SDK regeneration (#94)

Co-authored-by: fern-api <115122769+fern-api[bot]@users.noreply.github.com>

client/client.go

@@ -321,7 +321,7 @@ func (c *Client) Chat(
 }
 
 // <Warning>
-// This API is marked as "Legacy" and is no longer maintained. Follow the [migration guide](/docs/migrating-from-cogenerate-to-cochat) to start using the Chat API.
+// This API is marked as "Legacy" and is no longer maintained. Follow the [migration guide](https://docs.cohere.com/docs/migrating-from-cogenerate-to-cochat) to start using the Chat API.
 // </Warning>
 // Generates realistic text conditioned on a given input.
 func (c *Client) GenerateStream(
@@ -449,7 +449,7 @@ func (c *Client) GenerateStream(
 }
 
 // <Warning>
-// This API is marked as "Legacy" and is no longer maintained. Follow the [migration guide](/docs/migrating-from-cogenerate-to-cochat) to start using the Chat API.
+// This API is marked as "Legacy" and is no longer maintained. Follow the [migration guide](https://docs.cohere.com/docs/migrating-from-cogenerate-to-cochat) to start using the Chat API.
 // </Warning>
 // Generates realistic text conditioned on a given input.
 func (c *Client) Generate(
@@ -580,11 +580,11 @@ func (c *Client) Generate(
 	return response, nil
 }
 
-// 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).
+// If you want to learn more how to use the embedding model, have a look at the [Semantic Search Guide](https://docs.cohere.com/docs/semantic-search).
 func (c *Client) Embed(
 	ctx context.Context,
 	request *v2.EmbedRequest,
@@ -973,7 +973,7 @@ func (c *Client) Classify(
 }
 
 // <Warning>
-// This API is marked as "Legacy" and is no longer maintained. Follow the [migration guide](/docs/migrating-from-cogenerate-to-cochat) to start using the Chat API.
+// This API is marked as "Legacy" and is no longer maintained. Follow the [migration guide](https://docs.cohere.com/docs/migrating-from-cogenerate-to-cochat) to start using the Chat API.
 // </Warning>
 // Generates a summary in English for a given text.
 func (c *Client) Summarize(

connectors/client.go

@@ -174,7 +174,7 @@ func (c *Client) List(
 	return response, nil
 }
 
-// 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.
 func (c *Client) Create(
 	ctx context.Context,
 	request *v2.CreateConnectorRequest,

core/request_option.go

@@ -61,7 +61,7 @@ func (r *RequestOptions) cloneHeader() http.Header {
 	headers := r.HTTPHeader.Clone()
 	headers.Set("X-Fern-Language", "Go")
 	headers.Set("X-Fern-SDK-Name", "github.com/cohere-ai/cohere-go/v2")
-	headers.Set("X-Fern-SDK-Version", "v2.12.0")
+	headers.Set("X-Fern-SDK-Version", "v2.12.2")
 	return headers
 }
 

finetuning/types.go

@@ -633,12 +633,12 @@ func (s *Settings) String() string {
 //
 // - STATUS_UNSPECIFIED: Unspecified status.
 // - STATUS_FINETUNING: The fine-tuned model is being fine-tuned.
-// - STATUS_DEPLOYING_API: The fine-tuned model is being deployed.
+// - STATUS_DEPLOYING_API: Deprecated: The fine-tuned model is being deployed.
 // - STATUS_READY: The fine-tuned model is ready to receive requests.
 // - STATUS_FAILED: The fine-tuned model failed.
 // - STATUS_DELETED: The fine-tuned model was deleted.
-// - STATUS_TEMPORARILY_OFFLINE: The fine-tuned model is temporarily unavailable.
-// - STATUS_PAUSED: The fine-tuned model is paused (Vanilla only).
+// - STATUS_TEMPORARILY_OFFLINE: Deprecated: The fine-tuned model is temporarily unavailable.
+// - STATUS_PAUSED: Deprecated: The fine-tuned model is paused (Vanilla only).
 // - STATUS_QUEUED: The fine-tuned model is queued for training.
 type Status string