Python client SDK for kapsl-runtime with IPC, shared-memory, and hybrid inference transports
Project description
kapsl-sdk
kapsl-sdk is the Python client package for kapsl-runtime, the Kapsl inference runtime for local and embedded model execution.
It provides Python bindings for the runtime's transport layer so Python applications can talk to a running kapsl-runtime process over:
- TCP / IPC client connections with
KapslClient - shared-memory transport with
KapslShmClient - hybrid IPC + shared-memory transport with
KapslHybridClient
The package is intended for low-latency inference integrations where Python is orchestrating requests while the runtime performs the heavy model execution work.
Installation
pip install kapsl-sdk
What It Includes
- Python bindings backed by the Rust runtime client implementation
- support for CPython 3.9+
- transport options for local development and high-throughput deployments
- a small API surface aimed at direct integration into backend services and tools
Requirements
- A running
kapsl-runtimeinstance - The runtime endpoint details for your deployment
- Shared-memory transport setup if you want to use
KapslShmClientorKapslHybridClient
Usage
from kapsl_sdk import KapslClient
client = KapslClient()
result = client.infer(
model_id=0,
shape=[1, 4],
dtype="float32",
data=b"...",
)
Client Types
KapslClient
General-purpose client for runtime connections over TCP, Unix sockets, or Windows named pipes depending on platform and endpoint configuration.
KapslShmClient
Shared-memory client for lower-overhead local inference workflows where request and response payloads are exchanged through shared memory.
KapslHybridClient
Hybrid client that combines shared memory for tensor payloads with IPC signaling for coordination.
Notes
kapsl-sdkis the package name on PyPI.- The Python import name is
kapsl_sdk. - This package is an API client, not the runtime server itself.
License
Proprietary — see kapsl.ai for licensing information.
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