XLI: Open-Source Python Library for Claude Code-Style Terminal UIs
If you've tried to build your own coding agent, you've probably noticed the terminal UX is half the work. The Claude Code style transcript — where messages stream in, tool calls flip from running to done in place, and approvals pop up inline — is genuinely hard to reproduce. The team behind XLI kept rewriting this same layer every time. Full TUI frameworks like Textual (and even Rust-backed Ratatui bindings) take over the whole screen with their own widget tree, which kills your normal terminal scrollback. Lower-level toolkits leave you rebuilding streaming markdown, mutable tool cards, inline approvals, and a real input box from scratch.
So they built their own rendering engine and pulled it out into a library called XLI.
What You Get
- Streaming markdown responses
- Slash commands
u/filementions- Tool cards that update in place
- Inline approvals and pickers
- ESC to interrupt
- A status bar
The key design choice: it renders inline, so your transcript flows into the terminal's normal scrollback and stays selectable, scrollable, and searchable. It does not hijack the screen.
Framework-Agnostic
XLI does not care if your agent loop is Claude, OpenAI, or your own thing. It's framework-agnostic, so you can drop it into any Python-based agent architecture.
Installation
pip install python-xli📖 Read the full source: r/ClaudeAI
👀 See Also
ddash: Mermaid Diagram Tool with URL-Based Storage and Claude Code Integration
ddash is a free Mermaid diagram tool where the entire diagram is compressed into the URL hash, requiring no backend, accounts, or storage. It includes a Claude Code skill that lets you generate and open diagrams directly during conversations with commands like /diagram the auth flow.
hipEngine: Fast Native Qwen 3.6 Inference for RDNA3 (Strix Halo, 7900 XTX)
hipEngine is a new open-source (AGPLv3) ROCm-native inference engine for Qwen 3.6 MoE on RDNA3 GPUs. Benchmarks show prefill up to 2718 tok/s on 7900 XTX, competitive with llama.cpp, and INT8 KV cache enabling full 256K context in under 24GB.
MCP server for depth-packed codebase context
A new MCP server packs codebase context at 5 depth levels within token budgets, addressing the problem where AI coding agents either load too few files or get flat repo maps without actual content.
Measuring Claude Code MCP Stack: Cache Friendliness vs. Byte Savings, and a 2-Line Fix for Prompt Cache
Greg Shevchenko benchmarks MCP compressors and retrieval layers on two axes: byte savings and cache friendliness. A 2-line fix (sort rg hits, sort map entries) boosts cache from ~0% to 100% with no byte-savings loss. Open-source harness included.