What is Open-Fiesta
Open-Fiesta is an open-source multi-model AI chatplatform built on Next.js 14. The platform supports multiple AI providers (such as Gemini、OpenRouter , etc.) and multiple models, and users can select up to 5 models for comparison at the same time. Open-Fiesta features web search, image attachments (only supported by Gemini), and more, providing users with a clean user interface and a smooth interactive experience. Based on configuring environment variables (such as API keys), users can easily deploy and use it. Open-Fiesta is suitable for developers and AI enthusiasts to explore and experiment with different AI models.
Main features of Open-Fiesta
- Multi-model support: Supports multiple AI providers (such as Gemini, OpenRouter, etc.), and users can select up to 5 models for comparison.
- Web search feature: Each message supports choosing whether to enable web search, enhancing the accuracy and amount of information in responses.
- Image attachment support: Supports image attachments (only supported by Gemini models), allowing users to upload images and get related responses.
- Clean user interface: Provides a clean and smooth interactive experience, supporting keyboard submission and streaming APIs.
- Model comparison feature: Users can run multiple models simultaneously and compare the output results of different models.
Technical principles of Open-Fiesta
- Frontend tech stack: Built on Next.js 14, using App Router and TypeScript to provide an efficient development experience and good performance. Tailwind CSS is used to quickly build a clean, responsive user interface.
- Backend tech stack: Based on Next.js API routes to communicate with different AI providers. The model catalog and client helper tools are managed in the lib/ folder, making it convenient for users to select and switch between different models.
- Data processing: Standardizes model responses from different providers, such as removing DeepSeek R1's reasoning tags and converting Markdown to plain text, improving the readability of output. API keys are managed based on environment variables, ensuring security and flexibility.
Open-Fiesta project address
- GitHub repository：https://github.com/NiladriHazra/Open-Fiesta
Application scenarios of Open-Fiesta
- Personal learning and research: Students and researchers compare the outputs of different AI models, gain an in-depth understanding of model characteristics, and assist knowledge learning and research exploration.
- Development and testing: Developers test and optimize AI models, iterate and improve quickly, and enterprises use it for integration testing to ensure the performance of models in actual applications.
- Education and teaching: Teachers use it as a teaching tool to display AI model outputs and help students understand.
- Content creation: Content creators generate creative text to spark inspiration, and writers and editors get writing suggestions and content expansion, improving creative efficiency.
- Enterprise applications: Enterprises build intelligent customer service, compare model responses to choose the best solution to serve customers, or use it for data analysis and report generation, improving work efficiency.