nex-weaver 1.7.0.1

Python SDK for the Weaver platform

Weaver Python SDK

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Python client for the NexWeave Weaver server. The SDK mirrors the REST API exposed by weaver-server and provides ergonomic helpers for training, sampling, telemetry, and operations management.

Installing locally

pip install nex-weaver

Configuration

Configuration can be provided via keyword arguments or environment variables:

• WEAVER_API_KEY

Quickstart

from weaver import ServiceClient

def main():
    with ServiceClient() as client:
        session = client.ensure_session()
        print(session)

if __name__ == "__main__":
    main()

Usage

See examples/weaver_walkthrough.ipynb for an interactive walkthrough of the full SDK workflow using a Pig Latin translation task — covering data preparation, LoRA / full fine-tuning, sampling, and checkpoint management.

For a complete runnable script, see examples/pig_latin.py.

Ecosystem

NexRL is the companion RL training framework. In its training-service mode, NexRL orchestrates the full RL loop (rollouts, trajectory collection, policy updates) while Weaver handles the underlying training and inference services.

Use Cases

OpenClaw Autonomous Learning — MetaClaw has integrated Weaver as an RL backend. By setting rl.backend=weaver, MetaClaw turns every live conversation into a learning signal and uses Weaver for cloud-based LoRA training, enabling personal agents to continuously evolve without a local GPU.

Deep Dive

For more technical details, see Deep Dive into Weaver.