Asset Generate

Generate an image asset using Nano Banana 2: $ARGUMENTS

$ARGUMENTS should include:

• A description of the desired image (subject, mood, style)
• Optionally: asset type (hero, cover, thumbnail, social, og, banner)
• Optionally: aspect ratio, resolution, output path
• Optionally: reference image path(s) for style/subject matching
• Empty — ask the user what they want to generate

Before Starting

1. Confirm GOOGLE_GENERATIVE_AI_API_KEY is set in .env.local — if not, tell the user to add it
2. Read src/lib/config/tenant.config.ts to understand the tenant brand context
3. Read src/app/globals.css to understand the color palette and design tokens
4. Determine the appropriate asset preset from the table below

Asset Presets

If the user doesn't specify a type, infer from context or ask.

Prompt Construction — The Brief Method

Structure every prompt using this 5-part brief. Write in natural, descriptive language — NOT keyword soup. NB2 is a reasoning model that understands intent, physics, and composition.

1. SUBJECT (Who/What)

Describe the primary subject with specificity. Name materials, textures, ages, expressions.

• BAD: "a church leader"
• GOOD: "a middle-aged man with warm brown skin and short grey hair, wearing a linen shirt, gesturing passionately while speaking"

2. ACTION & RELATIONSHIPS (What's Happening)

Describe the scene dynamics — interaction between subjects, movement, energy.

• "leading a small group gathered in a circle on a sun-dappled patio"
• "hands resting on an open, well-worn Bible on a wooden table"

3. SETTING (Where, When, Atmosphere)

Place, time of day, weather, mood, cultural context.

• "in a bright, airy community hall in Melbourne, Australia, mid-morning golden light streaming through floor-to-ceiling windows"
• "an intimate home gathering, warm evening lamplight, bookshelves visible in the background"

4. STYLE & MEDIUM (Visual Language)

Name specific photographic or artistic references:

• Photography: "shot on Sony A7IV, 85mm f/1.4, shallow depth of field, natural light, warm color grading"
• Illustration: "watercolor illustration with visible brushstrokes, muted earth tones, editorial style"
• Conceptual: "minimalist flat illustration, geometric shapes, limited palette of warm terracotta and sage green"
• Abstract: "abstract texture, layered paper collage effect, warm amber and cream tones"

5. COMPOSITION & CAMERA (Framing)

Shot type, angle, lens behavior, negative space:

• "medium close-up, slightly off-center composition with rule of thirds, shallow depth of field blurring the background"
• "wide establishing shot, low angle, dramatic sky in upper third"
• "overhead flat lay, centered symmetrical composition"

Brand Context for Alan Hirsch Platform

Always incorporate these brand qualities unless the user specifies otherwise:

Tone & Mood

• Warm, scholarly, missional — not corporate, not clinical
• Community-oriented — images should feel inviting, relational, human
• Formation-focused — suggest growth, journey, transformation
• Grounded in practice — real settings, not stock-photo sterility

Color Affinity

• Warm earth tones: terracotta, amber, sage, cream, warm grey
• Accent with the platform's primary color (warm amber/gold)
• Avoid: cold blues, neon, high-saturation corporate palettes
• Dark mode assets: rich, warm darks (not pure black), warm highlights

Visual Motifs

• Open books, journals, handwritten notes
• Small group gatherings, circles, shared meals
• Urban neighborhoods, streets, community spaces
• Maps, pathways, journeys
• Natural textures: wood, linen, paper, stone

Execution

Step 1 — Compose the Prompt

Write the full NB2 prompt following the brief method above. Show it to the user for approval before generating.

Step 2 — Generate via Gemini API

Use the following script pattern (adapt as needed):

import { GoogleGenAI } from "@google/genai";
import * as fs from "fs";
import * as path from "path";

const ai = new GoogleGenAI({ apiKey: process.env.GOOGLE_GENERATIVE_AI_API_KEY });

const result = await ai.models.generateImages({
  model: "imagen-4.0-generate-001",  // Imagen 4.0
  prompt: "<THE_COMPOSED_PROMPT>",
  config: {
    numberOfImages: 4,        // Generate 4 variations
    aspectRatio: "16:9",      // From preset
    // resolution handled by model
  },
});

// Save generated images
for (let i = 0; i < result.generatedImages.length; i++) {
  const img = result.generatedImages[i];
  const buffer = Buffer.from(img.image.imageBytes, "base64");
  const outPath = path.join("public/images/generated", `${slug}-${i + 1}.png`);
  fs.mkdirSync(path.dirname(outPath), { recursive: true });
  fs.writeFileSync(outPath, buffer);
}

IMPORTANT: If the @google/genai package is not installed, install it first:

pnpm add @google/genai

If the Imagen API is not available or the user prefers the Gemini multimodal approach, use:

const response = await ai.models.generateContent({
  model: "gemini-2.5-flash-image",  // or latest available
  contents: "<THE_COMPOSED_PROMPT>. Generate this as an image.",
  config: {
    responseModalities: ["image", "text"],
  },
});

// Extract image parts from response
for (const part of response.candidates[0].content.parts) {
  if (part.inlineData) {
    const buffer = Buffer.from(part.inlineData.data, "base64");
    fs.writeFileSync(outPath, buffer);
  }
}

Step 3 — Save & Report

• Save images to public/images/generated/<asset-type>/<slug>-<n>.png
• Convert to WebP for production use if needed: use sharp or similar
• Report the file paths and let the user review

Output Format

## Asset Generation Report

### Prompt
> [The full prompt used]

### Settings
- Model: nano-banana-2
- Aspect ratio: 16:9
- Resolution: 2048
- Thinking mode: high
- Variations: 4

### Generated Files
1. public/images/generated/hero/forgotten-ways-1.png
2. public/images/generated/hero/forgotten-ways-2.png
3. public/images/generated/hero/forgotten-ways-3.png
4. public/images/generated/hero/forgotten-ways-4.png

### Next Steps
- Review the generated images and select the best one
- Use `/asset-edit` to refine if needed
- Use `/asset-text-overlay` to add text if needed

Iterative Refinement

If the first generation is close but not right, use NB2's conversational editing:

• "Make the lighting warmer and more golden"
• "Move the subject slightly to the left, more negative space on the right"
• "Reduce the saturation, make it feel more muted and scholarly"

Do NOT re-prompt from scratch — refine iteratively.

Error Handling

• Missing GOOGLE_GENERATIVE_AI_API_KEY → stop with instructions to add it to .env.local
• API rate limit → wait and retry once, then report
• Content policy block → adjust prompt (remove specific person references, etc.) and retry
• Generation failure → report error details and suggest prompt modifications