bria-aiUse when generating visual assets with Bria.ai - product photos, hero images, icons, backgrounds. Includes batch generation (multiple images concurrently), pipeline workflows (generate โ edit โ remove background), and parallel API patterns. Use for websites, presentations, e-commerce catalogs, or any task needing multiple AI-generated images.
Install via ClawdBot CLI:
clawdbot install galbria/bria-aiGenerate production-ready visual assets for websites, presentations, documents, and applications using Bria's commercially-safe AI models.
| Need | Capability | Use Case |
|------|------------|----------|
| Create new images | FIBO Generate | Hero images, product shots, illustrations |
| Edit by text | FIBO-Edit | Change colors, modify objects, transform scenes |
| Edit with mask | GenFill/Erase | Precise inpainting, add/replace specific regions |
| Add/Replace/Remove objects | Text-based editing | Add vase, replace apple with pear, remove table |
| Transparent backgrounds | RMBG-2.0 | Extract subjects for overlays, logos, cutouts |
| Background operations | Replace/Blur/Erase | Change, blur, or remove backgrounds |
| Expand images | Outpainting | Extend boundaries, change aspect ratios |
| Upscale images | Super Resolution | Increase resolution 2x or 4x |
| Enhance quality | Enhancement | Improve lighting, colors, details |
| Transform style | Restyle | Oil painting, anime, cartoon, 3D render |
| Change lighting | Relight | Golden hour, spotlight, dramatic lighting |
| Change season | Reseason | Spring, summer, autumn, winter |
| Blend/composite | Image Blending | Apply textures, logos, merge images |
| Text replacement | Rewrite | Change text in images |
| Restore photos | Restoration | Fix old/damaged photos |
| Colorize | Colorization | Add color to B&W, or convert to B&W |
| Sketch to photo | Sketch2Image | Convert drawings to realistic photos |
| Product photography | Lifestyle Shot | Place products in scenes |
curl -X POST "https://engine.prod.bria-api.com/v2/image/generate" \
-H "api_token: $BRIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "your description",
"aspect_ratio": "16:9"
}'Aspect ratios: 1:1 (square), 16:9 (hero/banner), 4:3 (presentation), 9:16 (mobile/story), 3:4 (portrait)
Advanced: For precise, deterministic control over generation, use VGL structured prompts instead of natural language. VGL defines every visual attribute (objects, lighting, composition) as explicit JSON.
curl -X POST "https://engine.prod.bria-api.com/v2/image/edit/remove_background" \
-H "api_token: $BRIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{"image": "https://..."}'Returns PNG with transparency.
Edit any image with natural language instructions:
curl -X POST "https://engine.prod.bria-api.com/v2/image/edit" \
-H "api_token: $BRIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"images": ["https://..."],
"instruction": "change the mug to red"
}'Python example:
from bria_client import BriaClient
client = BriaClient()
result = client.edit_image(image_url, "change the mug to red")
print(result['result']['image_url'])For precise control over which region to edit:
curl -X POST "https://engine.prod.bria-api.com/v2/image/edit/gen_fill" \
-H "api_token: $BRIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://...",
"mask": "https://...",
"prompt": "what to generate in masked area"
}'Extend image boundaries to new aspect ratio:
curl -X POST "https://engine.prod.bria-api.com/v2/image/edit/expand" \
-H "api_token: $BRIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "base64-or-url",
"aspect_ratio": "16:9",
"prompt": "coffee shop background, wooden table"
}'Increase image resolution 2x or 4x:
curl -X POST "https://engine.prod.bria-api.com/v2/image/edit/increase_resolution" \
-H "api_token: $BRIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{"image": "https://...", "scale": 2}'Place a product in a lifestyle scene:
curl -X POST "https://engine.prod.bria-api.com/v2/image/edit/lifestyle_shot_by_text" \
-H "api_token: $BRIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://product-with-transparent-bg.png",
"prompt": "modern kitchen countertop, natural morning light"
}'Generate wide banner images for landing pages:
{
"prompt": "Modern tech startup workspace with developers collaborating, bright natural lighting, clean minimal aesthetic",
"aspect_ratio": "16:9",
"negative_prompt": "cluttered, dark, low quality"
}Tips for hero images:
16:9 for full-width bannersGenerate e-commerce style product shots:
{
"prompt": "Professional product photo of [item] on white studio background, soft shadows, commercial photography lighting",
"aspect_ratio": "1:1"
}Then remove background for transparent PNG to composite anywhere:
{"image": "generated_image_url"}Generate slides-ready images:
{
"prompt": "Abstract visualization of data analytics, blue and purple gradient, modern corporate style, clean composition with space for text",
"aspect_ratio": "16:9"
}Common presentation themes:
Generate report or article images:
{
"prompt": "Isometric illustration of cloud computing infrastructure, flat design, vibrant colors, white background",
"aspect_ratio": "4:3"
}For icons, generate then remove background:
{
"prompt": "3D icon of a shield with checkmark, glossy material, soft gradient background, app icon style",
"aspect_ratio": "1:1"
}Then use RMBG-2.0 to get transparent PNG.
Instagram post (1:1):
{
"prompt": "Lifestyle photo of coffee and laptop on wooden desk, morning light, cozy atmosphere",
"aspect_ratio": "1:1"
}Story/Reel (9:16):
{
"prompt": "Vertical product showcase of smartphone, floating in gradient background, tech aesthetic",
"aspect_ratio": "9:16"
}Add these for polished results:
Exclude unwanted elements:
All endpoints return async responses:
{
"request_id": "uuid",
"status_url": "https://engine.prod.bria-api.com/v2/status/uuid"
}Poll the status_url until status: "COMPLETED", then get result.image_url.
import requests, time
def get_result(status_url, api_key):
while True:
r = requests.get(status_url, headers={"api_token": api_key})
data = r.json()
if data["status"] == "COMPLETED":
return data["result"]["image_url"]
if data["status"] == "FAILED":
raise Exception(data.get("error"))
time.sleep(2)For generating many images efficiently, launch requests in parallel and poll concurrently:
import asyncio
import aiohttp
async def generate_image(session, api_key, prompt, aspect_ratio="1:1"):
"""Launch a single generation request."""
async with session.post(
"https://engine.prod.bria-api.com/v2/image/generate",
headers={"api_token": api_key, "Content-Type": "application/json"},
json={"prompt": prompt, "aspect_ratio": aspect_ratio}
) as resp:
return await resp.json()
async def poll_status(session, api_key, status_url, timeout=120):
"""Poll until complete or failed."""
for _ in range(timeout // 2):
async with session.get(status_url, headers={"api_token": api_key}) as resp:
data = await resp.json()
if data["status"] == "COMPLETED":
return data["result"]["image_url"]
if data["status"] == "FAILED":
raise Exception(data.get("error", "Generation failed"))
await asyncio.sleep(2)
raise TimeoutError(f"Timeout polling {status_url}")
async def generate_batch(api_key, prompts, aspect_ratio="1:1", max_concurrent=5):
"""Generate multiple images with different prompts concurrently."""
semaphore = asyncio.Semaphore(max_concurrent) # Rate limiting
async def generate_one(prompt):
async with semaphore:
async with aiohttp.ClientSession() as session:
# Launch request
result = await generate_image(session, api_key, prompt, aspect_ratio)
# Poll for completion
return await poll_status(session, api_key, result["status_url"])
# Run all concurrently
results = await asyncio.gather(*[generate_one(p) for p in prompts], return_exceptions=True)
return results
# Usage
prompts = [
"Professional photo of running shoes on white background",
"Professional photo of leather handbag on white background",
"Professional photo of smartwatch on white background",
"Professional photo of sunglasses on white background",
]
image_urls = asyncio.run(generate_batch("YOUR_API_KEY", prompts, max_concurrent=3))Key points:
asyncio.Semaphore to limit concurrent requests (recommended: 3-5)return_exceptions=True prevents one failure from canceling all requeststype AspectRatio = "1:1" | "4:3" | "16:9" | "3:4" | "9:16";
interface BriaResponse {
request_id: string;
status_url: string;
}
interface BriaStatusResponse {
status: "IN_PROGRESS" | "COMPLETED" | "FAILED";
result?: { image_url: string };
error?: string;
}
interface GenerateBatchResult {
prompt: string;
imageUrl: string | null;
error: string | null;
}
async function generateBatch(
apiKey: string,
prompts: string[],
aspectRatio: AspectRatio = "1:1",
maxConcurrent = 5
): Promise<GenerateBatchResult[]> {
const semaphore = { count: 0, max: maxConcurrent };
async function withLimit<T>(fn: () => Promise<T>): Promise<T> {
while (semaphore.count >= semaphore.max) {
await new Promise(r => setTimeout(r, 100));
}
semaphore.count++;
try {
return await fn();
} finally {
semaphore.count--;
}
}
async function generateOne(prompt: string): Promise<string> {
return withLimit(async () => {
// Launch request
const res = await fetch("https://engine.prod.bria-api.com/v2/image/generate", {
method: "POST",
headers: { "api_token": apiKey, "Content-Type": "application/json" },
body: JSON.stringify({ prompt, aspect_ratio: aspectRatio })
});
const { status_url } = (await res.json()) as BriaResponse;
// Poll for result
for (let i = 0; i < 60; i++) {
const statusRes = await fetch(status_url, { headers: { "api_token": apiKey } });
const data = (await statusRes.json()) as BriaStatusResponse;
if (data.status === "COMPLETED") return data.result!.image_url;
if (data.status === "FAILED") throw new Error(data.error || "Generation failed");
await new Promise(r => setTimeout(r, 2000));
}
throw new Error("Timeout waiting for generation");
});
}
const results = await Promise.allSettled(prompts.map(generateOne));
return results.map((result, i) => ({
prompt: prompts[i],
imageUrl: result.status === "fulfilled" ? result.value : null,
error: result.status === "rejected" ? result.reason.message : null
}));
}
// Usage
const results = await generateBatch(process.env.BRIA_API_KEY!, [
"Modern office workspace with natural lighting",
"Abstract tech background with blue gradient",
"Professional headshot studio setup"
], "16:9", 3);
results.forEach(r => {
if (r.imageUrl) console.log(`โ ${r.prompt}: ${r.imageUrl}`);
else console.log(`โ ${r.prompt}: ${r.error}`);
});---
## Pipeline Workflows
Chain multiple operations on images (generate โ edit โ remove background).
### Complete Pipeline Exampleasync def product_pipeline(api_key, product_descriptions, scene_prompt):
"""
Pipeline: Generate product โ Remove background โ Place in lifestyle scene
"""
async with aiohttp.ClientSession() as session:
results = []
for desc in product_descriptions:
# Step 1: Generate product image
gen_result = await generate_image(session, api_key,
f"Professional product photo of {desc} on white background, studio lighting",
aspect_ratio="1:1")
product_url = await poll_status(session, api_key, gen_result["status_url"])
# Step 2: Remove background
async with session.post(
"https://engine.prod.bria-api.com/v2/image/edit/remove_background",
headers={"api_token": api_key, "Content-Type": "application/json"},
json={"image": product_url}
) as resp:
rmbg_result = await resp.json()
transparent_url = await poll_status(session, api_key, rmbg_result["status_url"])
# Step 3: Place in lifestyle scene
async with session.post(
"https://engine.prod.bria-api.com/v2/image/edit/lifestyle_shot_by_text",
headers={"api_token": api_key, "Content-Type": "application/json"},
json={"image": transparent_url, "prompt": scene_prompt}
) as resp:
lifestyle_result = await resp.json()
final_url = await poll_status(session, api_key, lifestyle_result["status_url"])
results.append({
"product": desc,
"original": product_url,
"transparent": transparent_url,
"lifestyle": final_url
})
return results
products = ["coffee mug", "water bottle", "notebook"]
scene = "modern minimalist desk, natural morning light, plants in background"
results = asyncio.run(product_pipeline("YOUR_API_KEY", products, scene))
### Parallel Pipeline (Advanced)
Process multiple products through the pipeline concurrently:async def parallel_pipeline(api_key, products, scene_prompt, max_concurrent=3):
"""Run full pipeline for multiple products in parallel."""
semaphore = asyncio.Semaphore(max_concurrent)
async def process_one(product):
async with semaphore:
return await single_product_pipeline(api_key, product, scene_prompt)
return await asyncio.gather(*[process_one(p) for p in products], return_exceptions=True)
### Common Pipeline Patterns
| Pipeline | Steps | Use Case |
|----------|-------|----------|
| Product โ Transparent | generate โ remove_background | E-commerce cutouts |
| Product โ Lifestyle | generate โ remove_background โ lifestyle_shot | Marketing photos |
| Edit โ Upscale | edit โ increase_resolution | High-res edited images |
| Generate โ Restyle | generate โ restyle | Artistic variations |
| Generate โ Variations | generate (num_results=4) | A/B testing options |
---
## Integration Examples
### React/Next.js Component// Generate and display a hero image
const [imageUrl, setImageUrl] = useState(null);
async function generateHero(prompt) {
const res = await fetch('/api/bria/generate', {
method: 'POST',
body: JSON.stringify({ prompt, aspect_ratio: '16:9' })
});
const { image_url } = await res.json();
setImageUrl(image_url);
}
### Python Script for Batch Generationimport asyncio
async def main():
api_key = "YOUR_API_KEY"
products = ["running shoes", "leather bag", "smart watch"]
prompts = [f"Professional product photo of {p} on white background" for p in products]
results = await generate_batch(api_key, prompts, aspect_ratio="1:1", max_concurrent=3)
for product, result in zip(products, results):
if isinstance(result, Exception):
print(f"{product}: FAILED - {result}")
else:
print(f"{product}: {result}")
asyncio.run(main())
---
## API Reference
See `references/api-endpoints.md` for complete endpoint documentation.
### Key Endpoints
**Generation**
| Endpoint | Purpose |
|----------|---------|
| `POST /v2/image/generate` | Generate images from text (FIBO) |
**Edit by Text (No Mask)**
| Endpoint | Purpose |
|----------|---------|
| `POST /v2/image/edit` | Edit image with natural language instruction |
| `POST /v2/image/edit/add_object_by_text` | Add objects to image |
| `POST /v2/image/edit/replace_object_by_text` | Replace objects in image |
| `POST /v2/image/edit/erase_by_text` | Remove objects by name |
**Edit with Mask**
| Endpoint | Purpose |
|----------|---------|
| `POST /v2/image/edit/gen_fill` | Inpaint/generate in masked region |
| `POST /v2/image/edit/erase` | Erase masked region |
**Background Operations**
| Endpoint | Purpose |
|----------|---------|
| `POST /v2/image/edit/remove_background` | Remove background (RMBG-2.0) |
| `POST /v2/image/edit/replace_background` | Replace with AI-generated background |
| `POST /v2/image/edit/blur_background` | Apply blur to background |
| `POST /v2/image/edit/erase_foreground` | Remove foreground, fill background |
| `POST /v2/image/edit/crop_foreground` | Crop tightly around subject |
**Image Transformation**
| Endpoint | Purpose |
|----------|---------|
| `POST /v2/image/edit/expand` | Outpaint to new aspect ratio |
| `POST /v2/image/edit/enhance` | Enhance quality and details |
| `POST /v2/image/edit/increase_resolution` | Upscale 2x or 4x |
| `POST /v2/image/edit/blend` | Blend/merge images or textures |
| `POST /v2/image/edit/reseason` | Change season/weather |
| `POST /v2/image/edit/restyle` | Transform artistic style |
| `POST /v2/image/edit/relight` | Modify lighting |
**Text & Restoration**
| Endpoint | Purpose |
|----------|---------|
| `POST /v2/image/edit/replace_text` | Replace text in image |
| `POST /v2/image/edit/sketch_to_image` | Convert sketch to photo |
| `POST /v2/image/edit/restore` | Restore old/damaged photos |
| `POST /v2/image/edit/colorize` | Colorize B&W or convert to B&W |
**Product Photography**
| Endpoint | Purpose |
|----------|---------|
| `POST /v2/image/edit/lifestyle_shot_by_text` | Place product in scene by text |
| `POST /v2/image/edit/shot_by_image` | Place product on reference background |
**Utilities**
| Endpoint | Purpose |
|----------|---------|
| `POST /v2/structured_instruction/generate` | Generate JSON instruction (no image) |
| `GET /v2/status/{id}` | Check async request status |
### Authentication
All requests need `api_token` header:api_token: YOUR_BRIA_API_KEY
```
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