chore: import upstream snapshot with attribution
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# AST-Aware Code chunking guide
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## Overview
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This guide covers best practices for using AST-aware code chunking in LEANN. AST chunking provides better semantic understanding of code structure compared to traditional text-based chunking.
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## Quick Start
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### Basic Usage
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```bash
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# Enable AST chunking for mixed content (code + docs)
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python -m apps.document_rag --enable-code-chunking --data-dir ./my_project
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# Specialized code repository indexing
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python -m apps.code_rag --repo-dir ./my_codebase
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# Global CLI with AST support
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leann build my-code-index --docs ./src --use-ast-chunking
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```
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### Installation
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```bash
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# Install LEANN with AST chunking support
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uv pip install -e "."
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```
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#### For normal users (PyPI install)
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- Use `pip install leann` or `uv pip install leann`.
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- `astchunk` is pulled automatically from PyPI as a dependency; no extra steps.
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#### For developers (from source, editable)
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```bash
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git clone https://github.com/yichuan-w/LEANN.git leann
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cd leann
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git submodule update --init --recursive
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uv sync
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```
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- This repo vendors `astchunk` as a git submodule at `packages/astchunk-leann` (our fork).
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- `[tool.uv.sources]` maps the `astchunk` package to that path in editable mode.
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- You can edit code under `packages/astchunk-leann` and Python will use your changes immediately (no separate `pip install astchunk` needed).
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## Best Practices
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### When to Use AST Chunking
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✅ **Recommended for:**
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- Code repositories with multiple languages
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- Mixed documentation and code content
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- Complex codebases with deep function/class hierarchies
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- When working with Claude Code for code assistance
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❌ **Not recommended for:**
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- Pure text documents
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- Very large files (>1MB)
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- Languages not supported by tree-sitter
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### Optimal Configuration
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```bash
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# Recommended settings for most codebases
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python -m apps.code_rag \
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--repo-dir ./src \
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--ast-chunk-size 768 \
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--ast-chunk-overlap 96 \
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--exclude-dirs .git __pycache__ node_modules build dist
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```
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### Supported Languages
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| Extension | Language | Status |
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|-----------|----------|--------|
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| `.py` | Python | ✅ Full support |
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| `.java` | Java | ✅ Full support |
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| `.cs` | C# | ✅ Full support |
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| `.ts`, `.tsx` | TypeScript | ✅ Full support |
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| `.js`, `.jsx` | JavaScript | ✅ Via TypeScript parser |
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## Integration Examples
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### Document RAG with Code Support
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```python
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# Enable code chunking in document RAG
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python -m apps.document_rag \
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--enable-code-chunking \
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--data-dir ./project \
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--query "How does authentication work in the codebase?"
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```
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### Claude Code Integration
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When using with Claude Code MCP server, AST chunking provides better context for:
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- Code completion and suggestions
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- Bug analysis and debugging
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- Architecture understanding
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- Refactoring assistance
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## Troubleshooting
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### Common Issues
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1. **Fallback to Traditional Chunking**
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- Normal behavior for unsupported languages
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- Check logs for specific language support
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2. **Performance with Large Files**
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- Adjust `--max-file-size` parameter
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- Use `--exclude-dirs` to skip unnecessary directories
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3. **Quality Issues**
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- Try different `--ast-chunk-size` values (512, 768, 1024)
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- Adjust overlap for better context preservation
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### Debug Mode
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```bash
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export LEANN_LOG_LEVEL=DEBUG
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python -m apps.code_rag --repo-dir ./my_code
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```
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## Migration from Traditional Chunking
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Existing workflows continue to work without changes. To enable AST chunking:
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```bash
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# Before
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python -m apps.document_rag --chunk-size 256
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# After (maintains traditional chunking for non-code files)
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python -m apps.document_rag --enable-code-chunking --chunk-size 256 --ast-chunk-size 768
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```
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## References
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- [astchunk GitHub Repository](https://github.com/yilinjz/astchunk)
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- [LEANN MCP Integration](../packages/leann-mcp/README.md)
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- [Research Paper](https://arxiv.org/html/2506.15655v1)
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---
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**Note**: AST chunking maintains full backward compatibility while enhancing code understanding capabilities.
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