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Lightweight MIT-licensed JavaScript chatbot UI widget for building support-agent chat interfaces on top of any LLM.
Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
Trae AI-powered IDE for developer collaboration; notable ByteDance-backed dev product.
Side-by-side arena to compare AI coding models and build multi-file apps, with a public leaderboard and battle mode.
AI app builder turning English prompts into full-stack apps with provisioned DB, auth and hosting; also hosts autonomous agents.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦MIT-licensed and free to use
- ✦Lightweight (~65kb) JavaScript widget
- ✦4 message display modes plus typewriter effect
- ✦Markdown support and chat history
- ✦Backend hook to integrate any LLM
- ✦Responsive, mobile-friendly, read-only mode
- ✦Single OpenAI-compatible API for 500+ models
- ✦Chat, image, video and audio models
- ✦Discounted per-request pricing
- ✦One dashboard for keys, quotas and usage
- ✦Multi-region routing and failover (99.9% uptime)
- ✦Multiple payment methods incl. crypto
- ✦AI Agents
- ✦Tool Integration
- ✦Context Awareness
- ✦Smart Autocompletion
- ✦Local Data Storage
- ✦Secure Data Access
- ✦Head-to-head model comparison
- ✦Battle mode matchups
- ✦Public model leaderboard
- ✦Multi-file app generation
- ✦File uploads as input
- ✦Natural-language full-stack app generation
- ✦Auto-provisioned Postgres, auth, storage and hosting
- ✦Full code ownership with GitHub export
- ✦Managed hosting for autonomous AI agents
- ✦200+ bundled AI models
- ✦MCP and CLI tooling
- →Adding an AI chat UI to web apps
- →Building LLM-powered support agents
- →Embedding chat widgets in existing products
- →Prototyping chatbot interfaces
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys
- →Automating coding tasks with AI agents
- →Integrating external tools for enhanced functionality
- →Improving code accuracy with context-aware suggestions
- →Boosting coding speed with smart autocompletion
- →Building RAG apps without writing code
- →Choosing the best coding model
- →Benchmarking AI code quality
- →Prototyping small apps
- →Ship a SaaS without an engineering team
- →Build internal tools from a description
- →Deploy always-on AI agents quickly
- →Provide infra for AI-coded apps