Nano Banana 2 Image Generation&Editing

The user needs an Atlas Cloud API key. Guide them to: 1. Sign up at https://www.atlascloud.ai 2. Go to Console → API Keys → Create new key 3. Set environment variable: export ATLASCLOUD_API_KEY="your-key"

Script Usage

This skill includes a Python script for image generation. Zero external dependencies required.

#### List available image models

python scripts/generate_image.py list-models

#### Generate an image

python scripts/generate_image.py generate \
  --model "MODEL_ID" \
  --prompt "Your prompt here" \
  --output ./output

#### Upload a local image (for editing)

python scripts/generate_image.py upload ./local-image.jpg

#### Edit an image

python scripts/generate_image.py generate \
  --model "MODEL_ID" \
  --prompt "Edit instruction" \
  --image "https://...uploaded-url..."

Run python scripts/generate_image.py generate --help for all options. Extra model params can be passed as key=value (e.g. aspect_ratio=16:9 resolution=2k).

Text-to-Image Generation

Parameters:

| Parameter | Type | Required | Default | Options | |-----------|------|----------|---------|---------| | prompt | string | Yes | - | Text description of the image | | aspect_ratio | string | No | 1:1 | 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9 | | resolution | string | No | 1k | 1k, 2k, 4k | | output_format | string | No | png | png, jpeg | | seed | integer | No | random | For reproducible results |

Workflow — submit, poll, download:

# Step 1: Submit generation request
curl -s -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/nano-banana-2/text-to-image",
    "prompt": "A serene Japanese garden with cherry blossoms",
    "aspect_ratio": "16:9",
    "resolution": "2k"
  }'
Response: { "code": 0, "data": { "id": "prediction-id" } }
Step 2: Poll for result (repeat until status is "completed" or "succeeded")
curl -s "https://api.atlascloud.ai/api/v1/model/prediction/{prediction-id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"
Response when done: { "code": 0, "data": { "status": "completed", "outputs": ["https://...image-url..."] } }
Step 3: Download the image
curl -o output.png "IMAGE_URL_FROM_OUTPUTS"

When implementing this workflow programmatically:

Uploading Local Images

To use local images for editing, first upload them to get a URL. The agent MUST confirm with the user before uploading any local file (e.g., "I'll upload /path/to/image.jpg to Atlas Cloud for editing. Proceed?").

curl -s -X POST "https://api.atlascloud.ai/api/v1/model/uploadMedia" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -F "file=@/path/to/local/image.jpg"
Returns: { "code": 200, "data": { "download_url": "https://...url...", "filename": "image.jpg", "size": 123456 } }

Use the returned download_url as the image URL in the images array for editing requests.

> Note: Uploaded files are for temporary use with Atlas Cloud generation tasks only. URLs may expire after a period of time.

Image Editing

Same workflow as text-to-image, but with additional images parameter:

| Parameter | Type | Required | Default | Options | |-----------|------|----------|---------|---------| | prompt | string | Yes | - | Editing instruction | | images | array of strings | Yes | - | 1-14 image URLs to edit | | aspect_ratio | string | No | - | Same options as above | | resolution | string | No | 1k | 1k, 2k, 4k |

curl -s -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/nano-banana-2/edit",
    "prompt": "Change the sky to a dramatic sunset",
    "images": ["https://example.com/photo.jpg"],
    "resolution": "2k"
  }'

Using Atlas Cloud MCP Tools (if available)

If the user has the Atlas Cloud MCP server configured, use the built-in tools directly:

# Quick generate
atlas_quick_generate(model_keyword="nano banana 2", type="Image", prompt="...")
Or with specific model
atlas_generate_image(model="google/nano-banana-2/text-to-image", params={...})
Check result
atlas_get_prediction(prediction_id="...")