# Vectorless
[](https://crates.io/crates/vectorless)
[](https://crates.io/crates/vectorless)
[](https://docs.rs/vectorless)
[](LICENSE)
[](https://www.rust-lang.org/)
A hierarchical, reasoning-native document intelligence engine. no vector db, no embeddings.
> ⭐ **Star us on [GitHub](https://github.com/vectorlessflow/vectorless)** — it helps the project grow!
## Features
- **Tree-based indexing** — Documents organized as hierarchical trees, not flat vectors
- **LLM-driven retrieval** — Uses reasoning to navigate document structure
- **No vector database** — Eliminates embedding infrastructure complexity
- **Multi-format support** — Markdown, PDF (basic), HTML/DOCX (planned)
- **Workspace persistence** — LRU-cached storage with lazy loading
- **Pluggable retrievers** — LLM navigate, beam search, MCTS, hybrid
## Quick Start
* Add to `Cargo.toml`:
```toml
[dependencies]
vectorless = "0.1"
```
* Create `vectorless.toml` in your project root (auto-detected):
```shell
cp config.example.toml vectorless.toml
```
```rust
use vectorless::client::{Vectorless, VectorlessBuilder};
#[tokio::main]
async fn main() -> vectorless::core::Result<()> {
// Create client (auto-loads config from ./vectorless.toml)
let mut client = VectorlessBuilder::new()
.with_workspace("./workspace")
.build()?;
// Index a document
let doc_id = client.index("./document.md").await?;
// Query
let result = client.query(&doc_id, "What is this about?").await?;
println!("{}", result.content);
Ok(())
}
```
## Contributing
⭐ If you find this project useful, please consider giving it a star on [GitHub](https://github.com/vectorlessflow/vectorless) — it helps others discover it and supports ongoing development.
## License
Apache-2.0