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Enable generating multiple images. Optionally stream partial images (#1251)

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## Motivation

Support OpenAI API `n` setting

## Changes

- Users can select `n` to generate more than one image with the same
prompt
- each image uses a different seed -> different results
- `stream` and `partial_images` settings can be overwritten in UI
This commit is contained in:
ciaranbor
2026-01-23 11:19:58 +00:00
committed by GitHub
parent df240f834d
commit cb9c9ee55c
6 changed files with 244 additions and 93 deletions
Download Patch File Download Diff File Expand all files Collapse all files
dashboard/src/lib/components/ImageParamsPanel.svelte
+83
View File
@@ -110,6 +110,36 @@
setImageGenerationParams({ negativePrompt: value || null });
}
function handleNumImagesChange(event: Event) {
const input = event.target as HTMLInputElement;
const value = input.value.trim();
if (value === "") {
setImageGenerationParams({ numImages: 1 });
} else {
const num = parseInt(value, 10);
if (!isNaN(num) && num >= 1) {
setImageGenerationParams({ numImages: num });
}
}
}
function handleStreamChange(enabled: boolean) {
setImageGenerationParams({ stream: enabled });
}
function handlePartialImagesChange(event: Event) {
const input = event.target as HTMLInputElement;
const value = input.value.trim();
if (value === "") {
setImageGenerationParams({ partialImages: 0 });
} else {
const num = parseInt(value, 10);
if (!isNaN(num) && num >= 0) {
setImageGenerationParams({ partialImages: num });
}
}
}
function clearSteps() {
setImageGenerationParams({ numInferenceSteps: null });
}
@@ -325,6 +355,59 @@
</div>
</div>
<!-- Number of Images (not in edit mode) -->
{#if !isEditMode}
<div class="flex items-center gap-1.5">
<span class="text-xs text-exo-light-gray uppercase tracking-wider"
>IMAGES:</span
>
<input
type="number"
min="1"
value={params.numImages}
oninput={handleNumImagesChange}
class="w-12 bg-exo-medium-gray/50 border border-exo-yellow/30 rounded px-2 py-1 text-xs font-mono text-exo-yellow text-center transition-all duration-200 hover:border-exo-yellow/50 focus:outline-none focus:border-exo-yellow/70"
/>
</div>
{/if}
<!-- Stream toggle -->
<div class="flex items-center gap-1.5">
<span class="text-xs text-exo-light-gray uppercase tracking-wider"
>STREAM:</span
>
<button
type="button"
onclick={() => handleStreamChange(!params.stream)}
class="w-8 h-4 rounded-full transition-all duration-200 cursor-pointer relative {params.stream
? 'bg-exo-yellow'
: 'bg-exo-medium-gray/50 border border-exo-yellow/30'}"
title={params.stream ? "Streaming enabled" : "Streaming disabled"}
>
<div
class="absolute top-0.5 w-3 h-3 rounded-full transition-all duration-200 {params.stream
? 'right-0.5 bg-exo-black'
: 'left-0.5 bg-exo-light-gray'}"
></div>
</button>
</div>
<!-- Partial Images (only when streaming) -->
{#if params.stream}
<div class="flex items-center gap-1.5">
<span class="text-xs text-exo-light-gray uppercase tracking-wider"
>PARTIALS:</span
>
<input
type="number"
min="0"
value={params.partialImages}
oninput={handlePartialImagesChange}
class="w-12 bg-exo-medium-gray/50 border border-exo-yellow/30 rounded px-2 py-1 text-xs font-mono text-exo-yellow text-center transition-all duration-200 hover:border-exo-yellow/50 focus:outline-none focus:border-exo-yellow/70"
/>
</div>
{/if}
<!-- Input Fidelity (edit mode only) -->
{#if isEditMode}
<div class="flex items-center gap-1.5">
dashboard/src/lib/stores/app.svelte.ts
+75 -24
View File
@@ -238,6 +238,10 @@ export interface ImageGenerationParams {
size: "512x512" | "768x768" | "1024x1024" | "1024x768" | "768x1024";
quality: "low" | "medium" | "high";
outputFormat: "png" | "jpeg";
numImages: number;
// Streaming params
stream: boolean;
partialImages: number;
// Advanced params
seed: number | null;
numInferenceSteps: number | null;
@@ -257,6 +261,9 @@ const DEFAULT_IMAGE_PARAMS: ImageGenerationParams = {
size: "1024x1024",
quality: "medium",
outputFormat: "png",
numImages: 1,
stream: true,
partialImages: 3,
seed: null,
numInferenceSteps: null,
guidance: null,
@@ -1809,12 +1816,13 @@ class AppStore {
const requestBody: Record<string, unknown> = {
model,
prompt,
n: params.numImages,
quality: params.quality,
size: params.size,
output_format: params.outputFormat,
response_format: "b64_json",
stream: true,
partial_images: 3,
stream: params.stream,
partial_images: params.partialImages,
};
if (hasAdvancedParams) {
@@ -1878,31 +1886,74 @@ class AppStore {
if (imageData && idx !== -1) {
const format = parsed.format || "png";
const mimeType = `image/${format}`;
const imageIndex = parsed.image_index ?? 0;
const numImages = params.numImages;
if (parsed.type === "partial") {
// Update with partial image and progress
const partialNum = (parsed.partial_index ?? 0) + 1;
const totalPartials = parsed.total_partials ?? 3;
this.messages[idx].content =
`Generating... ${partialNum}/${totalPartials}`;
this.messages[idx].attachments = [
{
type: "generated-image",
name: `generated-image.${format}`,
preview: `data:${mimeType};base64,${imageData}`,
mimeType,
},
];
const progressText =
numImages > 1
? `Generating image ${imageIndex + 1}/${numImages}... ${partialNum}/${totalPartials}`
: `Generating... ${partialNum}/${totalPartials}`;
this.messages[idx].content = progressText;
const partialAttachment: MessageAttachment = {
type: "generated-image",
name: `generated-image.${format}`,
preview: `data:${mimeType};base64,${imageData}`,
mimeType,
};
if (imageIndex === 0) {
// First image - safe to replace attachments with partial preview
this.messages[idx].attachments = [partialAttachment];
} else {
// Subsequent images - keep existing finals, show partial at current position
const existingAttachments =
this.messages[idx].attachments || [];
// Keep only the completed final images (up to current imageIndex)
const finals = existingAttachments.slice(0, imageIndex);
this.messages[idx].attachments = [
...finals,
partialAttachment,
];
}
} else if (parsed.type === "final") {
// Final image
this.messages[idx].content = "";
this.messages[idx].attachments = [
{
type: "generated-image",
name: `generated-image.${format}`,
preview: `data:${mimeType};base64,${imageData}`,
mimeType,
},
];
// Final image - replace partial at this position
const newAttachment: MessageAttachment = {
type: "generated-image",
name: `generated-image-${imageIndex + 1}.${format}`,
preview: `data:${mimeType};base64,${imageData}`,
mimeType,
};
if (imageIndex === 0) {
// First final image - replace any partial preview
this.messages[idx].attachments = [newAttachment];
} else {
// Subsequent images - keep previous finals, replace partial at current position
const existingAttachments =
this.messages[idx].attachments || [];
// Slice keeps indices 0 to imageIndex-1 (the previous final images)
const previousFinals = existingAttachments.slice(
0,
imageIndex,
);
this.messages[idx].attachments = [
...previousFinals,
newAttachment,
];
}
// Update progress message for multiple images
if (numImages > 1 && imageIndex < numImages - 1) {
this.messages[idx].content =
`Generating image ${imageIndex + 2}/${numImages}...`;
} else {
this.messages[idx].content = "";
}
}
}
} catch {
@@ -1983,8 +2034,8 @@ class AppStore {
formData.append("size", params.size);
formData.append("output_format", params.outputFormat);
formData.append("response_format", "b64_json");
formData.append("stream", "1"); // Use "1" instead of "true" for reliable FastAPI boolean parsing
formData.append("partial_images", "3");
formData.append("stream", params.stream ? "1" : "0");
formData.append("partial_images", params.partialImages.toString());
formData.append("input_fidelity", params.inputFidelity);
// Advanced params
src/exo/master/api.py
+1
View File
@@ -835,6 +835,7 @@ class API:
# Yield partial image event (always use b64_json for partials)
event_data = {
"type": "partial",
"image_index": chunk.image_index,
"partial_index": partial_idx,
"total_partials": total_partials,
"format": str(chunk.format),
src/exo/shared/types/worker/runner_response.py
+2
View File
@@ -30,6 +30,7 @@ class ImageGenerationResponse(BaseRunnerResponse):
image_data: bytes
format: Literal["png", "jpeg", "webp"] = "png"
stats: ImageGenerationStats | None = None
image_index: int = 0
def __repr_args__(self) -> Generator[tuple[str, Any], None, None]:
for name, value in super().__repr_args__(): # pyright: ignore[reportAny]
@@ -44,6 +45,7 @@ class PartialImageResponse(BaseRunnerResponse):
format: Literal["png", "jpeg", "webp"] = "png"
partial_index: int
total_partials: int
image_index: int = 0
def __repr_args__(self) -> Generator[tuple[str, Any], None, None]:
for name, value in super().__repr_args__(): # pyright: ignore[reportAny]
src/exo/worker/engines/image/generate.py
+82 -68
View File
@@ -75,19 +75,20 @@ def generate_image(
intermediate images, then ImageGenerationResponse for the final image.
Yields:
PartialImageResponse for intermediate images (if partial_images > 0)
ImageGenerationResponse for the final complete image
PartialImageResponse for intermediate images (if partial_images > 0, first image only)
ImageGenerationResponse for final complete images
"""
width, height = parse_size(task.size)
quality: Literal["low", "medium", "high"] = task.quality or "medium"
advanced_params = task.advanced_params
if advanced_params is not None and advanced_params.seed is not None:
seed = advanced_params.seed
base_seed = advanced_params.seed
else:
seed = random.randint(0, 2**32 - 1)
base_seed = random.randint(0, 2**32 - 1)
is_bench = getattr(task, "bench", False)
num_images = task.n or 1
generation_start_time: float = 0.0
@@ -95,7 +96,11 @@ def generate_image(
mx.reset_peak_memory()
generation_start_time = time.perf_counter()
partial_images = task.partial_images or (3 if task.stream else 0)
partial_images = (
task.partial_images
if task.partial_images is not None
else (3 if task.stream else 0)
)
image_path: Path | None = None
@@ -105,72 +110,81 @@ def generate_image(
image_path = Path(tmpdir) / "input.png"
image_path.write_bytes(base64.b64decode(task.image_data))
# Iterate over generator results
for result in model.generate(
prompt=task.prompt,
height=height,
width=width,
quality=quality,
seed=seed,
image_path=image_path,
partial_images=partial_images,
advanced_params=advanced_params,
):
if isinstance(result, tuple):
# Partial image: (Image, partial_index, total_partials)
image, partial_idx, total_partials = result
buffer = io.BytesIO()
image_format = task.output_format.upper()
if image_format == "JPG":
image_format = "JPEG"
if image_format == "JPEG" and image.mode == "RGBA":
image = image.convert("RGB")
image.save(buffer, format=image_format)
for image_num in range(num_images):
# Increment seed for each image to ensure unique results
current_seed = base_seed + image_num
yield PartialImageResponse(
image_data=buffer.getvalue(),
format=task.output_format,
partial_index=partial_idx,
total_partials=total_partials,
)
else:
image = result
for result in model.generate(
prompt=task.prompt,
height=height,
width=width,
quality=quality,
seed=current_seed,
image_path=image_path,
partial_images=partial_images,
advanced_params=advanced_params,
):
if isinstance(result, tuple):
# Partial image: (Image, partial_index, total_partials)
image, partial_idx, total_partials = result
buffer = io.BytesIO()
image_format = task.output_format.upper()
if image_format == "JPG":
image_format = "JPEG"
if image_format == "JPEG" and image.mode == "RGBA":
image = image.convert("RGB")
image.save(buffer, format=image_format)
stats: ImageGenerationStats | None = None
if is_bench:
generation_end_time = time.perf_counter()
total_generation_time = generation_end_time - generation_start_time
num_inference_steps = model.get_steps_for_quality(quality)
seconds_per_step = (
total_generation_time / num_inference_steps
if num_inference_steps > 0
else 0.0
yield PartialImageResponse(
image_data=buffer.getvalue(),
format=task.output_format,
partial_index=partial_idx,
total_partials=total_partials,
image_index=image_num,
)
else:
image = result
peak_memory_gb = mx.get_peak_memory() / (1024**3)
# Only include stats on the final image
stats: ImageGenerationStats | None = None
if is_bench and image_num == num_images - 1:
generation_end_time = time.perf_counter()
total_generation_time = (
generation_end_time - generation_start_time
)
stats = ImageGenerationStats(
seconds_per_step=seconds_per_step,
total_generation_time=total_generation_time,
num_inference_steps=num_inference_steps,
num_images=task.n or 1,
image_width=width,
image_height=height,
peak_memory_usage=Memory.from_gb(peak_memory_gb),
num_inference_steps = model.get_steps_for_quality(quality)
total_steps = num_inference_steps * num_images
seconds_per_step = (
total_generation_time / total_steps
if total_steps > 0
else 0.0
)
peak_memory_gb = mx.get_peak_memory() / (1024**3)
stats = ImageGenerationStats(
seconds_per_step=seconds_per_step,
total_generation_time=total_generation_time,
num_inference_steps=num_inference_steps,
num_images=num_images,
image_width=width,
image_height=height,
peak_memory_usage=Memory.from_gb(peak_memory_gb),
)
buffer = io.BytesIO()
image_format = task.output_format.upper()
if image_format == "JPG":
image_format = "JPEG"
if image_format == "JPEG" and image.mode == "RGBA":
image = image.convert("RGB")
image.save(buffer, format=image_format)
yield ImageGenerationResponse(
image_data=buffer.getvalue(),
format=task.output_format,
stats=stats,
image_index=image_num,
)
buffer = io.BytesIO()
image_format = task.output_format.upper()
if image_format == "JPG":
image_format = "JPEG"
if image_format == "JPEG" and image.mode == "RGBA":
image = image.convert("RGB")
image.save(buffer, format=image_format)
yield ImageGenerationResponse(
image_data=buffer.getvalue(),
format=task.output_format,
stats=stats,
)
src/exo/worker/runner/runner.py
+1 -1
View File
@@ -612,7 +612,7 @@ def _process_image_response(
command_id=command_id,
model_id=shard_metadata.model_card.model_id,
event_sender=event_sender,
image_index=response.partial_index if is_partial else image_index,
image_index=response.image_index,
is_partial=is_partial,
partial_index=response.partial_index if is_partial else None,
total_partials=response.total_partials if is_partial else None,