For developers building AI art platforms or Print-on-Demand (POD) services, relying on a Discord bot is not a scalable strategy. Reverse-engineering Discord interactions is fragile, and manual session management kills productivity.
LegNext offers the ultimate solution: a stable, production-ready Midjourney API wrapped in our official SDKs. We bridge the gap between your code and Midjourney v7, allowing you to automate Text-to-Image generation, Upscaling, and Variations without ever touching a Discord server.
Full Feature Support: Imagine, Blend, and Describe
Our SDKs provide native access to the entire suite of Midjourney features, ensuring you don't miss out on the latest capabilities:
Prompt Generation: Support for all parameters including --ar (Aspect Ratio), --stylize, and --chaos.
Advanced Modes: Full support for Zoom Out, Panning, and Vary (Region) endpoints.
Model Versatility: Switch seamlessly between Midjourney v7 and raw modes using typed parameters.
Image Analysis: Use the /describe endpoint programmatically to reverse-engineer prompts from images.
Engineering Excellence: Asynchronous & Webhooks
High-quality AI image generation takes time. Our SDKs are engineered to handle the asynchronous nature of the Midjourney API:
Non-Blocking Workflow: Native async/await support in Python and Node.js prevents your application from freezing while waiting for GPU rendering.
Smart Polling & Webhooks: Eliminate the need to manually query task status. The SDK handles polling internally, or you can configure Webhooks to receive a JSON payload instantly when the image is ready.
JSON Structured Responses: Get clean, parsed data (Image URLs, Seed IDs, Job IDs) instead of parsing raw Discord strings.
Implementation: Automated Print-on-Demand Pipeline
Here is a Python (Async) example showing a complete workflow: generating a pattern, ensuring it meets high-resolution standards, and fetching the result.
import os
import asyncio
from legnext import AsyncClient, MidjourneyError
async def main():
# Initialize the Midjourney API Client
client = AsyncClient(api_key=os.getenv("LEGNEXT_API_KEY"))
try:
print(" Starting AI Art Generation Task...")
# 1. Imagine: Create a T-shirt design with specific aspect ratio
imagine_task = await client.midjourney.imagine(
prompt="Retro vaporwave sunset, vector style, white background --ar 2:3 --v 6.0",
mode="fast" # Supports 'fast', 'relax', or 'turbo'
)
# SDK auto-polls until the grid is ready
grid_result = await imagine_task.wait_for_completion()
print(f" Grid Generated: {grid_result.job_id}")
# 2. Upscale: Select the best version (e.g., Image #2) for high-res output
upscale_task = await client.midjourney.upscale(
job_id=grid_result.job_id,
index=2
)
final_image = await upscale_task.wait_for_completion()
print(f" High-Res Image Ready for Download: {final_image.url}")
except MidjourneyError as e:
print(f" Generation Failed: {e.code} - {e.message}")
if __name__ == "__main__":
asyncio.run(main())
Scale Your Business with Type Safety
Commercial Scale: Our Go and Java SDKs feature connection pooling designed for high-concurrency SaaS applications, allowing you to process thousands of generations per minute.
Validation: Stop wasting credits on failed prompts. The SDK validates inputs (like invalid --ar ratios) locally before sending requests to the Midjourney API.
Closing: The Standard for AI Image Integration
LegNext provides the robust infrastructure you need to integrate Midjourney's AI generation capabilities into your product.
📚 API Docs: docs.legnext.ai/sdk