weaviate-client
A python native Weaviate client
Decision gist · record as of 2026-08-14
Yes. Active maintenance, low install friction, permissive license, no known vulnerabilities, and top-1000 popularity make this a safe choice. Install if you are building applications that need to interact with a Weaviate instance; skip if you do not have a Weaviate deployment or are not working with vector search.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a running Weaviate instance to connect to; Python 3.10 or higher.
- Low install friction with a pure-wheel distribution.
- Actively maintained with a release 1 day old and recent commits.
License · maintenance · safety
BSD 3-clause (permissive) — BSD 3-clause permissive license allows commercial and private use with minimal restrictions; suitable for most projects.
last release 2026-08-13 (1 days) · last repo commit 2026-08-13 · 226 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 213,203,009 downloads/mo, #193 on PyPI
Alternatives
Verify before relying
pip install weaviate-client
from weaviate import Client
client = Client("http://example.com")
results = client.query.get("ClassName").do()- Whether gRPC transport (grpcio, protobuf deps) is optional or required for all use cases
- Performance characteristics and latency expectations for typical semantic search queries
- Specific authentication methods supported by authlib integration
What it is and what it does
Weaviate-client is a Python wrapper for the Weaviate vector database, providing a native interface to create, manage, and query vector embeddings and semantic data. It abstracts the HTTP and gRPC communication layers, allowing developers to interact with Weaviate instances programmatically without writing raw API calls. The library depends on httpx for HTTP requests, pydantic for data validation, authlib for authentication, and gRPC libraries for protocol support.
Typically used in machine learning and AI workflows where semantic search, similarity matching, or neural retrieval is needed. Developers use it to store embeddings, perform vector similarity queries, and integrate Weaviate into Python applications. The client is actively maintained, recently released, and positioned as the primary way to interact with Weaviate from Python code.
Use it for
- Build semantic search engines that find similar documents or products based on meaning rather than keyword matching.
- Integrate vector embeddings from language models into a Python application for retrieval-augmented generation.
- Query and manage large collections of embeddings stored in a Weaviate instance for recommendation systems.
- Prototype or deploy AI-powered search features without writing raw HTTP requests to Weaviate.
- Validate and structure data being sent to Weaviate using pydantic models through the client.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Active maintenance, low install friction, permissive license, no known vulnerabilities, and top-1000 popularity make this a safe choice. Install if you are building applications that need to interact with a Weaviate instance; skip if you do not have a Weaviate deployment or are not working with vector search.
Install
weaviate-client on PyPI
Before you install
Low install friction with a pure-wheel distribution. Actively maintained with a release 1 day old and recent commits. Supports current Python versions (3.10+).
Requires a running Weaviate instance to connect to; Python 3.10 or higher.
License in practice
BSD 3-clause permissive license allows commercial and private use with minimal restrictions; suitable for most projects.
Quickstart
pip install weaviate-client
from weaviate import Client
client = Client("http://example.com")
results = client.query.get("ClassName").do()Verify before relying
- Whether gRPC transport (grpcio, protobuf deps) is optional or required for all use cases
- Performance characteristics and latency expectations for typical semantic search queries
- Specific authentication methods supported by authlib integration
Package facts
| License | BSD 3-clause permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packageshttpxvalidatorsauthlibpydanticgrpcioprotobufpackaging |
| Maintenance | Actively maintained 1 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 213,203,009 / month, #193 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: weaviate_client-4.23.0-py3-none-any.whl
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See also langchain-weaviate · apache-airflow-providers-weaviate · redisvl · voyageai · opentelemetry-instrumentation-weaviate · deeplake · qdrant-client · azure-search-documents · sqlite-vec · pgvector