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docs: Added params table #20

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Nov 17, 2024
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docs: Added params table #20

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21 changes: 21 additions & 0 deletions README.md
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Expand Up @@ -25,6 +25,7 @@
- [Quickstart](#quickstart)
- [Main Features](#main-features)
- [Supported Backends](#supported-backends)
- [Backend Parameters](#backend-parameters)
- [Usage](#usage)

Vicinity is the lightest-weight vector store. Just put in some vectors, calculate query vectors, and off you go. It provides a simple and intuitive API for nearest neighbor search, with support for different backends.
Expand Down Expand Up @@ -79,6 +80,26 @@ The following backends are supported:
- `ANNOY`: "Approximate Nearest Neighbors Oh Yeah" for approximate nearest neighbor search.
- `PYNNDescent`: Approximate nearest neighbor search using PyNNDescent.

### Backend Parameters

| Backend | Parameter | Description | Default Value |
|----------------|--------------------|-----------------------------------------------------------------------------------------------|---------------------|
| **Annoy** | `metric` | Similarity metric to use (`dot`, `euclidean`, `cosine`). | `"cosine"` |
| | `trees` | Number of trees to use for indexing. | `100` |
| | `length` | Optional length of the dataset. | `None` |
| **FAISS** | `index_type` | Type of FAISS index (`flat`, `ivf`, `hnsw`, `lsh`, `scalar`, `pq`, `ivf_scalar`, `ivfpq`, `ivfpqr`). | `"hnsw"` |
| | `metric` | Similarity metric to use (`cosine`, `l2`). | `"cosine"` |
| | `nlist` | Number of cells for IVF indexes. | `100` |
| | `m` | Number of subquantizers for PQ and HNSW indexes. | `8` |
| | `nbits` | Number of bits for LSH and PQ indexes. | `8` |
| | `refine_nbits` | Number of bits for the refinement stage in IVFPQR indexes. | `8` |
| **HNSW** | `space` | Similarity space to use (`cosine`, `l2`). | `"cosine"` |
| | `ef_construction` | Size of the dynamic list during index construction. | `200` |
| | `m` | Number of connections per layer. | `16` |
| **PyNNDescent**| `n_neighbors` | Number of neighbors to use for search. | `15` |
| | `metric` | Similarity metric to use (`cosine`, `euclidean`, `manhattan`). | `"cosine"` |


## Usage

<details>
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