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Brendan Clement
758f738b8c
This PR is part of the documentation revamp. Once the full set of PRs is merged, we’ll publish the combined site to staging for review before updating docs.lancedb.com. Ingestion, search and integration examples are incomplete or inconsistent across languages, and some guidance misstates SDK behavior. This brings the guides and their example sources together. It includes complete Python, TypeScript and Rust workflows, isolated provider and reranker examples, the Superlinked corrections, and guidance on retries that can duplicate writes. Stacked on #4491. Each MDX file has one PR owner. Rebase onto main after #4491 is squash-merged. Local assembly, Mint validation and link checks pass. Example code is unchanged from the previously validated package. Publication stays held through integration.
55 lines
2.3 KiB
Plaintext
55 lines
2.3 KiB
Plaintext
---
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title: Cohere
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sidebarTitle: Cohere
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---
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import { PyEmbeddingCohereUsage } from '/snippets/integrations.mdx';
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Using cohere API requires cohere package, which can be installed using `pip install cohere`. Cohere embeddings are used to generate embeddings for text data. The embeddings can be used for various tasks like semantic search, clustering, and classification.
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You also need to set the `COHERE_API_KEY` environment variable to use the Cohere API.
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```shell
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export COHERE_API_KEY="your-api-key"
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```
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Supported models are:
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- embed-english-v3.0
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- embed-multilingual-v3.0
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- embed-english-light-v3.0
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- embed-multilingual-light-v3.0
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- embed-english-v2.0
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- embed-english-light-v2.0
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- embed-multilingual-v2.0
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Supported parameters (to be passed in `create` method) are:
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| Parameter | Type | Default Value | Description |
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|---|---|--------|---------|
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| `name` | `str` | `"embed-english-v2.0"` | The model ID of the cohere model to use. Supported base models for Text Embeddings: embed-english-v3.0, embed-multilingual-v3.0, embed-english-light-v3.0, embed-multilingual-light-v3.0, embed-english-v2.0, embed-english-light-v2.0, embed-multilingual-v2.0 |
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| `source_input_type` | `str` | `"search_document"` | The type of input data to be used for the source column. |
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| `query_input_type` | `str` | `"search_query"` | The type of input data to be used for the query. |
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Cohere supports following input types:
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| Input Type | Description |
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|-------------------------|---------------------------------------|
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| "`search_document`" | Used for embeddings stored in a vector|
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| | database for search use-cases. |
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| "`search_query`" | Used for embeddings of search queries |
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| | run against a vector DB |
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| "`semantic_similarity`" | Specifies the given text will be used |
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| | for Semantic Textual Similarity (STS) |
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| "`classification`" | Used for embeddings passed through a |
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| | text classifier. |
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| "`clustering`" | Used for the embeddings run through a |
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| | clustering algorithm |
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Usage Example:
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<CodeGroup>
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<CodeBlock filename="Python" language="Python" icon="python">
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{PyEmbeddingCohereUsage}
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</CodeBlock>
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</CodeGroup> |