Weaviate Has a Free API — AI-Native Vector Database

#weaviate #vectordb #ai #api

Weaviate is an open-source vector database with built-in ML model integration. It vectorizes your data automatically and provides semantic search out of the box.

What Is Weaviate?

Weaviate combines vector search with structured filtering. It can auto-vectorize text and images using integrated ML models.

Free tier (Weaviate Cloud):

14-day sandbox
Serverless clusters
Embedded Weaviate (local, free forever)

Quick Start

docker run -p 8080:8080 -p 50051:50051 cr.weaviate.io/semitechnologies/weaviate:latest

REST API

# Create class
curl -X POST http://localhost:8080/v1/schema \
  -d '{"class":"Article","properties":[{"name":"title","dataType":["text"]},{"name":"content","dataType":["text"]}]}'

# Add object
curl -X POST http://localhost:8080/v1/objects \
  -d '{"class":"Article","properties":{"title":"AI in 2026","content":"Artificial intelligence continues to evolve..."}}'

# Semantic search (GraphQL)
curl -X POST http://localhost:8080/v1/graphql \
  -d '{"query":"{Get{Article(nearText:{concepts:[\"machine learning trends\"]}limit:5){title content}}}"}'

Python SDK

import weaviate

client = weaviate.connect_to_local()

collection = client.collections.get("Article")
results = collection.query.near_text(query="AI trends", limit=5)
for obj in results.objects:
    print(obj.properties["title"])