CodeKite Code Intelligence Toolkit

codekite is a modular, production-grade Python toolkit for codebase mapping, symbol extraction, code search, and building LLM-powered developer tools, agents, and workflows.

Use codekite to build things like code reviewers, code generators, even IDEs, all enriched with the right code context.

Quick Installation

Install from PyPI

# Installation (includes all features)
uv tool install codekite

Install from Source

git clone https://github.com/shaneholloman/codekite.git
cd codekite
uv sync
uv pip install -e .

Basic Usage

from codekite import Repository

# Load a local repository
repo = Repository("/path/to/your/local/codebase")

# Load a remote public GitHub repo
# repo = Repository("https://github.com/owner/repo")

# Explore the repo
print(repo.get_file_tree())
# Output: [{"path": "src/main.py", "is_dir": False, ...}, ...]

print(repo.extract_symbols('src/main.py'))
# Output: [{"name": "main", "type": "function", "file": "src/main.py", ...}, ...]

Key Features & Capabilities

codekite helps your apps and agents deeply understand and interact with codebases, providing the core components to build your own AI-powered developer tools. Here are just a few of the things you can do:

• Explore Code Structure:

  • Get a bird's-eye view with repo.get_file_tree() to list all files and directories.
  • Dive into specifics with repo.extract_symbols() to identify all functions, classes, and other code constructs, either across the entire repository or within a single file.

• Pinpoint Information:

  • Perform precise textual or regular expression searches across your codebase using repo.search_text().
  • Track down every definition and reference of a specific symbol (like a function or class) with repo.find_symbol_usages().

• Prepare Code for LLMs & Analysis:

  • Break down large files into manageable pieces for LLM context windows using repo.chunk_file_by_lines() or repo.chunk_file_by_symbols().
  • Instantly grab the full definition of a function or class just by knowing a line number within it using repo.extract_context_around_line().

• Generate Code Summaries (Alpha):

  • Leverage LLMs to create natural language summaries for files, functions, or classes using the Summarizer (e.g., summarizer.summarize_file(), summarizer.summarize_function()).
  • Build a searchable semantic index of these AI-generated docstrings with DocstringIndexer and query it with SummarySearcher to find code based on intent and meaning.

• And much more... codekite also offers capabilities for semantic search on raw code, building custom context for LLMs, and more.

License

MIT License