# Riverflow 1

> 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

## Quick Reference

- Model ID: riverflow-1
- Creator: Sourceful
- Status: active
- Family: riverflow
- Base URL: https://api.lumenfall.ai/openai/v1

## Specifications

- Max Resolution: 1024x1024
- Max Input Images: 3
- Input Modalities: text, image
- Output Modalities: image

## Model Identifiers

- Primary Slug: riverflow-1
- Aliases: riverflow-1-standard, riverflow-1-base

## Dates


## Tags

image-generation, image-editing

## Available Providers

### Runware

- Config Key: runware/riverflow-1
- Provider Model ID: sourceful:1@1
- Pricing:
  - source: official
  - currency: USD
  - components: [{"type" => "output", "metric" => "image", "unit_price" => 0.039}]
  - source_url: https://runware.ai/pricing
  - effective_at: 2026-01-03


## Image Gallery

1 images available for this model.
- Curated examples: 1
  - "A wide, cinematic long shot of a majestic river winding through a lush valley at golden hour, the deep blue water ref..."

## Example Prompt

The following prompt was used to generate an example image in our playground:

A sun-drenched Mediterranean balcony overlooking a sparkling turquoise bay, featuring ornate white tile work and vibrant pink bougainvillea. To the side, a calm capybara rests in the dappled shade of a lemon tree, enjoying the sea breeze.

## Code Examples

### Text to Image (Generation)

#### cURL

curl -X POST \
  https://api.lumenfall.ai/openai/v1/images/generations \
  -H "Authorization: Bearer $LUMENFALL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "riverflow-1",
    "prompt": "A serene mountain landscape at sunset",
    "size": "1024x1024"
  }'

# Response:
# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

#### JavaScript

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://api.lumenfall.ai/openai/v1'
});

const response = await client.images.generate({
  model: 'riverflow-1',
  prompt: 'A serene mountain landscape at sunset',
  size: '1024x1024'
});

// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }
console.log(response.data[0].url);

#### Python

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.lumenfall.ai/openai/v1"
)

response = client.images.generate(
    model="riverflow-1",
    prompt="A serene mountain landscape at sunset",
    size="1024x1024"
)

# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }
print(response.data[0].url)

### Image Editing

#### cURL

curl -X POST \
  https://api.lumenfall.ai/openai/v1/images/edits \
  -H "Authorization: Bearer $LUMENFALL_API_KEY" \
  -F "model=riverflow-1" \
  -F "image=@source.png" \
  -F "prompt=Add a starry night sky to this image" \
  -F "size=1024x1024"

# Response:
# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

#### JavaScript

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);

#### Python

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)


## About

## Overview
Riverflow 1 is a multimodal image editing model developed by Sourceful that focuses on high-precision design tasks. It differentiates itself from standard diffusion models by integrating a vision language model (VLM) that utilizes chain-of-thought reasoning to interpret complex editing instructions. This architecture allows the model to better understand spatial relationships and specific design constraints before executing pixel-level changes.

## Strengths
*   **Instruction Adherence:** The integration of chain-of-thought reasoning helps the model follow multi-step or nuanced natural language instructions more accurately than models that rely on simple CLIP embeddings.
*   **Design-Grade Precision:** Optimized for professional workflows where maintaining the structural integrity of the original image—such as perspective, lighting, and object proportions—is critical during the editing process.
*   **Spatial Awareness:** The vision-language component excels at identifying specific regions for modification, reducing the need for manual masking or complex in-painting coordinates.
*   **Multimodal Input Flexibility:** Seamlessly processes both text prompts and reference images to perform contextual edits, such as style transfers or object replacements that match the surrounding environment.

## Limitations
*   **Processing Latency:** Because the model performs cognitive reasoning steps (chain-of-thought) before generating the output, it may have higher inference times compared to single-pass diffusion models.
*   **Stylistic Range:** While highly effective for realistic and design-oriented modifications, it may not exhibit the same level of abstract creativity as specialized artistic models when given highly open-ended or vague prompts.

## Technical Background
Riverflow 1 is built on a hybrid architecture that bridges vision-language modeling with open-weights diffusion frameworks. The core innovation involves using the VLM to generate an internal reasoning path that guides the diffusion process, effectively acting as an intelligent controller for the image generation backbone. This approach mimics a designer’s logic by first analyzing the "what" and "where" of an edit before committing to the final visual output.

## Best For
Riverflow 1 is best suited for professional product photography editing, architectural visualization updates, and marketing asset iteration where precise control over existing imagery is required. It is an excellent choice for developers building tools that require "smart" image manipulation without forcing users to learn complex prompt engineering.

You can experiment with Riverflow 1 and integrate it into your applications through Lumenfall’s unified API and interactive playground.

## Frequently Asked Questions

### How much does Riverflow 1 cost?

Riverflow 1 starts at $0.039 per image through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.

### How do I use Riverflow 1 via API?

You can use Riverflow 1 through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "riverflow-1". Code examples are available in Python, JavaScript, and cURL.

### Which providers offer Riverflow 1?

Riverflow 1 is available through Runware on Lumenfall. Lumenfall automatically routes requests to the best available provider.

### What is the maximum resolution for Riverflow 1?

Riverflow 1 supports images up to 1024x1024 resolution.

## Links

- Model Page: https://lumenfall.ai/models/sourceful/riverflow-1
- About: https://lumenfall.ai/models/sourceful/riverflow-1/about
- Providers, Pricing & Performance: https://lumenfall.ai/models/sourceful/riverflow-1/providers
- API Reference: https://lumenfall.ai/models/sourceful/riverflow-1/api
- Benchmarks: https://lumenfall.ai/models/sourceful/riverflow-1/benchmarks
- Use Cases: https://lumenfall.ai/models/sourceful/riverflow-1/use-cases
- Gallery: https://lumenfall.ai/models/sourceful/riverflow-1/gallery
- Playground: https://lumenfall.ai/playground?model=riverflow-1
- API Documentation: https://docs.lumenfall.ai