Steer LLMs and Agents at the Token Level: An interactive tool for token visualization & control, model inspection and data annotation.

onPanda is designed for geeks, power users, curious minds, and engineers. Its UI is built for deep exploration and efficient data annotation.

- The core loop is simple: hover over a token → click an alternative or edit freely → continue generation. You can edit every part of model output exposed by onPanda, including reasoning and tool calls.

- Edit prompts directly, branch tool calls, and use a tree structure to record branch history. This makes onPanda useful for model inspection and prompt engineering.

- Support multiple modalities, including images, video, and audio; use tool calls and connect MCP servers to perform tasks in real environments.

- Connect popular harnesses such as Claude Code, Codex, and OpenCode to execute tasks. Explore and compare their tool sets, system prompts, skills, and memory mechanisms.

- onPanda includes browser-agent, an agent that runs in the user's browser without installation. It uses the browser as its harness and provides JavaScript execution, information retrieval, interface interaction, multimedia I/O, local file access, and persistent memory.

- onPanda stands for on-Policy Alignment Data Annotator.

I have been building onPanda since 2024.09, it took two years for it to gradually enrich its functionality and ease of use. In my opinion, onPanda is very suitable for the r/LocalLLaMA community. Any feedback and evaluation are welcome.

Try it online (works on mobile): https://onpanda.diyer22.com/

GitHub repo for self-hosting: https://github.com/on-panda/on-panda