Sourceful's state-of-the-art image editing model using a vision language model with chain-of-thought reasoning combined with open weights diffusion models for design-grade precision
riverflow-1-standard API OpenAI-compatible
Integrate Riverflow 1 into your applications via Lumenfall’s OpenAI-compatible API to perform complex image editing and high-fidelity image generation. Modern diffusion workflows allow for precise visual manipulations by leveraging this model’s chain-of-thought reasoning capabilities.
https://api.lumenfall.ai/openai/v1
riverflow-1
Code Examples
Image Edit
/v1/images/editscurl -X POST \
https://api.lumenfall.ai/openai/v1/images/edits \
-H "Authorization: Bearer $LUMENFALL_API_KEY" \
-F "model=riverflow-1" \
-F "[email protected]" \
-F "prompt=Add a starry night sky to this image" \
-F "size=1024x1024"
# Response:
# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }
import OpenAI from 'openai';
import fs from 'fs';
const client = new OpenAI({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.lumenfall.ai/openai/v1'
});
const response = await client.images.edit({
model: 'riverflow-1',
image: fs.createReadStream('source.png'),
prompt: 'Add a starry night sky to this image',
size: '1024x1024'
});
// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }
console.log(response.data[0].url);
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.lumenfall.ai/openai/v1"
)
response = client.images.edit(
model="riverflow-1",
image=open("source.png", "rb"),
prompt="Add a starry night sky to this image",
size="1024x1024"
)
# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }
print(response.data[0].url)
Parameter Reference
Core Parameters
| Parameter | Type | Description | Modes |
|---|---|---|---|
prompt
|
string | Required. Edit instruction for the image |
Edit
|
Size & Layout
| Parameter | Type | Description | Modes |
|---|---|---|---|
size
|
string |
Image dimensions as WxH pixels (e.g. "1024x1024") or aspect ratio (e.g. "16:9")
WxH determines both shape and scale (aspect_ratio and resolution are ignored when size is provided). W:H format is equivalent to aspect_ratio.
|
Edit
|
aspect_ratio
|
string |
Aspect ratio of the output image (e.g. "16:9", "1:1")
Controls shape independently of scale. Use with resolution to control both. If size is also provided, size takes precedence. Any ratio is accepted and mapped to the nearest supported value.
|
Edit
|
resolution
|
string |
Output resolution tier (e.g. "1K", "4K")
Controls scale independently of shape. Higher tiers produce larger images and cost more. If size is also provided, size takes precedence for scale. Any tier is accepted and mapped to the nearest supported value.
|
Edit
|
size
Exact pixel dimensions
"1920x1080"
aspect_ratio
Shape only, default scale
"16:9"
resolution
Scale tier, preserves shape
"1K"
Priority when combined
size is most specific and always wins. aspect_ratio and resolution control shape and scale independently.
How matching works
7:1 on a model with
4:1 and 8:1,
you get 8:1.
0.5K 1K 2K 4K)
or megapixel tiers (0.25 1).
If the exact tier isn't available, you get the nearest one.
Media Inputs
| Parameter | Type | Description | Modes |
|---|---|---|---|
image
|
file |
Required.
Input image(s) to edit
Supports PNG, JPEG, WebP.
Up to 3 images per request.
|
Edit
|
Output & Format
| Parameter | Type | Description | Modes |
|---|---|---|---|
response_format
|
string |
How to return the image
url
b64_json
Default:
"url" |
Edit
|
output_format
|
string |
Output image format
png
jpeg
gif
webp
avif
Gateway converts to requested format if provider doesn't support it natively.
|
Edit
|
output_compression
|
integer | Compression level for lossy formats (JPEG, WebP, AVIF) |
Edit
|
n
|
integer |
Number of images to generate
Default:
1Gateway generates multiple images in parallel even if provider only supports 1.
|
Edit
|
Additional Parameters
Provider-specific passthrough fields, available only when the request is routed to the listed provider.
| Parameter | Type | Description | Modes |
|---|---|---|---|
|
runware
|
|||
deliveryMethod
|
string |
How Runware delivers task results.
async
sync
|
Edit
|
height
|
integer | Output height in pixels. Supported width/height pairs are constrained by the model dimension presets. |
Edit
|
includeCost
|
boolean | Include task cost in the Runware response. |
Edit
|
inputs
|
object | The unified payload wrapper for complex media assets dictating image, video or audio inference constraints. |
Edit
|
outputQuality
|
integer | Compression quality of the output. Higher values preserve quality but increase file size. |
Edit
|
outputType
|
string |
How Runware returns generated image data.
URL
base64Data
dataURI
|
Edit
|
safety
|
object | Content safety checking configuration for image generation. |
Edit
|
ttl
|
integer | Time-to-live in seconds for URL outputs. |
Edit
|
uploadEndpoint
|
string | URL where Runware uploads generated content with HTTP PUT. |
Edit
|
webhookURL
|
string | Webhook URL where Runware sends JSON responses when generation completes. |
Edit
|
width
|
integer | Output width in pixels. Supported width/height pairs are constrained by the model dimension presets. |
Edit
|
Parameter Normalization
How we handle parameters across different providers
Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:
| Behavior | What happens | Example |
|---|---|---|
passthrough |
Sent as-is to the provider | style, quality |
renamed |
Same value, mapped to the field name the provider expects | prompt |
converted |
Transformed to the provider's native format | size |
emulated |
Works even if the provider has no concept of it | n, response_format |
Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.