bria-client 0.3.0

Bria.ai Python SDK

Bria Client

A Python client library for the Bria Engine API, designed to make integrating powerful image and video editing capabilities into your applications seamless and straightforward. The library provides both synchronous and asynchronous clients with flexible request execution modes.

Table of Contents

• Installation
• Quick Start
• Usage Guide
  • Two Client Types
  • Three Request Methods
  • Payload Handling
  • Webhooks
  • Video Upload
• Examples
• Development Setup
• Contributing
• Support

Installation

pip install bria-client

Quick Start

Set your API key:

export BRIA_API_TOKEN="your-api-key-here"

Basic example:

from bria_client import BriaSyncClient
from bria_client.toolkit.image import Image

client = BriaSyncClient()

# Process an image and get the result immediately
response = client.run(
    endpoint="image/edit/remove_background",
    payload={"image": Image("https://example.com/image.jpg").as_bria_api_input}
)

print(response.result)

Usage Guide

Two Client Types

Choose the client that fits your use case:

BriaSyncClient - For simple scripts and traditional applications

from bria_client import BriaSyncClient

client = BriaSyncClient()
response = client.run(endpoint="image/edit/remove_background", payload={...})

BriaAsyncClient - For async applications and concurrent processing

from bria_client import BriaAsyncClient

async def process_images():
    async with BriaAsyncClient() as client:
        response = await client.run(endpoint="image/edit/remove_background", payload={...})
    return response

Three Request Methods

.run() - Wait for immediate result

# Good for quick operations
response = client.run(endpoint="image/edit/remove_background", payload={...})
print(response.result)

.submit() - Submit and continue working

# Good for long operations - returns immediately with request_id
response = client.submit(endpoint="video/segment/mask_by_prompt", payload={...})
print(f"Submitted: {response.request_id}")
# Do other work...

.poll() - Wait for a submitted request to complete

# Check request status until done
response = client.submit(endpoint="...", payload={...})
final = client.poll(response, interval=2, timeout=300)
print(final.result)

Payload Handling

The client automatically strips None values from payloads before sending requests. This means you can safely include optional parameters without worrying about sending null values to the API:

response = client.run(
    endpoint="image/edit/remove_background",
    payload={
        "image": Image("https://example.com/image.jpg").as_bria_api_input,
        "bg_color": None,  # Will be omitted from the request
    }
)

Webhooks

Instead of polling, you can ask Bria to POST the result to your server as soon as a job completes. Pass webhook_url to .submit():

response = client.submit(
    endpoint="video/edit/remove_background",
    payload={"video": file_url},
    webhook_url="https://your-server.example.com/webhook",
)
print(f"Submitted: {response.request_id}")

Bria signs every delivery with HMAC-SHA256. Verify the signature before processing the payload:

from bria_client.toolkit import verify_webhook_signature

# In your webhook receiver (e.g. a FastAPI POST handler):
body = await request.body()
is_valid = verify_webhook_signature(
    payload=body,
    webhook_id=request.headers["bria-webhook-id"],
    timestamp=request.headers["bria-webhook-timestamp"],
    signature_header=request.headers["bria-webhook-signature"],
    api_token=os.environ["BRIA_API_TOKEN"],
)
if not is_valid:
    raise HTTPException(status_code=401, detail="Invalid webhook signature")

Best practices:

• Respond with a 2xx status within 10 seconds — defer any heavy processing to a background task.
• Always verify the signature before acting on the payload.

See examples/webhook_handler.py for a complete FastAPI receiver with optional ngrok tunnel for local development.

Video Upload

Video endpoints expect a hosted URL. If you have a local file, use client.upload() to get one via a presigned upload:

file_url = client.upload("path/to/video.mp4", media_type="video/mp4")

response = client.submit(
    endpoint="video/edit/remove_background",
    payload={"video": file_url},
)

result = client.poll(response, timeout=300)
print(result.result)

The returned file_url is valid for approximately 24 hours.

See examples/video_upload.py for the full example.

Examples

Basic Usage

from bria_client import BriaSyncClient
from bria_client.toolkit.image import Image

client = BriaSyncClient()

response = client.run(
    endpoint="image/edit/remove_background",
    payload={"image": Image("https://example.com/image.jpg").as_bria_api_input}
)

print(response.result)

Batch Processing

from bria_client import BriaSyncClient
from bria_client.toolkit.image import Image

client = BriaSyncClient()
images = ["image1.jpg", "image2.jpg", "image3.jpg"]

# Submit all requests
responses = [
    client.submit(
        endpoint="image/edit/remove_background",
        payload={"image": Image(img).as_bria_api_input}
    )
    for img in images
]

# Wait for all to complete
results = [client.poll(r, timeout=120) for r in responses]
print(f"Processed {len(results)} images")

Async Processing

import asyncio
from bria_client import BriaAsyncClient
from bria_client.toolkit.image import Image

async def process_images():
    async with BriaAsyncClient() as client:
        tasks = [
            client.run(
                endpoint="image/edit/remove_background",
                payload={"image": Image(url).as_bria_api_input}
            )
            for url in ["image1.jpg", "image2.jpg", "image3.jpg"]
        ]
        return await asyncio.gather(*tasks)

results = asyncio.run(process_images())

Error Handling

try:
    response = client.run(endpoint="...", payload={...}, raise_for_status=True)
    print(response.result)
except TimeoutError:
    print("Request timed out")
except Exception as e:
    print(f"Error: {e}")

Development Setup

Prerequisites

• Python 3.10+
• uv package manager

Installation

Install development and test dependencies:

uv sync --group dev

Pre-commit Hooks

This project uses pre-commit hooks to ensure code quality. Install them with:

pre-commit install

The following hooks run automatically on each commit:

Hook	Description
prettier	Formats YAML and JSON files
ruff-format	Formats Python code
ruff	Lints Python code with auto-fix
pyright	Type checking for src/ and tests/
pyright-examples	Type checking for examples/ (requires [examples] extra)
uv-lock-check	Ensures uv.lock is in sync with pyproject.toml

To run all hooks manually:

pre-commit run --all-files

Contributing

Contributions are welcome! Please follow the Development Setup instructions first, then:

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make your changes and add tests
4. Run tests: uv run pytest
5. Submit a pull request

Guidelines:

• Add type hints to new code
• Include tests for new features
• Follow existing code style
• Update documentation as needed

Found a bug? Open an issue with:

• Description of the problem
• Steps to reproduce
• Python version and environment

Support

• Documentation: docs.bria.ai
• Issues: GitHub Issues
• Examples: See examples/ directory

License

MIT License - see LICENSE file for details.

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Made by Bria.ai