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Jack Ye
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The pages describing this code lived in lancedb/docs, a repository with ten stars that neither contributing guide mentioned. A user who hit a wrong page while reading the source had to find a separate, near-invisible repository to fix it. These 102 pages now sit beside the code, and a documentation fix is a pull request in the repository the reader already had open. `docs/web` is a complete Mintlify site: `cd docs/web && mint dev` serves it with no other checkout. Enterprise pages stay private and are merged in when the published site is assembled, so links into them do not resolve here — every open-source page does. `docs/web-tests` holds the tests the code examples are extracted from. They ran against a published wheel before; here they can run against this repository's own SDK, so an example that stops compiling fails the pull request that broke it rather than being noticed later. Both directories sit beside `docs/src` and are invisible to it: mkdocs reads `docs_dir: src`, so the SDK reference builds and deploys exactly as before.
64 lines
3.4 KiB
Plaintext
64 lines
3.4 KiB
Plaintext
---
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title: Watsonx Reranker
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sidebarTitle: "IBM watsonx.ai"
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description: Rerank LanceDB search results with the IBM watsonx.ai text rerank API. Supports vector, FTS, and hybrid search with configurable models, projects, and spaces.
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---
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import { PyRerankingWatsonxUsage } from '/snippets/integrations.mdx';
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# Watsonx Reranker
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This reranker uses the [IBM watsonx.ai](https://cloud.ibm.com/docs/apis/watsonx-ai#text-rerank) text rerank API to reorder search results. Pass `WatsonxReranker()` to the `rerank()` method on a query. Credentials come from the `WATSONX_API_KEY` and `WATSONX_PROJECT_ID` (or `WATSONX_SPACE_ID`) environment variables, or can be passed explicitly as arguments.
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> **Note:** Supported query types – Hybrid, Vector, and FTS.
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```shell
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pip install ibm-watsonx-ai
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```
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<CodeGroup>
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<CodeBlock filename="Python" language="Python" icon="python">
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{PyRerankingWatsonxUsage}
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</CodeBlock>
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</CodeGroup>
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## Accepted Arguments {#accepted-arguments}
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| Argument | Type | Default | Description |
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| --- | --- | --- | --- |
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| `model_name` | `str` | `"cross-encoder/ms-marco-minilm-l-12-v2"` | The rerank model ID. See [supported rerank models](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/fm-models-embed.html?context=wx#rerank). |
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| `column` | `str` | `"text"` | The name of the table column to use as document input. |
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| `top_n` | `int` | `None` | The number of results to return. If `None`, all results are returned. |
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| `return_score` | `str` | `"relevance"` | Options are `"relevance"` or `"all"`. Controls which score columns are kept on the result. |
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| `api_key` | `str` | `None` | IBM Cloud API key. Falls back to the `WATSONX_API_KEY` environment variable. |
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| `project_id` | `str` | `None` | watsonx.ai project ID. Falls back to `WATSONX_PROJECT_ID`. Mutually exclusive with `space_id`. |
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| `space_id` | `str` | `None` | watsonx.ai deployment space ID. Falls back to `WATSONX_SPACE_ID`. Mutually exclusive with `project_id`. |
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| `url` | `str` | `"https://us-south.ml.cloud.ibm.com"` | watsonx.ai service URL. |
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| `truncate_input_tokens` | `int` | `None` | Truncate each document to this many tokens before scoring. |
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<Info>
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You must supply exactly one of `project_id` or `space_id` (either as an argument or via its environment variable). Setting both, or neither, raises a `ValueError`.
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</Info>
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## Supported scores for each query type {#supported-scores-for-each-query-type}
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You can specify the type of scores you want the reranker to return. The following are the supported scores for each query type:
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### Hybrid Search {#hybrid-search}
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|`return_score`| Status | Description |
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| --- | --- | --- |
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| `relevance` | ✅ Supported | Results only have the `_relevance_score` column. |
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| `all` | ❌ Not Supported | Results have vector(`_distance`) and FTS(`score`) along with Hybrid Search score(`_relevance_score`). |
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### Vector Search {#vector-search}
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|`return_score`| Status | Description |
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| --- | --- | --- |
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| `relevance` | ✅ Supported | Results only have the `_relevance_score` column. |
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| `all` | ✅ Supported | Results have vector(`_distance`) along with Hybrid Search score(`_relevance_score`). |
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### FTS Search {#fts-search}
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|`return_score`| Status | Description |
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| --- | --- | --- |
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| `relevance` | ✅ Supported | Results only have the `_relevance_score` column. |
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| `all` | ✅ Supported | Results have FTS(`score`) along with Hybrid Search score(`_relevance_score`). |
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