xinference-client
Client for Xinference
Decision gist · record as of 2026-08-14
Yes, if you are running a Xinference server and need a Python client to access it. The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive license. It is not useful standalone—it requires a running Xinference server to connect to.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a running Xinference server accessible at the specified URL (e.g., http://localhost:9997).
- Low friction installation with a pure Python wheel and four common dependencies (requests, aiohttp, typing-extensions, pydantic).
- Actively maintained with recent releases; last commit 2026-07-31.
License · maintenance · safety
Apache License 2.0 (permissive) — Apache License 2.0 is permissive, allowing commercial and private use with minimal restrictions—suitable for most projects without licensing concerns.
last release 2026-07-31 (14 days) · last repo commit 2026-07-31 · 9 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 204,341 downloads/mo, #9,610 on PyPI
Alternatives
Verify before relying
pip install xinference-client
from xinference_client import RESTfulClient as Client
client = Client("http://localhost:9997")
model_uid = client.launch_model(model_name="chatglm2")
model = client.get_model(model_uid)
model.chat("What is the largest animal?", chat_history=[], generate_config={"max_tokens": 1024})- Whether the package supports async/await patterns beyond aiohttp dependency presence.
- Supported Xinference server versions and compatibility guarantees.
- Whether model launch/retrieval operations have timeout or retry mechanisms.
What it is and what it does
xinference-client is a Python HTTP client for the Xinference model serving platform, allowing developers to programmatically launch, retrieve, and query language models running on a Xinference server. It wraps REST API calls into a Python-friendly interface, handling model lifecycle management (launch, get) and inference requests (chat completions with configurable generation parameters).
The package is built on standard HTTP libraries (requests, aiohttp) and integrates with pydantic for data validation. It's designed for scenarios where models are hosted on a separate Xinference server and accessed remotely, rather than for local model execution. The client abstracts away HTTP details and returns structured responses (chat completion objects with token counts, finish reasons, and assistant messages).
Use it for
- Launch and query language models on a remote Xinference server from a Python application without direct model management.
- Build chatbot or conversational AI applications that delegate inference to a centralized Xinference deployment.
- Integrate model inference into data pipelines or batch processing workflows using a simple client API.
- Prototype or test different language models by swapping model names without changing client code.
- Monitor and manage model lifecycle (launch, retrieve state) programmatically across multiple applications.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are running a Xinference server and need a Python client to access it.
The package is actively maintained, has low install friction, carries no known vulnerabilities, and uses a permissive license. It is not useful standalone—it requires a running Xinference server to connect to.
Install
xinference-client on PyPI
Before you install
Low friction installation with a pure Python wheel and four common dependencies (requests, aiohttp, typing-extensions, pydantic). Actively maintained with recent releases; last commit 2026-07-31.
Requires a running Xinference server accessible at the specified URL (e.g., http://localhost:9997).
License in practice
Apache License 2.0 is permissive, allowing commercial and private use with minimal restrictions—suitable for most projects without licensing concerns.
Quickstart
pip install xinference-client
from xinference_client import RESTfulClient as Client
client = Client("http://localhost:9997")
model_uid = client.launch_model(model_name="chatglm2")
model = client.get_model(model_uid)
model.chat("What is the largest animal?", chat_history=[], generate_config={"max_tokens": 1024})Verify before relying
- Whether the package supports async/await patterns beyond aiohttp dependency presence.
- Supported Xinference server versions and compatibility guarantees.
- Whether model launch/retrieval operations have timeout or retry mechanisms.
Package facts
| License | Apache License 2.0 permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesrequestsaiohttptyping-extensionspydantic |
| Maintenance | Actively maintained 14 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 204,341 / month, #9,610 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonTopic :: Software Development :: Libraries |
Evidence: xinference_client-3.1.0-py3-none-any.whl
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