A Python-based parallel file chunking system for large codebases
Project description
A Python-based parallel file chunking system designed for processing large codebases into LLM-friendly chunks. The tool provides intelligent file filtering, multi-threaded processing, and advanced chunking capabilities optimized for machine learning contexts.
Core Features
-
NEW Front end tool for chunking. Run
komodo --dashboard -
Parallel Processing: Multi-threaded file reading with configurable thread pools
-
Smart File Filtering:
- Built-in patterns for common excludes (.git, node_modules, pycache, etc.)
- Customizable ignore/unignore patterns
- Intelligent binary file detection
-
Flexible Chunking:
- Equal-parts chunking: Split content into N equal chunks
- Size-based chunking: Split by maximum chunk size
- Semantic (AST-based) chunking for Python files
- Dry-run mode: If you only want to see which files would be chunked
- Token based chunking: Split by tokens for LLMs
-
LLM Optimizations:
- Metadata extraction (functions, classes, imports, docstrings)
- Content relevance scoring
- Redundancy removal across chunks
- Configurable context window sizes
-
Chunking PDF Files:
- Split PDF content by pages and paragraphs (rather than lines)
- Perform basic text cleanup to handle multi-column layouts, or text from HTML-like elements if present
- Create multiple chunks for large PDFs while preserving some logical structure
-
We scan your repos for api keys and automatically redact it.
.envfiles are also ignored
Installation
pip install komodo==0.2.5
Link to pypi: https://pypi.org/project/pykomodo/
Quick Start
Command Line Usage
Here’s a complete list of available command-line options for the komodo tool:
| Option | Description | Default Value |
|---|---|---|
--dashboard |
Launches the front end for chunking | N/A |
--version |
Show the version of komodo | N/A |
dirs |
Directories to process (space-separated; e.g., komodo dir1/ dir2/). |
Current directory (.) |
--equal-chunks N |
Split content into N equal chunks. Mutually exclusive with --max-chunk-size. |
None |
--max-chunk-size M |
Maximum size per chunk (tokens without --semantic-chunks; lines for .py with it). |
None |
--max-tokens N |
Maximum tokens per chunk (uses token-based chunking). | None |
--output-dir DIR |
Directory where chunk files are saved. | "chunks" |
--ignore PATTERN |
Add a pattern to ignore (repeatable, e.g., --ignore "*.log"). |
None |
--unignore PATTERN |
Add a pattern to unignore (repeatable, overrides ignores). | None |
--dry-run |
List files that would be processed without creating chunks. | False |
--priority PATTERN,SCORE |
Set priority for file patterns (repeatable, e.g., --priority "*.py,10"). |
None |
--num-threads N |
Number of threads for parallel processing. | 4 |
--enhanced |
Use EnhancedParallelChunker for LLM optimizations. |
False |
--semantic-chunks |
Enable AST-based chunking for .py files (splits by functions/classes). |
False |
--context-window N |
Target LLM context window size in bytes (used with --enhanced). |
4096 |
--min-relevance F |
Minimum relevance score for chunks (0.0-1.0, used with --enhanced). |
0.3 |
--no-metadata |
Disable metadata extraction (used with --enhanced). |
False (metadata enabled) |
--keep-redundant |
Keep redundant content across chunks (used with --enhanced). |
False (removes redundancy) |
--no-summaries |
Disable summary generation (used with --enhanced; currently a placeholder in code). |
False (summaries enabled) |
--file-type TYPE |
Only process files of this extension (e.g., pdf, py). |
None |
Notes:
- Options like
--equal-chunksand--max-chunk-sizecannot be used together (enforced by the CLI). - Use
--dry-runto test your ignore/unignore patterns or priority rules without generating output.
Basic usage
CLI
# Split into 5 equal chunks
komodo . --equal-chunks 5
# Process multiple directories
komodo path1/ path2/ --max-chunk-size 1000
Chunking Modes
Komodo offers flexible chunking strategies, with behavior varying based on options and the chunker type (ParallelChunker or EnhancedParallelChunker with --enhanced).
-
Fixed Number of Chunks (
--equal-chunks N):-
Base Chunker: Keeps files whole, distributing them into N chunks with approximately equal total character counts. i.e. 5 different chunks or 5 text files.
komodo . --equal-chunks 5 --output-dir chunks
-
Enhanced Chunker: Combines all file contents into one text blob, then splits into N chunks of roughly equal byte size, potentially splitting files mid-content.
komodo . --equal-chunks 5 --enhanced
-
-
Fixed Size Chunks (--max-chunk-size M): Without
--semantic-chunks: Splits each file into chunks with at most M tokens (words), keeping lines whole. i.e. x number of chunks with 2000 tokens each or 5000 tokens each etc.komodo . --max-chunk-size 2000
Important: You must specify either --equal-chunks or --max-chunk-size, but not both.
-
With --semantic-chunks:
-
For .py files: Aims for chunks of M lines, grouping top-level functions/classes as atomic units. If a function exceeds M lines, it becomes a single chunk.
-
For non-.py files: Still splits by M tokens.
komodo . --max-chunk-size 200 --semantic-chunks
-
With --max-tokens:
komodo . --max-tokens 1000 --output-dir chunks
- Precise token limits: Chunks content based on token counts rather than line counts
- Tiktoken integration: Uses OpenAI's tiktoken library when available for accurate LLM token counting
- Fallback tokenization: Falls back to word-based splitting when tiktoken is unavailable
-
PDF Chunking:
Uses PyMuPDF to split PDFs by pages and paragraphs, respecting --max-chunk-size in tokens.
komodo . --max-chunk-size 500 /path/to/output --file-type pdf
or
komodo . --equal-chunks 10 --output-dir /path/to/output --file-type pdf
IMPORTANT: Do note that for PDFs with a lot of images, this PDF chunker will NOT WORK. This current PDF chunker is NOT capable of chunking formulas/images
Ignoring & Unignoring Files
-
Add ignore patterns with --ignore.
-
Unignore specific patterns with --unignore.
-
Komodo also has built-in ignores like .git, pycache, node_modules, etc.
# Skip everything in "results/" (relative) and "docs/" (relative) komodo . --equal-chunks 5 \ --ignore "results/**" \ --ignore "docs/**" # Skip an absolute path komodo . --equal-chunks 5 \ --ignore "/Users/oha/komodo/results/**" # Skip all .rst files, but unignore README.rst komodo . --equal-chunks 5 \ --ignore "*.rst" \ --unignore "README.rst"
Note: If node_modules fails to be ignored, run this command instead
komodo . --equal-chunks 5 --file-type js --ignore "**/node_modules/**". The key here is that you are specifying the file type.Safest (Recursive) Ignoring
If you want to ensure that Komodo skips all files inside a particular directory (including all subfolders), you can use the ** wildcard before and after the folder name:
# safest mode: skip everything in "results/" and "docs/" recursively komodo . --equal-chunks 5 \ --ignore "**/results/**" \ --ignore "**/docs/**"
Pro Tip: If in doubt, just use /folder/ to recursively ignore that folder and everything beneath it. This is the most reliable way to avoid processing unwanted files in subdirectories.
Fixed Number of Chunks with ignore mode
-
--ignore "/Users/oha/treeline/results/**"tells the chunker to skip any files in that absolute directory path. -
--ignore "docs/*"tells it to skip any files under a relative folder named docs/.komodo . --equal-chunks 5 --ignore "/Users/oha/treeline/results/**" --ignore "docs/*"
Priority Rules
Priority Rules help determine which files should be processed first or given more importance. Files with higher priority scores are processed first
# With equal chunks, 10 which is .py is higher than 5, so 10 will get processed first komodo . \ --equal-chunks 5 \ --priority "*.py,10" \ --priority "*.md,5" \ --output-dir chunks # Or with max chunk size komodo . \ --max-chunk-size 1000 \ --priority "*.py,10" \ --priority "*.md,5" \ --output-dir chunks
-
LLM Optimization Options
Enable metadata extraction and content optimization:
komodo . \
--equal-chunks 5 \
--enhanced \
--context-window 4096 \
--min-relevance 0.3
komodo . \
--equal-chunks 5 \
--enhanced \
--keep-redundant \
--min-relevance 0.5
komodo . \
--equal-chunks 5 \
--enhanced \
--no-metadata \
--context-window 8192
Dry Run
If you only want to see which files would be chunked (and in what priority order), without actually writing any output chunks, you can specify --dry-run. This is especially helpful if you’re testing new ignore/unignore patterns or priority rules. Note again, there will be NO CHUNKING being done. This is just to let you see what files will be chunked.
Example:
## vanilla approach
komodo . --equal-chunks 5 --dry-run
## with priorities for .py files. these get processed faster. but note this is just a dry run
komodo . --equal-chunks 5 --dry-run \
--priority "*.py,10" \
--priority "*.md,5"
No chunks are created. Komodo simply prints the would-be processed files, sorted by priority. This is an easy way to confirm your ignore patterns and see exactly which files the chunker will pick up.
Python API Usage
Basic usage:
from komodo import ParallelChunker
# Split into 5 equal chunks
chunker = ParallelChunker(
equal_chunks=5,
output_dir="chunks"
)
chunker.process_directory("path/to/code")
Advanced configuration:
chunker = ParallelChunker(
equal_chunks=5, # or max_chunk_size=1000
user_ignore=["*.log", "node_modules/**"],
user_unignore=["important.log"],
binary_extensions=["exe", "dll", "so", "bin"],
priority_rules=[
("*.py", 10),
("*.md", 5),
("*.txt", 1)
],
output_dir="chunks",
num_threads=4
)
chunker.process_directories(["src/", "docs/", "tests/"])
Basic configuration with file_type:
import os
from pykomodo.multi_dirs_chunker import ParallelChunker
os.makedirs("/Users/test/komodo/pdf", exist_ok=True)
output_dir = "/Users/test/komodo/pdf"
chunker = ParallelChunker(
max_chunk_size=1000,
output_dir=output_dir,
file_type="pdf"
)
chunker.process_directory("/Users/test/komodo/")
print("PDF processing completed successfully!")
Front-end Usage
To run the front end for chunking, just use komodo --dashboard
Advanced LLM Features
Metadata Extraction
Each chunk automatically extracts and includes:
- Function definitions
- Class declarations
- Import statements
- Docstrings
Relevance Scoring
Chunks are scored based on:
- Code/comment ratio
- Function/class density
- Documentation quality
- Import significance
Redundancy Removal
Automatically removes duplicate content across chunks while preserving unique context.
Example with LLM optimizations:
chunker = ParallelChunker(
equal_chunks=5,
extract_metadata=True,
remove_redundancy=True,
context_window=4096,
min_relevance_score=0.3
)
File Type Restriction
The file_type parameter of the ParallelChunker constructor lets you restrict which file extensions you process.
import os
from pykomodo.multi_dirs_chunker import ParallelChunker
os.makedirs("/path/to/dir", exist_ok=True)
output_dir = "/path/to/dir"
chunker = ParallelChunker(
max_chunk_size=1000,
output_dir=output_dir,
file_type="pdf"
)
chunker.process_directory("/path/to/dir")
print("PDF processing completed successfully!")
Typed Classes & Pydantic-Based Configuration
Komodo’s main classes (ParallelChunker, EnhancedParallelChunker, etc.) now include type hints. Nothing changes at runtime, but if you’re using an IDE or a type checker like mypy, you’ll get improved error checking and auto-completion - or hopefully.
You can also use Pydantic to configure Komodo with strongly typed settings. For instance:
from pydantic import BaseModel, Field
from typing import List, Optional
from pykomodo.multi_dirs_chunker import ParallelChunker
from pykomodo.enhanced_chunker import EnhancedParallelChunker
class KomodoConfig(BaseModel):
directories: List[str] = Field(default_factory=lambda: ["."], description="Directories to process.")
equal_chunks: Optional[int] = None
max_chunk_size: Optional[int] = None
output_dir: str = "chunks"
semantic_chunking: bool = False
enhanced: bool = False
context_window: int = 4096
min_relevance_score: float = 0.3
remove_redundancy: bool = True
extract_metadata: bool = True
def run_chunker_with_config(config: KomodoConfig):
ChunkerClass = EnhancedParallelChunker if config.enhanced else ParallelChunker
chunker = ChunkerClass(
equal_chunks=config.equal_chunks,
max_chunk_size=config.max_chunk_size,
output_dir=config.output_dir,
semantic_chunking=config.semantic_chunking,
context_window=config.context_window if config.enhanced else None,
min_relevance_score=config.min_relevance_score if config.enhanced else None,
remove_redundancy=config.remove_redundancy if config.enhanced else None,
extract_metadata=config.extract_metadata if config.enhanced else None,
)
chunker.process_directories(config.directories)
chunker.close()
if __name__ == "__main__":
# example use with typed + validated config
cfg = KomodoConfig(directories=["src/", "docs/"], equal_chunks=5, enhanced=True)
run_chunker_with_config(cfg)
Common Use Cases
1. Preparing Context for LLMs
Split a large codebase into equal chunks suitable for LLM context windows:
chunker = ParallelChunker(
equal_chunks=5,
priority_rules=[
("*.py", 10),
("README*", 8),
],
user_ignore=["tests/**", "**/__pycache__/**"],
output_dir="llm_chunks"
)
chunker.process_directory("my_project")
Built-in Ignore Patterns
The chunker automatically ignores common non-text and build-related files:
**/.git/****/.idea/**__pycache__*.pyc*.pyo**/node_modules/**targetvenv
Common Gotchas
- Leading Slash for Absolute Paths
- If you omit the leading
/in a pattern like/Users/oha/..., Komodo treats it as relative and won’t match your actual absolute path.
/**vs./*
folder/**matches all files and subfolders under folder.folder/*only matches the immediate contents of folder, not deeper subdirectories.- Overwriting Multiple
--ignoreFlags
- Folder Name vs. Actual Path
- If your path is really
src/komodo/content/results, but you only wroteresults/**, you may need a double-star approach(**/results/**)to cover deeper paths.
Acknowledgments
This project was inspired by repomix, a repository content chunking tool.
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
Apache 2.0
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