klyro 1.0.2

Klyro is AI pair programming in your terminal

Klyro

AI pair programming in your terminal.

Klyro lets you pair program with LLMs directly from your terminal. Start a new project or work on your existing codebase with an AI that can read, understand, and edit your code.

Quick Install

python -m pip install klyro

If Windows says klyro is not recognized after installation, run it with:

python -m klyro

Or add your Python user Scripts folder to PATH. To find it, run:

python -c "import sysconfig; print(sysconfig.get_path('scripts', 'nt_user'))"

Then add that path to your Windows user PATH environment variable, e.g.:

C:\Users\<YourName>\AppData\Roaming\Python\Python3XX\Scripts

Install from source:

git clone https://github.com/RavindraTirlangi/Klyro.git
cd Klyro
python -m pip install -e .

Usage

# Start Klyro in your project directory
klyro

# Use a specific model
klyro --model gpt-4o

# Use a local Ollama model
klyro --model ollama/llama3.2

Features

Smart Model Detection

Klyro auto-detects your environment:

• Local Ollama running? Uses it automatically with no API key needed.
• Cloud API keys set? Picks the best available model.
• No keys at all? Offers OpenRouter setup.

Slash Commands

Command	Description
/model [name]	Switch LLM model mid-session (e.g. /model gpt-4o, /model ollama/llama3.2). Run without args to see current model and examples.
/stats	Show model name, last message cost, and total session cost
/web <url>	Fetch a web page and add its content to the chat context
/export [filename]	Export chat history to a markdown file
/tokens	Report token usage for the current chat context
/add <file>	Add a file to the chat
/drop <file>	Remove a file from the chat
/diff	Show the diff of changes made
/undo	Undo the last change
/help	Show all available commands

Code Editing

• Whole-file and diff-based editing modes
• Automatic linting after every edit
• Built-in git integration with auto-commits

Repository Intelligence

• Builds a repo map using tree-sitter AST analysis
• Understands your codebase structure and relationships
• Manages context to stay within token limits

Configuration

Create a .klyro.conf.yml in your project root:

model: ollama/llama3.2
dark-mode: true
auto-commits: true

Or use environment variables:

export OPENAI_API_KEY=sk-...
export ANTHROPIC_API_KEY=sk-ant-...
export OLLAMA_API_BASE=http://localhost:11434

Publishing

This project uses GitHub Actions for automated PyPI publishing (using setuptools_scm for dynamic versioning based on git tags). To release version 0.1.0 (or any other version), simply create and push a tag:

git tag v0.1.0
git push origin v0.1.0

The workflow will automatically build the package (e.g., klyro-0.1.0) and attempt to publish it to PyPI. (Note: To successfully publish to PyPI, you must first configure PyPI Trusted Publishing for this GitHub repository.)

License

Apache License 2.0. See LICENSE for details.