stagewise

以下为收录时的原文，语言与页面不同，未做翻译。

Stagewise is a frontend coding agent that enhances development efficiency by allowing users to edit code directly in their browser, supporting various frameworks while generating clean, maintainable code with real-time updates and smart design suggestions.

官网介绍

stagewise is a next-gen agent orchestrator for software engineers, leveraging a frontier-grade agent harness. Full model sovereignty. Runs locally, connects to anything.

官方常见问题

What models can I use with stagewise?

stagewise supports any model with agentic capabilities. Use frontier models (Claude, GPT, Gemini), open-weight models (DeepSeek, Qwen, GLM, Kimi, MiniMax), or locally hosted models (Ollama, vLLM, Llama.cpp) — all through the same interface.

Do I need an API key to get started?

No. With a stagewise Account, you get preconfigured access to a wide variety of models through stagewise Cloud Inference — no keys, configuration, or external subscriptions required. You can also bring your own API key or connect a custom endpoint at any time.

Can I run models locally?

Yes. You can configure stagewise Agents to use models from any source, including a local setup using Ollama or an on-premise deployment with vLLM. We support any inference provider that serves models via OpenAI Chat Completions API, OpenResponses API, or Anthropic Messages API. The minimum recommended context size is 150k tokens.

Is stagewise open source?

Yes. The stagewise Agentic IDE is fully open source under the AGPLv3 license. The entire codebase is publicly available on GitHub at github.com/stagewise-io/stagewise — you can inspect it, build from source, or run your own instance. External contributions are welcome but reviewed carefully to maintain quality and project direction.

Can I use my existing coding subscription?

Yes. stagewise supports bringing your own API keys for existing subscriptions including OpenAI, Anthropic, Google Gemini, DeepSeek, Kimi, Qwen, and MiniMax. You can also use API aggregators like OpenRouter or fireworks.ai.

How does stagewise handle context for long-running tasks?

stagewise keeps the conversation prefix stable across turns to maximize cache hit rates. When the environment changes, it sends a compact state delta instead of rebuilding the full context. This ensures the agent stays continuously aware of changes in terminals, browser tabs, and more, while remaining extremely token-efficient. The runtime also automatically compresses context as tasks grow, keepi