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README

Go OpenAI

Go Reference Go Report Card codecov

This library provides unofficial Go clients for OpenAI API. We support:

  • ChatGPT
  • GPT-3, GPT-4
  • DALL·E 2, DALL·E 3
  • Whisper

Installation

go get github.com/FrainL/go-openai

Currently, go-openai requires Go version 1.18 or greater.

Usage

ChatGPT example usage:
package main

import (
	"context"
	"fmt"
	openai "github.com/FrainL/go-openai"
)

func main() {
	client := openai.NewClient("your token")
	resp, err := client.CreateChatCompletion(
		context.Background(),
		openai.ChatCompletionRequest{
			Model: openai.GPT3Dot5Turbo,
			Messages: []openai.ChatCompletionMessage{
				{
					Role:    openai.ChatMessageRoleUser,
					Content: "Hello!",
				},
			},
		},
	)

	if err != nil {
		fmt.Printf("ChatCompletion error: %v\n", err)
		return
	}

	fmt.Println(resp.Choices[0].Message.Content)
}
Getting an OpenAI API Key:
  1. Visit the OpenAI website at https://platform.openai.com/account/api-keys.
  2. If you don't have an account, click on "Sign Up" to create one. If you do, click "Log In".
  3. Once logged in, navigate to your API key management page.
  4. Click on "Create new secret key".
  5. Enter a name for your new key, then click "Create secret key".
  6. Your new API key will be displayed. Use this key to interact with the OpenAI API.

Note: Your API key is sensitive information. Do not share it with anyone.

Other examples:
ChatGPT streaming completion 
package main

import (
	"context"
	"errors"
	"fmt"
	"io"
	openai "github.com/FrainL/go-openai"
)

func main() {
	c := openai.NewClient("your token")
	ctx := context.Background()

	req := openai.ChatCompletionRequest{
		Model:     openai.GPT3Dot5Turbo,
		MaxTokens: 20,
		Messages: []openai.ChatCompletionMessage{
			{
				Role:    openai.ChatMessageRoleUser,
				Content: "Lorem ipsum",
			},
		},
		Stream: true,
	}
	stream, err := c.CreateChatCompletionStream(ctx, req)
	if err != nil {
		fmt.Printf("ChatCompletionStream error: %v\n", err)
		return
	}
	defer stream.Close()

	fmt.Printf("Stream response: ")
	for {
		response, err := stream.Recv()
		if errors.Is(err, io.EOF) {
			fmt.Println("\nStream finished")
			return
		}

		if err != nil {
			fmt.Printf("\nStream error: %v\n", err)
			return
		}

		fmt.Printf(response.Choices[0].Delta.Content)
	}
}
GPT-3 completion 
package main

import (
	"context"
	"fmt"
	openai "github.com/FrainL/go-openai"
)

func main() {
	c := openai.NewClient("your token")
	ctx := context.Background()

	req := openai.CompletionRequest{
		Model:     openai.GPT3Ada,
		MaxTokens: 5,
		Prompt:    "Lorem ipsum",
	}
	resp, err := c.CreateCompletion(ctx, req)
	if err != nil {
		fmt.Printf("Completion error: %v\n", err)
		return
	}
	fmt.Println(resp.Choices[0].Text)
}
GPT-3 streaming completion 
package main

import (
	"errors"
	"context"
	"fmt"
	"io"
	openai "github.com/FrainL/go-openai"
)

func main() {
	c := openai.NewClient("your token")
	ctx := context.Background()

	req := openai.CompletionRequest{
		Model:     openai.GPT3Ada,
		MaxTokens: 5,
		Prompt:    "Lorem ipsum",
		Stream:    true,
	}
	stream, err := c.CreateCompletionStream(ctx, req)
	if err != nil {
		fmt.Printf("CompletionStream error: %v\n", err)
		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)
	}
}
Audio Speech-To-Text 
package main

import (
	"context"
	"fmt"

	openai "github.com/FrainL/go-openai"
)

func main() {
	c := openai.NewClient("your token")
	ctx := context.Background()

	req := openai.AudioRequest{
		Model:    openai.Whisper1,
		FilePath: "recording.mp3",
	}
	resp, err := c.CreateTranscription(ctx, req)
	if err != nil {
		fmt.Printf("Transcription error: %v\n", err)
		return
	}
	fmt.Println(resp.Text)
}
Audio Captions 
package main

import (
	"context"
	"fmt"
	"os"

	openai "github.com/FrainL/go-openai"
)

func main() {
	c := openai.NewClient(os.Getenv("OPENAI_KEY"))

	req := openai.AudioRequest{
		Model:    openai.Whisper1,
		FilePath: os.Args[1],
		Format:   openai.AudioResponseFormatSRT,
	}
	resp, err := c.CreateTranscription(context.Background(), req)
	if err != nil {
		fmt.Printf("Transcription error: %v\n", err)
		return
	}
	f, err := os.Create(os.Args[1] + ".srt")
	if err != nil {
		fmt.Printf("Could not open file: %v\n", err)
		return
	}
	defer f.Close()
	if _, err := f.WriteString(resp.Text); err != nil {
		fmt.Printf("Error writing to file: %v\n", err)
		return
	}
}
DALL-E 2 image generation 
package main

import (
	"bytes"
	"context"
	"encoding/base64"
	"fmt"
	openai "github.com/FrainL/go-openai"
	"image/png"
	"os"
)

func main() {
	c := openai.NewClient("your token")
	ctx := context.Background()

	// Sample image by link
	reqUrl := openai.ImageRequest{
		Prompt:         "Parrot on a skateboard performs a trick, cartoon style, natural light, high detail",
		Size:           openai.CreateImageSize256x256,
		ResponseFormat: openai.CreateImageResponseFormatURL,
		N:              1,
	}

	respUrl, err := c.CreateImage(ctx, reqUrl)
	if err != nil {
		fmt.Printf("Image creation error: %v\n", err)
		return
	}
	fmt.Println(respUrl.Data[0].URL)

	// Example image as base64
	reqBase64 := openai.ImageRequest{
		Prompt:         "Portrait of a humanoid parrot in a classic costume, high detail, realistic light, unreal engine",
		Size:           openai.CreateImageSize256x256,
		ResponseFormat: openai.CreateImageResponseFormatB64JSON,
		N:              1,
	}

	respBase64, err := c.CreateImage(ctx, reqBase64)
	if err != nil {
		fmt.Printf("Image creation error: %v\n", err)
		return
	}

	imgBytes, err := base64.StdEncoding.DecodeString(respBase64.Data[0].B64JSON)
	if err != nil {
		fmt.Printf("Base64 decode error: %v\n", err)
		return
	}

	r := bytes.NewReader(imgBytes)
	imgData, err := png.Decode(r)
	if err != nil {
		fmt.Printf("PNG decode error: %v\n", err)
		return
	}

	file, err := os.Create("example.png")
	if err != nil {
		fmt.Printf("File creation error: %v\n", err)
		return
	}
	defer file.Close()

	if err := png.Encode(file, imgData); err != nil {
		fmt.Printf("PNG encode error: %v\n", err)
		return
	}

	fmt.Println("The image was saved as example.png")
}
Configuring proxy 
config := openai.DefaultConfig("token")
proxyUrl, err := url.Parse("http://localhost:{port}")
if err != nil {
	panic(err)
}
transport := &http.Transport{
	Proxy: http.ProxyURL(proxyUrl),
}
config.HTTPClient = &http.Client{
	Transport: transport,
}

c := openai.NewClientWithConfig(config)

See also: https://pkg.go.dev/github.com/FrainL/go-openai#ClientConfig

ChatGPT support context 
package main

import (
	"bufio"
	"context"
	"fmt"
	"os"
	"strings"

	"github.com/FrainL/go-openai"
)

func main() {
	client := openai.NewClient("your token")
	messages := make([]openai.ChatCompletionMessage, 0)
	reader := bufio.NewReader(os.Stdin)
	fmt.Println("Conversation")
	fmt.Println("---------------------")

	for {
		fmt.Print("-> ")
		text, _ := reader.ReadString('\n')
		// convert CRLF to LF
		text = strings.Replace(text, "\n", "", -1)
		messages = append(messages, openai.ChatCompletionMessage{
			Role:    openai.ChatMessageRoleUser,
			Content: text,
		})

		resp, err := client.CreateChatCompletion(
			context.Background(),
			openai.ChatCompletionRequest{
				Model:    openai.GPT3Dot5Turbo,
				Messages: messages,
			},
		)

		if err != nil {
			fmt.Printf("ChatCompletion error: %v\n", err)
			continue
		}

		content := resp.Choices[0].Message.Content
		messages = append(messages, openai.ChatCompletionMessage{
			Role:    openai.ChatMessageRoleAssistant,
			Content: content,
		})
		fmt.Println(content)
	}
}
Azure OpenAI ChatGPT 
package main

import (
	"context"
	"fmt"

	openai "github.com/FrainL/go-openai"
)

func main() {
	config := openai.DefaultAzureConfig("your Azure OpenAI Key", "https://your Azure OpenAI Endpoint")
	// If you use a deployment name different from the model name, you can customize the AzureModelMapperFunc function
	// config.AzureModelMapperFunc = func(model string) string {
	// 	azureModelMapping := map[string]string{
	// 		"gpt-3.5-turbo": "your gpt-3.5-turbo deployment name",
	// 	}
	// 	return azureModelMapping[model]
	// }

	client := openai.NewClientWithConfig(config)
	resp, err := client.CreateChatCompletion(
		context.Background(),
		openai.ChatCompletionRequest{
			Model: openai.GPT3Dot5Turbo,
			Messages: []openai.ChatCompletionMessage{
				{
					Role:    openai.ChatMessageRoleUser,
					Content: "Hello Azure OpenAI!",
				},
			},
		},
	)
	if err != nil {
		fmt.Printf("ChatCompletion error: %v\n", err)
		return
	}

	fmt.Println(resp.Choices[0].Message.Content)
}
Embedding Semantic Similarity 
package main

import (
	"context"
	"log"
	openai "github.com/FrainL/go-openai"

)

func main() {
	client := openai.NewClient("your-token")

	// Create an EmbeddingRequest for the user query
	queryReq := openai.EmbeddingRequest{
		Input: []string{"How many chucks would a woodchuck chuck"},
		Model: openai.AdaEmbeddingV2,
	}

	// Create an embedding for the user query
	queryResponse, err := client.CreateEmbeddings(context.Background(), queryReq)
	if err != nil {
		log.Fatal("Error creating query embedding:", err)
	}

	// Create an EmbeddingRequest for the target text
	targetReq := openai.EmbeddingRequest{
		Input: []string{"How many chucks would a woodchuck chuck if the woodchuck could chuck wood"},
		Model: openai.AdaEmbeddingV2,
	}

	// Create an embedding for the target text
	targetResponse, err := client.CreateEmbeddings(context.Background(), targetReq)
	if err != nil {
		log.Fatal("Error creating target embedding:", err)
	}

	// Now that we have the embeddings for the user query and the target text, we
	// can calculate their similarity.
	queryEmbedding := queryResponse.Data[0]
	targetEmbedding := targetResponse.Data[0]

	similarity, err := queryEmbedding.DotProduct(&targetEmbedding)
	if err != nil {
		log.Fatal("Error calculating dot product:", err)
	}

	log.Printf("The similarity score between the query and the target is %f", similarity)
}
Azure OpenAI Embeddings 
package main

import (
	"context"
	"fmt"

	openai "github.com/FrainL/go-openai"
)

func main() {

	config := openai.DefaultAzureConfig("your Azure OpenAI Key", "https://your Azure OpenAI Endpoint")
	config.APIVersion = "2023-05-15" // optional update to latest API version

	//If you use a deployment name different from the model name, you can customize the AzureModelMapperFunc function
	//config.AzureModelMapperFunc = func(model string) string {
	//    azureModelMapping := map[string]string{
	//        "gpt-3.5-turbo":"your gpt-3.5-turbo deployment name",
	//    }
	//    return azureModelMapping[model]
	//}

	input := "Text to vectorize"

	client := openai.NewClientWithConfig(config)
	resp, err := client.CreateEmbeddings(
		context.Background(),
		openai.EmbeddingRequest{
			Input: []string{input},
			Model: openai.AdaEmbeddingV2,
		})

	if err != nil {
		fmt.Printf("CreateEmbeddings error: %v\n", err)
		return
	}

	vectors := resp.Data[0].Embedding // []float32 with 1536 dimensions

	fmt.Println(vectors[:10], "...", vectors[len(vectors)-10:])
}
JSON Schema for function calling

It is now possible for chat completion to choose to call a function for more information (see developer docs here).

In order to describe the type of functions that can be called, a JSON schema must be provided. Many JSON schema libraries exist and are more advanced than what we can offer in this library, however we have included a simple jsonschema package for those who want to use this feature without formatting their own JSON schema payload.

The developer documents give this JSON schema definition as an example:

{
  "name":"get_current_weather",
  "description":"Get the current weather in a given location",
  "parameters":{
    "type":"object",
    "properties":{
        "location":{
          "type":"string",
          "description":"The city and state, e.g. San Francisco, CA"
        },
        "unit":{
          "type":"string",
          "enum":[
              "celsius",
              "fahrenheit"
          ]
        }
    },
    "required":[
        "location"
    ]
  }
}

Using the jsonschema package, this schema could be created using structs as such:

FunctionDefinition{
  Name: "get_current_weather",
  Parameters: jsonschema.Definition{
    Type: jsonschema.Object,
    Properties: map[string]jsonschema.Definition{
      "location": {
        Type: jsonschema.String,
        Description: "The city and state, e.g. San Francisco, CA",
      },
      "unit": {
        Type: jsonschema.String,
        Enum: []string{"celsius", "fahrenheit"},
      },
    },
    Required: []string{"location"},
  },
}

The Parameters field of a FunctionDefinition can accept either of the above styles, or even a nested struct from another library (as long as it can be marshalled into JSON).

Error handling

Open-AI maintains clear documentation on how to handle API errors

example:

e := &openai.APIError{}
if errors.As(err, &e) {
  switch e.HTTPStatusCode {
    case 401:
      // invalid auth or key (do not retry)
    case 429:
      // rate limiting or engine overload (wait and retry) 
    case 500:
      // openai server error (retry)
    default:
      // unhandled
  }
}
Fine Tune Model 
package main

import (
	"context"
	"fmt"
	"github.com/FrainL/go-openai"
)

func main() {
	client := openai.NewClient("your token")
	ctx := context.Background()

	// create a .jsonl file with your training data for conversational model
	// {"prompt": "<prompt text>", "completion": "<ideal generated text>"}
	// {"prompt": "<prompt text>", "completion": "<ideal generated text>"}
	// {"prompt": "<prompt text>", "completion": "<ideal generated text>"}

	// chat models are trained using the following file format:
	// {"messages": [{"role": "system", "content": "Marv is a factual chatbot that is also sarcastic."}, {"role": "user", "content": "What's the capital of France?"}, {"role": "assistant", "content": "Paris, as if everyone doesn't know that already."}]}
	// {"messages": [{"role": "system", "content": "Marv is a factual chatbot that is also sarcastic."}, {"role": "user", "content": "Who wrote 'Romeo and Juliet'?"}, {"role": "assistant", "content": "Oh, just some guy named William Shakespeare. Ever heard of him?"}]}
	// {"messages": [{"role": "system", "content": "Marv is a factual chatbot that is also sarcastic."}, {"role": "user", "content": "How far is the Moon from Earth?"}, {"role": "assistant", "content": "Around 384,400 kilometers. Give or take a few, like that really matters."}]}

	// you can use openai cli tool to validate the data
	// For more info - https://platform.openai.com/docs/guides/fine-tuning

	file, err := client.CreateFile(ctx, openai.FileRequest{
		FilePath: "training_prepared.jsonl",
		Purpose:  "fine-tune",
	})
	if err != nil {
		fmt.Printf("Upload JSONL file error: %v\n", err)
		return
	}

	// create a fine tuning job
	// Streams events until the job is done (this often takes minutes, but can take hours if there are many jobs in the queue or your dataset is large)
	// use below get method to know the status of your model
	fineTuningJob, err := client.CreateFineTuningJob(ctx, openai.FineTuningJobRequest{
		TrainingFile: file.ID,
		Model:        "davinci-002", // gpt-3.5-turbo-0613, babbage-002.
	})
	if err != nil {
		fmt.Printf("Creating new fine tune model error: %v\n", err)
		return
	}

	fineTuningJob, err = client.RetrieveFineTuningJob(ctx, fineTuningJob.ID)
	if err != nil {
		fmt.Printf("Getting fine tune model error: %v\n", err)
		return
	}
	fmt.Println(fineTuningJob.FineTunedModel)

	// once the status of fineTuningJob is `succeeded`, you can use your fine tune model in Completion Request or Chat Completion Request

	// resp, err := client.CreateCompletion(ctx, openai.CompletionRequest{
	//	 Model:  fineTuningJob.FineTunedModel,
	//	 Prompt: "your prompt",
	// })
	// if err != nil {
	//	 fmt.Printf("Create completion error %v\n", err)
	//	 return
	// }
	//
	// fmt.Println(resp.Choices[0].Text)
}
See the `examples/` folder for more.

Frequently Asked Questions

Why don't we get the same answer when specifying a temperature field of 0 and asking the same question?

Even when specifying a temperature field of 0, it doesn't guarantee that you'll always get the same response. Several factors come into play.

  1. Go OpenAI Behavior: When you specify a temperature field of 0 in Go OpenAI, the omitempty tag causes that field to be removed from the request. Consequently, the OpenAI API applies the default value of 1.
  2. Token Count for Input/Output: If there's a large number of tokens in the input and output, setting the temperature to 0 can still result in non-deterministic behavior. In particular, when using around 32k tokens, the likelihood of non-deterministic behavior becomes highest even with a temperature of 0.

Due to the factors mentioned above, different answers may be returned even for the same question.

Workarounds:

  1. As of November 2023, use the new seed parameter in conjunction with the system_fingerprint response field, alongside Temperature management.
  2. Try using math.SmallestNonzeroFloat32: By specifying math.SmallestNonzeroFloat32 in the temperature field instead of 0, you can mimic the behavior of setting it to 0.
  3. Limiting Token Count: By limiting the number of tokens in the input and output and especially avoiding large requests close to 32k tokens, you can reduce the risk of non-deterministic behavior.

By adopting these strategies, you can expect more consistent results.

Related Issues:
omitempty option of request struct will generate incorrect request when parameter is 0.

Does Go OpenAI provide a method to count tokens?

No, Go OpenAI does not offer a feature to count tokens, and there are no plans to provide such a feature in the future. However, if there's a way to implement a token counting feature with zero dependencies, it might be possible to merge that feature into Go OpenAI. Otherwise, it would be more appropriate to implement it in a dedicated library or repository.

For counting tokens, you might find the following links helpful:

Related Issues:
Is it possible to join the implementation of GPT3 Tokenizer

Contributing

By following Contributing Guidelines, we hope to ensure that your contributions are made smoothly and efficiently.

Thank you

We want to take a moment to express our deepest gratitude to the contributors and sponsors of this project:

To all of you: thank you. You've helped us achieve more than we ever imagined possible. Can't wait to see where we go next, together!

Documentation

Overview

Example 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))
resp, err := client.CreateChatCompletion(
	context.Background(),
	openai.ChatCompletionRequest{
		Model: openai.GPT3Dot5Turbo,
		Messages: []openai.ChatCompletionMessage{
			{
				Role:    openai.ChatMessageRoleUser,
				Content: "Hello!",
			},
		},
	},
)
if err != nil {
	fmt.Printf("ChatCompletion error: %v\n", err)
	return
}

fmt.Println(resp.Choices[0].Message.Content)

Output:
Example (Chatbot) 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))

req := openai.ChatCompletionRequest{
	Model: openai.GPT3Dot5Turbo,
	Messages: []openai.ChatCompletionMessage{
		{
			Role:    openai.ChatMessageRoleSystem,
			Content: "you are a helpful chatbot",
		},
	},
}
fmt.Println("Conversation")
fmt.Println("---------------------")
fmt.Print("> ")
s := bufio.NewScanner(os.Stdin)
for s.Scan() {
	req.Messages = append(req.Messages, openai.ChatCompletionMessage{
		Role:    openai.ChatMessageRoleUser,
		Content: s.Text(),
	})
	resp, err := client.CreateChatCompletion(context.Background(), req)
	if err != nil {
		fmt.Printf("ChatCompletion error: %v\n", err)
		continue
	}
	fmt.Printf("%s\n\n", resp.Choices[0].Message.Content)
	req.Messages = append(req.Messages, resp.Choices[0].Message)
	fmt.Print("> ")
}

Output:

Index

Examples

Constants

View Source 
const (
	ChatMessageRoleSystem    = "system"
	ChatMessageRoleUser      = "user"
	ChatMessageRoleAssistant = "assistant"
	ChatMessageRoleFunction  = "function"
	ChatMessageRoleTool      = "tool"
)

Chat message role defined by the OpenAI API.

View Source 
const (
	GPT432K0613           = "gpt-4-32k-0613"
	GPT432K0314           = "gpt-4-32k-0314"
	GPT432K               = "gpt-4-32k"
	GPT40613              = "gpt-4-0613"
	GPT40314              = "gpt-4-0314"
	GPT4o                 = "gpt-4o"
	GPT4o20240513         = "gpt-4o-2024-05-13"
	GPT4o20240806         = "gpt-4o-2024-08-06"
	GPT4oMini             = "gpt-4o-mini"
	GPT4oMini20240718     = "gpt-4o-mini-2024-07-18"
	GPT4Turbo             = "gpt-4-turbo"
	GPT4Turbo20240409     = "gpt-4-turbo-2024-04-09"
	GPT4Turbo0125         = "gpt-4-0125-preview"
	GPT4Turbo1106         = "gpt-4-1106-preview"
	GPT4TurboPreview      = "gpt-4-turbo-preview"
	GPT4VisionPreview     = "gpt-4-vision-preview"
	GPT4                  = "gpt-4"
	GPT3Dot5Turbo0125     = "gpt-3.5-turbo-0125"
	GPT3Dot5Turbo1106     = "gpt-3.5-turbo-1106"
	GPT3Dot5Turbo0613     = "gpt-3.5-turbo-0613"
	GPT3Dot5Turbo0301     = "gpt-3.5-turbo-0301"
	GPT3Dot5Turbo16K      = "gpt-3.5-turbo-16k"
	GPT3Dot5Turbo16K0613  = "gpt-3.5-turbo-16k-0613"
	GPT3Dot5Turbo         = "gpt-3.5-turbo"
	GPT3Dot5TurboInstruct = "gpt-3.5-turbo-instruct"
	// Deprecated: Model is shutdown. Use gpt-3.5-turbo-instruct instead.
	GPT3TextDavinci003 = "text-davinci-003"
	// Deprecated: Model is shutdown. Use gpt-3.5-turbo-instruct instead.
	GPT3TextDavinci002 = "text-davinci-002"
	// Deprecated: Model is shutdown. Use gpt-3.5-turbo-instruct instead.
	GPT3TextCurie001 = "text-curie-001"
	// Deprecated: Model is shutdown. Use gpt-3.5-turbo-instruct instead.
	GPT3TextBabbage001 = "text-babbage-001"
	// Deprecated: Model is shutdown. Use gpt-3.5-turbo-instruct instead.
	GPT3TextAda001 = "text-ada-001"
	// Deprecated: Model is shutdown. Use gpt-3.5-turbo-instruct instead.
	GPT3TextDavinci001 = "text-davinci-001"
	// Deprecated: Model is shutdown. Use gpt-3.5-turbo-instruct instead.
	GPT3DavinciInstructBeta = "davinci-instruct-beta"
	// Deprecated: Model is shutdown. Use davinci-002 instead.
	GPT3Davinci    = "davinci"
	GPT3Davinci002 = "davinci-002"
	// Deprecated: Model is shutdown. Use gpt-3.5-turbo-instruct instead.
	GPT3CurieInstructBeta = "curie-instruct-beta"
	GPT3Curie             = "curie"
	GPT3Curie002          = "curie-002"
	// Deprecated: Model is shutdown. Use babbage-002 instead.
	GPT3Ada    = "ada"
	GPT3Ada002 = "ada-002"
	// Deprecated: Model is shutdown. Use babbage-002 instead.
	GPT3Babbage    = "babbage"
	GPT3Babbage002 = "babbage-002"
)

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.

View Source 
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.

View Source 
const (
	CreateImageSize256x256   = "256x256"
	CreateImageSize512x512   = "512x512"
	CreateImageSize1024x1024 = "1024x1024"
	// dall-e-3 supported only.
	CreateImageSize1792x1024 = "1792x1024"
	CreateImageSize1024x1792 = "1024x1792"
)

Image sizes defined by the OpenAI API.

View Source 
const (
	CreateImageResponseFormatURL     = "url"
	CreateImageResponseFormatB64JSON = "b64_json"
)
View Source 
const (
	CreateImageModelDallE2 = "dall-e-2"
	CreateImageModelDallE3 = "dall-e-3"
)
View Source 
const (
	CreateImageQualityHD       = "hd"
	CreateImageQualityStandard = "standard"
)
View Source 
const (
	CreateImageStyleVivid   = "vivid"
	CreateImageStyleNatural = "natural"
)
View Source 
const (
	ModerationTextStable = "text-moderation-stable"
	ModerationTextLatest = "text-moderation-latest"
	// Deprecated: use ModerationTextStable and ModerationTextLatest instead.
	ModerationText001 = "text-moderation-001"
)

The default is text-moderation-latest which will be automatically upgraded over time. This ensures you are always using our most accurate model. If you use text-moderation-stable, we will provide advanced notice before updating the model. Accuracy of text-moderation-stable may be slightly lower than for text-moderation-latest.

View Source 
const (
	// TruncationStrategyAuto messages in the middle of the thread will be dropped to fit the context length of the model.
	TruncationStrategyAuto = TruncationStrategy("auto")
	// TruncationStrategyLastMessages the thread will be truncated to the n most recent messages in the thread.
	TruncationStrategyLastMessages = TruncationStrategy("last_messages")
)
View Source 
const AzureAPIKeyHeader = "api-key"
View Source 
const (
	Whisper1 = "whisper-1"
)

Whisper Defines the models provided by OpenAI to use when processing audio with OpenAI.

Variables

View Source 
var (
	ErrChatCompletionInvalidModel       = errors.New("this model is not supported with this method, please use CreateCompletion client method instead") //nolint:lll
	ErrChatCompletionStreamNotSupported = errors.New("streaming is not supported with this method, please use CreateChatCompletionStream")              //nolint:lll
	ErrContentFieldsMisused             = errors.New("can't use both Content and MultiContent properties simultaneously")
)
View Source 
var (
	ErrCompletionUnsupportedModel              = errors.New("this model is not supported with this method, please use CreateChatCompletion client method instead") //nolint:lll
	ErrCompletionStreamNotSupported            = errors.New("streaming is not supported with this method, please use CreateCompletionStream")                      //nolint:lll
	ErrCompletionRequestPromptTypeNotSupported = errors.New("the type of CompletionRequest.Prompt only supports string and []string")                              //nolint:lll
)
View Source 
var (
	ErrModerationInvalidModel = errors.New("this model is not supported with moderation, please use text-moderation-stable or text-moderation-latest instead") //nolint:lll
)
View Source 
var (
	ErrTooManyEmptyStreamMessages = errors.New("stream has sent too many empty messages")
)
View Source 
var ErrVectorLengthMismatch = errors.New("vector length mismatch")

Functions

This section is empty.

Types

type APIError 

type APIError struct {
	Code           any         `json:"code,omitempty"`
	Message        string      `json:"message"`
	Param          *string     `json:"param,omitempty"`
	Type           string      `json:"type"`
	HTTPStatusCode int         `json:"-"`
	InnerError     *InnerError `json:"innererror,omitempty"`
}

APIError provides error information returned by the OpenAI API. InnerError struct is only valid for Azure OpenAI Service.

Example

Open-AI maintains clear documentation on how to handle API errors.

see: https://platform.openai.com/docs/guides/error-codes/api-errors 

var err error // Assume this is the error you are checking.
e := &openai.APIError{}
if errors.As(err, &e) {
	switch e.HTTPStatusCode {
	case 401:
	// invalid auth or key (do not retry)
	case 429:
	// rate limiting or engine overload (wait and retry)
	case 500:
	// openai server error (retry)
	default:
		// unhandled
	}
}

Output:

func (*APIError) Error 

func (e *APIError) Error() string

func (*APIError) UnmarshalJSON 

func (e *APIError) UnmarshalJSON(data []byte) (err error)

type APIType 

type APIType string
const (
	APITypeOpenAI          APIType = "OPEN_AI"
	APITypeAzure           APIType = "AZURE"
	APITypeAzureAD         APIType = "AZURE_AD"
	APITypeCloudflareAzure APIType = "CLOUDFLARE_AZURE"
)

type Assistant 

type Assistant struct {
	ID            string                 `json:"id"`
	Object        string                 `json:"object"`
	CreatedAt     int64                  `json:"created_at"`
	Name          *string                `json:"name,omitempty"`
	Description   *string                `json:"description,omitempty"`
	Model         string                 `json:"model"`
	Instructions  *string                `json:"instructions,omitempty"`
	Tools         []AssistantTool        `json:"tools"`
	FileIDs       []string               `json:"file_ids,omitempty"`
	Metadata      map[string]any         `json:"metadata,omitempty"`
	ToolResources *AssistantToolResource `json:"tool_resources,omitempty"`
	// contains filtered or unexported fields
}

func (*Assistant) GetRateLimitHeaders 

func (h *Assistant) GetRateLimitHeaders() RateLimitHeaders

func (*Assistant) Header 

func (h *Assistant) Header() http.Header

func (*Assistant) SetHeader 

func (h *Assistant) SetHeader(header http.Header)

type AssistantDeleteResponse 

type AssistantDeleteResponse struct {
	ID      string `json:"id"`
	Object  string `json:"object"`
	Deleted bool   `json:"deleted"`
	// contains filtered or unexported fields
}

func (*AssistantDeleteResponse) GetRateLimitHeaders 

func (h *AssistantDeleteResponse) GetRateLimitHeaders() RateLimitHeaders

func (*AssistantDeleteResponse) Header 

func (h *AssistantDeleteResponse) Header() http.Header

func (*AssistantDeleteResponse) SetHeader 

func (h *AssistantDeleteResponse) SetHeader(header http.Header)

type AssistantFile 

type AssistantFile struct {
	ID          string `json:"id"`
	Object      string `json:"object"`
	CreatedAt   int64  `json:"created_at"`
	AssistantID string `json:"assistant_id"`
	// contains filtered or unexported fields
}

func (*AssistantFile) GetRateLimitHeaders 

func (h *AssistantFile) GetRateLimitHeaders() RateLimitHeaders

func (*AssistantFile) Header 

func (h *AssistantFile) Header() http.Header

func (*AssistantFile) SetHeader 

func (h *AssistantFile) SetHeader(header http.Header)

type AssistantFileRequest 

type AssistantFileRequest struct {
	FileID string `json:"file_id"`
}

type AssistantFilesList 

type AssistantFilesList struct {
	AssistantFiles []AssistantFile `json:"data"`
	// contains filtered or unexported fields
}

func (*AssistantFilesList) GetRateLimitHeaders 

func (h *AssistantFilesList) GetRateLimitHeaders() RateLimitHeaders

func (*AssistantFilesList) Header 

func (h *AssistantFilesList) Header() http.Header

func (*AssistantFilesList) SetHeader 

func (h *AssistantFilesList) SetHeader(header http.Header)

type AssistantRequest 

type AssistantRequest struct {
	Model          string                 `json:"model"`
	Name           *string                `json:"name,omitempty"`
	Description    *string                `json:"description,omitempty"`
	Instructions   *string                `json:"instructions,omitempty"`
	Tools          []AssistantTool        `json:"-"`
	FileIDs        []string               `json:"file_ids,omitempty"`
	Metadata       map[string]any         `json:"metadata,omitempty"`
	ToolResources  *AssistantToolResource `json:"tool_resources,omitempty"`
	ResponseFormat any                    `json:"response_format,omitempty"`
	Temperature    *float32               `json:"temperature,omitempty"`
	TopP           *float32               `json:"top_p,omitempty"`
}

AssistantRequest provides the assistant request parameters. When modifying the tools the API functions as the following: If Tools is undefined, no changes are made to the Assistant's tools. If Tools is empty slice it will effectively delete all of the Assistant's tools. If Tools is populated, it will replace all of the existing Assistant's tools with the provided tools.

func (AssistantRequest) MarshalJSON 

func (a AssistantRequest) MarshalJSON() ([]byte, error)

MarshalJSON provides a custom marshaller for the assistant request to handle the API use cases If Tools is nil, the field is omitted from the JSON. If Tools is an empty slice, it's included in the JSON as an empty array ([]). If Tools is populated, it's included in the JSON with the elements.

type AssistantTool 

type AssistantTool struct {
	Type     AssistantToolType   `json:"type"`
	Function *FunctionDefinition `json:"function,omitempty"`
}

type AssistantToolCodeInterpreter 

type AssistantToolCodeInterpreter struct {
	FileIDs []string `json:"file_ids"`
}

type AssistantToolFileSearch 

type AssistantToolFileSearch struct {
	VectorStoreIDs []string `json:"vector_store_ids"`
}

type AssistantToolResource 

type AssistantToolResource struct {
	FileSearch      *AssistantToolFileSearch      `json:"file_search,omitempty"`
	CodeInterpreter *AssistantToolCodeInterpreter `json:"code_interpreter,omitempty"`
}

type AssistantToolType 

type AssistantToolType string
const (
	AssistantToolTypeCodeInterpreter AssistantToolType = "code_interpreter"
	AssistantToolTypeRetrieval       AssistantToolType = "retrieval"
	AssistantToolTypeFunction        AssistantToolType = "function"
	AssistantToolTypeFileSearch      AssistantToolType = "file_search"
)

type AssistantsList 

type AssistantsList struct {
	Assistants []Assistant `json:"data"`
	LastID     *string     `json:"last_id"`
	FirstID    *string     `json:"first_id"`
	HasMore    bool        `json:"has_more"`
	// contains filtered or unexported fields
}

AssistantsList is a list of assistants.

func (*AssistantsList) GetRateLimitHeaders 

func (h *AssistantsList) GetRateLimitHeaders() RateLimitHeaders

func (*AssistantsList) Header 

func (h *AssistantsList) Header() http.Header

func (*AssistantsList) SetHeader 

func (h *AssistantsList) SetHeader(header http.Header)

type AudioRequest 

type AudioRequest struct {
	Model string

	// FilePath is either an existing file in your filesystem or a filename representing the contents of Reader.
	FilePath string

	// Reader is an optional io.Reader when you do not want to use an existing file.
	Reader io.Reader

	Prompt                 string
	Temperature            float32
	Language               string // Only for transcription.
	Format                 AudioResponseFormat
	TimestampGranularities []TranscriptionTimestampGranularity // Only for transcription.
}

AudioRequest represents a request structure for audio API.

func (AudioRequest) HasJSONResponse 

func (r AudioRequest) HasJSONResponse() bool

HasJSONResponse returns true if the response format is JSON.

type AudioResponse 

type AudioResponse struct {
	Task     string  `json:"task"`
	Language string  `json:"language"`
	Duration float64 `json:"duration"`
	Segments []struct {
		ID               int     `json:"id"`
		Seek             int     `json:"seek"`
		Start            float64 `json:"start"`
		End              float64 `json:"end"`
		Text             string  `json:"text"`
		Tokens           []int   `json:"tokens"`
		Temperature      float64 `json:"temperature"`
		AvgLogprob       float64 `json:"avg_logprob"`
		CompressionRatio float64 `json:"compression_ratio"`
		NoSpeechProb     float64 `json:"no_speech_prob"`
		Transient        bool    `json:"transient"`
	} `json:"segments"`
	Words []struct {
		Word  string  `json:"word"`
		Start float64 `json:"start"`
		End   float64 `json:"end"`
	} `json:"words"`
	Text string `json:"text"`
	// contains filtered or unexported fields
}

AudioResponse represents a response structure for audio API.

func (*AudioResponse) GetRateLimitHeaders 

func (h *AudioResponse) GetRateLimitHeaders() RateLimitHeaders

func (*AudioResponse) Header 

func (h *AudioResponse) Header() http.Header

func (*AudioResponse) SetHeader 

func (h *AudioResponse) SetHeader(header http.Header)

type AudioResponseFormat 

type AudioResponseFormat string

Response formats; Whisper uses AudioResponseFormatJSON by default. 

const (
	AudioResponseFormatJSON        AudioResponseFormat = "json"
	AudioResponseFormatText        AudioResponseFormat = "text"
	AudioResponseFormatSRT         AudioResponseFormat = "srt"
	AudioResponseFormatVerboseJSON AudioResponseFormat = "verbose_json"
	AudioResponseFormatVTT         AudioResponseFormat = "vtt"
)

type Base64Embedding 

type Base64Embedding struct {
	Object    string       `json:"object"`
	Embedding base64String `json:"embedding"`
	Index     int          `json:"index"`
}

Base64Embedding is a container for base64 encoded embeddings.

type Batch 

type Batch struct {
	ID       string        `json:"id"`
	Object   string        `json:"object"`
	Endpoint BatchEndpoint `json:"endpoint"`
	Errors   *struct {
		Object string `json:"object,omitempty"`
		Data   []struct {
			Code    string  `json:"code,omitempty"`
			Message string  `json:"message,omitempty"`
			Param   *string `json:"param,omitempty"`
			Line    *int    `json:"line,omitempty"`
		} `json:"data"`
	} `json:"errors"`
	InputFileID      string             `json:"input_file_id"`
	CompletionWindow string             `json:"completion_window"`
	Status           string             `json:"status"`
	OutputFileID     *string            `json:"output_file_id"`
	ErrorFileID      *string            `json:"error_file_id"`
	CreatedAt        int                `json:"created_at"`
	InProgressAt     *int               `json:"in_progress_at"`
	ExpiresAt        *int               `json:"expires_at"`
	FinalizingAt     *int               `json:"finalizing_at"`
	CompletedAt      *int               `json:"completed_at"`
	FailedAt         *int               `json:"failed_at"`
	ExpiredAt        *int               `json:"expired_at"`
	CancellingAt     *int               `json:"cancelling_at"`
	CancelledAt      *int               `json:"cancelled_at"`
	RequestCounts    BatchRequestCounts `json:"request_counts"`
	Metadata         map[string]any     `json:"metadata"`
}

type BatchChatCompletionRequest 

type BatchChatCompletionRequest struct {
	CustomID string                `json:"custom_id"`
	Body     ChatCompletionRequest `json:"body"`
	Method   string                `json:"method"`
	URL      BatchEndpoint         `json:"url"`
}

func (BatchChatCompletionRequest) MarshalBatchLineItem 

func (r BatchChatCompletionRequest) MarshalBatchLineItem() []byte

type BatchCompletionRequest 

type BatchCompletionRequest struct {
	CustomID string            `json:"custom_id"`
	Body     CompletionRequest `json:"body"`
	Method   string            `json:"method"`
	URL      BatchEndpoint     `json:"url"`
}

func (BatchCompletionRequest) MarshalBatchLineItem 

func (r BatchCompletionRequest) MarshalBatchLineItem() []byte

type BatchEmbeddingRequest 

type BatchEmbeddingRequest struct {
	CustomID string           `json:"custom_id"`
	Body     EmbeddingRequest `json:"body"`
	Method   string           `json:"method"`
	URL      BatchEndpoint    `json:"url"`
}

func (BatchEmbeddingRequest) MarshalBatchLineItem 

func (r BatchEmbeddingRequest) MarshalBatchLineItem() []byte

type BatchEndpoint 

type BatchEndpoint string
const (
	BatchEndpointChatCompletions BatchEndpoint = "/v1/chat/completions"
	BatchEndpointCompletions     BatchEndpoint = "/v1/completions"
	BatchEndpointEmbeddings      BatchEndpoint = "/v1/embeddings"
)

type BatchLineItem 

type BatchLineItem interface {
	MarshalBatchLineItem() []byte
}

type BatchRequestCounts 

type BatchRequestCounts struct {
	Total     int `json:"total"`
	Completed int `json:"completed"`
	Failed    int `json:"failed"`
}

type BatchResponse 

type BatchResponse struct {
	Batch
	// contains filtered or unexported fields
}

func (*BatchResponse) GetRateLimitHeaders 

func (h *BatchResponse) GetRateLimitHeaders() RateLimitHeaders

func (*BatchResponse) Header 

func (h *BatchResponse) Header() http.Header

func (*BatchResponse) SetHeader 

func (h *BatchResponse) SetHeader(header http.Header)

type ChatCompletionChoice 

type ChatCompletionChoice struct {
	Index   int                   `json:"index"`
	Message ChatCompletionMessage `json:"message"`
	// FinishReason
	// stop: API returned complete message,
	// or a message terminated by one of the stop sequences provided via the stop parameter
	// length: Incomplete model output due to max_tokens parameter or token limit
	// function_call: The model decided to call a function
	// content_filter: Omitted content due to a flag from our content filters
	// null: API response still in progress or incomplete
	FinishReason FinishReason `json:"finish_reason"`
	LogProbs     *LogProbs    `json:"logprobs,omitempty"`
}

type ChatCompletionMessage 

type ChatCompletionMessage struct {
	Role         string `json:"role"`
	Content      string `json:"content"`
	MultiContent []ChatMessagePart

	// This property isn't in the official documentation, but it's in
	// the documentation for the official library for python:
	// - https://github.com/openai/openai-python/blob/main/chatml.md
	// - https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
	Name string `json:"name,omitempty"`

	FunctionCall *FunctionCall `json:"function_call,omitempty"`

	// For Role=assistant prompts this may be set to the tool calls generated by the model, such as function calls.
	ToolCalls []ToolCall `json:"tool_calls,omitempty"`

	// For Role=tool prompts this should be set to the ID given in the assistant's prior request to call a tool.
	ToolCallID string `json:"tool_call_id,omitempty"`
}

func (ChatCompletionMessage) MarshalJSON 

func (m ChatCompletionMessage) MarshalJSON() ([]byte, error)

func (*ChatCompletionMessage) UnmarshalJSON 

func (m *ChatCompletionMessage) UnmarshalJSON(bs []byte) error

type ChatCompletionRequest 

type ChatCompletionRequest struct {
	Model            string                        `json:"model"`
	Messages         []ChatCompletionMessage       `json:"messages"`
	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"`
	Stop             []string                      `json:"stop,omitempty"`
	PresencePenalty  float32                       `json:"presence_penalty,omitempty"`
	ResponseFormat   *ChatCompletionResponseFormat `json:"response_format,omitempty"`
	Seed             *int                          `json:"seed,omitempty"`
	FrequencyPenalty float32                       `json:"frequency_penalty,omitempty"`
	// LogitBias is must be a token id string (specified by their token ID in the tokenizer), not a word string.
	// incorrect: `"logit_bias":{"You": 6}`, correct: `"logit_bias":{"1639": 6}`
	// refs: https://platform.openai.com/docs/api-reference/chat/create#chat/create-logit_bias
	LogitBias map[string]int `json:"logit_bias,omitempty"`
	// LogProbs indicates whether to return log probabilities of the output tokens or not.
	// If true, returns the log probabilities of each output token returned in the content of message.
	// This option is currently not available on the gpt-4-vision-preview model.
	LogProbs bool `json:"logprobs,omitempty"`
	// TopLogProbs is an integer between 0 and 5 specifying the number of most likely tokens to return at each
	// token position, each with an associated log probability.
	// logprobs must be set to true if this parameter is used.
	TopLogProbs int    `json:"top_logprobs,omitempty"`
	User        string `json:"user,omitempty"`
	// Deprecated: use Tools instead.
	Functions []FunctionDefinition `json:"functions,omitempty"`
	// Deprecated: use ToolChoice instead.
	FunctionCall any    `json:"function_call,omitempty"`
	Tools        []Tool `json:"tools,omitempty"`
	// This can be either a string or an ToolChoice object.
	ToolChoice any `json:"tool_choice,omitempty"`
	// Options for streaming response. Only set this when you set stream: true.
	StreamOptions *StreamOptions `json:"stream_options,omitempty"`
	// Disable the default behavior of parallel tool calls by setting it: false.
	ParallelToolCalls any `json:"parallel_tool_calls,omitempty"`
}

ChatCompletionRequest represents a request structure for chat completion API.

type ChatCompletionResponse 

type ChatCompletionResponse struct {
	ID                string                 `json:"id"`
	Object            string                 `json:"object"`
	Created           int64                  `json:"created"`
	Model             string                 `json:"model"`
	Choices           []ChatCompletionChoice `json:"choices"`
	Usage             Usage                  `json:"usage"`
	SystemFingerprint string                 `json:"system_fingerprint"`
	// contains filtered or unexported fields
}

ChatCompletionResponse represents a response structure for chat completion API.

func (*ChatCompletionResponse) GetRateLimitHeaders 

func (h *ChatCompletionResponse) GetRateLimitHeaders() RateLimitHeaders

func (*ChatCompletionResponse) Header 

func (h *ChatCompletionResponse) Header() http.Header

func (*ChatCompletionResponse) SetHeader 

func (h *ChatCompletionResponse) SetHeader(header http.Header)

type ChatCompletionResponseFormat 

type ChatCompletionResponseFormat struct {
	Type       ChatCompletionResponseFormatType        `json:"type,omitempty"`
	JSONSchema *ChatCompletionResponseFormatJSONSchema `json:"json_schema,omitempty"`
}

type ChatCompletionResponseFormatJSONSchema 

type ChatCompletionResponseFormatJSONSchema struct {
	Name        string                `json:"name"`
	Description string                `json:"description,omitempty"`
	Schema      jsonschema.Definition `json:"schema"`
	Strict      bool                  `json:"strict"`
}

type ChatCompletionResponseFormatType 

type ChatCompletionResponseFormatType string
const (
	ChatCompletionResponseFormatTypeJSONObject ChatCompletionResponseFormatType = "json_object"
	ChatCompletionResponseFormatTypeJSONSchema ChatCompletionResponseFormatType = "json_schema"
	ChatCompletionResponseFormatTypeText       ChatCompletionResponseFormatType = "text"
)

type ChatCompletionStream 

type ChatCompletionStream struct {
	// contains filtered or unexported fields
}

ChatCompletionStream Note: Perhaps it is more elegant to abstract Stream using generics.

func (ChatCompletionStream) Close 

func (stream ChatCompletionStream) Close() error

func (ChatCompletionStream) Recv 

func (stream ChatCompletionStream) Recv() (response T, err error)

type ChatCompletionStreamChoice 

type ChatCompletionStreamChoice struct {
	Index                int                             `json:"index"`
	Delta                ChatCompletionStreamChoiceDelta `json:"delta"`
	FinishReason         FinishReason                    `json:"finish_reason"`
	ContentFilterResults ContentFilterResults            `json:"content_filter_results,omitempty"`
}

type ChatCompletionStreamChoiceDelta 

type ChatCompletionStreamChoiceDelta struct {
	Content      string        `json:"content,omitempty"`
	Role         string        `json:"role,omitempty"`
	FunctionCall *FunctionCall `json:"function_call,omitempty"`
	ToolCalls    []ToolCall    `json:"tool_calls,omitempty"`
}

type ChatCompletionStreamResponse 

type ChatCompletionStreamResponse struct {
	ID                  string                       `json:"id"`
	Object              string                       `json:"object"`
	Created             int64                        `json:"created"`
	Model               string                       `json:"model"`
	Choices             []ChatCompletionStreamChoice `json:"choices"`
	SystemFingerprint   string                       `json:"system_fingerprint"`
	PromptAnnotations   []PromptAnnotation           `json:"prompt_annotations,omitempty"`
	PromptFilterResults []PromptFilterResult         `json:"prompt_filter_results,omitempty"`
	// An optional field that will only be present when you set stream_options: {"include_usage": true} in your request.
	// When present, it contains a null value except for the last chunk which contains the token usage statistics
	// for the entire request.
	Usage *Usage `json:"usage,omitempty"`
}

type ChatMessageImageURL 

type ChatMessageImageURL struct {
	URL    string         `json:"url,omitempty"`
	Detail ImageURLDetail `json:"detail,omitempty"`
}

type ChatMessagePart 

type ChatMessagePart struct {
	Type     ChatMessagePartType  `json:"type,omitempty"`
	Text     string               `json:"text,omitempty"`
	ImageURL *ChatMessageImageURL `json:"image_url,omitempty"`
}

type ChatMessagePartType 

type ChatMessagePartType string
const (
	ChatMessagePartTypeText     ChatMessagePartType = "text"
	ChatMessagePartTypeImageURL ChatMessagePartType = "image_url"
)

type ChunkingStrategy 

type ChunkingStrategy struct {
	Type   ChunkingStrategyType    `json:"type"`
	Static *StaticChunkingStrategy `json:"static,omitempty"`
}

type ChunkingStrategyType 

type ChunkingStrategyType string
const (
	ChunkingStrategyTypeAuto   ChunkingStrategyType = "auto"
	ChunkingStrategyTypeStatic ChunkingStrategyType = "static"
)

type Client 

type Client struct {
	// contains filtered or unexported fields
}

Client is OpenAI GPT-3 API client.

func NewClient 

func NewClient(authToken string) *Client

NewClient creates new OpenAI API client.

func NewClientWithConfig 

func NewClientWithConfig(config ClientConfig) *Client

NewClientWithConfig creates new OpenAI API client for specified config.

func NewOrgClient deprecated 

func NewOrgClient(authToken, org string) *Client

NewOrgClient creates new OpenAI API client for specified Organization ID.

Deprecated: Please use NewClientWithConfig.

func (*Client) CancelBatch 

func (c *Client) CancelBatch(
	ctx context.Context,
	batchID string,
) (response BatchResponse, err error)

CancelBatch — API call to Cancel batch.

func (*Client) CancelFineTune 

func (c *Client) CancelFineTune(ctx context.Context, fineTuneID string) (response FineTune, err error)

CancelFineTune cancel a fine-tune job. Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*Client) CancelFineTuningJob 

func (c *Client) CancelFineTuningJob(ctx context.Context, fineTuningJobID string) (response FineTuningJob, err error)

CancelFineTuningJob cancel a fine tuning job.

func (*Client) CancelRun 

func (c *Client) CancelRun(
	ctx context.Context,
	threadID string,
	runID string) (response Run, err error)

CancelRun cancels a run.

func (*Client) CancelVectorStoreFileBatch 

func (c *Client) CancelVectorStoreFileBatch(
	ctx context.Context,
	vectorStoreID string,
	batchID string,
) (response VectorStoreFileBatch, err error)

CancelVectorStoreFileBatch cancel a new vector store file batch.

func (*Client) CreateAssistant 

func (c *Client) CreateAssistant(ctx context.Context, request AssistantRequest) (response Assistant, err error)

CreateAssistant creates a new assistant.

func (*Client) CreateAssistantFile 

func (c *Client) CreateAssistantFile(
	ctx context.Context,
	assistantID string,
	request AssistantFileRequest,
) (response AssistantFile, err error)

CreateAssistantFile creates a new assistant file.

func (*Client) CreateBatch 

func (c *Client) CreateBatch(
	ctx context.Context,
	request CreateBatchRequest,
) (response BatchResponse, err error)

CreateBatch — API call to Create batch.

func (*Client) CreateBatchWithUploadFile 

func (c *Client) CreateBatchWithUploadFile(
	ctx context.Context,
	request CreateBatchWithUploadFileRequest,
) (response BatchResponse, err error)

CreateBatchWithUploadFile — API call to Create batch with upload file.

func (*Client) CreateChatCompletion 

func (c *Client) CreateChatCompletion(
	ctx context.Context,
	request ChatCompletionRequest,
) (response ChatCompletionResponse, err error)

CreateChatCompletion — API call to Create a completion for the chat message.

func (*Client) CreateChatCompletionStream 

func (c *Client) CreateChatCompletionStream(
	ctx context.Context,
	request ChatCompletionRequest,
) (stream *ChatCompletionStream, err error)

CreateChatCompletionStream — API call to create a chat 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.

Example 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))

stream, err := client.CreateChatCompletionStream(
	context.Background(),
	openai.ChatCompletionRequest{
		Model:     openai.GPT3Dot5Turbo,
		MaxTokens: 20,
		Messages: []openai.ChatCompletionMessage{
			{
				Role:    openai.ChatMessageRoleUser,
				Content: "Lorem ipsum",
			},
		},
		Stream: true,
	},
)
if err != nil {
	fmt.Printf("ChatCompletionStream error: %v\n", err)
	return
}
defer stream.Close()

fmt.Printf("Stream response: ")
for {
	var response openai.ChatCompletionStreamResponse
	response, err = stream.Recv()
	if errors.Is(err, io.EOF) {
		fmt.Println("\nStream finished")
		return
	}

	if err != nil {
		fmt.Printf("\nStream error: %v\n", err)
		return
	}

	fmt.Printf(response.Choices[0].Delta.Content)
}

Output:

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.

Example 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))
resp, err := client.CreateCompletion(
	context.Background(),
	openai.CompletionRequest{
		Model:     openai.GPT3Ada,
		MaxTokens: 5,
		Prompt:    "Lorem ipsum",
	},
)
if err != nil {
	fmt.Printf("Completion error: %v\n", err)
	return
}
fmt.Println(resp.Choices[0].Text)

Output:

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.

Example 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))
stream, err := client.CreateCompletionStream(
	context.Background(),
	openai.CompletionRequest{
		Model:     openai.GPT3Ada,
		MaxTokens: 5,
		Prompt:    "Lorem ipsum",
		Stream:    true,
	},
)
if err != nil {
	fmt.Printf("CompletionStream error: %v\n", err)
	return
}
defer stream.Close()

for {
	var response openai.CompletionResponse
	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)
}

Output:

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,
	conv EmbeddingRequestConverter,
) (res EmbeddingResponse, err error)

CreateEmbeddings returns an EmbeddingResponse which will contain an Embedding for every item in |body.Input|. https://beta.openai.com/docs/api-reference/embeddings/create

Body should be of type EmbeddingRequestStrings for embedding strings or EmbeddingRequestTokens for embedding groups of text already converted to tokens.

func (*Client) CreateFile 

func (c *Client) CreateFile(ctx context.Context, request FileRequest) (file File, err error)

CreateFile uploads a jsonl file to GPT3 FilePath must be a local file path.

func (*Client) CreateFileBytes 

func (c *Client) CreateFileBytes(ctx context.Context, request FileBytesRequest) (file File, err error)

CreateFileBytes uploads bytes directly to OpenAI without requiring a local file.

func (*Client) CreateFineTune deprecated 

func (c *Client) CreateFineTune(ctx context.Context, request FineTuneRequest) (response FineTune, err error)

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*Client) CreateFineTuningJob 

func (c *Client) CreateFineTuningJob(
	ctx context.Context,
	request FineTuningJobRequest,
) (response FineTuningJob, err error)

CreateFineTuningJob create a fine tuning job.

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.

Example 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))

respURL, err := client.CreateImage(
	context.Background(),
	openai.ImageRequest{
		Prompt:         "Parrot on a skateboard performs a trick, cartoon style, natural light, high detail",
		Size:           openai.CreateImageSize256x256,
		ResponseFormat: openai.CreateImageResponseFormatURL,
		N:              1,
	},
)
if err != nil {
	fmt.Printf("Image creation error: %v\n", err)
	return
}
fmt.Println(respURL.Data[0].URL)

Output:
Example (Base64) 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))

resp, err := client.CreateImage(
	context.Background(),
	openai.ImageRequest{
		Prompt:         "Portrait of a humanoid parrot in a classic costume, high detail, realistic light, unreal engine",
		Size:           openai.CreateImageSize512x512,
		ResponseFormat: openai.CreateImageResponseFormatB64JSON,
		N:              1,
	},
)
if err != nil {
	fmt.Printf("Image creation error: %v\n", err)
	return
}

b, err := base64.StdEncoding.DecodeString(resp.Data[0].B64JSON)
if err != nil {
	fmt.Printf("Base64 decode error: %v\n", err)
	return
}

f, err := os.Create("example.png")
if err != nil {
	fmt.Printf("File creation error: %v\n", err)
	return
}
defer f.Close()

_, err = f.Write(b)
if err != nil {
	fmt.Printf("File write error: %v\n", err)
	return
}

fmt.Println("The image was saved as example.png")

Output:

func (*Client) CreateMessage 

func (c *Client) CreateMessage(ctx context.Context, threadID string, request MessageRequest) (msg Message, err error)

CreateMessage creates a new message.

func (*Client) CreateRun 

func (c *Client) CreateRun(
	ctx context.Context,
	threadID string,
	request RunRequest,
) (response Run, err error)

CreateRun creates a new run.

func (*Client) CreateSpeech 

func (c *Client) CreateSpeech(ctx context.Context, request CreateSpeechRequest) (response RawResponse, err error)

func (*Client) CreateThread 

func (c *Client) CreateThread(ctx context.Context, request ThreadRequest) (response Thread, err error)

CreateThread creates a new thread.

func (*Client) CreateThreadAndRun 

func (c *Client) CreateThreadAndRun(
	ctx context.Context,
	request CreateThreadAndRunRequest) (response Run, err error)

CreateThreadAndRun submits tool outputs.

func (*Client) CreateTranscription 

func (c *Client) CreateTranscription(
	ctx context.Context,
	request AudioRequest,
) (response AudioResponse, err error)

CreateTranscription — API call to create a transcription. Returns transcribed text.

Example 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))
resp, err := client.CreateTranscription(
	context.Background(),
	openai.AudioRequest{
		Model:    openai.Whisper1,
		FilePath: "recording.mp3",
	},
)
if err != nil {
	fmt.Printf("Transcription error: %v\n", err)
	return
}
fmt.Println(resp.Text)

Output:
Example (Captions) 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))

resp, err := client.CreateTranscription(
	context.Background(),
	openai.AudioRequest{
		Model:    openai.Whisper1,
		FilePath: os.Args[1],
		Format:   openai.AudioResponseFormatSRT,
	},
)
if err != nil {
	fmt.Printf("Transcription error: %v\n", err)
	return
}
f, err := os.Create(os.Args[1] + ".srt")
if err != nil {
	fmt.Printf("Could not open file: %v\n", err)
	return
}
defer f.Close()
if _, err = f.WriteString(resp.Text); err != nil {
	fmt.Printf("Error writing to file: %v\n", err)
	return
}

Output:

func (*Client) CreateTranslation 

func (c *Client) CreateTranslation(
	ctx context.Context,
	request AudioRequest,
) (response AudioResponse, err error)

CreateTranslation — API call to translate audio into English.

Example 
client := openai.NewClient(os.Getenv("OPENAI_API_KEY"))
resp, err := client.CreateTranslation(
	context.Background(),
	openai.AudioRequest{
		Model:    openai.Whisper1,
		FilePath: "recording.mp3",
	},
)
if err != nil {
	fmt.Printf("Translation error: %v\n", err)
	return
}
fmt.Println(resp.Text)

Output:

func (*Client) CreateVariImage 

func (c *Client) CreateVariImage(ctx context.Context, request ImageVariRequest) (response ImageResponse, err error)

CreateVariImage - API call to create an image variation. This is the main endpoint of the DALL-E API. Use abbreviations(vari for variation) because ci-lint has a single-line length limit ...

func (*Client) CreateVectorStore 

func (c *Client) CreateVectorStore(ctx context.Context, request VectorStoreRequest) (response VectorStore, err error)

CreateVectorStore creates a new vector store.

func (*Client) CreateVectorStoreFile 

func (c *Client) CreateVectorStoreFile(
	ctx context.Context,
	vectorStoreID string,
	request VectorStoreFileRequest,
) (response VectorStoreFile, err error)

CreateVectorStoreFile creates a new vector store file.

func (*Client) CreateVectorStoreFileBatch 

func (c *Client) CreateVectorStoreFileBatch(
	ctx context.Context,
	vectorStoreID string,
	request VectorStoreFileBatchRequest,
) (response VectorStoreFileBatch, err error)

CreateVectorStoreFileBatch creates a new vector store file batch.

func (*Client) DeleteAssistant 

func (c *Client) DeleteAssistant(
	ctx context.Context,
	assistantID string,
) (response AssistantDeleteResponse, err error)

DeleteAssistant deletes an assistant.

func (*Client) DeleteAssistantFile 

func (c *Client) DeleteAssistantFile(
	ctx context.Context,
	assistantID string,
	fileID string,
) (err error)

DeleteAssistantFile deletes an existing file.

func (*Client) DeleteFile 

func (c *Client) DeleteFile(ctx context.Context, fileID string) (err error)

DeleteFile deletes an existing file.

func (*Client) DeleteFineTune deprecated 

func (c *Client) DeleteFineTune(ctx context.Context, fineTuneID string) (response FineTuneDeleteResponse, err error)

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*Client) DeleteFineTuneModel 

func (c *Client) DeleteFineTuneModel(ctx context.Context, modelID string) (
	response FineTuneModelDeleteResponse, err error)

DeleteFineTuneModel Deletes a fine-tune model. You must have the Owner role in your organization to delete a model.

func (*Client) DeleteThread 

func (c *Client) DeleteThread(
	ctx context.Context,
	threadID string,
) (response ThreadDeleteResponse, err error)

DeleteThread deletes a thread.

func (*Client) DeleteVectorStore 

func (c *Client) DeleteVectorStore(
	ctx context.Context,
	vectorStoreID string,
) (response VectorStoreDeleteResponse, err error)

DeleteVectorStore deletes an vector store.

func (*Client) DeleteVectorStoreFile 

func (c *Client) DeleteVectorStoreFile(
	ctx context.Context,
	vectorStoreID string,
	fileID string,
) (err error)

DeleteVectorStoreFile deletes an existing file.

func (*Client) Edits 

func (c *Client) Edits(ctx context.Context, request EditsRequest) (response EditsResponse, err error)

Edits Perform an API call to the Edits endpoint. 

Deprecated: Users of the Edits API and its associated models (e.g., text-davinci-edit-001 or code-davinci-edit-001)

will need to migrate to GPT-3.5 Turbo by January 4, 2024. You can use CreateChatCompletion or CreateChatCompletionStream instead.

func (*Client) GetEngine 

func (c *Client) GetEngine(
	ctx context.Context,
	engineID string,
) (engine Engine, err error)

GetEngine Retrieves an engine instance, providing basic information about the engine such as the owner and availability.

func (*Client) GetFile 

func (c *Client) GetFile(ctx context.Context, fileID string) (file File, err error)

GetFile Retrieves a file instance, providing basic information about the file such as the file name and purpose.

func (*Client) GetFileContent 

func (c *Client) GetFileContent(ctx context.Context, fileID string) (content RawResponse, err error)

func (*Client) GetFineTune deprecated 

func (c *Client) GetFineTune(ctx context.Context, fineTuneID string) (response FineTune, err error)

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*Client) GetModel 

func (c *Client) GetModel(ctx context.Context, modelID string) (model Model, err error)

GetModel Retrieves a model instance, providing basic information about the model such as the owner and permissioning.

func (*Client) ListAssistantFiles 

func (c *Client) ListAssistantFiles(
	ctx context.Context,
	assistantID string,
	limit *int,
	order *string,
	after *string,
	before *string,
) (response AssistantFilesList, err error)

ListAssistantFiles Lists the currently available files for an assistant.

func (*Client) ListAssistants 

func (c *Client) ListAssistants(
	ctx context.Context,
	limit *int,
	order *string,
	after *string,
	before *string,
) (response AssistantsList, err error)

ListAssistants Lists the currently available assistants.

func (*Client) ListBatch 

func (c *Client) ListBatch(ctx context.Context, after *string, limit *int) (response ListBatchResponse, err error)

ListBatch API call to List batch.

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 

func (c *Client) ListFiles(ctx context.Context) (files FilesList, err error)

ListFiles Lists the currently available files, and provides basic information about each file such as the file name and purpose.

func (*Client) ListFineTuneEvents deprecated 

func (c *Client) ListFineTuneEvents(ctx context.Context, fineTuneID string) (response FineTuneEventList, err error)

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*Client) ListFineTunes deprecated 

func (c *Client) ListFineTunes(ctx context.Context) (response FineTuneList, err error)

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*Client) ListFineTuningJobEvents 

func (c *Client) ListFineTuningJobEvents(
	ctx context.Context,
	fineTuningJobID string,
	setters ...ListFineTuningJobEventsParameter,
) (response FineTuningJobEventList, err error)

ListFineTuningJobs list fine tuning jobs events.

func (*Client) ListMessage 

func (c *Client) ListMessage(ctx context.Context, threadID string,
	limit *int,
	order *string,
	after *string,
	before *string,
) (messages MessagesList, err error)

ListMessage fetches all messages in the thread.

func (*Client) ListMessageFiles 

func (c *Client) ListMessageFiles(
	ctx context.Context,
	threadID, messageID string,
) (files MessageFilesList, err error)

ListMessageFiles fetches all files attached to a message.

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) ListRunSteps 

func (c *Client) ListRunSteps(
	ctx context.Context,
	threadID string,
	runID string,
	pagination Pagination,
) (response RunStepList, err error)

ListRunSteps lists run steps.

func (*Client) ListRuns 

func (c *Client) ListRuns(
	ctx context.Context,
	threadID string,
	pagination Pagination,
) (response RunList, err error)

ListRuns lists runs.

func (*Client) ListVectorStoreFiles 

func (c *Client) ListVectorStoreFiles(
	ctx context.Context,
	vectorStoreID string,
	pagination Pagination,
) (response VectorStoreFilesList, err error)

ListVectorStoreFiles Lists the currently available files for a vector store.

func (*Client) ListVectorStoreFilesInBatch 

func (c *Client) ListVectorStoreFilesInBatch(
	ctx context.Context,
	vectorStoreID string,
	batchID string,
	pagination Pagination,
) (response VectorStoreFilesList, err error)

ListVectorStoreFiles Lists the currently available files for a vector store.

func (*Client) ListVectorStores 

func (c *Client) ListVectorStores(
	ctx context.Context,
	pagination Pagination,
) (response VectorStoresList, err error)

ListVectorStores Lists the currently available vector store.

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.

func (*Client) ModifyAssistant 

func (c *Client) ModifyAssistant(
	ctx context.Context,
	assistantID string,
	request AssistantRequest,
) (response Assistant, err error)

ModifyAssistant modifies an assistant.

func (*Client) ModifyMessage 

func (c *Client) ModifyMessage(
	ctx context.Context,
	threadID, messageID string,
	metadata map[string]string,
) (msg Message, err error)

ModifyMessage modifies a message.

func (*Client) ModifyRun 

func (c *Client) ModifyRun(
	ctx context.Context,
	threadID string,
	runID string,
	request RunModifyRequest,
) (response Run, err error)

ModifyRun modifies a run.

func (*Client) ModifyThread 

func (c *Client) ModifyThread(
	ctx context.Context,
	threadID string,
	request ModifyThreadRequest,
) (response Thread, err error)

ModifyThread modifies a thread.

func (*Client) ModifyVectorStore 

func (c *Client) ModifyVectorStore(
	ctx context.Context,
	vectorStoreID string,
	request VectorStoreRequest,
) (response VectorStore, err error)

ModifyVectorStore modifies a vector store.

func (*Client) RetrieveAssistant 

func (c *Client) RetrieveAssistant(
	ctx context.Context,
	assistantID string,
) (response Assistant, err error)

RetrieveAssistant retrieves an assistant.

func (*Client) RetrieveAssistantFile 

func (c *Client) RetrieveAssistantFile(
	ctx context.Context,
	assistantID string,
	fileID string,
) (response AssistantFile, err error)

RetrieveAssistantFile retrieves an assistant file.

func (*Client) RetrieveBatch 

func (c *Client) RetrieveBatch(
	ctx context.Context,
	batchID string,
) (response BatchResponse, err error)

RetrieveBatch — API call to Retrieve batch.

func (*Client) RetrieveFineTuningJob 

func (c *Client) RetrieveFineTuningJob(
	ctx context.Context,
	fineTuningJobID string,
) (response FineTuningJob, err error)

RetrieveFineTuningJob retrieve a fine tuning job.

func (*Client) RetrieveMessage 

func (c *Client) RetrieveMessage(
	ctx context.Context,
	threadID, messageID string,
) (msg Message, err error)

RetrieveMessage retrieves a Message.

func (*Client) RetrieveMessageFile 

func (c *Client) RetrieveMessageFile(
	ctx context.Context,
	threadID, messageID, fileID string,
) (file MessageFile, err error)

RetrieveMessageFile fetches a message file.

func (*Client) RetrieveRun 

func (c *Client) RetrieveRun(
	ctx context.Context,
	threadID string,
	runID string,
) (response Run, err error)

RetrieveRun retrieves a run.

func (*Client) RetrieveRunStep 

func (c *Client) RetrieveRunStep(
	ctx context.Context,
	threadID string,
	runID string,
	stepID string,
) (response RunStep, err error)

RetrieveRunStep retrieves a run step.

func (*Client) RetrieveThread 

func (c *Client) RetrieveThread(ctx context.Context, threadID string) (response Thread, err error)

RetrieveThread retrieves a thread.

func (*Client) RetrieveVectorStore 

func (c *Client) RetrieveVectorStore(
	ctx context.Context,
	vectorStoreID string,
) (response VectorStore, err error)

RetrieveVectorStore retrieves an vector store.

func (*Client) RetrieveVectorStoreFile 

func (c *Client) RetrieveVectorStoreFile(
	ctx context.Context,
	vectorStoreID string,
	fileID string,
) (response VectorStoreFile, err error)

RetrieveVectorStoreFile retrieves a vector store file.

func (*Client) RetrieveVectorStoreFileBatch 

func (c *Client) RetrieveVectorStoreFileBatch(
	ctx context.Context,
	vectorStoreID string,
	batchID string,
) (response VectorStoreFileBatch, err error)

RetrieveVectorStoreFileBatch retrieves a vector store file batch.

func (*Client) SubmitToolOutputs 

func (c *Client) SubmitToolOutputs(
	ctx context.Context,
	threadID string,
	runID string,
	request SubmitToolOutputsRequest) (response Run, err error)

SubmitToolOutputs submits tool outputs.

func (*Client) UploadBatchFile 

func (c *Client) UploadBatchFile(ctx context.Context, request UploadBatchFileRequest) (File, error)

UploadBatchFile — upload batch file.

type ClientConfig 

type ClientConfig struct {
	BaseURL              string
	OrgID                string
	APIType              APIType
	APIVersion           string // required when APIType is APITypeAzure or APITypeAzureAD
	AssistantVersion     string
	AzureModelMapperFunc func(model string) string // replace model to azure deployment name func
	HTTPClient           *http.Client

	EmptyMessagesLimit uint
	// contains filtered or unexported fields
}

ClientConfig is a configuration of a client.

Example (ClientWithProxy) 
config := openai.DefaultConfig(os.Getenv("OPENAI_API_KEY"))
port := os.Getenv("OPENAI_PROXY_PORT")
proxyURL, err := url.Parse(fmt.Sprintf("http://localhost:%s", port))
if err != nil {
	panic(err)
}
transport := &http.Transport{
	Proxy: http.ProxyURL(proxyURL),
}
config.HTTPClient = &http.Client{
	Transport: transport,
}

client := openai.NewClientWithConfig(config)

client.CreateChatCompletion( //nolint:errcheck // outside of the scope of this example.
	context.Background(),
	openai.ChatCompletionRequest{
		// etc...
	},
)

Output:

func DefaultAzureConfig 

func DefaultAzureConfig(apiKey, baseURL string) ClientConfig
Example 
azureKey := os.Getenv("AZURE_OPENAI_API_KEY")       // Your azure API key
azureEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT") // Your azure OpenAI endpoint
config := openai.DefaultAzureConfig(azureKey, azureEndpoint)
client := openai.NewClientWithConfig(config)
resp, err := client.CreateChatCompletion(
	context.Background(),
	openai.ChatCompletionRequest{
		Model: openai.GPT3Dot5Turbo,
		Messages: []openai.ChatCompletionMessage{
			{
				Role:    openai.ChatMessageRoleUser,
				Content: "Hello Azure OpenAI!",
			},
		},
	},
)
if err != nil {
	fmt.Printf("ChatCompletion error: %v\n", err)
	return
}

fmt.Println(resp.Choices[0].Message.Content)

Output:

func DefaultConfig 

func DefaultConfig(authToken string) ClientConfig

func (ClientConfig) GetAzureDeploymentByModel 

func (c ClientConfig) GetAzureDeploymentByModel(model string) string

func (ClientConfig) String 

func (ClientConfig) String() string

type CodeInterpreterToolResources 

type CodeInterpreterToolResources struct {
	FileIDs []string `json:"file_ids,omitempty"`
}

type CodeInterpreterToolResourcesRequest 

type CodeInterpreterToolResourcesRequest struct {
	FileIDs []string `json:"file_ids,omitempty"`
}

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           any      `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 is must be a token id string (specified by their token ID in the tokenizer), not a word string.
	// incorrect: `"logit_bias":{"You": 6}`, correct: `"logit_bias":{"1639": 6}`
	// refs: https://platform.openai.com/docs/api-reference/completions/create#completions/create-logit_bias
	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"`
	// contains filtered or unexported fields
}

CompletionResponse represents a response structure for completion API.

func (*CompletionResponse) GetRateLimitHeaders 

func (h *CompletionResponse) GetRateLimitHeaders() RateLimitHeaders

func (*CompletionResponse) Header 

func (h *CompletionResponse) Header() http.Header

func (*CompletionResponse) SetHeader 

func (h *CompletionResponse) SetHeader(header http.Header)

type CompletionStream 

type CompletionStream struct {
	// contains filtered or unexported fields
}

func (CompletionStream) Close 

func (stream CompletionStream) Close() error

func (CompletionStream) Recv 

func (stream CompletionStream) Recv() (response T, err error)

type ContentFilterResults 

type ContentFilterResults struct {
	Hate     Hate     `json:"hate,omitempty"`
	SelfHarm SelfHarm `json:"self_harm,omitempty"`
	Sexual   Sexual   `json:"sexual,omitempty"`
	Violence Violence `json:"violence,omitempty"`
}

type CreateBatchRequest 

type CreateBatchRequest struct {
	InputFileID      string         `json:"input_file_id"`
	Endpoint         BatchEndpoint  `json:"endpoint"`
	CompletionWindow string         `json:"completion_window"`
	Metadata         map[string]any `json:"metadata"`
}

type CreateBatchWithUploadFileRequest 

type CreateBatchWithUploadFileRequest struct {
	Endpoint         BatchEndpoint  `json:"endpoint"`
	CompletionWindow string         `json:"completion_window"`
	Metadata         map[string]any `json:"metadata"`
	UploadBatchFileRequest
}

type CreateSpeechRequest 

type CreateSpeechRequest struct {
	Model          SpeechModel          `json:"model"`
	Input          string               `json:"input"`
	Voice          SpeechVoice          `json:"voice"`
	ResponseFormat SpeechResponseFormat `json:"response_format,omitempty"` // Optional, default to mp3
	Speed          float64              `json:"speed,omitempty"`           // Optional, default to 1.0
}

type CreateThreadAndRunRequest 

type CreateThreadAndRunRequest struct {
	RunRequest
	Thread ThreadRequest `json:"thread"`
}

type EditsChoice 

type EditsChoice struct {
	Text  string `json:"text"`
	Index int    `json:"index"`
}

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"`
	// contains filtered or unexported fields
}

EditsResponse represents a response structure for Edits API.

func (*EditsResponse) GetRateLimitHeaders 

func (h *EditsResponse) GetRateLimitHeaders() RateLimitHeaders

func (*EditsResponse) Header 

func (h *EditsResponse) Header() http.Header

func (*EditsResponse) SetHeader 

func (h *EditsResponse) SetHeader(header http.Header)

type Embedding 

type Embedding struct {
	Object    string    `json:"object"`
	Embedding []float32 `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.

func (*Embedding) DotProduct 

func (e *Embedding) DotProduct(other *Embedding) (float32, error)

DotProduct calculates the dot product of the embedding vector with another embedding vector. Both vectors must have the same length; otherwise, an ErrVectorLengthMismatch is returned. The method returns the calculated dot product as a float32 value.

type EmbeddingEncodingFormat 

type EmbeddingEncodingFormat string

EmbeddingEncodingFormat is the format of the embeddings data. Currently, only "float" and "base64" are supported, however, "base64" is not officially documented. If not specified OpenAI will use "float". 

const (
	EmbeddingEncodingFormatFloat  EmbeddingEncodingFormat = "float"
	EmbeddingEncodingFormatBase64 EmbeddingEncodingFormat = "base64"
)

type EmbeddingModel 

type EmbeddingModel string

EmbeddingModel enumerates the models which can be used to generate Embedding vectors. 

const (
	// Deprecated: The following block is shut down. Use text-embedding-ada-002 instead.
	AdaSimilarity         EmbeddingModel = "text-similarity-ada-001"
	BabbageSimilarity     EmbeddingModel = "text-similarity-babbage-001"
	CurieSimilarity       EmbeddingModel = "text-similarity-curie-001"
	DavinciSimilarity     EmbeddingModel = "text-similarity-davinci-001"
	AdaSearchDocument     EmbeddingModel = "text-search-ada-doc-001"
	AdaSearchQuery        EmbeddingModel = "text-search-ada-query-001"
	BabbageSearchDocument EmbeddingModel = "text-search-babbage-doc-001"
	BabbageSearchQuery    EmbeddingModel = "text-search-babbage-query-001"
	CurieSearchDocument   EmbeddingModel = "text-search-curie-doc-001"
	CurieSearchQuery      EmbeddingModel = "text-search-curie-query-001"
	DavinciSearchDocument EmbeddingModel = "text-search-davinci-doc-001"
	DavinciSearchQuery    EmbeddingModel = "text-search-davinci-query-001"
	AdaCodeSearchCode     EmbeddingModel = "code-search-ada-code-001"
	AdaCodeSearchText     EmbeddingModel = "code-search-ada-text-001"
	BabbageCodeSearchCode EmbeddingModel = "code-search-babbage-code-001"
	BabbageCodeSearchText EmbeddingModel = "code-search-babbage-text-001"

	AdaEmbeddingV2  EmbeddingModel = "text-embedding-ada-002"
	SmallEmbedding3 EmbeddingModel = "text-embedding-3-small"
	LargeEmbedding3 EmbeddingModel = "text-embedding-3-large"
)

type EmbeddingRequest 

type EmbeddingRequest struct {
	Input          any                     `json:"input"`
	Model          EmbeddingModel          `json:"model"`
	User           string                  `json:"user"`
	EncodingFormat EmbeddingEncodingFormat `json:"encoding_format,omitempty"`
	// Dimensions The number of dimensions the resulting output embeddings should have.
	// Only supported in text-embedding-3 and later models.
	Dimensions int `json:"dimensions,omitempty"`
}

func (EmbeddingRequest) Convert 

func (r EmbeddingRequest) Convert() EmbeddingRequest

type EmbeddingRequestConverter 

type EmbeddingRequestConverter interface {
	// Needs to be of type EmbeddingRequestStrings or EmbeddingRequestTokens
	Convert() EmbeddingRequest
}

type EmbeddingRequestStrings 

type EmbeddingRequestStrings struct {
	// Input is a slice of strings for which you want to generate an Embedding vector.
	// Each input must not exceed 8192 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"`
	// EmbeddingEncodingFormat is the format of the embeddings data.
	// Currently, only "float" and "base64" are supported, however, "base64" is not officially documented.
	// If not specified OpenAI will use "float".
	EncodingFormat EmbeddingEncodingFormat `json:"encoding_format,omitempty"`
	// Dimensions The number of dimensions the resulting output embeddings should have.
	// Only supported in text-embedding-3 and later models.
	Dimensions int `json:"dimensions,omitempty"`
}

EmbeddingRequestStrings is the input to a create embeddings request with a slice of strings.

func (EmbeddingRequestStrings) Convert 

func (r EmbeddingRequestStrings) Convert() EmbeddingRequest

type EmbeddingRequestTokens 

type EmbeddingRequestTokens struct {
	// Input is a slice of slices of ints ([][]int) for which you want to generate an Embedding vector.
	// Each input must not exceed 8192 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 [][]int `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"`
	// EmbeddingEncodingFormat is the format of the embeddings data.
	// Currently, only "float" and "base64" are supported, however, "base64" is not officially documented.
	// If not specified OpenAI will use "float".
	EncodingFormat EmbeddingEncodingFormat `json:"encoding_format,omitempty"`
	// Dimensions The number of dimensions the resulting output embeddings should have.
	// Only supported in text-embedding-3 and later models.
	Dimensions int `json:"dimensions,omitempty"`
}

func (EmbeddingRequestTokens) Convert 

func (r EmbeddingRequestTokens) Convert() EmbeddingRequest

type EmbeddingResponse 

type EmbeddingResponse struct {
	Object string         `json:"object"`
	Data   []Embedding    `json:"data"`
	Model  EmbeddingModel `json:"model"`
	Usage  Usage          `json:"usage"`
	// contains filtered or unexported fields
}

EmbeddingResponse is the response from a Create embeddings request.

func (*EmbeddingResponse) GetRateLimitHeaders 

func (h *EmbeddingResponse) GetRateLimitHeaders() RateLimitHeaders

func (*EmbeddingResponse) Header 

func (h *EmbeddingResponse) Header() http.Header

func (*EmbeddingResponse) SetHeader 

func (h *EmbeddingResponse) SetHeader(header http.Header)

type EmbeddingResponseBase64 

type EmbeddingResponseBase64 struct {
	Object string            `json:"object"`
	Data   []Base64Embedding `json:"data"`
	Model  EmbeddingModel    `json:"model"`
	Usage  Usage             `json:"usage"`
	// contains filtered or unexported fields
}

EmbeddingResponseBase64 is the response from a Create embeddings request with base64 encoding format.

func (*EmbeddingResponseBase64) GetRateLimitHeaders 

func (h *EmbeddingResponseBase64) GetRateLimitHeaders() RateLimitHeaders

func (*EmbeddingResponseBase64) Header 

func (h *EmbeddingResponseBase64) Header() http.Header

func (*EmbeddingResponseBase64) SetHeader 

func (h *EmbeddingResponseBase64) SetHeader(header http.Header)

func (*EmbeddingResponseBase64) ToEmbeddingResponse 

func (r *EmbeddingResponseBase64) ToEmbeddingResponse() (EmbeddingResponse, error)

ToEmbeddingResponse converts an embeddingResponseBase64 to an EmbeddingResponse.

type Engine 

type Engine struct {
	ID     string `json:"id"`
	Object string `json:"object"`
	Owner  string `json:"owner"`
	Ready  bool   `json:"ready"`
	// contains filtered or unexported fields
}

Engine struct represents engine from OpenAPI API.

func (*Engine) GetRateLimitHeaders 

func (h *Engine) GetRateLimitHeaders() RateLimitHeaders

func (*Engine) Header 

func (h *Engine) Header() http.Header

func (*Engine) SetHeader 

func (h *Engine) SetHeader(header http.Header)

type EnginesList 

type EnginesList struct {
	Engines []Engine `json:"data"`
	// contains filtered or unexported fields
}

EnginesList is a list of engines.

func (*EnginesList) GetRateLimitHeaders 

func (h *EnginesList) GetRateLimitHeaders() RateLimitHeaders

func (*EnginesList) Header 

func (h *EnginesList) Header() http.Header

func (*EnginesList) SetHeader 

func (h *EnginesList) SetHeader(header http.Header)

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"`
	Status        string `json:"status"`
	Purpose       string `json:"purpose"`
	StatusDetails string `json:"status_details"`
	// contains filtered or unexported fields
}

File struct represents an OpenAPI file.

func (*File) GetRateLimitHeaders 

func (h *File) GetRateLimitHeaders() RateLimitHeaders

func (*File) Header 

func (h *File) Header() http.Header

func (*File) SetHeader 

func (h *File) SetHeader(header http.Header)

type FileBytesRequest 

type FileBytesRequest struct {
	// the name of the uploaded file in OpenAI
	Name string
	// the bytes of the file
	Bytes []byte
	// the purpose of the file
	Purpose PurposeType
}

FileBytesRequest represents a file upload request.

type FileRequest 

type FileRequest struct {
	FileName string `json:"file"`
	FilePath string `json:"-"`
	Purpose  string `json:"purpose"`
}

type FileSearchToolResources 

type FileSearchToolResources struct {
	VectorStoreIDs []string `json:"vector_store_ids,omitempty"`
}

type FileSearchToolResourcesRequest 

type FileSearchToolResourcesRequest struct {
	VectorStoreIDs []string                   `json:"vector_store_ids,omitempty"`
	VectorStores   []VectorStoreToolResources `json:"vector_stores,omitempty"`
}

type FilesList 

type FilesList struct {
	Files []File `json:"data"`
	// contains filtered or unexported fields
}

FilesList is a list of files that belong to the user or organization.

func (*FilesList) GetRateLimitHeaders 

func (h *FilesList) GetRateLimitHeaders() RateLimitHeaders

func (*FilesList) Header 

func (h *FilesList) Header() http.Header

func (*FilesList) SetHeader 

func (h *FilesList) SetHeader(header http.Header)

type FineTune deprecated 

type FineTune struct {
	ID                string              `json:"id"`
	Object            string              `json:"object"`
	Model             string              `json:"model"`
	CreatedAt         int64               `json:"created_at"`
	FineTuneEventList []FineTuneEvent     `json:"events,omitempty"`
	FineTunedModel    string              `json:"fine_tuned_model"`
	HyperParams       FineTuneHyperParams `json:"hyperparams"`
	OrganizationID    string              `json:"organization_id"`
	ResultFiles       []File              `json:"result_files"`
	Status            string              `json:"status"`
	ValidationFiles   []File              `json:"validation_files"`
	TrainingFiles     []File              `json:"training_files"`
	UpdatedAt         int64               `json:"updated_at"`
	// contains filtered or unexported fields
}

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*FineTune) GetRateLimitHeaders 

func (h *FineTune) GetRateLimitHeaders() RateLimitHeaders

func (*FineTune) Header 

func (h *FineTune) Header() http.Header

func (*FineTune) SetHeader 

func (h *FineTune) SetHeader(header http.Header)

type FineTuneDeleteResponse deprecated 

type FineTuneDeleteResponse struct {
	ID      string `json:"id"`
	Object  string `json:"object"`
	Deleted bool   `json:"deleted"`
	// contains filtered or unexported fields
}

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*FineTuneDeleteResponse) GetRateLimitHeaders 

func (h *FineTuneDeleteResponse) GetRateLimitHeaders() RateLimitHeaders

func (*FineTuneDeleteResponse) Header 

func (h *FineTuneDeleteResponse) Header() http.Header

func (*FineTuneDeleteResponse) SetHeader 

func (h *FineTuneDeleteResponse) SetHeader(header http.Header)

type FineTuneEvent deprecated 

type FineTuneEvent struct {
	Object    string `json:"object"`
	CreatedAt int64  `json:"created_at"`
	Level     string `json:"level"`
	Message   string `json:"message"`
}

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

type FineTuneEventList deprecated 

type FineTuneEventList struct {
	Object string          `json:"object"`
	Data   []FineTuneEvent `json:"data"`
	// contains filtered or unexported fields
}

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*FineTuneEventList) GetRateLimitHeaders 

func (h *FineTuneEventList) GetRateLimitHeaders() RateLimitHeaders

func (*FineTuneEventList) Header 

func (h *FineTuneEventList) Header() http.Header

func (*FineTuneEventList) SetHeader 

func (h *FineTuneEventList) SetHeader(header http.Header)

type FineTuneHyperParams deprecated 

type FineTuneHyperParams struct {
	BatchSize              int     `json:"batch_size"`
	LearningRateMultiplier float64 `json:"learning_rate_multiplier"`
	Epochs                 int     `json:"n_epochs"`
	PromptLossWeight       float64 `json:"prompt_loss_weight"`
}

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

type FineTuneList deprecated 

type FineTuneList struct {
	Object string     `json:"object"`
	Data   []FineTune `json:"data"`
	// contains filtered or unexported fields
}

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

func (*FineTuneList) GetRateLimitHeaders 

func (h *FineTuneList) GetRateLimitHeaders() RateLimitHeaders

func (*FineTuneList) Header 

func (h *FineTuneList) Header() http.Header

func (*FineTuneList) SetHeader 

func (h *FineTuneList) SetHeader(header http.Header)

type FineTuneModelDeleteResponse 

type FineTuneModelDeleteResponse struct {
	ID      string `json:"id"`
	Object  string `json:"object"`
	Deleted bool   `json:"deleted"`
	// contains filtered or unexported fields
}

FineTuneModelDeleteResponse represents the deletion status of a fine-tuned model.

func (*FineTuneModelDeleteResponse) GetRateLimitHeaders 

func (h *FineTuneModelDeleteResponse) GetRateLimitHeaders() RateLimitHeaders

func (*FineTuneModelDeleteResponse) Header 

func (h *FineTuneModelDeleteResponse) Header() http.Header

func (*FineTuneModelDeleteResponse) SetHeader 

func (h *FineTuneModelDeleteResponse) SetHeader(header http.Header)

type FineTuneRequest deprecated 

type FineTuneRequest struct {
	TrainingFile                 string    `json:"training_file"`
	ValidationFile               string    `json:"validation_file,omitempty"`
	Model                        string    `json:"model,omitempty"`
	Epochs                       int       `json:"n_epochs,omitempty"`
	BatchSize                    int       `json:"batch_size,omitempty"`
	LearningRateMultiplier       float32   `json:"learning_rate_multiplier,omitempty"`
	PromptLossRate               float32   `json:"prompt_loss_rate,omitempty"`
	ComputeClassificationMetrics bool      `json:"compute_classification_metrics,omitempty"`
	ClassificationClasses        int       `json:"classification_n_classes,omitempty"`
	ClassificationPositiveClass  string    `json:"classification_positive_class,omitempty"`
	ClassificationBetas          []float32 `json:"classification_betas,omitempty"`
	Suffix                       string    `json:"suffix,omitempty"`
}

Deprecated: On August 22nd, 2023, OpenAI announced the deprecation of the /v1/fine-tunes API. This API will be officially deprecated on January 4th, 2024. OpenAI recommends to migrate to the new fine tuning API implemented in fine_tuning_job.go.

type FineTuningJob 

type FineTuningJob struct {
	ID              string          `json:"id"`
	Object          string          `json:"object"`
	CreatedAt       int64           `json:"created_at"`
	FinishedAt      int64           `json:"finished_at"`
	Model           string          `json:"model"`
	FineTunedModel  string          `json:"fine_tuned_model,omitempty"`
	OrganizationID  string          `json:"organization_id"`
	Status          string          `json:"status"`
	Hyperparameters Hyperparameters `json:"hyperparameters"`
	TrainingFile    string          `json:"training_file"`
	ValidationFile  string          `json:"validation_file,omitempty"`
	ResultFiles     []string        `json:"result_files"`
	TrainedTokens   int             `json:"trained_tokens"`
	// contains filtered or unexported fields
}

func (*FineTuningJob) GetRateLimitHeaders 

func (h *FineTuningJob) GetRateLimitHeaders() RateLimitHeaders

func (*FineTuningJob) Header 

func (h *FineTuningJob) Header() http.Header

func (*FineTuningJob) SetHeader 

func (h *FineTuningJob) SetHeader(header http.Header)

type FineTuningJobEvent 

type FineTuningJobEvent struct {
	Object    string `json:"object"`
	ID        string `json:"id"`
	CreatedAt int    `json:"created_at"`
	Level     string `json:"level"`
	Message   string `json:"message"`
	Data      any    `json:"data"`
	Type      string `json:"type"`
}

type FineTuningJobEventList 

type FineTuningJobEventList struct {
	Object  string          `json:"object"`
	Data    []FineTuneEvent `json:"data"`
	HasMore bool            `json:"has_more"`
	// contains filtered or unexported fields
}

func (*FineTuningJobEventList) GetRateLimitHeaders 

func (h *FineTuningJobEventList) GetRateLimitHeaders() RateLimitHeaders

func (*FineTuningJobEventList) Header 

func (h *FineTuningJobEventList) Header() http.Header

func (*FineTuningJobEventList) SetHeader 

func (h *FineTuningJobEventList) SetHeader(header http.Header)

type FineTuningJobRequest 

type FineTuningJobRequest struct {
	TrainingFile    string           `json:"training_file"`
	ValidationFile  string           `json:"validation_file,omitempty"`
	Model           string           `json:"model,omitempty"`
	Hyperparameters *Hyperparameters `json:"hyperparameters,omitempty"`
	Suffix          string           `json:"suffix,omitempty"`
}

type FinishReason 

type FinishReason string
const (
	FinishReasonStop          FinishReason = "stop"
	FinishReasonLength        FinishReason = "length"
	FinishReasonFunctionCall  FinishReason = "function_call"
	FinishReasonToolCalls     FinishReason = "tool_calls"
	FinishReasonContentFilter FinishReason = "content_filter"
	FinishReasonNull          FinishReason = "null"
)

func (FinishReason) MarshalJSON 

func (r FinishReason) MarshalJSON() ([]byte, error)

type FunctionCall 

type FunctionCall struct {
	Name string `json:"name,omitempty"`
	// call function with arguments in JSON format
	Arguments string `json:"arguments,omitempty"`
}

type FunctionDefine deprecated 

type FunctionDefine = FunctionDefinition

Deprecated: use FunctionDefinition instead.

type FunctionDefinition 

type FunctionDefinition struct {
	Name        string `json:"name"`
	Description string `json:"description,omitempty"`
	// Parameters is an object describing the function.
	// You can pass json.RawMessage to describe the schema,
	// or you can pass in a struct which serializes to the proper JSON schema.
	// The jsonschema package is provided for convenience, but you should
	// consider another specialized library if you require more complex schemas.
	Parameters any `json:"parameters"`
}

type Hate 

type Hate struct {
	Filtered bool   `json:"filtered"`
	Severity string `json:"severity,omitempty"`
}

type Hyperparameters 

type Hyperparameters struct {
	Epochs                 any `json:"n_epochs,omitempty"`
	LearningRateMultiplier any `json:"learning_rate_multiplier,omitempty"`
	BatchSize              any `json:"batch_size,omitempty"`
}

type ImageEditRequest 

type ImageEditRequest struct {
	Image          *os.File `json:"image,omitempty"`
	Mask           *os.File `json:"mask,omitempty"`
	Prompt         string   `json:"prompt,omitempty"`
	Model          string   `json:"model,omitempty"`
	N              int      `json:"n,omitempty"`
	Size           string   `json:"size,omitempty"`
	ResponseFormat string   `json:"response_format,omitempty"`
}

ImageEditRequest represents the request structure for the image API.

type ImageFile 

type ImageFile struct {
	FileID string `json:"file_id"`
}

type ImageRequest 

type ImageRequest struct {
	Prompt         string `json:"prompt,omitempty"`
	Model          string `json:"model,omitempty"`
	N              int    `json:"n,omitempty"`
	Quality        string `json:"quality,omitempty"`
	Size           string `json:"size,omitempty"`
	Style          string `json:"style,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"`
	// contains filtered or unexported fields
}

ImageResponse represents a response structure for image API.

func (*ImageResponse) GetRateLimitHeaders 

func (h *ImageResponse) GetRateLimitHeaders() RateLimitHeaders

func (*ImageResponse) Header 

func (h *ImageResponse) Header() http.Header

func (*ImageResponse) SetHeader 

func (h *ImageResponse) SetHeader(header http.Header)

type ImageResponseDataInner 

type ImageResponseDataInner struct {
	URL           string `json:"url,omitempty"`
	B64JSON       string `json:"b64_json,omitempty"`
	RevisedPrompt string `json:"revised_prompt,omitempty"`
}

ImageResponseDataInner represents a response data structure for image API.

type ImageURLDetail 

type ImageURLDetail string
const (
	ImageURLDetailHigh ImageURLDetail = "high"
	ImageURLDetailLow  ImageURLDetail = "low"
	ImageURLDetailAuto ImageURLDetail = "auto"
)

type ImageVariRequest 

type ImageVariRequest struct {
	Image          *os.File `json:"image,omitempty"`
	Model          string   `json:"model,omitempty"`
	N              int      `json:"n,omitempty"`
	Size           string   `json:"size,omitempty"`
	ResponseFormat string   `json:"response_format,omitempty"`
}

ImageVariRequest represents the request structure for the image API.

type InnerError 

type InnerError struct {
	Code                 string               `json:"code,omitempty"`
	ContentFilterResults ContentFilterResults `json:"content_filter_result,omitempty"`
}

InnerError Azure Content filtering. Only valid for Azure OpenAI Service.

type ListBatchResponse 

type ListBatchResponse struct {
	Object  string  `json:"object"`
	Data    []Batch `json:"data"`
	FirstID string  `json:"first_id"`
	LastID  string  `json:"last_id"`
	HasMore bool    `json:"has_more"`
	// contains filtered or unexported fields
}

func (*ListBatchResponse) GetRateLimitHeaders 

func (h *ListBatchResponse) GetRateLimitHeaders() RateLimitHeaders

func (*ListBatchResponse) Header 

func (h *ListBatchResponse) Header() http.Header

func (*ListBatchResponse) SetHeader 

func (h *ListBatchResponse) SetHeader(header http.Header)

type ListFineTuningJobEventsParameter 

type ListFineTuningJobEventsParameter func(*listFineTuningJobEventsParameters)

func ListFineTuningJobEventsWithAfter 

func ListFineTuningJobEventsWithAfter(after string) ListFineTuningJobEventsParameter

func ListFineTuningJobEventsWithLimit 

func ListFineTuningJobEventsWithLimit(limit int) ListFineTuningJobEventsParameter

type LogProb 

type LogProb struct {
	Token   string  `json:"token"`
	LogProb float64 `json:"logprob"`
	Bytes   []byte  `json:"bytes,omitempty"` // Omitting the field if it is null
	// TopLogProbs is a list of the most likely tokens and their log probability, at this token position.
	// In rare cases, there may be fewer than the number of requested top_logprobs returned.
	TopLogProbs []TopLogProbs `json:"top_logprobs"`
}

LogProb represents the probability information for a token.

type LogProbs 

type LogProbs struct {
	// Content is a list of message content tokens with log probability information.
	Content []LogProb `json:"content"`
}

LogProbs is the top-level structure containing the log probability information.

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 Message 

type Message struct {
	ID          string           `json:"id"`
	Object      string           `json:"object"`
	CreatedAt   int              `json:"created_at"`
	ThreadID    string           `json:"thread_id"`
	Role        string           `json:"role"`
	Content     []MessageContent `json:"content"`
	FileIds     []string         `json:"file_ids"` //nolint:revive //backwards-compatibility
	AssistantID *string          `json:"assistant_id,omitempty"`
	RunID       *string          `json:"run_id,omitempty"`
	Metadata    map[string]any   `json:"metadata"`
	// contains filtered or unexported fields
}

func (*Message) GetRateLimitHeaders 

func (h *Message) GetRateLimitHeaders() RateLimitHeaders

func (*Message) Header 

func (h *Message) Header() http.Header

func (*Message) SetHeader 

func (h *Message) SetHeader(header http.Header)

type MessageContent 

type MessageContent struct {
	Type      string       `json:"type"`
	Text      *MessageText `json:"text,omitempty"`
	ImageFile *ImageFile   `json:"image_file,omitempty"`
}

type MessageFile 

type MessageFile struct {
	ID        string `json:"id"`
	Object    string `json:"object"`
	CreatedAt int    `json:"created_at"`
	MessageID string `json:"message_id"`
	// contains filtered or unexported fields
}

func (*MessageFile) GetRateLimitHeaders 

func (h *MessageFile) GetRateLimitHeaders() RateLimitHeaders

func (*MessageFile) Header 

func (h *MessageFile) Header() http.Header

func (*MessageFile) SetHeader 

func (h *MessageFile) SetHeader(header http.Header)

type MessageFilesList 

type MessageFilesList struct {
	MessageFiles []MessageFile `json:"data"`
	// contains filtered or unexported fields
}

func (*MessageFilesList) GetRateLimitHeaders 

func (h *MessageFilesList) GetRateLimitHeaders() RateLimitHeaders

func (*MessageFilesList) Header 

func (h *MessageFilesList) Header() http.Header

func (*MessageFilesList) SetHeader 

func (h *MessageFilesList) SetHeader(header http.Header)

type MessageRequest 

type MessageRequest struct {
	Role     string         `json:"role"`
	Content  string         `json:"content"`
	FileIds  []string       `json:"file_ids,omitempty"` //nolint:revive // backwards-compatibility
	Metadata map[string]any `json:"metadata,omitempty"`
}

type MessageText 

type MessageText struct {
	Value       string `json:"value"`
	Annotations []any  `json:"annotations"`
}

type MessagesList 

type MessagesList struct {
	Messages []Message `json:"data"`

	Object  string  `json:"object"`
	FirstID *string `json:"first_id"`
	LastID  *string `json:"last_id"`
	HasMore bool    `json:"has_more"`
	// contains filtered or unexported fields
}

func (*MessagesList) GetRateLimitHeaders 

func (h *MessagesList) GetRateLimitHeaders() RateLimitHeaders

func (*MessagesList) Header 

func (h *MessagesList) Header() http.Header

func (*MessagesList) SetHeader 

func (h *MessagesList) SetHeader(header http.Header)

type Model 

type Model struct {
	CreatedAt  int64        `json:"created"`
	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"`
	// contains filtered or unexported fields
}

Model struct represents an OpenAPI model.

func (*Model) GetRateLimitHeaders 

func (h *Model) GetRateLimitHeaders() RateLimitHeaders

func (*Model) Header 

func (h *Model) Header() http.Header

func (*Model) SetHeader 

func (h *Model) SetHeader(header http.Header)

type ModelsList 

type ModelsList struct {
	Models []Model `json:"data"`
	// contains filtered or unexported fields
}

ModelsList is a list of models, including those that belong to the user or organization.

func (*ModelsList) GetRateLimitHeaders 

func (h *ModelsList) GetRateLimitHeaders() RateLimitHeaders

func (*ModelsList) Header 

func (h *ModelsList) Header() http.Header

func (*ModelsList) SetHeader 

func (h *ModelsList) SetHeader(header http.Header)

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"`
	// contains filtered or unexported fields
}

ModerationResponse represents a response structure for moderation API.

func (*ModerationResponse) GetRateLimitHeaders 

func (h *ModerationResponse) GetRateLimitHeaders() RateLimitHeaders

func (*ModerationResponse) Header 

func (h *ModerationResponse) Header() http.Header

func (*ModerationResponse) SetHeader 

func (h *ModerationResponse) SetHeader(header http.Header)

type ModifyThreadRequest 

type ModifyThreadRequest struct {
	Metadata      map[string]any `json:"metadata"`
	ToolResources *ToolResources `json:"tool_resources,omitempty"`
}

type Pagination 

type Pagination struct {
	Limit  *int
	Order  *string
	After  *string
	Before *string
}

type Permission 

type Permission struct {
	CreatedAt          int64       `json:"created"`
	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 PromptAnnotation 

type PromptAnnotation struct {
	PromptIndex          int                  `json:"prompt_index,omitempty"`
	ContentFilterResults ContentFilterResults `json:"content_filter_results,omitempty"`
}

type PromptFilterResult 

type PromptFilterResult struct {
	Index                int                  `json:"index"`
	ContentFilterResults ContentFilterResults `json:"content_filter_results,omitempty"`
}

type PurposeType 

type PurposeType string

PurposeType represents the purpose of the file when uploading. 

const (
	PurposeFineTune         PurposeType = "fine-tune"
	PurposeFineTuneResults  PurposeType = "fine-tune-results"
	PurposeAssistants       PurposeType = "assistants"
	PurposeAssistantsOutput PurposeType = "assistants_output"
	PurposeBatch            PurposeType = "batch"
)

type RateLimitHeaders 

type RateLimitHeaders struct {
	LimitRequests     int       `json:"x-ratelimit-limit-requests"`
	LimitTokens       int       `json:"x-ratelimit-limit-tokens"`
	RemainingRequests int       `json:"x-ratelimit-remaining-requests"`
	RemainingTokens   int       `json:"x-ratelimit-remaining-tokens"`
	ResetRequests     ResetTime `json:"x-ratelimit-reset-requests"`
	ResetTokens       ResetTime `json:"x-ratelimit-reset-tokens"`
}

RateLimitHeaders struct represents Openai rate limits headers.

type RawResponse 

type RawResponse struct {
	io.ReadCloser
	// contains filtered or unexported fields
}

func (*RawResponse) GetRateLimitHeaders 

func (h *RawResponse) GetRateLimitHeaders() RateLimitHeaders

func (*RawResponse) Header 

func (h *RawResponse) Header() http.Header

func (*RawResponse) SetHeader 

func (h *RawResponse) SetHeader(header http.Header)

type ReponseFormat 

type ReponseFormat struct {
	Type string `json:"type"`
}

ReponseFormat specifies the format the model must output. https://platform.openai.com/docs/api-reference/runs/createRun#runs-createrun-response_format. Type can either be text or json_object.

type RequestError 

type RequestError struct {
	HTTPStatusCode int
	Err            error
}

RequestError provides information about generic request errors.

func (*RequestError) Error 

func (e *RequestError) Error() string

func (*RequestError) Unwrap 

func (e *RequestError) Unwrap() error

type RequiredActionType 

type RequiredActionType string
const (
	RequiredActionTypeSubmitToolOutputs RequiredActionType = "submit_tool_outputs"
)

type ResetTime 

type ResetTime string

func (ResetTime) String 

func (r ResetTime) String() string

func (ResetTime) Time 

func (r ResetTime) Time() time.Time

type Response 

type Response interface {
	SetHeader(http.Header)
}

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"`
	Harassment            bool `json:"harassment"`
	HarassmentThreatening bool `json:"harassment/threatening"`
	SelfHarm              bool `json:"self-harm"`
	SelfHarmIntent        bool `json:"self-harm/intent"`
	SelfHarmInstructions  bool `json:"self-harm/instructions"`
	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"`
	Harassment            float32 `json:"harassment"`
	HarassmentThreatening float32 `json:"harassment/threatening"`
	SelfHarm              float32 `json:"self-harm"`
	SelfHarmIntent        float32 `json:"self-harm/intent"`
	SelfHarmInstructions  float32 `json:"self-harm/instructions"`
	Sexual                float32 `json:"sexual"`
	SexualMinors          float32 `json:"sexual/minors"`
	Violence              float32 `json:"violence"`
	ViolenceGraphic       float32 `json:"violence/graphic"`
}

ResultCategoryScores represents CategoryScores of Result.

type Run 

type Run struct {
	ID             string             `json:"id"`
	Object         string             `json:"object"`
	CreatedAt      int64              `json:"created_at"`
	ThreadID       string             `json:"thread_id"`
	AssistantID    string             `json:"assistant_id"`
	Status         RunStatus          `json:"status"`
	RequiredAction *RunRequiredAction `json:"required_action,omitempty"`
	LastError      *RunLastError      `json:"last_error,omitempty"`
	ExpiresAt      int64              `json:"expires_at"`
	StartedAt      *int64             `json:"started_at,omitempty"`
	CancelledAt    *int64             `json:"cancelled_at,omitempty"`
	FailedAt       *int64             `json:"failed_at,omitempty"`
	CompletedAt    *int64             `json:"completed_at,omitempty"`
	Model          string             `json:"model"`
	Instructions   string             `json:"instructions,omitempty"`
	Tools          []Tool             `json:"tools"`
	FileIDS        []string           `json:"file_ids"` //nolint:revive // backwards-compatibility
	Metadata       map[string]any     `json:"metadata"`
	Usage          Usage              `json:"usage,omitempty"`

	Temperature *float32 `json:"temperature,omitempty"`
	// The maximum number of prompt tokens that may be used over the course of the run.
	// If the run exceeds the number of prompt tokens specified, the run will end with status 'incomplete'.
	MaxPromptTokens int `json:"max_prompt_tokens,omitempty"`
	// The maximum number of completion tokens that may be used over the course of the run.
	// If the run exceeds the number of completion tokens specified, the run will end with status 'incomplete'.
	MaxCompletionTokens int `json:"max_completion_tokens,omitempty"`
	// ThreadTruncationStrategy defines the truncation strategy to use for the thread.
	TruncationStrategy *ThreadTruncationStrategy `json:"truncation_strategy,omitempty"`
	// contains filtered or unexported fields
}

func (*Run) GetRateLimitHeaders 

func (h *Run) GetRateLimitHeaders() RateLimitHeaders

func (*Run) Header 

func (h *Run) Header() http.Header

func (*Run) SetHeader 

func (h *Run) SetHeader(header http.Header)

type RunError 

type RunError string
const (
	RunErrorServerError       RunError = "server_error"
	RunErrorRateLimitExceeded RunError = "rate_limit_exceeded"
)

type RunLastError 

type RunLastError struct {
	Code    RunError `json:"code"`
	Message string   `json:"message"`
}

type RunList 

type RunList struct {
	Runs []Run `json:"data"`
	// contains filtered or unexported fields
}

RunList is a list of runs.

func (*RunList) GetRateLimitHeaders 

func (h *RunList) GetRateLimitHeaders() RateLimitHeaders

func (*RunList) Header 

func (h *RunList) Header() http.Header

func (*RunList) SetHeader 

func (h *RunList) SetHeader(header http.Header)

type RunModifyRequest 

type RunModifyRequest struct {
	Metadata map[string]any `json:"metadata,omitempty"`
}

type RunRequest 

type RunRequest struct {
	AssistantID            string         `json:"assistant_id"`
	Model                  string         `json:"model,omitempty"`
	Instructions           string         `json:"instructions,omitempty"`
	AdditionalInstructions string         `json:"additional_instructions,omitempty"`
	Tools                  []Tool         `json:"tools,omitempty"`
	Metadata               map[string]any `json:"metadata,omitempty"`

	// Sampling temperature between 0 and 2. Higher values like 0.8 are  more random.
	// lower values are more focused and deterministic.
	Temperature *float32 `json:"temperature,omitempty"`
	TopP        *float32 `json:"top_p,omitempty"`

	// The maximum number of prompt tokens that may be used over the course of the run.
	// If the run exceeds the number of prompt tokens specified, the run will end with status 'incomplete'.
	MaxPromptTokens int `json:"max_prompt_tokens,omitempty"`

	// The maximum number of completion tokens that may be used over the course of the run.
	// If the run exceeds the number of completion tokens specified, the run will end with status 'incomplete'.
	MaxCompletionTokens int `json:"max_completion_tokens,omitempty"`

	// ThreadTruncationStrategy defines the truncation strategy to use for the thread.
	TruncationStrategy *ThreadTruncationStrategy `json:"truncation_strategy,omitempty"`

	// This can be either a string or a ToolChoice object.
	ToolChoice any `json:"tool_choice,omitempty"`
	// This can be either a string or a ResponseFormat object.
	ResponseFormat any `json:"response_format,omitempty"`
}

type RunRequiredAction 

type RunRequiredAction struct {
	Type              RequiredActionType `json:"type"`
	SubmitToolOutputs *SubmitToolOutputs `json:"submit_tool_outputs,omitempty"`
}

type RunStatus 

type RunStatus string
const (
	RunStatusQueued         RunStatus = "queued"
	RunStatusInProgress     RunStatus = "in_progress"
	RunStatusRequiresAction RunStatus = "requires_action"
	RunStatusCancelling     RunStatus = "cancelling"
	RunStatusFailed         RunStatus = "failed"
	RunStatusCompleted      RunStatus = "completed"
	RunStatusIncomplete     RunStatus = "incomplete"
	RunStatusExpired        RunStatus = "expired"
	RunStatusCancelled      RunStatus = "cancelled"
)

type RunStep 

type RunStep struct {
	ID          string         `json:"id"`
	Object      string         `json:"object"`
	CreatedAt   int64          `json:"created_at"`
	AssistantID string         `json:"assistant_id"`
	ThreadID    string         `json:"thread_id"`
	RunID       string         `json:"run_id"`
	Type        RunStepType    `json:"type"`
	Status      RunStepStatus  `json:"status"`
	StepDetails StepDetails    `json:"step_details"`
	LastError   *RunLastError  `json:"last_error,omitempty"`
	ExpiredAt   *int64         `json:"expired_at,omitempty"`
	CancelledAt *int64         `json:"cancelled_at,omitempty"`
	FailedAt    *int64         `json:"failed_at,omitempty"`
	CompletedAt *int64         `json:"completed_at,omitempty"`
	Metadata    map[string]any `json:"metadata"`
	// contains filtered or unexported fields
}

func (*RunStep) GetRateLimitHeaders 

func (h *RunStep) GetRateLimitHeaders() RateLimitHeaders

func (*RunStep) Header 

func (h *RunStep) Header() http.Header

func (*RunStep) SetHeader 

func (h *RunStep) SetHeader(header http.Header)

type RunStepList 

type RunStepList struct {
	RunSteps []RunStep `json:"data"`

	FirstID string `json:"first_id"`
	LastID  string `json:"last_id"`
	HasMore bool   `json:"has_more"`
	// contains filtered or unexported fields
}

RunStepList is a list of steps.

func (*RunStepList) GetRateLimitHeaders 

func (h *RunStepList) GetRateLimitHeaders() RateLimitHeaders

func (*RunStepList) Header 

func (h *RunStepList) Header() http.Header

func (*RunStepList) SetHeader 

func (h *RunStepList) SetHeader(header http.Header)

type RunStepStatus 

type RunStepStatus string
const (
	RunStepStatusInProgress RunStepStatus = "in_progress"
	RunStepStatusCancelling RunStepStatus = "cancelled"
	RunStepStatusFailed     RunStepStatus = "failed"
	RunStepStatusCompleted  RunStepStatus = "completed"
	RunStepStatusExpired    RunStepStatus = "expired"
)

type RunStepType 

type RunStepType string
const (
	RunStepTypeMessageCreation RunStepType = "message_creation"
	RunStepTypeToolCalls       RunStepType = "tool_calls"
)

type SelfHarm 

type SelfHarm struct {
	Filtered bool   `json:"filtered"`
	Severity string `json:"severity,omitempty"`
}

type Sexual 

type Sexual struct {
	Filtered bool   `json:"filtered"`
	Severity string `json:"severity,omitempty"`
}

type SpeechModel 

type SpeechModel string
const (
	TTSModel1      SpeechModel = "tts-1"
	TTSModel1HD    SpeechModel = "tts-1-hd"
	TTSModelCanary SpeechModel = "canary-tts"
)

type SpeechResponseFormat 

type SpeechResponseFormat string
const (
	SpeechResponseFormatMp3  SpeechResponseFormat = "mp3"
	SpeechResponseFormatOpus SpeechResponseFormat = "opus"
	SpeechResponseFormatAac  SpeechResponseFormat = "aac"
	SpeechResponseFormatFlac SpeechResponseFormat = "flac"
	SpeechResponseFormatWav  SpeechResponseFormat = "wav"
	SpeechResponseFormatPcm  SpeechResponseFormat = "pcm"
)

type SpeechVoice 

type SpeechVoice string
const (
	VoiceAlloy   SpeechVoice = "alloy"
	VoiceEcho    SpeechVoice = "echo"
	VoiceFable   SpeechVoice = "fable"
	VoiceOnyx    SpeechVoice = "onyx"
	VoiceNova    SpeechVoice = "nova"
	VoiceShimmer SpeechVoice = "shimmer"
)

type StaticChunkingStrategy 

type StaticChunkingStrategy struct {
	MaxChunkSizeTokens int `json:"max_chunk_size_tokens"`
	ChunkOverlapTokens int `json:"chunk_overlap_tokens"`
}

type StepDetails 

type StepDetails struct {
	Type            RunStepType                 `json:"type"`
	MessageCreation *StepDetailsMessageCreation `json:"message_creation,omitempty"`
	ToolCalls       []ToolCall                  `json:"tool_calls,omitempty"`
}

type StepDetailsMessageCreation 

type StepDetailsMessageCreation struct {
	MessageID string `json:"message_id"`
}

type StreamOptions 

type StreamOptions struct {
	// If set, an additional chunk will be streamed before the data: [DONE] message.
	// The usage field on this chunk shows the token usage statistics for the entire request,
	// and the choices field will always be an empty array.
	// All other chunks will also include a usage field, but with a null value.
	IncludeUsage bool `json:"include_usage,omitempty"`
}

type SubmitToolOutputs 

type SubmitToolOutputs struct {
	ToolCalls []ToolCall `json:"tool_calls"`
}

type SubmitToolOutputsRequest 

type SubmitToolOutputsRequest struct {
	ToolOutputs []ToolOutput `json:"tool_outputs"`
}

type Thread 

type Thread struct {
	ID            string         `json:"id"`
	Object        string         `json:"object"`
	CreatedAt     int64          `json:"created_at"`
	Metadata      map[string]any `json:"metadata"`
	ToolResources ToolResources  `json:"tool_resources,omitempty"`
	// contains filtered or unexported fields
}

func (*Thread) GetRateLimitHeaders 

func (h *Thread) GetRateLimitHeaders() RateLimitHeaders

func (*Thread) Header 

func (h *Thread) Header() http.Header

func (*Thread) SetHeader 

func (h *Thread) SetHeader(header http.Header)

type ThreadAttachment 

type ThreadAttachment struct {
	FileID string                 `json:"file_id"`
	Tools  []ThreadAttachmentTool `json:"tools"`
}

type ThreadAttachmentTool 

type ThreadAttachmentTool struct {
	Type string `json:"type"`
}

type ThreadDeleteResponse 

type ThreadDeleteResponse struct {
	ID      string `json:"id"`
	Object  string `json:"object"`
	Deleted bool   `json:"deleted"`
	// contains filtered or unexported fields
}

func (*ThreadDeleteResponse) GetRateLimitHeaders 

func (h *ThreadDeleteResponse) GetRateLimitHeaders() RateLimitHeaders

func (*ThreadDeleteResponse) Header 

func (h *ThreadDeleteResponse) Header() http.Header

func (*ThreadDeleteResponse) SetHeader 

func (h *ThreadDeleteResponse) SetHeader(header http.Header)

type ThreadMessage 

type ThreadMessage struct {
	Role        ThreadMessageRole  `json:"role"`
	Content     string             `json:"content"`
	FileIDs     []string           `json:"file_ids,omitempty"`
	Attachments []ThreadAttachment `json:"attachments,omitempty"`
	Metadata    map[string]any     `json:"metadata,omitempty"`
}

type ThreadMessageRole 

type ThreadMessageRole string
const (
	ThreadMessageRoleAssistant ThreadMessageRole = "assistant"
	ThreadMessageRoleUser      ThreadMessageRole = "user"
)

type ThreadRequest 

type ThreadRequest struct {
	Messages      []ThreadMessage       `json:"messages,omitempty"`
	Metadata      map[string]any        `json:"metadata,omitempty"`
	ToolResources *ToolResourcesRequest `json:"tool_resources,omitempty"`
}

type ThreadTruncationStrategy 

type ThreadTruncationStrategy struct {
	// default 'auto'.
	Type TruncationStrategy `json:"type,omitempty"`
	// this field should be set if the truncation strategy is set to LastMessages.
	LastMessages *int `json:"last_messages,omitempty"`
}

ThreadTruncationStrategy defines the truncation strategy to use for the thread. https://platform.openai.com/docs/assistants/how-it-works/truncation-strategy.

type Tool 

type Tool struct {
	Type     ToolType            `json:"type"`
	Function *FunctionDefinition `json:"function,omitempty"`
	Strict   bool                `json:"strict,omitempty"`
}

type ToolCall 

type ToolCall struct {
	// Index is not nil only in chat completion chunk object
	Index    *int         `json:"index,omitempty"`
	ID       string       `json:"id"`
	Type     ToolType     `json:"type"`
	Function FunctionCall `json:"function"`
}

type ToolChoice 

type ToolChoice struct {
	Type     ToolType     `json:"type"`
	Function ToolFunction `json:"function,omitempty"`
}

type ToolFunction 

type ToolFunction struct {
	Name string `json:"name"`
}

type ToolOutput 

type ToolOutput struct {
	ToolCallID string `json:"tool_call_id"`
	Output     any    `json:"output"`
}

type ToolResources 

type ToolResources struct {
	CodeInterpreter *CodeInterpreterToolResources `json:"code_interpreter,omitempty"`
	FileSearch      *FileSearchToolResources      `json:"file_search,omitempty"`
}

type ToolResourcesRequest 

type ToolResourcesRequest struct {
	CodeInterpreter *CodeInterpreterToolResourcesRequest `json:"code_interpreter,omitempty"`
	FileSearch      *FileSearchToolResourcesRequest      `json:"file_search,omitempty"`
}

type ToolType 

type ToolType string
const (
	ToolTypeFunction ToolType = "function"
)

type TopLogProbs 

type TopLogProbs struct {
	Token   string  `json:"token"`
	LogProb float64 `json:"logprob"`
	Bytes   []byte  `json:"bytes,omitempty"`
}

type TranscriptionTimestampGranularity 

type TranscriptionTimestampGranularity string
const (
	TranscriptionTimestampGranularityWord    TranscriptionTimestampGranularity = "word"
	TranscriptionTimestampGranularitySegment TranscriptionTimestampGranularity = "segment"
)

type TruncationStrategy 

type TruncationStrategy string

TruncationStrategy defines the existing truncation strategies existing for thread management in an assistant.

type UploadBatchFileRequest 

type UploadBatchFileRequest struct {
	FileName string
	Lines    []BatchLineItem
}

func (*UploadBatchFileRequest) AddChatCompletion 

func (r *UploadBatchFileRequest) AddChatCompletion(customerID string, body ChatCompletionRequest)

func (*UploadBatchFileRequest) AddCompletion 

func (r *UploadBatchFileRequest) AddCompletion(customerID string, body CompletionRequest)

func (*UploadBatchFileRequest) AddEmbedding 

func (r *UploadBatchFileRequest) AddEmbedding(customerID string, body EmbeddingRequest)

func (*UploadBatchFileRequest) MarshalJSONL 

func (r *UploadBatchFileRequest) MarshalJSONL() []byte

type Usage 

type Usage struct {
	PromptTokens     int `json:"prompt_tokens"`
	CompletionTokens int `json:"completion_tokens"`
	TotalTokens      int `json:"total_tokens"`
}

Usage Represents the total token usage per request to OpenAI.

type VectorStore 

type VectorStore struct {
	ID           string               `json:"id"`
	Object       string               `json:"object"`
	CreatedAt    int64                `json:"created_at"`
	Name         string               `json:"name"`
	UsageBytes   int                  `json:"usage_bytes"`
	FileCounts   VectorStoreFileCount `json:"file_counts"`
	Status       string               `json:"status"`
	ExpiresAfter *VectorStoreExpires  `json:"expires_after"`
	ExpiresAt    *int                 `json:"expires_at"`
	Metadata     map[string]any       `json:"metadata"`
	// contains filtered or unexported fields
}

func (*VectorStore) GetRateLimitHeaders 

func (h *VectorStore) GetRateLimitHeaders() RateLimitHeaders

func (*VectorStore) Header 

func (h *VectorStore) Header() http.Header

func (*VectorStore) SetHeader 

func (h *VectorStore) SetHeader(header http.Header)

type VectorStoreDeleteResponse 

type VectorStoreDeleteResponse struct {
	ID      string `json:"id"`
	Object  string `json:"object"`
	Deleted bool   `json:"deleted"`
	// contains filtered or unexported fields
}

func (*VectorStoreDeleteResponse) GetRateLimitHeaders 

func (h *VectorStoreDeleteResponse) GetRateLimitHeaders() RateLimitHeaders

func (*VectorStoreDeleteResponse) Header 

func (h *VectorStoreDeleteResponse) Header() http.Header

func (*VectorStoreDeleteResponse) SetHeader 

func (h *VectorStoreDeleteResponse) SetHeader(header http.Header)

type VectorStoreExpires 

type VectorStoreExpires struct {
	Anchor string `json:"anchor"`
	Days   int    `json:"days"`
}

type VectorStoreFile 

type VectorStoreFile struct {
	ID            string `json:"id"`
	Object        string `json:"object"`
	CreatedAt     int64  `json:"created_at"`
	VectorStoreID string `json:"vector_store_id"`
	UsageBytes    int    `json:"usage_bytes"`
	Status        string `json:"status"`
	// contains filtered or unexported fields
}

func (*VectorStoreFile) GetRateLimitHeaders 

func (h *VectorStoreFile) GetRateLimitHeaders() RateLimitHeaders

func (*VectorStoreFile) Header 

func (h *VectorStoreFile) Header() http.Header

func (*VectorStoreFile) SetHeader 

func (h *VectorStoreFile) SetHeader(header http.Header)

type VectorStoreFileBatch 

type VectorStoreFileBatch struct {
	ID            string               `json:"id"`
	Object        string               `json:"object"`
	CreatedAt     int64                `json:"created_at"`
	VectorStoreID string               `json:"vector_store_id"`
	Status        string               `json:"status"`
	FileCounts    VectorStoreFileCount `json:"file_counts"`
	// contains filtered or unexported fields
}

func (*VectorStoreFileBatch) GetRateLimitHeaders 

func (h *VectorStoreFileBatch) GetRateLimitHeaders() RateLimitHeaders

func (*VectorStoreFileBatch) Header 

func (h *VectorStoreFileBatch) Header() http.Header

func (*VectorStoreFileBatch) SetHeader 

func (h *VectorStoreFileBatch) SetHeader(header http.Header)

type VectorStoreFileBatchRequest 

type VectorStoreFileBatchRequest struct {
	FileIDs []string `json:"file_ids"`
}

type VectorStoreFileCount 

type VectorStoreFileCount struct {
	InProgress int `json:"in_progress"`
	Completed  int `json:"completed"`
	Failed     int `json:"failed"`
	Cancelled  int `json:"cancelled"`
	Total      int `json:"total"`
}

type VectorStoreFileRequest 

type VectorStoreFileRequest struct {
	FileID string `json:"file_id"`
}

type VectorStoreFilesList 

type VectorStoreFilesList struct {
	VectorStoreFiles []VectorStoreFile `json:"data"`
	// contains filtered or unexported fields
}

func (*VectorStoreFilesList) GetRateLimitHeaders 

func (h *VectorStoreFilesList) GetRateLimitHeaders() RateLimitHeaders

func (*VectorStoreFilesList) Header 

func (h *VectorStoreFilesList) Header() http.Header

func (*VectorStoreFilesList) SetHeader 

func (h *VectorStoreFilesList) SetHeader(header http.Header)

type VectorStoreRequest 

type VectorStoreRequest struct {
	Name         string              `json:"name,omitempty"`
	FileIDs      []string            `json:"file_ids,omitempty"`
	ExpiresAfter *VectorStoreExpires `json:"expires_after,omitempty"`
	Metadata     map[string]any      `json:"metadata,omitempty"`
}

VectorStoreRequest provides the vector store request parameters.

type VectorStoreToolResources 

type VectorStoreToolResources struct {
	FileIDs          []string          `json:"file_ids,omitempty"`
	ChunkingStrategy *ChunkingStrategy `json:"chunking_strategy,omitempty"`
	Metadata         map[string]any    `json:"metadata,omitempty"`
}

type VectorStoresList 

type VectorStoresList struct {
	VectorStores []VectorStore `json:"data"`
	LastID       *string       `json:"last_id"`
	FirstID      *string       `json:"first_id"`
	HasMore      bool          `json:"has_more"`
	// contains filtered or unexported fields
}

VectorStoresList is a list of vector store.

func (*VectorStoresList) GetRateLimitHeaders 

func (h *VectorStoresList) GetRateLimitHeaders() RateLimitHeaders

func (*VectorStoresList) Header 

func (h *VectorStoresList) Header() http.Header

func (*VectorStoresList) SetHeader 

func (h *VectorStoresList) SetHeader(header http.Header)

type Violence 

type Violence struct {
	Filtered bool   `json:"filtered"`
	Severity string `json:"severity,omitempty"`
}

Source Files

View all Source files

Directories

Path Synopsis
examples
chatbot
completion
completion-with-tool
images
voice-to-text
test
test/checks
Package jsonschema provides very simple functionality for representing a JSON schema as a (nested) struct.
 Package jsonschema provides very simple functionality for representing a JSON schema as a (nested) struct.

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