https://github.com/tominaga-h/jarvis-shell

I spend most of my day in the terminal, and I got incredibly frustrated with the standard error-resolution loop: command fails -> copy the stderr -> open a browser -> paste into ChatGPT/Google -> copy the fix -> paste back into the terminal. It completely breaks the flow state.

I wanted a seamless experience where the shell already knows the context of what just happened.

So I built Jarvish. It’s a fully functional interactive shell written in Rust, but with an AI agent seamlessly integrated into the REPL loop. You don't need any special prefixes—if you type `ls -la`, it runs it. If you type `Jarvis, why did that build fail?`, it routes to the AI.

Here is how it works under the hood:

- The "Black Box" (I/O Capture): It uses `os_pipe` and multithreading to tee the `stdout`/`stderr` of child processes in real-time. This captures the output to memory for the AI while simultaneously rendering it to the terminal without breaking interactive TUI tools.

- Context Memory: The captured I/O is compressed with `zstd`, hashed (like Git blobs), and the metadata is stored in a local SQLite database (`rusqlite`). When you ask the AI a question, it automatically retrieves this recent I/O history as context.

- Agentic Capabilities: Using `async-openai` with function calling, the AI can autonomously read files, execute shell commands, and investigate issues before giving you an answer.

- REPL: Built on top of `reedline` for a Fish-like experience (syntax highlighting, autosuggestions).

I’ve been using it as my daily driver (currently v1.1.0). I would absolutely love to hear your thoughts on the architecture, the Rust implementation, or any feature requests!