alibaba Tongyi Qianwen, etc. The unified gateway supports model routing (assigning requests to appropriate models) and ensemble (aggregating outputs from multiple models), opening up new possibilities for intelligent applications.

Chats has comprehensive core features such as conversation management (context retention), streaming responses (real-time output), cost monitoring (usage statistics and limits), and security control (API key management, access permissions, rate limiting), meeting the diverse needs of developers and enterprises.

Chats' use cases include: 1. Developers quickly setting up local test environments; 2. Enterprise internal AI middle platform (unified access point, simplifying operation and maintenance and cost control); 3. Multi-tenant SaaS foundation (supporting users to independently select models and manage quotas).

Chats has received 561 stars and 95 forks on GitHub, with an active community. It uses the Apache 2.0 open-source license, supporting secondary development and customization. Notably, it supports domestic models like DeepSeek and ChatGLM, promoting the development of the domestic AI ecosystem.

As the LLM market evolves, the value of unified gateways like Chats will become increasingly prominent. It lowers the threshold for developers, provides enterprises with controllable AI infrastructure, and promotes healthy competition in the ecosystem. Having a flexible, open, and multi-compatible gateway layer is a wise technical strategic choice.