axio-repl¶

axio-repl is a terminal coding assistant that runs an Axio agent with file and shell tools. It auto-detects your LLM backend from environment variables and streams every token and tool call directly to the terminal.

Install¶

uv tool install axio-repl

Add optional transports:

# Anthropic Claude
uv tool install axio-repl --with axio-transport-anthropic

# Google Gemini
uv tool install axio-repl --with axio-transport-google

Within the monorepo workspace:

uv run axio-repl

Start the REPL¶

axio-repl

The REPL picks the first transport whose environment variable is set:

Transport	Env Variable	Package
`google`	`GEMINI_API_KEY`	`axio-transport-google`
`google-vertex`	`GOOGLE_GENAI_USE_VERTEXAI`	`axio-transport-google`
`anthropic`	`ANTHROPIC_API_KEY`	`axio-transport-anthropic`
`openai`	`OPENAI_API_KEY`	`axio-transport-openai`
`nebius`	`NEBIUS_API_KEY`	`axio-transport-openai`
`openrouter`	`OPENROUTER_API_KEY`	`axio-transport-openai`

Override with --transport <name>:

axio-repl --transport anthropic --model claude-sonnet-4-20250514
axio-repl --transport google --model gemini-3.1-pro-preview

Single-prompt mode¶

Pass a prompt as an argument for non-interactive use:

axio-repl "list the files in this project"
axio-repl --transport openai "write tests for src/auth.py"

CLI flags¶

Flag	Default	Description
`--transport`	auto	Transport name (see table above)
`--model`	transport default	Model name
`--temperature`	transport default	Sampling temperature
`--thinking`	off	Thinking level: `LOW`, `MEDIUM`, `HIGH`, or a token budget
`--max-tokens`	transport default	Max output tokens
`--max-iterations`	30	Max agent iterations
`--debug`	off	Log raw request/response bodies

REPL commands¶

Command	Description
`/model`	Show current model and list available models
`/model <query>`	Switch to a model matching the query
`/thinking [level]`	Show or set thinking level/budget
`/temperature [val]`	Show or set sampling temperature
`/max-tokens [val]`	Show or set max output tokens
`/iterations [val]`	Show or set max agent iterations
`/debug [on\|off]`	Toggle request/response debug logging
`/help`	List all tools and commands
`/quit`, `/exit`, `/q`	Exit the REPL

Tools¶

Tool	Description
`read_file`	Read file contents; images and videos are returned as vision blocks
`write_file`	Create or overwrite files
`patch_file`	Replace line ranges (1-indexed, inclusive)
`list_files`	List directory contents
`search_files`	Text or regex search across files
`shell`	Run shell commands with streaming stdout/stderr
`generate_image`	Generate images via Gemini (Google transport only)
`generate_video`	Generate videos via Veo (Google transport only)

AGENTS.md¶

Place an AGENTS.md file in the working directory to inject workspace-specific instructions into the system prompt:

# My project

- Always run `make test` after editing Python files
- The main entry point is `src/app.py`
- Use the `dev` branch for all changes

The file is loaded at startup and on every /model switch. It is optional - if absent, the default system prompt is used unchanged.

Capability-aware system prompt¶

The system prompt adapts to the selected model’s capabilities. Switching models with /model recalculates capabilities and rewrites the prompt automatically:

Vision - read_file on images (PNG, JPG, GIF, WebP) returns pixel data. Screenshot-based UI review loops are unlocked.
Reasoning - Extended thinking (chain-of-thought) is available.
Image generation - Inline image generation via generate_image.
Video - read_file on video files returns vision blocks.

Multiline input¶

Paste multi-line text directly into the prompt. The REPL detects continuation lines and joins them before sending:

You> Refactor this function:
...   def old(x):
...     return x+1

Interrupting the agent¶

Press Ctrl-C to cancel the running agent loop. Partial tool output (stdout already captured, files already written) is preserved in conversation context so the model sees what happened and can resume cleanly.