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🌿 Fern Regeneration -- October 28, 2024 #595

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79 changes: 40 additions & 39 deletions poetry.lock

Some generated files are not rendered by default. Learn more about how customized files appear on GitHub.

2 changes: 1 addition & 1 deletion pyproject.toml
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
[tool.poetry]
name = "cohere"
version = "5.11.1"
version = "5.11.2"
description = ""
readme = "README.md"
authors = []
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10 changes: 5 additions & 5 deletions reference.md
Original file line number Diff line number Diff line change
Expand Up @@ -236,7 +236,7 @@ Compatible Deployments:

**connectors:** `typing.Optional[typing.Sequence[ChatConnector]]`

Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/docs/creating-and-deploying-a-connector) one.
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) one.

When specified, the model's reply will be enriched with information found by querying each of the connectors (RAG).

Expand Down Expand Up @@ -721,7 +721,7 @@ Compatible Deployments:

**connectors:** `typing.Optional[typing.Sequence[ChatConnector]]`

Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/docs/creating-and-deploying-a-connector) one.
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) one.

When specified, the model's reply will be enriched with information found by querying each of the connectors (RAG).

Expand Down Expand Up @@ -1584,9 +1584,9 @@ If `ALL` is selected, the token likelihoods will be provided both for the prompt
<dl>
<dd>

This endpoint returns text embeddings. An embedding is a list of floating point numbers that captures semantic information about the text that it represents.
This endpoint returns text and image embeddings. An embedding is a list of floating point numbers that captures semantic information about the content that it represents.

Embeddings can be used to create text classifiers as well as empower semantic search. To learn more about embeddings, see the embedding page.
Embeddings can be used to create classifiers as well as empower semantic search. To learn more about embeddings, see the embedding page.

If you want to learn more how to use the embedding model, have a look at the [Semantic Search Guide](/docs/semantic-search).
</dd>
Expand Down Expand Up @@ -4015,7 +4015,7 @@ client.connectors.list()
<dl>
<dd>

Creates a new connector. The connector is tested during registration and will cancel registration when the test is unsuccessful. See ['Creating and Deploying a Connector'](https://docs.cohere.com/docs/creating-and-deploying-a-connector) for more information.
Creates a new connector. The connector is tested during registration and will cancel registration when the test is unsuccessful. See ['Creating and Deploying a Connector'](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) for more information.
</dd>
</dl>
</dd>
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2 changes: 2 additions & 0 deletions src/cohere/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -138,6 +138,7 @@
Generation,
GetConnectorResponse,
GetModelResponse,
Image,
JsonObjectResponseFormat,
JsonObjectResponseFormatV2,
JsonResponseFormat,
Expand Down Expand Up @@ -421,6 +422,7 @@
"Generation",
"GetConnectorResponse",
"GetModelResponse",
"Image",
"InternalServerError",
"JsonObjectResponseFormat",
"JsonObjectResponseFormatV2",
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16 changes: 8 additions & 8 deletions src/cohere/base_client.py
Original file line number Diff line number Diff line change
Expand Up @@ -250,7 +250,7 @@ def chat_stream(


connectors : typing.Optional[typing.Sequence[ChatConnector]]
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/docs/creating-and-deploying-a-connector) one.
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) one.

When specified, the model's reply will be enriched with information found by querying each of the connectors (RAG).

Expand Down Expand Up @@ -801,7 +801,7 @@ def chat(


connectors : typing.Optional[typing.Sequence[ChatConnector]]
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/docs/creating-and-deploying-a-connector) one.
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) one.

When specified, the model's reply will be enriched with information found by querying each of the connectors (RAG).

Expand Down Expand Up @@ -1777,9 +1777,9 @@ def embed(
request_options: typing.Optional[RequestOptions] = None,
) -> EmbedResponse:
"""
This endpoint returns text embeddings. An embedding is a list of floating point numbers that captures semantic information about the text that it represents.
This endpoint returns text and image embeddings. An embedding is a list of floating point numbers that captures semantic information about the content that it represents.

Embeddings can be used to create text classifiers as well as empower semantic search. To learn more about embeddings, see the embedding page.
Embeddings can be used to create classifiers as well as empower semantic search. To learn more about embeddings, see the embedding page.

If you want to learn more how to use the embedding model, have a look at the [Semantic Search Guide](/docs/semantic-search).

Expand Down Expand Up @@ -3245,7 +3245,7 @@ async def chat_stream(


connectors : typing.Optional[typing.Sequence[ChatConnector]]
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/docs/creating-and-deploying-a-connector) one.
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) one.

When specified, the model's reply will be enriched with information found by querying each of the connectors (RAG).

Expand Down Expand Up @@ -3804,7 +3804,7 @@ async def chat(


connectors : typing.Optional[typing.Sequence[ChatConnector]]
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/docs/creating-and-deploying-a-connector) one.
Accepts `{"id": "web-search"}`, and/or the `"id"` for a custom [connector](https://docs.cohere.com/docs/connectors), if you've [created](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) one.

When specified, the model's reply will be enriched with information found by querying each of the connectors (RAG).

Expand Down Expand Up @@ -4804,9 +4804,9 @@ async def embed(
request_options: typing.Optional[RequestOptions] = None,
) -> EmbedResponse:
"""
This endpoint returns text embeddings. An embedding is a list of floating point numbers that captures semantic information about the text that it represents.
This endpoint returns text and image embeddings. An embedding is a list of floating point numbers that captures semantic information about the content that it represents.

Embeddings can be used to create text classifiers as well as empower semantic search. To learn more about embeddings, see the embedding page.
Embeddings can be used to create classifiers as well as empower semantic search. To learn more about embeddings, see the embedding page.

If you want to learn more how to use the embedding model, have a look at the [Semantic Search Guide](/docs/semantic-search).

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4 changes: 2 additions & 2 deletions src/cohere/connectors/client.py
Original file line number Diff line number Diff line change
Expand Up @@ -225,7 +225,7 @@ def create(
request_options: typing.Optional[RequestOptions] = None,
) -> CreateConnectorResponse:
"""
Creates a new connector. The connector is tested during registration and will cancel registration when the test is unsuccessful. See ['Creating and Deploying a Connector'](https://docs.cohere.com/docs/creating-and-deploying-a-connector) for more information.
Creates a new connector. The connector is tested during registration and will cancel registration when the test is unsuccessful. See ['Creating and Deploying a Connector'](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) for more information.

Parameters
----------
Expand Down Expand Up @@ -1303,7 +1303,7 @@ async def create(
request_options: typing.Optional[RequestOptions] = None,
) -> CreateConnectorResponse:
"""
Creates a new connector. The connector is tested during registration and will cancel registration when the test is unsuccessful. See ['Creating and Deploying a Connector'](https://docs.cohere.com/docs/creating-and-deploying-a-connector) for more information.
Creates a new connector. The connector is tested during registration and will cancel registration when the test is unsuccessful. See ['Creating and Deploying a Connector'](https://docs.cohere.com/v1/docs/creating-and-deploying-a-connector) for more information.

Parameters
----------
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2 changes: 1 addition & 1 deletion src/cohere/core/client_wrapper.py
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@ def get_headers(self) -> typing.Dict[str, str]:
headers: typing.Dict[str, str] = {
"X-Fern-Language": "Python",
"X-Fern-SDK-Name": "cohere",
"X-Fern-SDK-Version": "5.11.1",
"X-Fern-SDK-Version": "5.11.2",
}
if self._client_name is not None:
headers["X-Client-Name"] = self._client_name
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