Queryable concept map of a codebase for LLM coding agents
Project description
combfind
Give an AI agent a codebase. combfind tells it where to look.
combfind builds a local index of a repository so an agent can find the right files and functions for a task with a plain-text query, without reading the entire codebase.
Install
pip install "combfind[llm]" \
--extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cpu
Download a model (one-time, ~2 GB):
combfind download-model
Usage
# Index a repository
combfind build /path/to/repo --db repo.db
# Query it
combfind query "how does authentication work" --db repo.db
combfind query "where are database migrations" --db repo.db --format json
Query output (JSON)
[
{
"rank": 1,
"concept": "Token Refresh",
"role": "implementation",
"score": 0.87,
"files": [{"path": "auth/service.py", "start_line": 42, "end_line": 91}],
"symbols": ["AuthService.refresh", "AuthService.validate"],
"why_relevant": "Handles session token validation and refresh logic.",
"sibling_implementations": ["MobileAuthService", "OAuthService"]
}
]
Build options
| Flag | Default | Description |
|---|---|---|
--db |
<repo>/.combfind.db |
Output path |
--force |
off | Ignore cache, re-index from scratch |
--llm-model |
auto | Path to a GGUF model file |
--exclude-paths |
- | Paths to skip, relative to repo root (repeatable) |
--exclude-regex |
- | Regex matched against file paths to skip |
Supported languages
Python, Go. More languages can be added via tree-sitter grammars.
Project details
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