artificialbrains-sdk 0.2.4

ArtificialBrains Python SDK

Artificial Brains Python SDK

A realtime SDK for connecting robots to Artificial Brains.

This SDK handles:

• communication with the brain runtime
• encoding sensor inputs into spike signals
• decoding spike outputs into control commands
• streaming inputs, outputs, and rewards in realtime

You focus on the robot.
The SDK handles the brain.

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Core Idea

The system is split into two responsibilities:

Controller (your configuration)

• read sensors
• apply motor commands
• compute rewards

SDK

• send inputs to the brain
• receive outputs from the brain
• route rewards to learning layers
• manage realtime session lifecycle

---

Installation

pip install artificialbrains-sdk

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Quick Start

1. Configure

Create a .env file:

AB_PROJECT_ID=your_project_id
AB_PYTHON_URL=http://localhost:8000
AB_NODE_URL=http://localhost:3000
AB_API_KEY=your_api_key

---

2. Start a session

from ab_sdk import ABClient

client = ABClient.from_env(env_path=".env")
session = client.start_from_env()

---

3. Send inputs

session.publish_input(
    sensor="ps0",
    signal=1234.0,
    vmax=4095.0
)

---

4. Receive outputs

def handle_output(output):
    print(output)

session.on_output(handle_output)

---

5. Send rewards

session.send_global_reward(1.0)
session.send_local_reward("on_line", 0.5)

---

Robot Loop (Recommended)

from ab_sdk import RobotLoop

def get_state():
    return {
        "ps0": 1200.0,
        "ps1": 800.0,
    }

def compute_reward():
    return {
        "global": 0.1,
        "local": {"on_line": 1.0}
    }

def apply_command(cmd):
    print(cmd)

loop = RobotLoop(
    session,
    state_provider=get_state,
    reward_provider=compute_reward,
    command_executor=apply_command,
)

loop.run_forever()

---

Architecture

Session

RealtimeSession is the core runtime object.

It manages:

• input encoding
• output streaming
• reward routing
• decoder execution

---

Maps

Maps define how the brain connects to your robot:

• InputSensorMap → sensors → brain inputs
• OutputMotorMap → brain outputs → motors
• RewardMap → outputs → learning layers

Make sure your IDs in the brain match the IDs of the sensors and motors.

Encoder

SpikeEncoder converts sensor values into spike populations.

---

Decoder

GenericSpikeDecoder converts spike activity into control commands.

The brain emits spikes per output population (neurons firing at each timestep).
The decoder reconstructs this activity into dense vectors and transforms it into actuator deltas.

Each output is mapped using a decoding scheme:

• bipolarSplit
  Splits the population in two halves:
  first half = positive, second half = negative
  → output = (positive − negative)
  → useful for continuous control (e.g. wheels, joints)

• addition
  Sums all active neurons
  → output = total spike count
  → useful for accumulating signals or intensity-based control

• booleanThreshold
  Activates only if spike count crosses a threshold
  → output = 1 or 0
  → useful for discrete actions (e.g. trigger, grasp)

• bipolarScalar
  Compares positive vs negative halves
  → output ∈ {-1, 0, +1}
  → useful for directional decisions

---

From spikes to movement

The decoder pipeline is:

1. Collect spikes from runtime output
2. Reconstruct population activity (bit vector per output)
3. Apply decoding scheme → scalar value
4. Scale to delta (using gain, limits, etc.)
5. Aggregate into command

Final output:

{
    "t": step,
    "deltas": {
        "left_wheel": 0.01,
        "right_wheel": -0.01,
    }
}

---

## Philosophy

The brain learns.  
The robot acts.  
The SDK connects them.

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## License

Artificial Brains SDK is **source-available**.

You are free to:
- use the SDK in personal and commercial projects  
- integrate it into your robots, simulators, and applications  
- modify the code for your own internal use  

You may **not**:
- repackage or redistribute the SDK as a standalone product  
- offer the SDK as a hosted or managed service  
- use the SDK to build or operate a competing platform  
- sublicense or resell the SDK itself  

This SDK is designed to enable developers to build on top of Artificial Brains — not to replicate it.

If you are interested in partnerships, embedding at scale, or special licensing terms, contact us.