fabric-compute-sdk 1.0.7

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

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

Documentation

Complete documentation, guides, and examples are available in the Fabric Dashboard.

Key Features

• Custom Workloads - Upload and run your own Python code on Fabric
• Enterprise Integration - Complete API reference and best practices
• Batch Submission - Large-scale job processing (1M+ jobs/week)
• API Key Management - Secure authentication for production systems

Support

Access the Fabric Dashboard for documentation, support, and account management.

License

Apache License 2.0

Copyright 2025 Carmel Labs, Inc.