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zzszmyf/codefuse

19GoAudience · developerComplexity · 3/5Setup · moderate

TLDR

CodeFuse pre-indexes a codebase into a searchable graph of functions, classes, and their relationships so AI coding assistants can find code faster and more accurately than plain text search.

Mindmap

mindmap
  root((codefuse))
    What it does
      Pre-indexes codebase
      Builds call graph
      Incremental updates
    Supported Languages
      Go
      TypeScript
      Python
      Rust
    Access Methods
      Command line queries
      Plain text file export
      FUSE filesystem mount
    Parsing Modes
      Fast regex mode
      Accurate tree-sitter mode
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Code map

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Things people build with this

USE CASE 1

Speed up AI coding assistants by giving them a pre-built index instead of running slow text searches every time they look for a function.

USE CASE 2

Browse your codebase as a virtual filesystem to see which functions call which, navigating it like a folder tree.

USE CASE 3

Export an indexed snapshot of your codebase as plain text files so any AI tool can read code structure without special plugins.

Tech stack

Gotree-sitterFUSE

Getting it running

Difficulty · moderate Time to first run · 30min

Requires Go installed to build, FUSE mount option needs the FUSE library on your OS.

No license information was mentioned in the explanation.

In plain English

CodeFuse is a tool that pre-indexes a codebase so that AI coding assistants can find and understand code faster and more accurately. The problem it addresses is that most AI coding tools currently navigate code by running text searches across files every time they need to find something. This is slow, imprecise, and produces results that include false matches from comments or unrelated code. Instead of searching files on demand, CodeFuse reads the entire codebase once and builds a graph that tracks every function, class, and method along with which ones call which others. That graph is then stored locally. When an AI agent needs to find a symbol, look at who calls a particular function, or see the structure of a file, it queries the pre-built index rather than scanning raw text. The result is faster lookups and more accurate results, particularly for cross-file relationships that are invisible to plain text search. The tool exposes the index in a few different ways. The command line accepts queries for symbol names with support for wildcards, so you can search for everything matching a pattern like "get*User". It can also generate a folder of plain text files that mirrors the index structure, so an AI agent can navigate code using ordinary file-listing and file-reading operations without any special integration. Optionally it can mount the index as an actual filesystem using FUSE, letting you browse symbols the same way you browse a directory tree. Indexing supports Go, TypeScript, JavaScript, Python, and Rust. The fast default mode uses the Go compiler's own parser for Go files and regular expressions for other languages. A slower but more thorough mode uses tree-sitter, an open-source code parsing library, for more accurate results across all languages. The index is stored in a project subfolder and supports incremental updates, so only changed files are re-parsed on subsequent runs.

Copy-paste prompts

Prompt 1
Using the CodeFuse index in my Go project, write a CLI command that queries the index for all functions matching the pattern 'get*User' and prints their file locations.
Prompt 2
Help me integrate CodeFuse's FUSE filesystem mount into my AI coding workflow so my assistant reads from the symbol index instead of scanning raw files.
Prompt 3
I want to add incremental indexing to my TypeScript project with CodeFuse. Show me the commands to build the initial index and then update it after a file change.
Prompt 4
Explain how to use CodeFuse's tree-sitter mode versus the fast regex mode and when I should choose each for my Python codebase.
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