Image Generation

resp, err := client.NewResponses(
    context.Background(),
    &responses.Request{
        Model:        "OpenAI/gpt-4.1-mini",
        Instructions: utils.Ptr("Describe this image"),
        Input: responses.InputUnion{
            OfInputMessageList: responses.InputMessageList{
                {
                    OfEasyInput: &responses.EasyMessage{
                        Role: constants.RoleUser,
                        Content: responses.EasyInputContentUnion{
                            OfString: utils.Ptr("Describe this image"),
                        },
                    },
                },
                {
                    OfInputMessage: &responses.InputMessage{
                        Role: constants.RoleUser,
                        Content: responses.InputContent{
                            {
                                OfInputImage: &responses.InputImageContent{
                                    // or https://picsum.photos/200/300
                                    ImageURL: utils.Ptr("data:image/png;base64,yourbase64image"),
                                    Detail:   "auto",
                                },
                            },
                        },
                    },
                },
            },
        },
    },
)

resp, err := client.NewResponses(
    context.Background(),
    &responses.Request{
        Model: "OpenAI/gpt-4.1-mini",
        Input: responses.InputUnion{
            OfString: utils.Ptr("Generate a beautiful sunset over mountains"),
        },
        Tools: []responses.ToolUnion{
            {
                OfImageGeneration: &responses.ImageGenerationTool{},
            },
        },
    },
)

import (
    "context"
    "encoding/base64"
    "fmt"
    "os"
    "github.com/hastekit/hastekit-sdk-go/pkg/gateway/llm/responses"
    "github.com/hastekit/hastekit-sdk-go/pkg/utils"
)

func main() {
    // ... client initialization ...

    resp, err := client.NewResponses(context.Background(), &responses.Request{
        Model: "OpenAI/gpt-4.1-mini",
        Input: responses.InputUnion{
            OfString: utils.Ptr("Create an image of a serene lake at sunset"),
        },
        Tools: []responses.ToolUnion{
            {
                OfImageGeneration: &responses.ImageGenerationTool{},
            },
        },
    })
    if err != nil {
        panic(err)
    }

    // Process the response
    for _, output := range resp.Output {
        if output.OfImageGenerationCall != nil {
            imgCall := output.OfImageGenerationCall
            
            fmt.Printf("Image ID: %s\n", imgCall.ID)
            fmt.Printf("Status: %s\n", imgCall.Status)
            fmt.Printf("Format: %s\n", imgCall.OutputFormat)
            fmt.Printf("Size: %s\n", imgCall.Size)
            fmt.Printf("Quality: %s\n", imgCall.Quality)
            
            // Decode and save the image
            if imgCall.Result != "" {
                imageData, err := base64.StdEncoding.DecodeString(imgCall.Result)
                if err != nil {
                    panic(err)
                }
                
                filename := fmt.Sprintf("generated_image.%s", imgCall.OutputFormat)
                if err := os.WriteFile(filename, imageData, 0644); err != nil {
                    panic(err)
                }
                
                fmt.Printf("Image saved to %s\n", filename)
            }
        }
    }
}

import (
    "context"
    "encoding/base64"
    "fmt"
    "os"
    "github.com/hastekit/hastekit-sdk-go/pkg/gateway/llm/responses"
    "github.com/hastekit/hastekit-sdk-go/pkg/utils"
)

func main() {
    // ... client initialization ...

    stream, err := client.NewStreamingResponses(context.Background(), &responses.Request{
        Model: "OpenAI/gpt-4.1-mini",
        Input: responses.InputUnion{
            OfString: utils.Ptr("Generate a futuristic cityscape"),
        },
        Parameters: responses.Parameters{
            Stream: utils.Ptr(true),
        },
        Tools: []responses.ToolUnion{
            {
                OfImageGeneration: &responses.ImageGenerationTool{
                    Type: "image_generation",
                },
            },
        },
    })
    if err != nil {
        panic(err)
    }

    var imageResult *responses.ImageGenerationCallMessage

    for chunk := range stream {
        // Check for image generation progress
        if chunk.OfImageGenerationCallInProgress != nil {
            fmt.Println("Image generation started...")
        }
        
        if chunk.OfImageGenerationCallGenerating != nil {
            fmt.Println("Generating image...")
        }
        
        if chunk.OfImageGenerationCallPartialImage != nil {
            partial := chunk.OfImageGenerationCallPartialImage
            fmt.Printf("Received partial image chunk %d\n", partial.PartialImageIndex)
            
            // You can optionally decode and display partial images
            if partial.PartialImageBase64 != "" {
                // Handle partial image data if needed
            }
        }
        
        // Check for completed output items
        if chunk.ChunkType() == "response.output_item.done" {
            item := chunk.OfOutputItemDone.Item
            if item.Type == "image_generation_call" {
                // The image generation is complete
				// Final image is available in chunk.OfOutputItemDone.Result
            }
        }
    }
}