feat(gateway): add Seedream 5.0 Pro
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@@ -4,6 +4,7 @@ import (
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"context"
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"encoding/base64"
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"encoding/json"
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"fmt"
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"net/http"
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"net/http/httptest"
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"strings"
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@@ -1673,6 +1674,119 @@ func TestVolcesClientImageEditPreservesExplicitSequentialDisabledAndClampsMaxIma
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}
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}
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func TestVolcesClientSeedreamProGenerationUsesRealModelAndSingleOutput(t *testing.T) {
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var captured map[string]any
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server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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if err := json.NewDecoder(r.Body).Decode(&captured); err != nil {
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t.Fatalf("decode request: %v", err)
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}
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_ = json.NewEncoder(w).Encode(map[string]any{
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"id": "img-seedream-pro",
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"data": []any{map[string]any{"url": "https://example.com/out.png"}},
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})
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}))
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defer server.Close()
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_, err := (VolcesClient{HTTPClient: server.Client()}).Run(context.Background(), Request{
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Kind: "images.generations",
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ModelType: "image_generate",
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Model: "Seedream-5.0-Pro",
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Body: map[string]any{
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"model": "Seedream-5.0-Pro",
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"prompt": "draw a mountain",
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"resolution": "2K",
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"n": 4,
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"sequential_image_generation": "auto",
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"sequential_image_generation_options": map[string]any{"max_images": 4},
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},
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Candidate: store.RuntimeModelCandidate{
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BaseURL: server.URL,
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ModelName: "Seedream-5.0-Pro",
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ModelAlias: "Seedream-5.0-Pro",
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ProviderModelName: "doubao-seedream-5-0-pro-260628",
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Credentials: map[string]any{"apiKey": "volces-key"},
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Capabilities: map[string]any{
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"image_generate": map[string]any{
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"output_multiple_images": false,
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"output_max_images_count": 1,
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},
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},
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},
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})
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if err != nil {
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t.Fatalf("run Seedream Pro generation: %v", err)
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}
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if captured["model"] != "doubao-seedream-5-0-pro-260628" || captured["size"] != "2K" {
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t.Fatalf("Seedream Pro should use the real model and resolution size, got %+v", captured)
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}
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if captured["n"] != float64(1) {
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t.Fatalf("Seedream Pro should force single-image output, got %+v", captured)
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}
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if _, ok := captured["sequential_image_generation"]; ok {
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t.Fatalf("Seedream Pro request must not include sequential image generation, got %+v", captured)
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}
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if _, ok := captured["sequential_image_generation_options"]; ok {
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t.Fatalf("Seedream Pro request must not include sequential image options, got %+v", captured)
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}
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}
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func TestVolcesClientSeedreamProEditForwardsTenReferencesAndCustomSize(t *testing.T) {
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var captured map[string]any
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server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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if err := json.NewDecoder(r.Body).Decode(&captured); err != nil {
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t.Fatalf("decode request: %v", err)
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}
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_ = json.NewEncoder(w).Encode(map[string]any{
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"id": "img-seedream-pro-edit",
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"data": []any{map[string]any{"url": "https://example.com/out.png"}},
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})
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}))
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defer server.Close()
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images := make([]any, 10)
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for index := range images {
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images[index] = fmt.Sprintf("https://example.com/reference-%d.png", index+1)
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}
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_, err := (VolcesClient{HTTPClient: server.Client()}).Run(context.Background(), Request{
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Kind: "images.edits",
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ModelType: "image_edit",
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Model: "Seedream-5.0-Pro",
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Body: map[string]any{
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"model": "Seedream-5.0-Pro",
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"prompt": "combine the references",
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"image": images,
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"width": 1600,
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"height": 900,
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},
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Candidate: store.RuntimeModelCandidate{
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BaseURL: server.URL,
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ModelName: "Seedream-5.0-Pro",
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ModelAlias: "Seedream-5.0-Pro",
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ProviderModelName: "doubao-seedream-5-0-pro-260628",
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Credentials: map[string]any{"apiKey": "volces-key"},
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Capabilities: map[string]any{
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"image_edit": map[string]any{
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"input_multiple_images": true,
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"input_max_images_count": 10,
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"output_multiple_images": false,
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"output_max_images_count": 1,
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"input_max_file_size_bytes": 30 * 1024 * 1024,
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},
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},
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},
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})
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if err != nil {
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t.Fatalf("run Seedream Pro edit: %v", err)
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}
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gotImages, _ := captured["image"].([]any)
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if captured["model"] != "doubao-seedream-5-0-pro-260628" || captured["size"] != "1600x900" || len(gotImages) != 10 {
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t.Fatalf("Seedream Pro edit should preserve ten references and custom size, got %+v", captured)
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}
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if _, ok := captured["sequential_image_generation"]; ok {
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t.Fatalf("Seedream Pro edit must not include sequential image generation, got %+v", captured)
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}
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}
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func TestVolcesClientVideoSubmitsAndPollsTask(t *testing.T) {
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var submitPath string
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var pollPath string
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@@ -781,14 +781,22 @@ func supportsMultipleOutputs(request Request, capabilityName string) bool {
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}
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func normalizeVolcesSequentialImageGeneration(body map[string]any, request Request) {
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if !supportsMultipleOutputs(request, request.ModelType) {
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delete(body, "sequential_image_generation")
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delete(body, "sequential_image_generation_options")
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if numericValue(body["n"], 1) > 1 {
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body["n"] = 1
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}
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if numericValue(body["batch_size"], 1) > 1 {
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body["batch_size"] = 1
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}
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return
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}
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options, hasOptions := volcesSequentialImageGenerationOptions(body)
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normalizeVolcesSequentialMaxImages(options, request)
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if _, explicit := body["sequential_image_generation"]; explicit {
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return
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}
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if !supportsMultipleOutputs(request, request.ModelType) {
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return
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}
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count := requestedVolcesSequentialImageCount(body, options)
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if count <= 1 {
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return
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