legnext 0.2.1

Python SDK for Legnext AI API - Professional image and video generation using Midjourney models

Legnext Python SDK

Official Python client library for the Legnext Midjourney API - Professional image and video generation.

Installation

pip install legnext

Quick Start

from legnext import Client

# Initialize client
client = Client(api_key="your-api-key")

# Generate an image
response = client.midjourney.diffusion(
    text="a beautiful sunset over mountains"
)

# Wait for completion
result = client.tasks.wait_for_completion(response.job_id)
print(result.output.image_urls)

API Methods

Image Generation

diffusion(text, callback=None)

Create a new text-to-image generation task.

response = client.midjourney.diffusion(
    text="a serene mountain landscape at sunset",
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• text (str): Text prompt for image generation (1-8192 characters)
• callback (str, optional): Webhook URL for completion notification

Returns: TaskResponse with job_id and status

---

variation(job_id, image_no, type, remix_prompt=None, callback=None)

Create variations of a generated image.

response = client.midjourney.variation(
    job_id="original-job-id",
    image_no=0,                    # Image index (0-3)
    type=1,                        # 0=Subtle, 1=Strong
    remix_prompt="add more clouds", # Optional
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original image generation task
• image_no (int): Image number to vary (0-3)
• type (int): Variation intensity (0=Subtle, 1=Strong)
• remix_prompt (str, optional): Additional prompt for guided variation
• callback (str, optional): Webhook URL

---

upscale(job_id, image_no, type, callback=None)

Upscale a generated image.

response = client.midjourney.upscale(
    job_id="original-job-id",
    image_no=0,                    # Image index (0-3)
    type=1,                        # 0=Subtle, 1=Creative
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original image generation task
• image_no (int): Image number to upscale (0-3)
• type (int): Upscaling type (0=Subtle, 1=Creative)
• callback (str, optional): Webhook URL

---

reroll(job_id, callback=None)

Re-generate with the same prompt to get new variations.

response = client.midjourney.reroll(
    job_id="original-job-id",
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the task to reroll
• callback (str, optional): Webhook URL

---

Image Composition

blend(img_urls, aspect_ratio, callback=None)

Blend 2-5 images together.

response = client.midjourney.blend(
    img_urls=[
        "https://example.com/image1.png",
        "https://example.com/image2.png"
    ],
    aspect_ratio="1:1",  # Required: "2:3", "1:1", or "3:2"
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• img_urls (list[str]): 2-5 image URLs to blend
• aspect_ratio (str): Aspect ratio - "2:3", "1:1", or "3:2"
• callback (str, optional): Webhook URL

---

describe(img_url, callback=None)

Generate text descriptions from an image.

response = client.midjourney.describe(
    img_url="https://example.com/image.png",
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• img_url (str): URL of image to describe
• callback (str, optional): Webhook URL

---

shorten(prompt, callback=None)

Optimize and shorten a prompt.

response = client.midjourney.shorten(
    prompt="a very detailed and long prompt text that needs optimization",
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• prompt (str): Prompt to shorten (1-8192 characters)
• callback (str, optional): Webhook URL

---

Image Extension

pan(job_id, image_no, direction, scale, remix_prompt=None, callback=None)

Extend an image in a specific direction.

response = client.midjourney.pan(
    job_id="original-job-id",
    image_no=0,                    # Image index (0-3)
    direction=0,                   # 0=UP, 1=DOWN, 2=LEFT, 3=RIGHT
    scale=1.5,                     # Extension scale (1.1-3.0)
    remix_prompt="add mountains",  # Optional
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original image
• image_no (int): Image number to extend (0-3)
• direction (int): Direction to extend (0=UP, 1=DOWN, 2=LEFT, 3=RIGHT)
• scale (float): Extension scale ratio (1.1-3.0)
• remix_prompt (str, optional): Text prompt for the extended area
• callback (str, optional): Webhook URL

---

outpaint(job_id, image_no, scale, remix_prompt=None, callback=None)

Expand an image in all directions.

response = client.midjourney.outpaint(
    job_id="original-job-id",
    image_no=0,                    # Image index (0-3)
    scale=1.3,                     # Extension scale (1.1-2.0)
    remix_prompt="add forest background",  # Optional
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original image
• image_no (int): Image number to extend (0-3)
• scale (float): Extension scale ratio (1.1-2.0)
• remix_prompt (str, optional): Text prompt for the extended areas
• callback (str, optional): Webhook URL

---

Image Editing

inpaint(job_id, image_no, mask, remix_prompt=None, callback=None)

Edit specific regions of an image using a mask.

with open("mask.png", "rb") as f:
    mask_data = f.read()

response = client.midjourney.inpaint(
    job_id="original-job-id",
    image_no=0,                    # Image index (0-3)
    mask=mask_data,                # PNG mask file
    remix_prompt="add a rainbow in the sky",  # Optional
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original image
• image_no (int): Image number to edit (0-3)
• mask (bytes): Mask image (PNG) indicating regions to modify
• remix_prompt (str, optional): Text prompt for the edited region (1-8192 characters)
• callback (str, optional): Webhook URL

---

remix(job_id, image_no, remix_prompt, mode=None, callback=None)

Transform an image with a new prompt.

response = client.midjourney.remix(
    job_id="original-job-id",
    image_no=0,                    # Image index (0-3)
    remix_prompt="turn into a watercolor painting",
    mode=0,                        # Optional: 0=Low, 1=High
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original image
• image_no (int): Image number to remix (0-3)
• remix_prompt (str): New prompt for remix (1-8192 characters)
• mode (int, optional): Remix mode (0=Low, 1=High)
• callback (str, optional): Webhook URL

---

edit(job_id, image_no, canvas, img_pos, remix_prompt, mask=None, callback=None)

Edit specific areas of an image with canvas positioning.

from legnext.types import Canvas, CanvasImg, Mask, Polygon

response = client.midjourney.edit(
    job_id="original-job-id",
    image_no=0,
    canvas=Canvas(width=1024, height=1024),
    img_pos=CanvasImg(width=512, height=512, x=256, y=256),
    remix_prompt="change the sky to sunset colors",
    mask=Mask(areas=[
        Polygon(width=1024, height=1024, points=[100, 100, 500, 100, 500, 500, 100, 500])
    ]),
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original image
• image_no (int): Image number to edit (0-3)
• canvas (Canvas): Target canvas dimensions
• img_pos (CanvasImg): Image position and size on canvas
• remix_prompt (str): Edit instructions (1-8192 characters)
• mask (Mask, optional): Areas to repaint (polygon areas or mask URL)
• callback (str, optional): Webhook URL

---

upload_paint(img_url, canvas, img_pos, remix_prompt, mask, callback=None)

Advanced painting on uploaded images with canvas positioning.

from legnext.types import Canvas, CanvasImg, Mask

response = client.midjourney.upload_paint(
    img_url="https://example.com/image.png",
    canvas=Canvas(width=1024, height=1024),
    img_pos=CanvasImg(width=768, height=768, x=128, y=128),
    remix_prompt="add magical effects",
    mask=Mask(url="https://example.com/mask.png"),
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• img_url (str): URL of the image to edit
• canvas (Canvas): Target canvas dimensions
• img_pos (CanvasImg): Image position and size on canvas
• remix_prompt (str): Painting instructions (1-8192 characters)
• mask (Mask): Areas to edit (required - polygon areas or mask URL)
• callback (str, optional): Webhook URL

---

Image Enhancement

retexture(img_url, remix_prompt, callback=None)

Change textures and surfaces of an image.

response = client.midjourney.retexture(
    img_url="https://example.com/image.png",
    remix_prompt="metallic and shiny surfaces",
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• img_url (str): URL of the image to retexture
• remix_prompt (str): Texture description (1-8192 characters)
• callback (str, optional): Webhook URL

---

remove_background(img_url, callback=None)

Remove the background from an image.

response = client.midjourney.remove_background(
    img_url="https://example.com/image.png",
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• img_url (str): URL of the image to process
• callback (str, optional): Webhook URL

---

enhance(job_id, image_no, callback=None)

Enhance image quality (draft to high-res).

response = client.midjourney.enhance(
    job_id="draft-job-id",
    image_no=0,                    # Image index (0-3)
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the draft mode image
• image_no (int): Image number to enhance (0-3)
• callback (str, optional): Webhook URL

---

Video Generation

video_diffusion(prompt, video_type=None, callback=None)

Generate a video from text prompt with image URL.

# Generate video with image URL in prompt
response = client.midjourney.video_diffusion(
    prompt="https://example.com/image.png a flowing river through mountains",
    video_type=1,                  # Optional: 0=480p, 1=720p
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• prompt (str): Video generation prompt. Format: "[image_url] your prompt text" (1-8192 characters)
• video_type (int, optional): Video quality type (0: 480p, 1: 720p)
• callback (str, optional): Webhook URL

---

extend_video(job_id, video_no, prompt=None, callback=None)

Extend an existing video.

response = client.midjourney.extend_video(
    job_id="original-video-job-id",
    video_no=0,                             # Video index (0 or 1)
    prompt="continue with dramatic lighting",  # Optional
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original video task
• video_no (int): Video number to extend (0 or 1)
• prompt (str, optional): Text prompt to guide the extension (1-8192 characters)
• callback (str, optional): Webhook URL

---

video_upscale(job_id, video_no, callback=None)

Upscale a video to higher resolution.

response = client.midjourney.video_upscale(
    job_id="original-video-job-id",
    video_no=0,                    # Video index (0 or 1)
    callback="https://your-domain.com/webhook"  # Optional
)

Parameters:

• job_id (str): ID of the original video task
• video_no (int): Video number to upscale (0 or 1)
• callback (str, optional): Webhook URL

---

Task Management

tasks.get(job_id)

Get the current status of a task.

task = client.tasks.get(job_id="job-123")
print(f"Status: {task.status}")
if task.status == "completed":
    print(f"Images: {task.output.image_urls}")

---

tasks.wait_for_completion(job_id, timeout=300, poll_interval=3, on_progress=None)

Wait for a task to complete with automatic polling.

def show_progress(task):
    print(f"Status: {task.status}")

result = client.tasks.wait_for_completion(
    job_id="job-123",
    timeout=600,                   # Max wait time in seconds
    poll_interval=5,               # Check every 5 seconds
    on_progress=show_progress      # Optional callback
)

print(f"Completed! Images: {result.output.image_urls}")

Parameters:

• job_id (str): The job ID to wait for
• timeout (float, optional): Maximum time to wait in seconds (default: 300)
• poll_interval (float, optional): Time between status checks in seconds (default: 3)
• on_progress (callable, optional): Callback function called on each status check

---

Async Support

All methods are available in async form using AsyncClient:

import asyncio
from legnext import AsyncClient

async def main():
    async with AsyncClient(api_key="your-api-key") as client:
        # Generate image
        response = await client.midjourney.diffusion(
            text="a futuristic cityscape"
        )

        # Wait for completion
        result = await client.tasks.wait_for_completion(response.job_id)
        print(result.output.image_urls)

asyncio.run(main())

Batch Processing

async def generate_multiple():
    async with AsyncClient(api_key="your-api-key") as client:
        # Start multiple tasks
        tasks = [
            client.midjourney.diffusion(text=f"image prompt {i}")
            for i in range(5)
        ]
        responses = await asyncio.gather(*tasks)

        # Wait for all completions
        results = await asyncio.gather(*[
            client.tasks.wait_for_completion(r.job_id)
            for r in responses
        ])

        return results

---

Error Handling

from legnext import Client, LegnextAPIError, RateLimitError, ValidationError

client = Client(api_key="your-api-key")

try:
    response = client.midjourney.diffusion(text="a beautiful landscape")
except ValidationError as e:
    print(f"Invalid parameters: {e.message}")
except RateLimitError as e:
    print(f"Rate limit exceeded: {e.message}")
except LegnextAPIError as e:
    print(f"API error: {e.message} (status: {e.status_code})")

Exception Types:

• ValidationError (400): Invalid request parameters
• AuthenticationError (401): Invalid API key
• NotFoundError (404): Resource not found
• RateLimitError (429): Rate limit exceeded
• ServerError (5xx): Server errors
• LegnextAPIError: Base exception for all API errors

---

Requirements

• Python 3.10+
• httpx >= 0.27.0
• pydantic >= 2.0.0

---

Support

For questions or issues, please contact:

• Email: [e-mail]
• Website: https://legnext.ai

---

License

Apache License 2.0 - See LICENSE for details.