func Float32Ptr(ffloat32) *float32

func IntPtr(iint) *int

type APIError struct {RateLimitHeadersRateLimitHeadersStatusCodeint    `json:"status_code"`Messagestring `json:"message"`Typestring `json:"type"`}

func (APIError)Error¶added inv1.1.2

func (eAPIError) Error()string

type APIErrorResponse struct {ErrorAPIError `json:"error"`}

type ChatCompletionFunctionParameters struct {Typestring                                       `json:"type"`Descriptionstring                                       `json:"description,omitempty"`Properties  map[string]FunctionParameterPropertyMetadata `json:"properties"`Required    []string                                     `json:"required"`}

type ChatCompletionFunctions struct {Namestring                           `json:"name"`Descriptionstring                           `json:"description,omitempty"`ParametersChatCompletionFunctionParameters `json:"parameters"`}

type ChatCompletionRequest struct {// Model is the name of the model to use. If not specified, will default to gpt-3.5-turbo.Modelstring `json:"model"`// Messages is a list of messages to use as the context for the chat completion.Messages []ChatCompletionRequestMessage `json:"messages"`// Functions is a list of functions the model may generate JSON inputs for.Functions []ChatCompletionFunctions `json:"functions,omitempty"`// What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministicTemperature *float32 `json:"temperature,omitempty"`// An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.TopPfloat32 `json:"top_p,omitempty"`// Number of responses to generateNint `json:"n,omitempty"`// Whether or not to stream responses back as they are generatedStreambool `json:"stream,omitempty"`// Up to 4 sequences where the API will stop generating further tokens.Stop []string `json:"stop,omitempty"`// MaxTokens is the maximum number of tokens to return.MaxTokensint `json:"max_tokens,omitempty"`// (-2, 2) Penalize tokens that haven't appeared yet in the history.PresencePenaltyfloat32 `json:"presence_penalty,omitempty"`// (-2, 2) Penalize tokens that appear too frequently in the history.FrequencyPenaltyfloat32 `json:"frequency_penalty,omitempty"`// Modify the probability of specific tokens appearing in the completion.LogitBias map[string]float32 `json:"logit_bias,omitempty"`// Can be used to identify an end-userUserstring `json:"user,omitempty"`}

type ChatCompletionRequestMessage struct {// Role is the role is the role of the the message. Can be "system", "user", or "assistant"Rolestring `json:"role"`// Content is the content of the messageContentstring `json:"content"`// FunctionCall is the name and arguments of a function that should be called, as generated by the model.FunctionCall *Function `json:"function_call,omitempty"`// Name is the the name of the author of this message. `name` is required if role is `function`, and it should be the name of the function whose response is in the `content`.Namestring `json:"name,omitempty"`}

type ChatCompletionResponse struct {RateLimitHeadersRateLimitHeadersIDstring                         `json:"id"`Objectstring                         `json:"object"`Createdint                            `json:"created"`Modelstring                         `json:"model"`Choices []ChatCompletionResponseChoice `json:"choices"`UsageChatCompletionsResponseUsage   `json:"usage"`}

type ChatCompletionResponseChoice struct {Indexint                           `json:"index"`FinishReasonstring                        `json:"finish_reason"`MessageChatCompletionResponseMessage `json:"message"`}

type ChatCompletionResponseMessage struct {Rolestring    `json:"role"`Contentstring    `json:"content"`FunctionCall *Function `json:"function_call,omitempty"`}

type ChatCompletionStreamResponse struct {IDstring                               `json:"id"`Objectstring                               `json:"object"`Createdint                                  `json:"created"`Modelstring                               `json:"model"`Choices []ChatCompletionStreamResponseChoice `json:"choices"`UsageChatCompletionsResponseUsage         `json:"usage"`}

type ChatCompletionStreamResponseChoice struct {Indexint                           `json:"index"`FinishReasonstring                        `json:"finish_reason"`DeltaChatCompletionResponseMessage `json:"delta"`}

type ChatCompletionsResponseUsage struct {PromptTokensint `json:"prompt_tokens"`CompletionTokensint `json:"completion_tokens"`TotalTokensint `json:"total_tokens"`}

type Client interface {// Engines lists the currently available engines, and provides basic information about each// option such as the owner and availability.Engines(ctxcontext.Context) (*EnginesResponse,error)// Engine retrieves an engine instance, providing basic information about the engine such// as the owner and availability.Engine(ctxcontext.Context, enginestring) (*EngineObject,error)// ChatCompletion creates a completion with the Chat completion endpoint which// is what powers the ChatGPT experience.ChatCompletion(ctxcontext.Context, requestChatCompletionRequest) (*ChatCompletionResponse,error)// ChatCompletion creates a completion with the Chat completion endpoint which// is what powers the ChatGPT experience.ChatCompletionStream(ctxcontext.Context, requestChatCompletionRequest, onData func(*ChatCompletionStreamResponse)error)error// Completion creates a completion with the default engine. This is the main endpoint of the API// which auto-completes based on the given prompt.Completion(ctxcontext.Context, requestCompletionRequest) (*CompletionResponse,error)// CompletionStream creates a completion with the default engine and streams the results through// multiple calls to onData.CompletionStream(ctxcontext.Context, requestCompletionRequest, onData func(*CompletionResponse))error// CompletionWithEngine is the same as Completion except allows overriding the default engine on the clientCompletionWithEngine(ctxcontext.Context, enginestring, requestCompletionRequest) (*CompletionResponse,error)// CompletionStreamWithEngine is the same as CompletionStream except allows overriding the default engine on the clientCompletionStreamWithEngine(ctxcontext.Context, enginestring, requestCompletionRequest, onData func(*CompletionResponse))error// Given a prompt and an instruction, the model will return an edited version of the prompt.Edits(ctxcontext.Context, requestEditsRequest) (*EditsResponse,error)// Search performs a semantic search over a list of documents with the default engine.Search(ctxcontext.Context, requestSearchRequest) (*SearchResponse,error)// SearchWithEngine performs a semantic search over a list of documents with the specified engine.SearchWithEngine(ctxcontext.Context, enginestring, requestSearchRequest) (*SearchResponse,error)// Returns an embedding using the provided request.Embeddings(ctxcontext.Context, requestEmbeddingsRequest) (*EmbeddingsResponse,error)// Moderation performs a moderation check on the given text against an OpenAI classifier to determine whether the// provided content complies with OpenAI's usage policies.Moderation(ctxcontext.Context, requestModerationRequest) (*ModerationResponse,error)}

funcNewClient¶

func NewClient(apiKeystring, options ...ClientOption)Client

NewClient returns a new OpenAI GPT-3 API client. An apiKey is required to use the client

type ClientOption func(*client)error

funcWithBaseURL¶

func WithBaseURL(baseURLstring)ClientOption

WithBaseURL is a client option that allows you to override the default base url of the client.The default base url is "https://api.openai.com/v1"

funcWithDefaultEngine¶

func WithDefaultEngine(enginestring)ClientOption

WithDefaultEngine is a client option that allows you to override the default engine of the client

funcWithHTTPClient¶added inv1.1.2

func WithHTTPClient(httpClient *http.Client)ClientOption

WithHTTPClient allows you to override the internal http.Client used

funcWithOrg¶added inv1.1.4

func WithOrg(idstring)ClientOption

WithOrg is a client option that allows you to override the organization ID

funcWithTimeout¶

func WithTimeout(timeouttime.Duration)ClientOption

WithTimeout is a client option that allows you to override the default timeout duration of requestsfor the client. The default is 30 seconds. If you are overriding the http client as well, just includethe timeout there.

funcWithUserAgent¶

func WithUserAgent(userAgentstring)ClientOption

WithUserAgent is a client option that allows you to override the default user agent of the client

type CompletionRequest struct {// A list of string prompts to use.// TODO there are other prompt types here for using token integers that we could add support for.Prompt []string `json:"prompt"`// How many tokens to complete up to. Max of 512MaxTokens *int `json:"max_tokens,omitempty"`// Sampling temperature to useTemperature *float32 `json:"temperature,omitempty"`// Alternative to temperature for nucleus samplingTopP *float32 `json:"top_p,omitempty"`// How many choice to create for each promptN *int `json:"n"`// Include the probabilities of most likely tokensLogProbs *int `json:"logprobs"`// Echo back the prompt in addition to the completionEchobool `json:"echo"`// Up to 4 sequences where the API will stop generating tokens. Response will not contain the stop sequence.Stop []string `json:"stop,omitempty"`// PresencePenalty number between 0 and 1 that penalizes tokens that have already appeared in the text so far.PresencePenaltyfloat32 `json:"presence_penalty"`// FrequencyPenalty number between 0 and 1 that penalizes tokens on existing frequency in the text so far.FrequencyPenaltyfloat32 `json:"frequency_penalty"`// Whether to stream back results or not. Don't set this value in the request yourself// as it will be overriden depending on if you use CompletionStream or Completion methods.Streambool `json:"stream,omitempty"`}

type CompletionResponse struct {RateLimitHeadersRateLimitHeadersIDstring                     `json:"id"`Objectstring                     `json:"object"`Createdint                        `json:"created"`Modelstring                     `json:"model"`Choices []CompletionResponseChoice `json:"choices"`UsageCompletionResponseUsage    `json:"usage"`}

type CompletionResponseChoice struct {Textstring        `json:"text"`Indexint           `json:"index"`LogProbsLogprobResult `json:"logprobs"`FinishReasonstring        `json:"finish_reason"`}

type CompletionResponseUsage struct {PromptTokensint `json:"prompt_tokens"`CompletionTokensint `json:"completion_tokens"`TotalTokensint `json:"total_tokens"`}

type EditsRequest struct {// ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.Modelstring `json:"model"`// The input text to use as a starting point for the edit.Inputstring `json:"input"`// The instruction that tells the model how to edit the prompt.Instructionstring `json:"instruction"`// Sampling temperature to useTemperature *float32 `json:"temperature,omitempty"`// Alternative to temperature for nucleus samplingTopP *float32 `json:"top_p,omitempty"`// How many edits to generate for the input and instruction. Defaults to 1N *int `json:"n"`}

type EditsResponse struct {Objectstring                `json:"object"`Createdint                   `json:"created"`Choices []EditsResponseChoice `json:"choices"`UsageEditsResponseUsage    `json:"usage"`}

type EditsResponseChoice struct {Textstring `json:"text"`Indexint    `json:"index"`}

type EditsResponseUsage struct {PromptTokensint `json:"prompt_tokens"`CompletionTokensint `json:"completion_tokens"`TotalTokensint `json:"total_tokens"`}

type EmbeddingEnginestring

type EmbeddingsRequest struct {// Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings// for multiple inputs in a single request, pass an array of strings or array of token arrays.// Each input must not exceed 2048 tokens in length.Input []string `json:"input"`// ID of the model to useModelstring `json:"model"`// The request user is an optional parameter meant to be used to trace abusive requests// back to the originating user. OpenAI states:// "The [user] IDs should be a string that uniquely identifies each user. We recommend hashing// their username or email address, in order to avoid sending us any identifying information.// If you offer a preview of your product to non-logged in users, you can send a session ID// instead."Userstring `json:"user,omitempty"`}

type EmbeddingsResponse struct {Objectstring             `json:"object"`Data   []EmbeddingsResult `json:"data"`UsageEmbeddingsUsage    `json:"usage"`}

type EmbeddingsResult struct {// The type of object returned (e.g., "list", "object")Objectstring `json:"object"`// The embedding data for the inputEmbedding []float64 `json:"embedding"`Indexint       `json:"index"`}

type EmbeddingsUsage struct {// The number of tokens used by the promptPromptTokensint `json:"prompt_tokens"`// The total tokens usedTotalTokensint `json:"total_tokens"`}

type EngineObject struct {IDstring `json:"id"`Objectstring `json:"object"`Ownerstring `json:"owner"`Readybool   `json:"ready"`}

type EnginesResponse struct {Data   []EngineObject `json:"data"`Objectstring         `json:"object"`}

type Function struct {Namestring `json:"name"`Argumentsstring `json:"arguments"`}

type FunctionParameterPropertyMetadata struct {Typestring   `json:"type"`Descriptionstring   `json:"description,omitempty"`Enum        []string `json:"enum,omitempty"`}

type LogprobResult struct {Tokens        []string             `json:"tokens"`TokenLogprobs []float32            `json:"token_logprobs"`TopLogprobs   []map[string]float32 `json:"top_logprobs"`TextOffset    []int                `json:"text_offset"`}

type ModerationCategoryResult struct {Hatebool `json:"hate"`HateThreateningbool `json:"hate/threatening"`SelfHarmbool `json:"self-harm"`Sexualbool `json:"sexual"`SexualMinorsbool `json:"sexual/minors"`Violencebool `json:"violence"`ViolenceGraphicbool `json:"violence/graphic"`}

type ModerationCategoryScores struct {Hatefloat32 `json:"hate"`HateThreateningfloat32 `json:"hate/threatening"`SelfHarmfloat32 `json:"self-harm"`Sexualfloat32 `json:"sexual"`SexualMinorsfloat32 `json:"sexual/minors"`Violencefloat32 `json:"violence"`ViolenceGraphicfloat32 `json:"violence/graphic"`}

type ModerationRequest struct {// Input is the input text that should be classified. Required.Inputstring `json:"input"`// Model is the content moderation model to use. If not specified, will default to OpenAI API defaults, which is// currently "text-moderation-latest".Modelstring `json:"model,omitempty"`}

type ModerationResponse struct {IDstring             `json:"id"`Modelstring             `json:"model"`Results []ModerationResult `json:"results"`}

type ModerationResult struct {Flaggedbool                     `json:"flagged"`CategoriesModerationCategoryResult `json:"categories"`CategoryScoresModerationCategoryScores `json:"category_scores"`}

type RateLimitHeaders struct {// x-ratelimit-limit-requests: The maximum number of requests that are permitted before exhausting the rate limit.LimitRequestsint// x-ratelimit-limit-tokens: The maximum number of tokens that are permitted before exhausting the rate limit.LimitTokensint// x-ratelimit-remaining-requests: The remaining number of requests that are permitted before exhausting the rate limit.RemainingRequestsint// x-ratelimit-remaining-tokens: The remaining number of tokens that are permitted before exhausting the rate limit.RemainingTokensint// x-ratelimit-reset-requests: The time until the rate limit (based on requests) resets to its initial state.ResetRequeststime.Duration// x-ratelimit-reset-tokens: The time until the rate limit (based on tokens) resets to its initial state.ResetTokenstime.Duration}

funcNewRateLimitHeadersFromResponse¶added inv1.1.18

func NewRateLimitHeadersFromResponse(resp *http.Response)RateLimitHeaders

NewRateLimitHeadersFromResponse does a best effort to parse the rate limit information included in response headers

type SearchData struct {Documentint     `json:"document"`Objectstring  `json:"object"`Scorefloat64 `json:"score"`}

type SearchRequest struct {Documents []string `json:"documents"`Querystring   `json:"query"`}

type SearchResponse struct {Data   []SearchData `json:"data"`Objectstring       `json:"object"`}