How To Quickly Build A Semantic Search System With txtai And Weaviate
Last Updated on July 25, 2023 by Editorial Team
Author(s): ___
Originally published on Towards AI.
Step 1: Define the image for the txtai API server
This member-only story is on us. Upgrade to access all of Medium.
In this article, I will explain how to quickly build a machine learning-based semantic search engine using docker compose and the following tools/libraries:
txtai: A framework to run machine-learning workflows to transform data and build AI-powered semantic search applications.weaviate: A vector search enginetxt-weaviate: A small library to make it easy to integrate weaviate with txtai
The code to reproduce this solution can be found here.
We only need to follow 3 steps to get started:
Step 1: Define the image for the txtai API serverStep 2: Define the txtai configurationStep 3: Deploy with… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.
Related posts
Recent Posts
