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231 lines
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6.6 KiB
Text
231 lines
No EOL
6.6 KiB
Text
[[infer-service-cohere]]
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=== Cohere {infer} integration
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.New API reference
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[sidebar]
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--
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For the most up-to-date API details, refer to {api-es}/group/endpoint-inference[{infer-cap} APIs].
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--
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Creates an {infer} endpoint to perform an {infer} task with the `cohere` service.
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[discrete]
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[[infer-service-cohere-api-request]]
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==== {api-request-title}
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`PUT /_inference/<task_type>/<inference_id>`
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[discrete]
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[[infer-service-cohere-api-path-params]]
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==== {api-path-parms-title}
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`<inference_id>`::
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(Required, string)
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include::inference-shared.asciidoc[tag=inference-id]
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`<task_type>`::
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(Required, string)
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include::inference-shared.asciidoc[tag=task-type]
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+
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--
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Available task types:
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* `completion`,
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* `rerank`,
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* `text_embedding`.
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--
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[discrete]
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[[infer-service-cohere-api-request-body]]
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==== {api-request-body-title}
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`chunking_settings`::
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(Optional, object)
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include::inference-shared.asciidoc[tag=chunking-settings]
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`max_chunk_size`:::
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(Optional, integer)
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include::inference-shared.asciidoc[tag=chunking-settings-max-chunking-size]
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`overlap`:::
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(Optional, integer)
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include::inference-shared.asciidoc[tag=chunking-settings-overlap]
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`sentence_overlap`:::
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(Optional, integer)
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include::inference-shared.asciidoc[tag=chunking-settings-sentence-overlap]
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`strategy`:::
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(Optional, string)
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include::inference-shared.asciidoc[tag=chunking-settings-strategy]
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`service`::
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(Required, string)
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The type of service supported for the specified task type. In this case,
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`cohere`.
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`service_settings`::
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(Required, object)
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include::inference-shared.asciidoc[tag=service-settings]
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--
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These settings are specific to the `cohere` service.
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--
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`api_key`:::
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(Required, string)
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A valid API key of your Cohere account.
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You can find your Cohere API keys or you can create a new one
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https://dashboard.cohere.com/api-keys[on the API keys settings page].
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+
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--
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include::inference-shared.asciidoc[tag=api-key-admonition]
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--
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`rate_limit`:::
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(Optional, object)
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By default, the `cohere` service sets the number of requests allowed per minute to `10000`.
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This value is the same for all task types.
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This helps to minimize the number of rate limit errors returned from Cohere.
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To modify this, set the `requests_per_minute` setting of this object in your service settings:
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+
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--
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include::inference-shared.asciidoc[tag=request-per-minute-example]
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More information about Cohere's rate limits can be found in https://docs.cohere.com/docs/going-live#production-key-specifications[Cohere's production key docs].
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--
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.`service_settings` for the `completion` task type
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[%collapsible%closed]
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=====
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`model_id`::
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(Optional, string)
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The name of the model to use for the {infer} task.
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To review the available `completion` models, refer to the
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https://docs.cohere.com/docs/models#command[Cohere docs].
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=====
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+
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.`service_settings` for the `rerank` task type
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[%collapsible%closed]
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=====
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`model_id`::
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(Optional, string)
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The name of the model to use for the {infer} task.
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To review the available `rerank` models, refer to the
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https://docs.cohere.com/reference/rerank-1[Cohere docs].
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=====
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.`service_settings` for the `text_embedding` task type
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[%collapsible%closed]
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=====
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`embedding_type`:::
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(Optional, string)
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Specifies the types of embeddings you want to get back.
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Defaults to `float`.
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Valid values are:
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* `byte`: use it for signed int8 embeddings (this is a synonym of `int8`).
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* `float`: use it for the default float embeddings.
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* `int8`: use it for signed int8 embeddings.
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`model_id`:::
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(Optional, string)
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The name of the model to use for the {infer} task.
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To review the available `text_embedding` models, refer to the
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https://docs.cohere.com/reference/embed[Cohere docs].
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The default value for `text_embedding` is `embed-english-v2.0`.
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`similarity`:::
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(Optional, string)
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Similarity measure. One of `cosine`, `dot_product`, `l2_norm`.
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Defaults based on the `embedding_type` (`float` -> `dot_product`, `int8/byte` -> `cosine`).
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=====
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`task_settings`::
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(Optional, object)
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include::inference-shared.asciidoc[tag=task-settings]
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+
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.`task_settings` for the `rerank` task type
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[%collapsible%closed]
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=====
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`return_documents`::
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(Optional, boolean)
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Specify whether to return doc text within the results.
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`top_n`::
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(Optional, integer)
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The number of most relevant documents to return, defaults to the number of the documents.
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If this {infer} endpoint is used in a `text_similarity_reranker` retriever query and `top_n` is set, it must be greater than or equal to `rank_window_size` in the query.
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=====
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+
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.`task_settings` for the `text_embedding` task type
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[%collapsible%closed]
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=====
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`input_type`:::
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(Optional, string)
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Specifies the type of input passed to the model.
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Valid values are:
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* `classification`: use it for embeddings passed through a text classifier.
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* `clusterning`: use it for the embeddings run through a clustering algorithm.
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* `ingest`: use it for storing document embeddings in a vector database.
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* `search`: use it for storing embeddings of search queries run against a vector database to find relevant documents.
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IMPORTANT: The `input_type` field is required when using embedding models `v3` and higher.
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`truncate`:::
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(Optional, string)
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Specifies how the API handles inputs longer than the maximum token length.
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Defaults to `END`.
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Valid values are:
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* `NONE`: when the input exceeds the maximum input token length an error is returned.
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* `START`: when the input exceeds the maximum input token length the start of the input is discarded.
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* `END`: when the input exceeds the maximum input token length the end of the input is discarded.
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=====
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[discrete]
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[[inference-example-cohere]]
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==== Cohere service examples
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The following example shows how to create an {infer} endpoint called
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`cohere-embeddings` to perform a `text_embedding` task type.
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[source,console]
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------------------------------------------------------------
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PUT _inference/text_embedding/cohere-embeddings
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{
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"service": "cohere",
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"service_settings": {
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"api_key": "<api_key>",
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"model_id": "embed-english-light-v3.0",
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"embedding_type": "byte"
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}
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}
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------------------------------------------------------------
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// TEST[skip:TBD]
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The following example shows how to create an {infer} endpoint called
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`cohere-rerank` to perform a `rerank` task type.
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[source,console]
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------------------------------------------------------------
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PUT _inference/rerank/cohere-rerank
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{
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"service": "cohere",
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"service_settings": {
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"api_key": "<API-KEY>",
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"model_id": "rerank-english-v3.0"
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},
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"task_settings": {
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"top_n": 10,
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"return_documents": true
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}
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}
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------------------------------------------------------------
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// TEST[skip:TBD]
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For more examples, also review the
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https://docs.cohere.com/docs/elasticsearch-and-cohere#rerank-search-results-with-cohere-and-elasticsearch[Cohere documentation]. |