A vector-powered CLI for semantic search over filenames.
Project description
Vexor
Vexor is a vector-powered CLI that searches file names semantically. It uses Google GenAI's gemini-embedding-001 model to embed file names and queries, then ranks matches with cosine similarity.
Install
pip install -e .
The CLI entry point is vexor (or python -m vexor).
Configure
Set the Gemini API key once and reuse it everywhere:
vexor config --set-api-key "YOUR_KEY"
Optional defaults:
vexor config --set-model gemini-embedding-001
vexor config --set-batch-size 0 # 0 = single request
Configuration is stored in ~/.vexor/config.json.
Workflow
- Index the project root (includes every subdirectory):
vexor index --path ~/projects/demo --include-hidden
- Search from anywhere, pointing to the same path:
vexor search "api client config" --path ~/projects/demo --top 5
Output example:Vexor semantic file search results ────────────────────────────────── 1 0.923 ./src/config_loader.py 2 0.871 ./src/utils/config_parse.py 3 0.809 ./tests/test_config_loader.py
Tips:
- Keep one index per project root; subdirectories need separate indexes only if you explicitly run
vexor indexon them. - Hidden files are included only if both
indexandsearchuse--include-hidden.
Commands
| Command | Description |
|---|---|
vexor index --path PATH [--include-hidden] |
Recursively scans PATH, embeds file names, and writes a cache under ~/.vexor. |
vexor search QUERY --path PATH [--top K] [--include-hidden] |
Loads the cached embeddings for PATH and ranks matches for QUERY. |
vexor config --set-api-key/--clear-api-key |
Manage the stored Gemini API key. |
vexor config --set-model/--set-batch-size/--show |
Manage default model and batch size. |
Development
Run tests with:
pip install -e .[dev]
pytest
Tests rely on fake embedding backends, so no network access is required.
Cache files and configuration live in ~/.vexor. Adjust _label_for_path or VexorSearcher._prepare_text if you need to encode additional context (e.g., relative paths).
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