llmstxt

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A Python tool for compressing and organizing code files into a single, LLM-friendly text file. This tool is designed to help prepare codebases for analysis by Large Language Models by removing unnecessary content while preserving important semantic information.

llmstxt 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# llmstxt

A Python tool for compressing and organizing code files into a single, LLM-friendly text file. This tool is designed to help prepare codebases for analysis by Large Language Models by removing unnecessary content while preserving important semantic information.

## Features

### Smart Code Compression

- Preserves docstrings and important comments
- Removes redundant whitespace and formatting
- Maintains code structure and readability
- Handles multiple programming languages

### Language Support

- Python (with AST-based compression)
- JavaScript
- Java
- C/C++
- Shell scripts
- HTML/CSS
- Configuration files (JSON, YAML, TOML, INI)
- Markdown

### LLM-Friendly Output

- XML-style semantic markers
- File metadata and type information
- Organized imports section
- Clear file boundaries
- Consistent formatting

### Automation

- GitHub Actions integration
- Automatic updates on code changes
- CI/CD friendly

## Installation

This project uses [uv](https://github.com/astral-sh/uv) for dependency management, but can also be installed directly with pip.

```bash
# Using pip
pip install git+https://github.com/ngmisl/llmstxt.git

# Using uv (recommended for development)
curl -LsSf https://astral.sh/uv/install.sh | sh
uv pip install .

# For development
uv pip install -e ".[dev]"
```

## Usage

### Local Usage

```bash
# Generate llms.txt from current directory
python -m llmstxt

# Or import and use in your code
from llmstxt import generate_llms_txt
generate_llms_txt()
```

The script will:

1. Scan the current directory recursively
2. Process files according to .gitignore rules
3. Generate `llms.txt` with compressed content

### Install Locally

```bash
pip install --user .
```

Now you can use the `llmstxt` command from your terminal.

### GitHub Actions Integration

There are two ways to use this tool with GitHub Actions:

1. **For Your Own Repository**

Create `.github/workflows/update-llms.yml` with:

```yaml
name: Update llms.txt

on:
  push:
    branches: [main, master]
  pull_request:
    branches: [main, master]
  workflow_dispatch: # Allow manual triggering

permissions:
  contents: write

jobs:
  update-llms:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
        uses: actions/checkout@v4

- name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: "3.12"
          cache: "pip"

- name: Install llmstxt tool
        run: |
          python -m venv .venv
          . .venv/bin/activate
          python -m pip install --upgrade pip
          pip install git+https://github.com/ngmisl/llmstxt.git

- name: Generate llms.txt
        run: |
          . .venv/bin/activate
          rm -f llms.txt
          python -c "from llmstxt import generate_llms_txt; generate_llms_txt()"

- name: Configure Git
        run: |
          git config --local user.email "github-actions[bot]@users.noreply.github.com"
          git config --local user.name "github-actions[bot]"

- name: Commit and push changes
        run: |
          git add llms.txt
          if git diff --staged --quiet; then
            echo "No changes to commit"
          else
            git commit -m "chore: update llms.txt"
            git push
          fi
```

The workflow will:

- Run on push to main/master
- Run on pull requests
- Can be triggered manually
- Generate and commit `llms.txt` automatically

2. **For Remote Repositories**
   You can trigger the action for any repository using the GitHub API:

```bash
curl -X POST \
  -H "Authorization: token $GITHUB_TOKEN" \
  -H "Accept: application/vnd.github.v3+json" \
  https://api.github.com/repos/ngmisl/llmstxt/dispatches \
  -d '{"event_type": "update-llms", "client_payload": {"repository": "https://github.com/user/repo.git"}}'
```

## Output Format

The generated `llms.txt` file follows this structure:

```python
# Project: llmstxt

## Project Structure
This file contains the compressed and processed contents of the project.

### File Types
- .py
- .js
- .java
...

<file>src/main.py</file>
<metadata>
path: src/main.py
type: py
size: 1234 bytes
</metadata>

<imports>
import ast
from typing import Optional
</imports>

<code lang='python'>
def example():
    """Docstring preserved."""
    return True
</code>

<file>src/utils.js</file>
<metadata>
path: src/utils.js
type: js
size: 567 bytes
</metadata>

<code lang='javascript'>
function helper() {
  return true;
}
</code>
```

## Configuration

The tool can be configured through function parameters:

```python
generate_llms_txt(
    output_file="llms.txt",      # Output filename
    max_file_size=100 * 1024,    # Max file size (100KB)
    allowed_extensions=(         # Supported file types
        ".py", ".js", ".java",
        ".c", ".cpp", ".h", ".hpp",
        ".sh", ".txt", ".md",
        ".json", ".xml", ".yaml",
        ".yml", ".toml", ".ini"
    )
)
```

## Development

Requirements:

- Python 3.8+
- [uv](https://github.com/astral-sh/uv) for dependency management (recommended)

```bash
# Clone the repository
git clone https://github.com/ngmisl/llmstxt.git
cd llmstxt

# Install development dependencies
uv pip install -e ".[dev]"

# Run type checking
mypy llmstxt

# Run linting and formatting
ruff check llmstxt
ruff format llmstxt
```

## License

MIT License - See LICENSE file for details

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