---
title: Cohere Reranker
sidebarTitle: "Cohere"
description: Integrate Cohere's powerful reranking API with LanceDB for enhanced search results. Supports English and multilingual models with configurable scoring options for vector, FTS, and hybrid search.

---

import { PyRerankingCohereUsage } from '/snippets/integrations.mdx';

# Cohere Reranker

This reranker uses the [Cohere](https://cohere.ai/) API to rerank the search results. You can use this reranker by passing `CohereReranker()` to the `rerank()` method. Note that you'll either need to set the `COHERE_API_KEY` environment variable or pass the `api_key` argument to use this reranker.


> **Note:** Supported query types – Hybrid, Vector, and FTS.

```shell
pip install cohere
```

<CodeGroup>
  <CodeBlock filename="Python" language="Python" icon="python">
    {PyRerankingCohereUsage}
  </CodeBlock>
</CodeGroup>

## Accepted Arguments {#accepted-arguments}
| Argument | Type | Default | Description |
| --- | --- | --- | --- |
| `model_name` | `str` | `"rerank-english-v2.0"` | The name of the reranker model to use. Available cohere models are: rerank-english-v2.0, rerank-multilingual-v2.0 |
| `column` | `str` | `"text"` | The name of the column to use as input to the cross encoder model. |
| `top_n` | `str` | `None` | The number of results to return. If None, will return all results. |
| `api_key` | `str` | `None` | The API key for the Cohere API. If not provided, the `COHERE_API_KEY` environment variable is used. |
| `return_score` | `str` | `"relevance"` | Options are "relevance" or "all". The type of score to return. If "relevance", will return only the `_relevance_score. If "all" is supported, will return relevance score along with the vector and/or fts scores depending on query type |



## Supported Scores for each query type {#supported-scores-for-each-query-type}
You can specify the type of scores you want the reranker to return. The following are the supported scores for each query type:

### Hybrid Search {#hybrid-search}
|`return_score`| Status | Description |
| --- | --- | --- |
| `relevance` | ✅ Supported | Results only have the `_relevance_score` column |
| `all` | ❌ Not Supported | Results have vector(`_distance`) and FTS(`score`) along with Hybrid Search score(`_relevance_score`) |

### Vector Search {#vector-search}
|`return_score`| Status | Description |
| --- | --- | --- |
| `relevance` | ✅ Supported | Results only have the `_relevance_score` column |
| `all` | ✅ Supported | Results have vector(`_distance`) along with Hybrid Search score(`_relevance_score`) |

### FTS Search {#fts-search}
|`return_score`| Status | Description |
| --- | --- | --- |
| `relevance` | ✅ Supported | Results only have the `_relevance_score` column |
| `all` | ✅ Supported | Results have FTS(`score`) along with Hybrid Search score(`_relevance_score`) |