Legnext Midjourney

Generate professional AI images using Midjourney's capabilities through the Legnext API.

Setup

CRITICAL: This skill requires a Legnext API key. Before running, check if the user has configured their API key:

Check for existing configuration:

• Look for a

  .env

  file in the project directory or parent directories
• Check for

  LEGNEXT_API_KEY=<key>

  in the

  .env

  file
• Or check environment variable:

  echo $LEGNEXT_API_KEY

If not found, inform the user they need to:

Option 1: Create a .env file (recommended)

# Create .env file in the project root
echo "LEGNEXT_API_KEY=your-api-key-here" > .env

Option 2: Set environment variable

export LEGNEXT_API_KEY=your-api-key-here

Get an API key from:

https://legnext.ai/app/api-keys

Verify API key:

python scripts/verify_api_key.py

The scripts will automatically detect the

.env

file and provide clear error messages if the API key is missing or invalid.

Quick Start

For simple image generation requests:

python scripts/generate_and_wait.py "a beautiful sunset over mountains --v 7 --ar 16:9"

This handles the complete workflow: submit task → poll status → return results.

Complete Workflow

1. Understand the User's Request

Identify what type of image the user wants:

• Subject matter (people, landscapes, objects, abstract)
• Style (photographic, illustrated, artistic)
• Mood and atmosphere
• Technical requirements (aspect ratio, quality)

2. Craft the Prompt

Transform the user's natural language request into an effective Midjourney prompt.

Use the 7-Element Framework for systematic prompts:

• Subject, Medium, Environment, Lighting, Color, Mood, Composition

Quick structure:

[Subject] [Description] [Environment] [Lighting] [Style] [Parameters]

Example transformations:

User request: "I need a professional headshot" → Prompt:

professional headshot, studio lighting, neutral background, sharp focus, 85mm lens --ar 2:3 --style raw

User request: "Create a cyberpunk city scene" → Prompt:

cyberpunk city at night, neon lights, flying cars, rain-soaked streets, cinematic, blade runner aesthetic --ar 16:9

Key principles:

• Be specific about what you want to SEE (not abstract concepts)
• Front-load important elements
• Trust V7's default quality — avoid junk words (4K, HDR, award-winning)
• Use

  --style raw

  for photorealism

For the complete 7-Element Framework and advanced techniques, see

references/prompt_engineering.md

. For photography terminology (camera, lighting, film stocks), see

references/photography.md

.

3. Add Midjourney Parameters

Append parameters to optimize the generation:

Common parameters:

• --v 7

  - Use Midjourney v7 (recommended)

• --ar 16:9

  - Aspect ratio (1:1, 16:9, 9:16, 3:2, etc.)

• --s 500

  - Stylization level (0-1000)

• --q 1

  - Quality (0.25, 0.5, 1, 2)

• --chaos 20

  - Variation amount (0-100)

Example:

a majestic lion in savanna --v 7 --ar 16:9 --s 500 --q 1

For complete parameter reference, consult

references/midjourney_parameters.md

.

4. Submit and Monitor

Use the appropriate script based on your needs:

Option A: Complete workflow (recommended)

python scripts/generate_and_wait.py "your prompt here"

This automatically:

• Submits the task to Legnext API
• Polls every 5 seconds for status updates
• Returns final results when complete
• Times out after 5 minutes if not completed

Option B: Manual control

Submit task:

python scripts/imagine.py "your prompt here"
# Returns: {"job_id": "uuid", "status": "pending"}

Check status:

python scripts/get_task.py <job_id>
# Returns: {"status": "processing|completed|failed", "output": {...}}

5. Handle Results

When the task completes successfully:

Output structure:

{
  "job_id": "uuid",
  "status": "completed",
  "output": {
    "images": ["url1", "url2", "url3", "url4"],
    "seed": 123456789
  }
}

Typically 4 image variations are generated.

Present the image URLs to the user. Images are:

• Accessible via HTTPS URLs
• Stored temporarily (download if needed for permanent storage)
• Usually high resolution

If the user wants variations of a specific result, note the

seed

value and include

--seed <value>

in future prompts for consistency.

Common Usage Patterns

Pattern 1: Single Image Request

User: "Generate a photo of a coffee shop interior"

Response workflow:

1. Craft prompt:

   cozy coffee shop interior, wooden furniture, plants, warm lighting, customers, rustic decor --ar 16:9 --v 7

2. Run:

   python scripts/generate_and_wait.py "..."

3. Present the 4 generated image URLs
4. Ask if they'd like variations or adjustments

Pattern 2: Specific Style Request

User: "Create a logo design for a tech startup"

Response workflow:

1. Craft prompt:

   minimalist logo design for tech startup, modern, clean lines, geometric, professional, simple icon --v 7 --ar 1:1 --s 250

2. Generate and present results
3. If needed, iterate with

   --seed

   for consistency

Pattern 3: Batch Generation

User: "I need several variations of a mountain landscape"

Response workflow:

1. Generate first set:

   majestic mountain landscape, snow peaks, alpine lake, dramatic sky --ar 16:9 --v 7

2. Use different

   --chaos

   or

   --seed

   values for variations
3. Or adjust prompt slightly for different moods/times of day

Pattern 4: Iterative Refinement

User: "The image is too dark, can you make it brighter?"

Response workflow:

1. Add lighting keywords: "bright, well-lit, sunny, vibrant colors"
2. Keep successful elements from original prompt
3. Adjust

   --s

   (stylization) if needed
4. Use original

   --seed

   with modifications for consistency

Troubleshooting

API Key Issues

Error: LEGNEXT_API_KEY environment variable not set

→ User needs to set:

export LEGNEXT_API_KEY=their_key

Task Timeout

Error: Task did not complete within 300 seconds

→ Complex prompts may take longer. Manually check with

get_task.py <job_id>

Failed Tasks

Status: failed

→ Common causes:

• Invalid prompt (too short/long, forbidden content)
• Insufficient credits in Legnext account
• Invalid parameter combinations Check error details in the response

Generation Quality Issues

If results don't match expectations:

• Add more descriptive keywords
• Adjust

  --s

  (stylization) parameter
• Try different versions (

  --v 6

  vs

  --v 7

  )
• Consult

  references/prompt_engineering.md

  for techniques

Advanced Features

Using Reference Images

Include image URLs in prompts:

https://example.com/reference.jpg a painting in this style --v 7

Negative Prompting

Exclude unwanted elements:

a bedroom interior --no clutter --no windows --v 7

Multi-Prompting

Weight different concepts:

cat::2 dog::1 playing together --v 7

This emphasizes "cat" twice as much as "dog".

Consistent Seeds

For variations of the same concept:

1. Note the seed from a successful generation
2. Use

   --seed <value>

   in subsequent prompts
3. Modify other aspects while maintaining consistency

Reference Documentation

• Midjourney Parameters: See

  references/midjourney_parameters.md

  for complete parameter list and usage
• Prompt Engineering: See

  references/prompt_engineering.md

  for advanced techniques and patterns
• API Reference: See

  references/api_reference.md

  for detailed API documentation

Scripts

This skill provides four Python scripts:

1. verify_api_key.py - Verify API key

   • Check API key validity and account balance
   • Usage:

     python scripts/verify_api_key.py

2. generate_and_wait.py - Complete workflow (recommended)

   • Submits task and waits for completion
   • Usage:

     python scripts/generate_and_wait.py "prompt"

3. imagine.py - Submit generation task

   • Returns job_id immediately
   • Usage:

     python scripts/imagine.py "prompt"

4. get_task.py - Check task status

   • Query any task by job_id
   • Usage:

     python scripts/get_task.py <job_id>

All scripts require

LEGNEXT_API_KEY

environment variable.

Best Practices

1. Start with clear descriptions - More detail usually produces better results
2. Use appropriate aspect ratios - Match the intended use case
3. Iterate based on results - Refine prompts based on what works
4. Save successful prompts - Build a library of effective patterns
5. Mind the credits - Each generation consumes Legnext API points
6. Download important images - Temporary storage may expire

Notes

• Generation typically takes 30-80 seconds
• Initial wait: 10s before first status check
• Polling: Every 5s, timeout after 3 minutes
• Each request usually generates 4 image variations
• Images are temporarily stored; download for permanent use
• API usage is tracked via points system in Legnext dashboard