README ¶
go-gpt3
OpenAI GPT-3 API wrapper for Go
Installation:
go get github.com/sashabaranov/go-gpt3
Example usage:
package main
import (
"context"
"fmt"
gogpt "github.com/sashabaranov/go-gpt3"
)
func main() {
c := gogpt.NewClient("your token")
ctx := context.Background()
req := gogpt.CompletionRequest{
Model: gogpt.GPT3Ada,
MaxTokens: 5,
Prompt: "Lorem ipsum",
}
resp, err := c.CreateCompletion(ctx, req)
if err != nil {
return
}
fmt.Println(resp.Choices[0].Text)
}
Streaming response example:
package main
import (
"errors"
"context"
"fmt"
"io"
gogpt "github.com/sashabaranov/go-gpt3"
)
func main() {
c := gogpt.NewClient("your token")
ctx := context.Background()
req := gogpt.CompletionRequest{
Model: gogpt.GPT3Ada,
MaxTokens: 5,
Prompt: "Lorem ipsum",
Stream: true,
}
stream, err := c.CreateCompletionStream(ctx, req)
if err != nil {
return
}
defer stream.Close()
for {
response, err := stream.Recv()
if errors.Is(err, io.EOF) {
fmt.Println("Stream finished")
return
}
if err != nil {
fmt.Printf("Stream error: %v\n", err)
return
}
fmt.Printf("Stream response: %v\n", response)
}
}
Documentation ¶
Overview ¶
common.go defines common types used throughout the OpenAI API.
Index ¶
- Constants
- Variables
- type APIError
- type AnswerRequest
- type AnswerResponse
- type Client
- func (c *Client) Answers(ctx context.Context, request AnswerRequest) (response AnswerResponse, err error)
- func (c *Client) CreateCompletion(ctx context.Context, request CompletionRequest) (response CompletionResponse, err error)
- func (c *Client) CreateCompletionStream(ctx context.Context, request CompletionRequest) (stream *CompletionStream, err error)
- func (c *Client) CreateEditImage(ctx context.Context, request ImageEditRequest) (response ImageResponse, err error)
- func (c *Client) CreateEmbeddings(ctx context.Context, request EmbeddingRequest) (resp EmbeddingResponse, err error)
- func (c *Client) CreateFile(ctx context.Context, request FileRequest) (file File, err error)
- func (c *Client) CreateImage(ctx context.Context, request ImageRequest) (response ImageResponse, err error)
- func (c *Client) DeleteFile(ctx context.Context, fileID string) (err error)
- func (c *Client) Edits(ctx context.Context, request EditsRequest) (response EditsResponse, err error)
- func (c *Client) GetEngine(ctx context.Context, engineID string) (engine Engine, err error)
- func (c *Client) GetFile(ctx context.Context, fileID string) (file File, err error)
- func (c *Client) ListEngines(ctx context.Context) (engines EnginesList, err error)
- func (c *Client) ListFiles(ctx context.Context) (files FilesList, err error)
- func (c *Client) ListModels(ctx context.Context) (models ModelsList, err error)
- func (c *Client) Moderations(ctx context.Context, request ModerationRequest) (response ModerationResponse, err error)
- type CompletionChoice
- type CompletionRequest
- type CompletionResponse
- type CompletionStream
- type EditsChoice
- type EditsRequest
- type EditsResponse
- type Embedding
- type EmbeddingModel
- type EmbeddingRequest
- type EmbeddingResponse
- type Engine
- type EnginesList
- type ErrorResponse
- type File
- type FileRequest
- type FilesList
- type ImageEditRequest
- type ImageRequest
- type ImageResponse
- type ImageResponseDataInner
- type LogprobResult
- type Model
- type ModelsList
- type ModerationRequest
- type ModerationResponse
- type Permission
- type RequestError
- type Result
- type ResultCategories
- type ResultCategoryScores
- type Usage
Constants ¶
const ( GPT3TextDavinci003 = "text-davinci-003" GPT3TextDavinci002 = "text-davinci-002" GPT3TextCurie001 = "text-curie-001" GPT3TextBabbage001 = "text-babbage-001" GPT3TextAda001 = "text-ada-001" GPT3TextDavinci001 = "text-davinci-001" GPT3DavinciInstructBeta = "davinci-instruct-beta" GPT3Davinci = "davinci" GPT3CurieInstructBeta = "curie-instruct-beta" GPT3Curie = "curie" GPT3Ada = "ada" GPT3Babbage = "babbage" )
GPT3 Defines the models provided by OpenAI to use when generating completions from OpenAI. GPT3 Models are designed for text-based tasks. For code-specific tasks, please refer to the Codex series of models.
const ( CodexCodeDavinci002 = "code-davinci-002" CodexCodeCushman001 = "code-cushman-001" CodexCodeDavinci001 = "code-davinci-001" )
Codex Defines the models provided by OpenAI. These models are designed for code-specific tasks, and use a different tokenizer which optimizes for whitespace.
const ( CreateImageSize256x256 = "256x256" CreateImageSize512x512 = "512x512" CreateImageSize1024x1024 = "1024x1024" )
Image sizes defined by the OpenAI API.
const ( CreateImageResponseFormatURL = "url" CreateImageResponseFormatB64JSON = "b64_json" )
Variables ¶
var (
ErrTooManyEmptyStreamMessages = errors.New("stream has sent too many empty messages")
)
Functions ¶
This section is empty.
Types ¶
type APIError ¶
type APIError struct { Code *string `json:"code,omitempty"` Message string `json:"message"` Param *string `json:"param,omitempty"` Type string `json:"type"` StatusCode int `json:"-"` }
APIError provides error information returned by the OpenAI API.
type AnswerRequest ¶
type AnswerRequest struct { Documents []string `json:"documents,omitempty"` File string `json:"file,omitempty"` Question string `json:"question"` SearchModel string `json:"search_model,omitempty"` Model string `json:"model"` ExamplesContext string `json:"examples_context"` Examples [][]string `json:"examples"` MaxTokens int `json:"max_tokens,omitempty"` Stop []string `json:"stop,omitempty"` Temperature *float64 `json:"temperature,omitempty"` }
type AnswerResponse ¶
type AnswerResponse struct { Answers []string `json:"answers"` Completion string `json:"completion"` Model string `json:"model"` Object string `json:"object"` SearchModel string `json:"search_model"` SelectedDocuments []struct { Document int `json:"document"` Text string `json:"text"` } `json:"selected_documents"` }
type Client ¶
type Client struct { BaseURL string HTTPClient *http.Client // contains filtered or unexported fields }
Client is OpenAI GPT-3 API client.
func NewOrgClient ¶
NewOrgClient creates new OpenAI API client for specified Organization ID.
func (*Client) Answers ¶
func (c *Client) Answers(ctx context.Context, request AnswerRequest) (response AnswerResponse, err error)
Search — perform a semantic search api call over a list of documents.
func (*Client) CreateCompletion ¶
func (c *Client) CreateCompletion( ctx context.Context, request CompletionRequest, ) (response CompletionResponse, err error)
CreateCompletion — API call to create a completion. This is the main endpoint of the API. Returns new text as well as, if requested, the probabilities over each alternative token at each position.
If using a fine-tuned model, simply provide the model's ID in the CompletionRequest object, and the server will use the model's parameters to generate the completion.
func (*Client) CreateCompletionStream ¶
func (c *Client) CreateCompletionStream( ctx context.Context, request CompletionRequest, ) (stream *CompletionStream, err error)
CreateCompletionStream — API call to create a completion w/ streaming support. It sets whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.
func (*Client) CreateEditImage ¶
func (c *Client) CreateEditImage(ctx context.Context, request ImageEditRequest) (response ImageResponse, err error)
CreateEditImage - API call to create an image. This is the main endpoint of the DALL-E API.
func (*Client) CreateEmbeddings ¶
func (c *Client) CreateEmbeddings(ctx context.Context, request EmbeddingRequest) (resp EmbeddingResponse, err error)
CreateEmbeddings returns an EmbeddingResponse which will contain an Embedding for every item in |request.Input|. https://beta.openai.com/docs/api-reference/embeddings/create
func (*Client) CreateFile ¶
CreateFile uploads a jsonl file to GPT3 FilePath can be either a local file path or a URL.
func (*Client) CreateImage ¶
func (c *Client) CreateImage(ctx context.Context, request ImageRequest) (response ImageResponse, err error)
CreateImage - API call to create an image. This is the main endpoint of the DALL-E API.
func (*Client) DeleteFile ¶
DeleteFile deletes an existing file.
func (*Client) Edits ¶
func (c *Client) Edits(ctx context.Context, request EditsRequest) (response EditsResponse, err error)
Perform an API call to the Edits endpoint.
func (*Client) GetEngine ¶
GetEngine Retrieves an engine instance, providing basic information about the engine such as the owner and availability.
func (*Client) GetFile ¶
GetFile Retrieves a file instance, providing basic information about the file such as the file name and purpose.
func (*Client) ListEngines ¶
func (c *Client) ListEngines(ctx context.Context) (engines EnginesList, err error)
ListEngines Lists the currently available engines, and provides basic information about each option such as the owner and availability.
func (*Client) ListFiles ¶
ListFiles Lists the currently available files, and provides basic information about each file such as the file name and purpose.
func (*Client) ListModels ¶
func (c *Client) ListModels(ctx context.Context) (models ModelsList, err error)
ListModels Lists the currently available models, and provides basic information about each model such as the model id and parent.
func (*Client) Moderations ¶
func (c *Client) Moderations(ctx context.Context, request ModerationRequest) (response ModerationResponse, err error)
Moderations — perform a moderation api call over a string. Input can be an array or slice but a string will reduce the complexity.
type CompletionChoice ¶
type CompletionChoice struct { Text string `json:"text"` Index int `json:"index"` FinishReason string `json:"finish_reason"` LogProbs LogprobResult `json:"logprobs"` }
CompletionChoice represents one of possible completions.
type CompletionRequest ¶
type CompletionRequest struct { Model string `json:"model"` Prompt string `json:"prompt,omitempty"` Suffix string `json:"suffix,omitempty"` MaxTokens int `json:"max_tokens,omitempty"` Temperature float32 `json:"temperature,omitempty"` TopP float32 `json:"top_p,omitempty"` N int `json:"n,omitempty"` Stream bool `json:"stream,omitempty"` LogProbs int `json:"logprobs,omitempty"` Echo bool `json:"echo,omitempty"` Stop []string `json:"stop,omitempty"` PresencePenalty float32 `json:"presence_penalty,omitempty"` FrequencyPenalty float32 `json:"frequency_penalty,omitempty"` BestOf int `json:"best_of,omitempty"` LogitBias map[string]int `json:"logit_bias,omitempty"` User string `json:"user,omitempty"` }
CompletionRequest represents a request structure for completion API.
type CompletionResponse ¶
type CompletionResponse struct { ID string `json:"id"` Object string `json:"object"` Created int64 `json:"created"` Model string `json:"model"` Choices []CompletionChoice `json:"choices"` Usage Usage `json:"usage"` }
CompletionResponse represents a response structure for completion API.
type CompletionStream ¶
type CompletionStream struct {
// contains filtered or unexported fields
}
func (*CompletionStream) Close ¶
func (stream *CompletionStream) Close()
func (*CompletionStream) Recv ¶
func (stream *CompletionStream) Recv() (response CompletionResponse, err error)
type EditsChoice ¶
EditsChoice represents one of possible edits.
type EditsRequest ¶
type EditsRequest struct { Model *string `json:"model,omitempty"` Input string `json:"input,omitempty"` Instruction string `json:"instruction,omitempty"` N int `json:"n,omitempty"` Temperature float32 `json:"temperature,omitempty"` TopP float32 `json:"top_p,omitempty"` }
EditsRequest represents a request structure for Edits API.
type EditsResponse ¶
type EditsResponse struct { Object string `json:"object"` Created int64 `json:"created"` Usage Usage `json:"usage"` Choices []EditsChoice `json:"choices"` }
EditsResponse represents a response structure for Edits API.
type Embedding ¶
type Embedding struct { Object string `json:"object"` Embedding []float64 `json:"embedding"` Index int `json:"index"` }
Embedding is a special format of data representation that can be easily utilized by machine learning models and algorithms. The embedding is an information dense representation of the semantic meaning of a piece of text. Each embedding is a vector of floating point numbers, such that the distance between two embeddings in the vector space is correlated with semantic similarity between two inputs in the original format. For example, if two texts are similar, then their vector representations should also be similar.
type EmbeddingModel ¶
type EmbeddingModel int
EmbeddingModel enumerates the models which can be used to generate Embedding vectors.
const ( Unknown EmbeddingModel = iota AdaSimilarity BabbageSimilarity CurieSimilarity DavinciSimilarity AdaSearchDocument AdaSearchQuery BabbageSearchDocument BabbageSearchQuery CurieSearchDocument CurieSearchQuery DavinciSearchDocument DavinciSearchQuery AdaCodeSearchCode AdaCodeSearchText BabbageCodeSearchCode BabbageCodeSearchText AdaEmbeddingV2 )
func (EmbeddingModel) MarshalText ¶
func (e EmbeddingModel) MarshalText() ([]byte, error)
MarshalText implements the encoding.TextMarshaler interface.
func (EmbeddingModel) String ¶
func (e EmbeddingModel) String() string
String implements the fmt.Stringer interface.
func (*EmbeddingModel) UnmarshalText ¶
func (e *EmbeddingModel) UnmarshalText(b []byte) error
UnmarshalText implements the encoding.TextUnmarshaler interface. On unrecognized value, it sets |e| to Unknown.
type EmbeddingRequest ¶
type EmbeddingRequest struct { // Input is a slice of strings for which you want to generate an Embedding vector. // Each input must not exceed 2048 tokens in length. // OpenAPI suggests replacing newlines (\n) in your input with a single space, as they // have observed inferior results when newlines are present. // E.g. // "The food was delicious and the waiter..." Input []string `json:"input"` // 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. Model EmbeddingModel `json:"model"` // A unique identifier representing your end-user, which will help OpenAI to monitor and detect abuse. User string `json:"user"` }
EmbeddingRequest is the input to a Create embeddings request.
type EmbeddingResponse ¶
type EmbeddingResponse struct { Object string `json:"object"` Data []Embedding `json:"data"` Model EmbeddingModel `json:"model"` Usage Usage `json:"usage"` }
EmbeddingResponse is the response from a Create embeddings request.
type Engine ¶
type Engine struct { ID string `json:"id"` Object string `json:"object"` Owner string `json:"owner"` Ready bool `json:"ready"` }
Engine struct represents engine from OpenAPI API.
type EnginesList ¶
type EnginesList struct {
Engines []Engine `json:"data"`
}
EnginesList is a list of engines.
type ErrorResponse ¶
type ErrorResponse struct {
Error *APIError `json:"error,omitempty"`
}
type File ¶
type File struct { Bytes int `json:"bytes"` CreatedAt int64 `json:"created_at"` ID string `json:"id"` FileName string `json:"filename"` Object string `json:"object"` Owner string `json:"owner"` Purpose string `json:"purpose"` }
File struct represents an OpenAPI file.
type FileRequest ¶
type FilesList ¶
type FilesList struct {
Files []File `json:"data"`
}
FilesList is a list of files that belong to the user or organization.
type ImageEditRequest ¶
type ImageEditRequest struct { Image *os.File `json:"image,omitempty"` Mask *os.File `json:"mask,omitempty"` Prompt string `json:"prompt,omitempty"` N int `json:"n,omitempty"` Size string `json:"size,omitempty"` }
ImageEditRequest represents the request structure for the image API.
type ImageRequest ¶
type ImageRequest struct { Prompt string `json:"prompt,omitempty"` N int `json:"n,omitempty"` Size string `json:"size,omitempty"` ResponseFormat string `json:"response_format,omitempty"` User string `json:"user,omitempty"` }
ImageRequest represents the request structure for the image API.
type ImageResponse ¶
type ImageResponse struct { Created int64 `json:"created,omitempty"` Data []ImageResponseDataInner `json:"data,omitempty"` }
ImageResponse represents a response structure for image API.
type ImageResponseDataInner ¶
type ImageResponseDataInner struct { URL string `json:"url,omitempty"` B64JSON string `json:"b64_json,omitempty"` }
ImageResponseData represents a response data structure for image API.
type LogprobResult ¶
type LogprobResult struct { Tokens []string `json:"tokens"` TokenLogprobs []float32 `json:"token_logprobs"` TopLogprobs []map[string]float32 `json:"top_logprobs"` TextOffset []int `json:"text_offset"` }
LogprobResult represents logprob result of Choice.
type Model ¶
type Model struct { CreatedAt int64 `json:"created_at"` ID string `json:"id"` Object string `json:"object"` OwnedBy string `json:"owned_by"` Permission []Permission `json:"permission"` Root string `json:"root"` Parent string `json:"parent"` }
Model struct represents an OpenAPI model.
type ModelsList ¶
type ModelsList struct {
Models []Model `json:"data"`
}
ModelsList is a list of models, including those that belong to the user or organization.
type ModerationRequest ¶
type ModerationRequest struct { Input string `json:"input,omitempty"` Model *string `json:"model,omitempty"` }
ModerationRequest represents a request structure for moderation API.
type ModerationResponse ¶
type ModerationResponse struct { ID string `json:"id"` Model string `json:"model"` Results []Result `json:"results"` }
ModerationResponse represents a response structure for moderation API.
type Permission ¶
type Permission struct { CreatedAt int64 `json:"created_at"` ID string `json:"id"` Object string `json:"object"` AllowCreateEngine bool `json:"allow_create_engine"` AllowSampling bool `json:"allow_sampling"` AllowLogprobs bool `json:"allow_logprobs"` AllowSearchIndices bool `json:"allow_search_indices"` AllowView bool `json:"allow_view"` AllowFineTuning bool `json:"allow_fine_tuning"` Organization string `json:"organization"` Group interface{} `json:"group"` IsBlocking bool `json:"is_blocking"` }
Permission struct represents an OpenAPI permission.
type RequestError ¶
RequestError provides informations about generic request errors.
func (*RequestError) Error ¶
func (e *RequestError) Error() string
func (*RequestError) Unwrap ¶
func (e *RequestError) Unwrap() error
type Result ¶
type Result struct { Categories ResultCategories `json:"categories"` CategoryScores ResultCategoryScores `json:"category_scores"` Flagged bool `json:"flagged"` }
Result represents one of possible moderation results.
type ResultCategories ¶
type ResultCategories struct { Hate bool `json:"hate"` HateThreatening bool `json:"hate/threatening"` SelfHarm bool `json:"self-harm"` Sexual bool `json:"sexual"` SexualMinors bool `json:"sexual/minors"` Violence bool `json:"violence"` ViolenceGraphic bool `json:"violence/graphic"` }
ResultCategories represents Categories of Result.
type ResultCategoryScores ¶
type ResultCategoryScores struct { Hate float32 `json:"hate"` HateThreatening float32 `json:"hate/threatening"` SelfHarm float32 `json:"self-harm"` Sexual float32 `json:"sexual"` SexualMinors float32 `json:"sexual/minors"` Violence float32 `json:"violence"` ViolenceGraphic float32 `json:"violence/graphic"` }
ResultCategoryScores represents CategoryScores of Result.