# How to Use awesome‑gpt‑image‑2: Best Practices for the GPT‑Image‑2 Prompt Engine

> Master awesome-gpt-image-2 prompt engineering with best practices. Learn to set env variables, use style-library, manage prompt length, and authenticate API calls for production-ready images.

- Repository: [苍何/awesome-gpt-image-2](https://github.com/freestylefly/awesome-gpt-image-2)
- Tags: best-practices
- Published: 2026-08-27

---

**Set your environment variables, use the style‑library skill to select structured templates, keep prompts under 6000 characters, and call the `/api/generate-image` endpoint with proper JWT authentication to generate production‑ready images via the GPT‑Image‑2 model.**

The **awesome‑gpt‑image‑2** repository is a full‑stack prompt‑as‑code engine that transforms natural language intentions into optimized prompts for the GPT‑Image‑2 model. According to the source code maintained by freestylefly, it combines a curated gallery of 500+ image cases, a deterministic agent skill for prompt construction, and a credit‑managed generation API. This guide covers the architectural patterns, practical usage guidelines, and code examples you need to implement awesome‑gpt‑image‑2 effectively.

---

## Architecture Overview: Three Core Pillars

The awesome‑gpt‑image‑2 codebase is organized around three integrated components that handle discovery, generation, and prompt engineering.

| Pillar | Function | Key Source File |
|--------|----------|-----------------|
| **Web UI & Gallery** | Browse cases, user authentication, initiate generation | [`README.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/README.md) |
| **Generation API** | Auth validation, credit reservation, CIYUAN service call | [`api/generate-image.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/generate-image.js) |
| **Style Library & Agent Skill** | Taxonomy of templates, deterministic prompt assembly | [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json) & [`agents/skills/gpt-image-2-style-library/SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/agents/skills/gpt-image-2-style-library/SKILL.md) |

Understanding how these layers interact ensures you configure and extend the system correctly.

---

## Authentication and Environment Setup

### Required Environment Variables

Before running awesome‑gpt‑image‑2, populate your environment with all keys listed in the README. These variables are consumed across the stack:

```bash

# Frontend (Vite) — exposed to browser

VITE_SUPABASE_URL=https://your-project.supabase.co
VITE_SUPABASE_ANON_KEY=eyJ...

# Server‑only — never expose to client

SUPABASE_SERVICE_ROLE_KEY=eyJ...
CIYUAN_API_KEY=sk-...
STRIPE_SECRET_KEY=sk_test_...

```

**Critical security practice:** Keep `SUPABASE_SERVICE_ROLE_KEY`, `CIYUAN_API_KEY`, and Stripe secrets server‑only. The frontend uses [`src/supabaseClient.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/src/supabaseClient.js) (Vite env vars), while serverless functions access [`api/_lib/supabase.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/_lib/supabase.js) with elevated privileges.

### Supabase Client Initialization

The frontend client is instantiated in [`src/supabaseClient.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/src/supabaseClient.js):

```javascript
import { createClient } from '@supabase/supabase-js'

const supabaseUrl = import.meta.env.VITE_SUPABASE_URL
const supabaseAnonKey = import.meta.env.VITE_SUPABASE_ANON_KEY

export const supabase = createClient(supabaseUrl, supabaseAnonKey)

```

Server‑side helpers in [`api/_lib/supabase.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/_lib/supabase.js) handle JWT validation via `getAuthContext` and provide `reserveGeneration`, `reserveCreditGeneration`, `completeReservation`, and `releaseReservation` functions for the credit flow.

---

## Credit Reservation and Generation Flow

The generation pipeline in [`api/generate-image.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/generate-image.js) follows a strict transactional pattern to prevent double‑spending credits.

### Step‑by‑Step Flow

1. **Authenticate** — `getAuthContext` validates the `Authorization: Bearer <jwt>` header
2. **Reserve** — `reserveGeneration` (or `reserveCreditGeneration` for admin batch jobs) creates a row in `user_generation_reservations` via Postgres RPC
3. **Generate** — `generateImage` POSTs to the CIYUAN endpoint `/v1/images/generations`
4. **Finalize** — `completeReservation` on success, `releaseReservation` on failure

### Error Handling Patterns

The `handler` function in [`api/generate-image.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/generate-image.js) returns structured status codes:

- `502` / `503` — upstream CIYUAN service errors
- `402` — `CREDITS_REQUIRED` when balance insufficient
- `400` — prompt exceeds 6000‑character limit

Validate your integration by running `npm run dev` locally and hitting `/api/generate-image` with a minimal payload before deploying.

---

## Prompt Construction with the Style Library

The **style library** is the deterministic engine that converts user intent into optimized prompts. It is defined in [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json) and consumed by the agent skill documented in [`SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/SKILL.md).

### Structure of the Style Library

The JSON defines four hierarchical levels:

- **Categories** — broad domains (e.g., "UI/UX", "Illustration", "Photography")
- **Styles** — aesthetic approaches within a category
- **Scenes** — environmental contexts
- **Templates** — complete prompt structures with `guidance`, `pitfalls`, and `exampleCases`

### The Six‑Block Prompt Structure

According to [`agents/skills/gpt-image-2-style-library/SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/agents/skills/gpt-image-2-style-library/SKILL.md), every generated prompt must contain:

1. **Subject** — what to depict
2. **Layout/Composition** — spatial arrangement
3. **Style** — visual aesthetic reference
4. **Aspect Ratio** — output dimensions
5. **Positive Constraints** — specific requirements from `guidance`
6. **Negative Constraints** — pitfalls to avoid

### Skill Workflow

The agent skill executes deterministically:

1. Detect request language
2. Map intent → category → style → scene
3. Select highest‑scoring template (or present 2‑3 options for user choice)
4. Assemble the six‑block prompt with localized output

---

## Practical Usage Guidelines

| Practice | Implementation | Benefit |
|----------|---------------|---------|
| **Prompt length** | Trim to ≤ 6000 characters before submission | Prevents 400 Bad Request errors enforced in [`generate-image.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/generate-image.js) |
| **Credit monitoring** | Poll `/api/me` for balance; use `reserveCreditGeneration` for batch jobs | Avoids 402 errors, enables deterministic budgeting |
| **Template selection** | Prefer highest‑scoring template; offer 2‑3 options when ambiguous | Improves relevance, reduces model hallucination |
| **Guidance embedding** | Always include `guidance` block and `pitfalls` as negative constraints | Cleaner, more controllable images |
| **Localization** | Match final prompt language to request (auto‑detected by skill) | Consistent with user expectations |
| **Batch generation** | Reuse template, vary `subject`, `palette`, `scene` | Style consistency across series |
| **Pre‑deployment testing** | Run `npm run dev`, test auth → reservation → image return | Catches integration bugs early |

---

## Installation and CLI Usage

### Install the Style‑Library Skill

The skill package includes a global CLI installer:

```bash

# Global install (recommended)

npm install -g gpt-image-2-style-library

# Install into all local agents (Codex, Claude, etc.)

gpt-image-2-style-library install all

```

The install script is defined in `agents/skills/gpt-image-2-style-library/bin/install.mjs`.

### Generate Prompts from Command Line

```bash

# Example: UI screenshot system for finance dashboard

gpt-image-2-style-library \
  "Create a UI screenshot of a finance dashboard with dark theme, showing charts and a navigation bar"

```

The skill selects the **UI Screenshot System** template (`tpl-ui`) and outputs a copy‑able six‑block prompt.

---

## Direct API Integration

For programmatic access, call the generation endpoint with proper JWT authentication:

```javascript
import fetch from 'node-fetch';

const payload = {
  prompt: "UI screenshot system: finance dashboard, dark theme, 3 charts, top navigation, 16:9",
  caseId: 17  // Template ID from style-library.json
};

const res = await fetch('https://gpt-image2.canghe.ai/api/generate-image', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.VITE_SUPABASE_ANON_KEY}`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify(payload)
});

const data = await res.json();
if (data.ok) {
  console.log('Base64 image:', data.image);  // data:image/jpeg;base64,...
} else {
  console.error('Generation error:', data.error);
}

```

The handler returns a complete base64‑encoded JPEG data URI on success.

---

## Extending the Style Library

To add custom templates:

1. Edit [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json) — add new object under `templates`
2. Regenerate skill reference:
   ```bash
   npm run generate:style-skill
   ```

3. Deploy (Vercel rebuilds automatically)

---

## Summary

- **Environment configuration** is foundational — separate server‑only and client‑exposed variables per [`src/supabaseClient.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/src/supabaseClient.js) and [`api/_lib/supabase.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/_lib/supabase.js)
- **Credit flow** is transactional — authenticate, reserve, generate, commit/release via functions in [`api/generate-image.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/generate-image.js)
- **Prompt engineering** is deterministic — use the style‑library skill to enforce the six‑block structure from [`SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/SKILL.md)
- **Operational limits** — 6000‑character prompt cap, credit balance checks, and proper error handling for 402/502/503 statuses
- **Extensibility** — modify [`data/style-library.json`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json), run `npm run generate:style-skill`, and redeploy

---

## Frequently Asked Questions

### How do I resolve CREDITS_REQUIRED errors in awesome‑gpt‑image‑2?

Check your balance via `/api/me` and ensure you're not exceeding free‑generation limits. For automated workflows, use the admin endpoint `reserveCreditGeneration` instead of the standard `reserveGeneration` function to bypass restrictions.

### What is the maximum prompt length for the generate‑image endpoint?

The hard limit is **6000 characters**, enforced by validation logic in [`api/generate-image.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/generate-image.js). Exceeding this returns a 400 Bad Request error — trim verbose descriptions before submission.

### How does the style‑library skill choose between multiple matching templates?

The skill selects the highest‑scoring template based on intent→category→style→scene mapping. When confidence is ambiguous, it presents 2–3 options for user selection, as specified in [`agents/skills/gpt-image-2-style-library/SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/agents/skills/gpt-image-2-style-library/SKILL.md) step 4.

### Can I use awesome‑gpt‑image‑2 without the web UI?

Yes — install the `gpt-image-2-style-library` CLI globally, or call the `/api/generate-image` endpoint directly with a JWT token and JSON payload containing `prompt` and optional `caseId`.