Open-Fiesta - an open-source AI chat platform capable of running multiple model comparisons simultaneously.
Open-Fiesta is an open-source, multi-model AI chat platform built on Next.js 14. The platform supports various AI providers (such as Gemini and OpenRouter) and multiple models, allowing users to select up to five models simultaneously...
What is Open-Fiesta?
Open-Fiesta is an open-source, multi-model AI chat platform built on Next.js 14. The platform supports various AI providers (such as Gemini and OpenRouter) and multiple models, allowing users to compare up to five models simultaneously. Open-Fiesta features web search and image attachments (Gemini only), providing users with a clean user interface and a smooth interactive experience. Based on configuration 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 functions of Open-Fiesta
- Multi-model supportIt supports multiple AI providers (such as Gemini, OpenRouter, etc.) and users can select up to 5 models for comparison.
- Web search functionEach message allows users to choose whether to enable web search, enhancing the accuracy and information content of their responses.
- Image attachment supportSupports image attachments (Gemini model only), allowing users to upload images and receive related answers.
- Simple user interfaceIt provides a simple and smooth interactive experience, supporting keyboard submission and streaming API.
- Model comparison functionUsers can run multiple models simultaneously and compare the output results of different models.
Open-Fiesta's technical principles
- Front-end technology stackBuilt on Next.js 14, Tailwind offers an efficient development experience and excellent performance using App Router and TypeScript. Tailwind CSS is used to quickly build clean, responsive user interfaces.
- Backend technology stackIt uses Next.js-based API routing to communicate with different AI providers. The lib/ folder manages model directories and client-side tools, making it easy for users to select and switch between different models.
- Data processingStandardize model responses from different providers, such as removing DeepSeek R1 inference tags and converting Markdown to plain text to improve output readability. Manage API keys based on environment variables to ensure security and flexibility.
Open-Fiesta project address
- GitHub repositoryhttps://github.com/NiladriHazra/Open-Fiesta
Application scenarios of Open-Fiesta
- Personal learning and researchStudents and researchers can compare the outputs of different AI models to gain a deeper understanding of model characteristics, which can help with knowledge learning and research exploration.
- Development and TestingDevelopers test and optimize AI models for rapid iteration and improvement, while enterprises use them for integration testing to ensure the model's performance in real-world applications.
- Education and teachingTeachers use AI model outputs as a teaching tool to help students understand the concepts.
- Content creationContent creators generate creative texts to inspire others, while writers and editors receive writing suggestions and content expansion, improving creative efficiency.
- Enterprise ApplicationsEnterprises can build intelligent customer service systems, compare model responses to select the optimal solution for serving customers, or use them in data analysis and report generation to improve work efficiency.