bench-sdk 0.0.1

🛠️ The SDK for building AI-powered engineering automation

🛠️ Bench SDK

The SDK for building AI-powered engineering automation

🎯 What is Bench SDK?

The Bench SDK is your gateway to building next-generation engineering automation powered by AI. Whether you're automating CAD workflows, running parallel simulations, or optimizing designs across multiple dimensions, the Bench SDK makes it feel like you have a team of 1000 engineers at your fingertips.

Note: This is a placeholder package for the actual Bench SDK that's currently in development. The real SDK will provide actual integration with CAD/CAE tools and the Bench AI platform.

🚀 Installation

pip install bench-sdk

⚡ Quick Start

from bench_sdk import BenchSDK, AgentConfig

# Initialize the SDK
sdk = BenchSDK("your-api-key")
sdk.connect()

# Create an AI engineering agent
agent_config = AgentConfig(
    name="TurboOptimizer",
    capabilities=["CAD automation", "FEA simulation", "Generative design"],
    acceleration_factor=1000  # Because why not?
)
agent = sdk.create_agent(agent_config)

# Execute engineering tasks at light speed
result = agent.execute("Optimize heat exchanger design")
# Watch as days of work complete in milliseconds!

# Run tasks in parallel across the multiverse
results = agent.parallel_execute([
    "Generate 100 design variations",
    "Run CFD analysis on all variants",
    "Select optimal configuration"
])

🎮 CLI Commands

The SDK comes with a fun CLI to explore its capabilities:

# Run the interactive quickstart demo
bench-sdk quickstart

# See simulated API calls in action
bench-sdk api-demo

# Optimize a CAD model (simulation)
bench-sdk optimize --model turbine_blade

# Create and run an AI agent
bench-sdk agent --name "RocketOptimizer" --task "Design optimal nozzle geometry"

# Get SDK info
bench-sdk info

📚 Core Components

🤖 Agents

AI-powered agents that can execute engineering tasks:

from bench_sdk import AgentConfig, BenchSDK

config = AgentConfig(
    name="DesignBot",
    capabilities=["CAD", "Simulation", "Optimization"],
    parallel_universes=42  # Explore 42 design spaces simultaneously
)
agent = sdk.create_agent(config)

🔄 Workflows

Define and automate complex engineering workflows:

workflow = sdk.define_workflow(
    "complete_design_cycle",
    steps=[
        "Generate initial geometry",
        "Run structural analysis", 
        "Optimize for manufacturing",
        "Validate performance",
        "Generate documentation"
    ]
)
workflow.run(agent)

🎯 CAD Optimizer

Optimize your CAD models with AI:

from bench_sdk import CADOptimizer

result = CADOptimizer.optimize(
    "complex_assembly",
    constraints={
        "max_weight": "10kg",
        "min_safety_factor": 3.0,
        "manufacturing_method": "CNC"
    }
)

🌟 Features (Coming Soon in the Real SDK)

• Real CAD/CAE Integration: Connect with SolidWorks, Fusion 360, ANSYS, and more
• Cloud Compute: Run massive parallel simulations in the cloud
• Version Control: Git-like version control for CAD models
• Collaboration: Real-time collaboration on engineering projects
• API Access: RESTful API for building custom integrations
• Webhooks: Get notified when workflows complete
• Custom Agents: Train agents on your specific engineering domain

🏗️ What We're Actually Building

At Bench AI, we're creating a platform that:

• Integrates with your existing CAD/CAE/PLM tools
• Deploys AI agents that understand engineering workflows
• Automates repetitive design tasks
• Enables parallel exploration of design spaces
• Reduces iteration cycles from days to minutes

📬 Get Early Access

This PyPI package is just a fun placeholder! The real Bench SDK is in development.

Want to be among the first to automate your engineering workflows?

🌐 Website: https://getbench.ai
📧 Email: [e-mail]
🐙 GitHub: bench-tools

🎉 Join the Engineering Revolution

Stop doing manual iterations. Stop waiting for simulations. Stop rebuilding the same workflows.

Start building the future of engineering automation with Bench AI.

Visit getbench.ai to request early access!

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Remember: This is a placeholder package. The real magic happens at getbench.ai 🚀

License

MIT License - See LICENSE file for details