This project provides a professional platform for AI prompt optimization, debugging, and sharing, targeting AI application developers and content creators. It aims to enhance AI interaction effectiveness and response accuracy through intelligent algorithms, deep reasoning, visualization tools, and community features.

How It Works

The platform leverages .NET 9.0 and React 19.1.0, integrating Microsoft Semantic Kernel 1.54.0 for AI orchestration. It employs intelligent optimization algorithms for prompt structure analysis and multidimensional refinement. Deep inference mode allows for detailed AI reasoning processes, while a visualization debugging environment offers real-time preview and history tracking. Community features enable sharing and discovery of prompt templates.

Quick Start & Requirements

• Standard Deployment: Clone the repository, then run docker-compose up -d. Access at http://localhost:10426.
• Prerequisites: Docker and Docker Compose.
• Customization: Supports custom API endpoints, local AI services (Ollama), and PostgreSQL databases via docker-compose.override.yaml, docker-compose.ollama.yaml, and docker-compose.postgres.yaml respectively.
• Documentation: Quick Start, Deployment Guide

Highlighted Details

• Integrates OpenAI API compatible interfaces and supports local AI models via Ollama.
• Features a visual interface with real-time preview and history records for prompt debugging.
• Includes a community platform for sharing, discovering, and interacting with prompt templates.
• Offers multi-language support (Chinese/English) with real-time translation.

Maintenance & Community

• Project is hosted on GitHub with active development.
• Contact via GitHub Issues for feedback and technical support.
• Official website: https://token-ai.cn

Licensing & Compatibility

• Licensed under LGPL (Lesser General Public License).
• Allows commercial use and distribution of original/modified code for internal use.
• Prohibits commercial distribution of modified source code.

Limitations & Caveats

The project relies heavily on Docker for deployment. While commercial use is permitted, distributing modified source code commercially is restricted by the LGPL license.