Articles

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Qdrant under the hood: Scalar Quantization
Scalar Quantization is a newly introduced mechanism of reducing the memory footprint and increasing performance
March 27, 2023 | Kacper Łukawski
Extending ChatGPT with a Qdrant-based knowledge base
ChatGPT factuality might be improved with semantic search. Here is how.
March 23, 2023 | Kacper Łukawski
On Hybrid Search
What Hybrid Search is and how to get the best of both worlds.
February 15, 2023 | Kacper Łukawski
Question Answering with LangChain and Qdrant without boilerplate
We combined LangChain, pretrained LLM from OpenAI, SentenceTransformers and Qdrant to create a Q&A system with just a few lines of code.
January 31, 2023 | Kacper Łukawski
Minimal RAM you need to serve a million vectors
How to properly measure RAM usage and optimize Qdrant for memory consumption.
December 7, 2022 | Andrei Vasnetsov
Question Answering as a Service with Cohere and Qdrant
End-to-end Question Answering system for the biomedical data with SaaS tools: Cohere co.embed API and Qdrant
November 29, 2022 | Kacper Łukawski
Finding errors in datasets with Similarity Search
Improving quality of text-and-images datasets on the online furniture marketplace example.
July 18, 2022 | George Panchuk
Q&A with Similarity Learning
A complete guide to building a Q&A system using Quaterion and SentenceTransformers.
June 28, 2022 | George Panchuk
Layer Recycling and Fine-tuning Efficiency
Learn when and how to use layer recycling to achieve different performance targets.
August 23, 2022 | Yusuf Sarıgöz
Fine Tuning Similar Cars Search
Learn how to train a similarity model that can retrieve similar car images in novel categories.
June 28, 2022 | Yusuf Sarıgöz
Metric Learning Tips & Tricks
Practical recommendations on how to train a matching model and serve it in production. Even with no labeled data.
May 15, 2021 | Andrei Vasnetsov
Metric Learning for Anomaly Detection
Practical use of metric learning for anomaly detection. A way to match the results of a classification-based approach with only ~0.6% of the labeled data.
May 4, 2022 | Yusuf Sarıgöz
Triplet Loss - Advanced Intro
What are the advantages of Triplet Loss over Contrastive loss and how to efficiently implement it?
March 24, 2022 | Yusuf Sarıgöz
Neural Search Tutorial
Our step-by-step guide on how to build a neural search service with BERT + Qdrant + FastAPI.
June 10, 2021 | Andrei Vasnetsov
Filtrable HNSW
How to make ANN search with custom filtering? Search in selected subsets without loosing the results.
November 24, 2019 | Andrei Vasnetsov
Introducing Qdrant 0.11
Replication support is the most important change introduced by Qdrant 0.11. Check out what else has been added!
October 26, 2022 | Kacper Łukawski
Qdrant 0.10 released
Qdrant 0.10 brings a lot of changes. Check out what's new!
September 19, 2022 | Kacper Łukawski

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