fabric-compute-sdk 1.0.6

Official Python SDK for Fabric - Distributed AI Compute Network

Fabric SDK

Official Python SDK for Fabric - Distributed AI Compute Network

Submit AI workloads to the Fabric network programmatically.

Installation

pip install fabric-compute-sdk

Quick Start

Option 1: Email/Password Authentication

from fabric_sdk import FabricClient

# Initialize client with email/password
client = FabricClient(
    api_url="https://api.fabric.carmel.so",
    email="[e-mail]",
    password="your_password"
)

# Submit a job
job = client.submit_job(
    workload_type="llm_inference",
    params={
        "prompt": "Explain quantum computing in simple terms",
        "max_length": 200,
        "temperature": 0.7,
        "use_gpu": True
    },
    job_name="My LLM Inference Job"
)

print(f"Job submitted: {job['id']}")

# Wait for completion
result = client.wait_for_job(job['id'], timeout=300)
print(f"Job completed in {result['duration_seconds']}s")
print(f"Cost: ${result['actual_cost']}")

Option 2: API Key Authentication (Recommended for Google OAuth users)

from fabric_sdk import FabricClient

# Initialize client with API key
client = FabricClient(
    api_url="https://api.fabric.carmel.so",
    api_key="fb_live_..."  # Get this from dashboard Settings > API Keys
)

# Works exactly the same!
job = client.submit_job(
    workload_type="llm_inference",
    params={"prompt": "Explain quantum computing"},
    job_name="My Job"
)

Why use API keys?

• No password needed (great for Google/GitHub OAuth users)
• More secure for CI/CD pipelines
• Easy to rotate and revoke
• Each project can have its own key

Features

• Dual Authentication - Email/password OR API keys (NEW!)
• API Key Management - Create, list, and revoke keys programmatically
• Job Submission - Submit 28 production workload types
• Batch Submission - Submit 1000s of jobs in seconds (100x faster!)
• Custom Workloads - Upload and run your own Python code
• Job Monitoring - Track progress and get results
• Credit Management - Check balance and purchase credits
• Node Discovery - List available compute nodes
• Auto-Retry - Built-in network resilience
• Type Hints - Full TypeScript-style typing support

🆕 New: Batch Submission (December 2025)

For large-scale parameter sweeps and production workloads, use batch submission:

# Submit 1000 jobs in ~5 seconds (vs 50 minutes with loop)
jobs = [
    {
        'workload_type': 'custom_python',
        'params': {'param1': i, 'param2': 'value'},
        'custom_workload_id': workload_id,
        'job_name': f'Job_{i}'
    }
    for i in range(1000)
]

result = client.submit_batch(jobs)
print(f"Submitted {result['total_submitted']} jobs!")
print(f"Cost: ${result['total_cost_estimate']:.2f}")

Performance:

• 1,000 jobs: ~5 seconds
• 10,000 jobs: ~50 seconds
• 100,000 jobs: ~8 minutes

Supports: 1-3 million jobs/week for production use cases

Supported Workload Types (26 Total)

Compute & Simulation (5)

• cpu_compute_benchmark, gpu_compute_benchmark
• eigenvalue_decomposition, financial_forecast_simulation, agent_simulation

Data Processing (5)

• data_cleaning, feature_extraction, csv_vectorization
• data_augmentation, outlier_detection

AI Inference (7)

• llm_inference, llm_inference_batch, image_classification
• embedding_generation, sentiment_analysis
• text_summarization, question_answering

Media Processing (5)

• video_transcode, audio_to_text, video_object_detection
• image_resize_batch, video_summarization

ML Training (4)

• random_forest_training, svm_training
• xgboost_training, neural_network_training

Custom (1)

• custom_python

For detailed parameter documentation for each workload type, see DEVELOPER_GUIDE.md.

Documentation

For Developers

• Developer Guide - Complete SDK API reference
• Custom Workloads Guide - Upload and run your own Python code on Fabric
• Publishing to PyPI - How to release new versions

For Enterprises

• Enterprise Integration Guide - Complete documentation with examples, best practices, and API reference
• SDK Playground Specification - Interactive playground implementation guide for dashboard integration

License

MIT License - See LICENSE