SDK regeneration

client/client.go

@@ -7,6 +7,7 @@ import (
 	context "context"
 	json "encoding/json"
 	errors "errors"
+	fmt "fmt"
 	v2 "github.com/cohere-ai/cohere-go/v2"
 	connectors "github.com/cohere-ai/cohere-go/v2/connectors"
 	core "github.com/cohere-ai/cohere-go/v2/core"
@@ -55,7 +56,7 @@ func NewClient(opts ...option.RequestOption) *Client {
 }
 
 // Generates a text response to a user message.
-// To learn how to use the Chat API with Streaming and RAG follow our [Text Generation guides](https://docs.cohere.com/docs/chat-api).
+// To learn how to use the Chat API and RAG follow our [Text Generation guides](https://docs.cohere.com/docs/chat-api).
 func (c *Client) ChatStream(
 	ctx context.Context,
 	request *v2.ChatStreamRequest,
@@ -73,6 +74,9 @@ func (c *Client) ChatStream(
 	endpointURL := baseURL + "/v1/chat"
 
 	headers := core.MergeHeaders(c.header.Clone(), options.ToHeader())
+	if request.Accepts != nil {
+		headers.Add("Accepts", fmt.Sprintf("%v", request.Accepts))
+	}
 
 	errorDecoder := func(statusCode int, body io.Reader) error {
 		raw, err := io.ReadAll(body)
@@ -179,7 +183,7 @@ func (c *Client) ChatStream(
 }
 
 // Generates a text response to a user message.
-// To learn how to use the Chat API with Streaming and RAG follow our [Text Generation guides](https://docs.cohere.com/docs/chat-api).
+// To learn how to use the Chat API and RAG follow our [Text Generation guides](https://docs.cohere.com/docs/chat-api).
 func (c *Client) Chat(
 	ctx context.Context,
 	request *v2.ChatRequest,
@@ -197,6 +201,9 @@ func (c *Client) Chat(
 	endpointURL := baseURL + "/v1/chat"
 
 	headers := core.MergeHeaders(c.header.Clone(), options.ToHeader())
+	if request.Accepts != nil {
+		headers.Add("Accepts", fmt.Sprintf("%v", request.Accepts))
+	}
 
 	errorDecoder := func(statusCode int, body io.Reader) error {
 		raw, err := io.ReadAll(body)

core/request_option.go

@@ -56,7 +56,7 @@ 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", "v2.11.0")
+	headers.Set("X-Fern-SDK-Version", "v2.11.1")
 	return headers
 }
 

finetuning/types.go

@@ -61,7 +61,7 @@ func (b *BaseModel) String() string {
 // The possible types of fine-tuned models.
 //
 // - BASE_TYPE_UNSPECIFIED: Unspecified model.
-// - BASE_TYPE_GENERATIVE: Generative model.
+// - BASE_TYPE_GENERATIVE: Deprecated: Generative model.
 // - BASE_TYPE_CLASSIFICATION: Classification model.
 // - BASE_TYPE_RERANK: Rerank model.
 // - BASE_TYPE_CHAT: Chat model.
@@ -546,7 +546,7 @@ type Settings struct {
 	Hyperparameters *Hyperparameters `json:"hyperparameters,omitempty" url:"hyperparameters,omitempty"`
 	// read-only. Whether the model is single-label or multi-label (only for classification).
 	MultiLabel *bool `json:"multi_label,omitempty" url:"multi_label,omitempty"`
-	// The Weights & Biases configuration.
+	// The Weights & Biases configuration (Chat fine-tuning only).
 	Wandb *WandbConfig `json:"wandb,omitempty" url:"wandb,omitempty"`
 
 	extraProperties map[string]interface{}
@@ -644,7 +644,7 @@ func (s Status) Ptr() *Status {
 // The possible strategy used to serve a fine-tuned models.
 //
 // - STRATEGY_UNSPECIFIED: Unspecified strategy.
-// - STRATEGY_VANILLA: Serve the fine-tuned model on a dedicated GPU.
+// - STRATEGY_VANILLA: Deprecated: Serve the fine-tuned model on a dedicated GPU.
 // - STRATEGY_TFEW: Serve the fine-tuned model on a shared GPU.
 type Strategy string
 

types.go

@@ -10,6 +10,8 @@ import (
 )
 
 type ChatRequest struct {
+	// Pass text/event-stream to receive the streamed response as server-sent events. The default is `\n` delimited events.
+	Accepts *string `json:"-" url:"-"`
 	// Text input for the model to respond to.
 	//
 	// Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments
@@ -237,6 +239,8 @@ func (c *ChatRequest) MarshalJSON() ([]byte, error) {
 }
 
 type ChatStreamRequest struct {
+	// Pass text/event-stream to receive the streamed response as server-sent events. The default is `\n` delimited events.
+	Accepts *string `json:"-" url:"-"`
 	// Text input for the model to respond to.
 	//
 	// Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments
@@ -491,6 +495,10 @@ type DetokenizeRequest struct {
 type EmbedRequest struct {
 	// An array of strings for the model to embed. Maximum number of texts per call is `96`. We recommend reducing the length of each text to be under `512` tokens for optimal quality.
 	Texts []string `json:"texts,omitempty" url:"-"`
+	// An array of image data URIs for the model to embed. Maximum number of images per call is `1`.
+	//
+	// The image must be a valid [data URI](https://developer.mozilla.org/en-US/docs/Web/URI/Schemes/data). The image must be in either `image/jpeg` or `image/png` format and has a maximum size of 5MB.
+	Images []string `json:"images,omitempty" url:"-"`
 	// Defaults to embed-english-v2.0
 	//
 	// The identifier of the model. Smaller "light" models are faster, while larger models will perform better. [Custom models](/docs/training-custom-models) can also be supplied with their full ID.
@@ -3174,13 +3182,15 @@ func (e *EmbedFloatsResponse) String() string {
 // - `"search_query"`: Used for embeddings of search queries run against a vector DB to find relevant documents.
 // - `"classification"`: Used for embeddings passed through a text classifier.
 // - `"clustering"`: Used for the embeddings run through a clustering algorithm.
+// - `"image"`: Used for embeddings with image input.
 type EmbedInputType string
 
 const (
 	EmbedInputTypeSearchDocument EmbedInputType = "search_document"
 	EmbedInputTypeSearchQuery    EmbedInputType = "search_query"
 	EmbedInputTypeClassification EmbedInputType = "classification"
 	EmbedInputTypeClustering     EmbedInputType = "clustering"
+	EmbedInputTypeImage          EmbedInputType = "image"
 )
 
 func NewEmbedInputTypeFromString(s string) (EmbedInputType, error) {
@@ -3193,6 +3203,8 @@ func NewEmbedInputTypeFromString(s string) (EmbedInputType, error) {
 		return EmbedInputTypeClassification, nil
 	case "clustering":
 		return EmbedInputTypeClustering, nil
+	case "image":
+		return EmbedInputTypeImage, nil
 	}
 	var t EmbedInputType
 	return "", fmt.Errorf("%s is not a valid %T", s, t)