Name: Riverflow 2.0 Pro API: Precise AI Image Generation
Brand: magicapi
SKU: api-magicapi-high-precision-image-generator-sourceful-riverflow-2-0-pro
Availability: InStock
Author: API Market

Shashank Agarwal

# 🎨 Image Generation and Editing API with Font Control (Sourceful Riverflow 2.0 Pro)

## Overview
Riverflow 2.0 Pro is an agentic image model from Sourceful. Its developer describes it as optimized for robust, high-precision generations, with support for font control.

Send a text `instruction` to generate an image, or add up to 10 `init_images` to edit them or build a new image around them. You can pass up to 2 font files with the exact text to render in each, and up to 4 reference images that the model uses to fix fine detail. The model works in up to 3 internal reasoning iterations (`max_iterations`) before it returns. The output is a list of image URLs; the example request returned one image.

## Features
- **Text-to-image and editing**: one `instruction` field covers both generation and edits (minimum 2 characters).
- **Input images**: up to 10 `init_images` for image-to-image generation and editing.
- **Font control**: pass up to 2 font files in `font_urls` (public URLs to .ttf, .otf, .woff or .woff2 files) and the matching text strings in `font_texts` (up to 300 characters each).
- **Detail references**: up to 4 `super_resolution_refs` images that the model uses to fix fine detail in matching regions.
- **Resolutions**: `1K` (default), `2K` or `4K`.
- **Aspect ratios**: `auto` (default, the model chooses), `21:9`, `16:9`, `3:2`, `4:3`, `5:4`, `1:1`, `4:5`, `3:4`, `2:3`, `9:16`.
- **Output formats**: `webp` (default) or `png`, with an optional transparent background (`transparency`) when supported.
- **Reasoning iterations**: `max_iterations` from 1 to 3 (default 3).
- **Prompt enhancement**: `enhance_prompt` (default `false`) lets the model rewrite the instruction.
- **Safety checker**: `safety_checker` (default `true`) runs the developer's safety checker on text-to-image requests.

## Use Cases
1. **Product marketing visuals**: send a product photo and ask for a landing page, banner or social post built around it.
2. **Branded text in images**: render headlines or labels in your own brand font with `font_urls` and `font_texts`.
3. **Image edits**: change the background, scene or layout of an existing image with a plain-language instruction.
4. **Multi-image compositions**: combine several product or brand images (up to 10) into one scene.
5. **High-resolution assets**: generate at `2K` or `4K` for print and large displays.

## Visual Examples
### Example Input
Instruction: "Create a landing page mockup for this hair oil"

Input image (`init_images`):

![Example input image: a hair oil product photo](https://blog.api.market/wp-content/uploads/2026/10/riverflow-2-0-pro-input-api-market.jpg)

Settings: `resolution` `1K`, `aspect_ratio` `4:3`, `max_iterations` `3`. All other fields were left at their defaults.

### Example Output
![Riverflow 2.0 Pro output: a landing page mockup built around the hair oil product](https://blog.api.market/wp-content/uploads/2026/10/riverflow-2-0-pro-output-api-market.webp)

## Input Parameters
| Field | Type | Required | Default | Allowed values | Description |
| --- | --- | --- | --- | --- | --- |
| `instruction` | string | Yes |  | Minimum 2 characters | Generation instruction, for text-to-image or an edit |
| `init_images` | array of strings (URLs) | No | none | Up to 10 | Input images for image-to-image generation and editing |
| `super_resolution_refs` | array of strings (URLs) | No | none | Up to 4 | Reference images the model uses to fix fine detail in matching regions |
| `resolution` | string | No | `1K` | `1K`, `2K`, `4K` | Target resolution |
| `aspect_ratio` | string | No | `auto` | `auto`, `21:9`, `16:9`, `3:2`, `4:3`, `5:4`, `1:1`, `4:5`, `3:4`, `2:3`, `9:16` | Aspect ratio of the output. `auto` lets the model choose |
| `output_format` | string | No | `webp` | `webp`, `png` | Output image format. Images are generated as webp; `png` output is converted from webp |
| `font_urls` | array of strings | No | none | Up to 2 | Public URLs of font files (.ttf, .otf, .woff or .woff2) |
| `font_texts` | array of strings | No | none | Up to 300 characters each | Text strings to render, matching `font_urls` in order |
| `transparency` | boolean | No | `false` |  | Transparent background when supported |
| `enhance_prompt` | boolean | No | `false` |  | Let the model enhance the instruction |
| `max_iterations` | integer | No | `3` | 1 to 3 | Number of internal reasoning iterations |
| `safety_checker` | boolean | No | `true` |  | Enable the developer's safety checker (text-to-image) |

## Pricing
- **Pay As You Go (PAYG) pricing**: you only pay for what you use.
- **Price**: $0.013 per API unit.
- **1 API unit = $0.013. Each request uses a number of units set by its options**, and you are billed for the units the request uses:

| Options | Units per request | Price per request |
| --- | --- | --- |
| `1K` or `2K` | 15 | $0.20 |
| `4K` | 33 | $0.43 |
| `1K` or `2K` with 1 font | 18 | $0.23 |
| `1K` or `2K` with 2 fonts | 21 | $0.27 |
| `4K` with 1 font | 36 | $0.47 |
| `4K` with 2 fonts | 39 | $0.51 |

- Each font in `font_urls` / `font_texts` adds 3 units (up to 2 fonts).
- `super_resolution_refs` adds units for each region the model repairs, so the count depends on how many regions of the image match the references.
- If `resolution` is omitted it is `1K`.
- **Example cost**: the example request above (`1K`, no fonts, no references) used 15 units: 15 x $0.013 = $0.195.
- **Failed or cancelled predictions are not billed.**
- **GET requests to check prediction status** are free and don't count toward API unit usage.
- **No monthly subscription fee.**

## API Documentation

### Base URL
All API requests go to: `https://prod.api.market/api/v1/magicapi/high-precision-image-generator-sourceful-riverflow-2-0-pro`

### Authentication
Send your api.market API key in the `x-api-market-key` header:
```
x-api-market-key: YOUR_API_MARKET_KEY
```

### Asynchronous Processing
**IMPORTANT**: This API is asynchronous. The flow is:
1. Send a POST request to `/predictions`. A successful request returns **201 Created** with a prediction `id` and a `status` of `starting` or `processing`.
2. Poll GET `/predictions/{id}` with that ID.
3. Keep polling while `status` is `starting` or `processing`.
4. Stop when `status` is `succeeded` (read `output`), `failed` or `canceled` (read `error`).

The example request took about 47 seconds. A polling interval of 2 seconds and an overall timeout of 600 seconds (10 minutes) work well.

### Endpoints

#### Create a Prediction
```bash
curl -X POST "https://prod.api.market/api/v1/magicapi/high-precision-image-generator-sourceful-riverflow-2-0-pro/predictions" \
  -H "Content-Type: application/json" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY" \
  -d '{
    "version": "d46bdf05d249002bbf46683d9d1372860c309f8ceb41ad4fca8cce1180b91d8f",
    "input": {
      "instruction": "Create a landing page mockup for this hair oil",
      "init_images": [
        "https://blog.api.market/wp-content/uploads/2026/10/riverflow-2-0-pro-input-api-market.jpg"
      ],
      "resolution": "1K",
      "aspect_ratio": "4:3",
      "max_iterations": 3
    }
  }'
```

Response (201 Created):
```json
{
  "id": "tkwwtf4c59rmw0d17ypsat33ew",
  "version": "d46bdf05d249002bbf46683d9d1372860c309f8ceb41ad4fca8cce1180b91d8f",
  "status": "starting",
  "created_at": "2026-10-15T13:08:20.835Z"
}
```

#### Check Prediction Status
```bash
curl -X GET "https://prod.api.market/api/v1/magicapi/high-precision-image-generator-sourceful-riverflow-2-0-pro/predictions/{id}" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY"
```

Response when the prediction has finished (200 OK):
```json
{
  "id": "tkwwtf4c59rmw0d17ypsat33ew",
  "status": "succeeded",
  "output": [
    "https://blog.api.market/wp-content/uploads/2026/10/riverflow-2-0-pro-output-api-market.webp"
  ],
  "error": null,
  "created_at": "2026-10-15T13:08:20.835Z",
  "started_at": "2026-10-15T13:08:20.856Z",
  "completed_at": "2026-10-15T13:09:08.194Z"
}
```

`output` is a list of image URLs. The example request returned one image.

### Status Codes
- **201 Created**: prediction created (POST `/predictions`). This is the normal success response.
- **200 OK**: prediction details returned (GET `/predictions/{id}`).
- **400 Bad Request**: invalid input, for example a missing `instruction`, a `resolution` that is not in the list or `max_iterations` outside 1 to 3.
- **401 Unauthorized**: missing or invalid API key.
- **404 Not Found**: no prediction with that ID.
- **429 Too Many Requests**: rate limit exceeded.
- **500 Internal Server Error** or **503 Service Unavailable**: temporary server problem; retry later.

## Rate Limits

All plans allow 10 requests per second. Requests above that return `429 Too Many Requests`; back off before retrying and honour any `Retry-After` header. Polling a prediction with GET is free but still counts toward the per-second limit, so poll every 1 to 5 seconds rather than in a tight loop.

## Error Handling
- Check the HTTP status code of every request and read the response body for the error message.
- A prediction can also end with `status` set to `failed`; the `error` field then explains why. Failed predictions are not billed.
- Retry 429, 500 and 503 responses with exponential backoff. Fix the input before retrying a 400.

## Implementation Guide
### Example Code

#### JavaScript
```javascript
const apiKey = "YOUR_API_MARKET_KEY";
const baseUrl = "https://prod.api.market/api/v1/magicapi/high-precision-image-generator-sourceful-riverflow-2-0-pro";

async function createAndWaitForPrediction(input) {
  const response = await fetch(`${baseUrl}/predictions`, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      "x-api-market-key": apiKey
    },
    body: JSON.stringify({ version: "d46bdf05d249002bbf46683d9d1372860c309f8ceb41ad4fca8cce1180b91d8f", input })
  });

  if (response.status !== 201) {
    throw new Error(`API error: ${response.status} ${await response.text()}`);
  }

  const prediction = await response.json();
  return pollForResults(prediction.id);
}

const delay = (ms) => new Promise((resolve) => setTimeout(resolve, ms));

async function pollForResults(predictionId) {
  const maxTimeout = 600000;
  const pollInterval = 2000;
  const startTime = Date.now();

  while (Date.now() - startTime < maxTimeout) {
    const response = await fetch(`${baseUrl}/predictions/${predictionId}`, {
      headers: { "x-api-market-key": apiKey }
    });

    if (!response.ok) {
      throw new Error(`API error: ${response.status} ${await response.text()}`);
    }

    const prediction = await response.json();

    if (prediction.status === "succeeded") {
      return prediction.output;
    }

    if (prediction.status === "failed" || prediction.status === "canceled") {
      throw new Error(`Prediction ${prediction.status}: ${prediction.error || "Unknown error"}`);
    }

    await delay(pollInterval);
  }

  throw new Error("Prediction timed out after 10 minutes");
}

createAndWaitForPrediction({
  instruction: "Create a landing page mockup for this hair oil",
  init_images: [
    "https://blog.api.market/wp-content/uploads/2026/10/riverflow-2-0-pro-input-api-market.jpg"
  ],
  resolution: "1K",
  aspect_ratio: "4:3",
  max_iterations: 3
}).then((output) => console.log(output));
```

#### Python
```python
import time
import requests

API_KEY = "YOUR_API_MARKET_KEY"
BASE_URL = "https://prod.api.market/api/v1/magicapi/high-precision-image-generator-sourceful-riverflow-2-0-pro"


def create_and_wait_for_prediction(input_data):
    headers = {"Content-Type": "application/json", "x-api-market-key": API_KEY}
    response = requests.post(
        f"{BASE_URL}/predictions",
        headers=headers,
        json={"version": "d46bdf05d249002bbf46683d9d1372860c309f8ceb41ad4fca8cce1180b91d8f", "input": input_data},
    )

    if response.status_code != 201:
        raise Exception(f"API error: {response.status_code} {response.text}")

    return poll_for_results(response.json()["id"])


def poll_for_results(prediction_id):
    max_timeout = 600
    poll_interval = 2
    headers = {"x-api-market-key": API_KEY}
    start_time = time.time()

    while time.time() - start_time < max_timeout:
        response = requests.get(f"{BASE_URL}/predictions/{prediction_id}", headers=headers)

        if response.status_code != 200:
            raise Exception(f"API error: {response.status_code} {response.text}")

        prediction = response.json()

        if prediction["status"] == "succeeded":
            return prediction["output"]

        if prediction["status"] in ("failed", "canceled"):
            raise Exception(f"Prediction {prediction['status']}: {prediction.get('error') or 'Unknown error'}")

        time.sleep(poll_interval)

    raise Exception("Prediction timed out after 10 minutes")


print(create_and_wait_for_prediction({
    "instruction": "Create a landing page mockup for this hair oil",
    "init_images": [
        "https://blog.api.market/wp-content/uploads/2026/10/riverflow-2-0-pro-input-api-market.jpg"
    ],
    "resolution": "1K",
    "aspect_ratio": "4:3",
    "max_iterations": 3,
}))
```

## FAQ
- **How do I render text in my own font?**
  - Put up to 2 public font file URLs (.ttf, .otf, .woff or .woff2) in `font_urls` and the text for each font, in the same order, in `font_texts` (up to 300 characters each). Mention the text in your `instruction` too. Each font adds 3 units to the request.
- **How much does a request cost?**
  - A `1K` or `2K` image uses 15 units ($0.195) and a `4K` image uses 33 units ($0.429). Fonts add 3 units each, and `super_resolution_refs` adds units for each region the model repairs.
- **Can I edit an existing image?**
  - Yes. Pass it in `init_images` (up to 10 images) and describe the change in `instruction`.
- **What are `super_resolution_refs` for?**
  - They are reference images (up to 4) that the model uses to fix fine detail in regions of the output that match them. Each repaired region adds units, so the cost depends on how many regions match.
- **Why does a request take close to a minute?**
  - The model runs up to `max_iterations` internal reasoning iterations (default 3). Lower it to 1 for fewer iterations. The example request took about 47 seconds.
- **What if my prediction fails?**
  - Failed predictions are not billed. Read the `error` field, adjust the input and try again.

## Contact Us
If you have any questions or need assistance, you can reach out to us through the embedded chat on the bottom right corner of the page or send an email to hello@magicapi.com.


Riverflow 2.0 Pro API by Sourceful: generate and edit images from text and up to 10 reference images, with custom fonts for exact text, at 1K, 2K or 4K.