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🚀 Announcing Meilisearch 1.7
Meilisearch 1.7 stabilizes ranking score details, adds GPU support for Hugging Face embeddings, and integrates the latest OpenAI embedding models. It’s time to upgrade. 👇
⚖️ Introducing hybrid search
Meilisearch 1.7 introduced new OpenAI embedders, adding to Meilisearch's AI-enhanced hybrid search capabilities. Read the blog post to learn more about hybrid search and sign up to our waiting list.
🍿 Watch our launch event
On March 7th, we discussed our roadmap, our recent releases and showcased Meilisearch Cloud’s new features, including monitoring metrics and hybrid search.
🤔 Full-text search vs vector search
Join @StriftCodes in this comparative analysis as he delves into the pros and cons of each solution and how hybrid search might offer the best of both worlds.
🖇️ Links, links, links
🟧 Laravel multitenancy guide
Implement search in a multitenant Laravel application.
💻 Computing Hugging Face embeddings with the GPU
Learn to compile a Meilisearch binary that leverages an Nvidia GPU to generate Hugging Face embeddings.
🔢 From ranking to scoring
Our journey to add relevancy scores to search results in Meilisearch.
🪼 Meilisearch v1.8 release candidate
Get a preview of what’s coming next (and give your feedback!)
🚀 Strapi v4 guide
Learn how to integrate Meilisearch with Strapi.
🥰 Made with Meilisearch
The folks at Blazity have created this impressive Next.js storefront designed for high-performance eCommerce, featuring AI capabilities and one-click deployment.
We’re always looking to promote new projects from the community. Post yours in the #built-with-meilisearch Discord channel!
🏡 Life at Meili
Join our Head of Engineering, @clurquizar, as she walks us through key points of Meilisearch’s history and our evolution as an open-source company.
🦸 We're hiring!
See our open positions:
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For more things Meilisearch, join our developers community on Discord. You can learn more about the product by checking out the roadmap and participating in product discussions.
Until next time!
