product
qdrant
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
product
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Vector storage is coming to Meilisearch to empower search through AI
We’re excited to walk our first steps toward semantic search. We can’t wait to hear your thoughts on integrating Meilisearch as a vector store. You can give your feedback in this Github discussion.
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Meilisearch across the Semantic Verse
Looks good in fact! We will eventually let users use third-party API like OpenAi and Hugging Face to compute the embedding of the documents and queries. You can try our first prototype if you want.
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Meilisearch vs. Elasticsearch
Hey @jiripospisil,
Indeed Meilisearch does not offer an aggregation feature yet although it will be possible to get stats for the `min` and `max` values of a faceted field in the next version (v1.1)
Please tell us more about what you mean by aggregation and why it is critical for your use-case by creating a discussion on Github here (https://github.com/meilisearch/product/discussions) or by proposing a new idea on our public portal here (https://roadmap.meilisearch.com) if you don't have a Github account.
Thank you!
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Show HN: Podcastsaver.com – a search engine testbench dressed as a podcast site
If you remove the URLs from indexation, it'll generally save a ton of place and will be much, much faster to index. We are thinking about not indexing URLs by default; you can help us by explaining your use case here -> https://github.com/meilisearch/product/discussions/553
Just a detail, if you're making a `du -sh` on your computer, the size on the disk will stay unchanged because we are doing soft deletion ;). Don't worry. It will be physically deleted after a while if you need it in the future.
If you kept the default configuration of Meilisearch, the maximum size of the HTTP payload is 100Mb (for security). You change it here -> https://docs.meilisearch.com/learn/configuration/instance_op...
addDocumentsInBatches() is just an helper to send your big json array into multiple parts, not absolutely sure you'll need it. (Code -> https://github.com/meilisearch/meilisearch-js/blob/807a6d827...)
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Meilisearch just announced its $15M Serie A, the search Rust engine strikes again
I advise you to fill out a discussion on our product repository for us to evaluate your needs, and use case and then see what we plan about that.
qdrant
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Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain
Great. Now that we have the embeddings, we need to store them in a vector database. We will be using Qdrant for this purpose. Qdrant is an open-source vector database that allows you to store and query high-dimensional vectors. The easiest way to get started with the Qdrant database is using the docker.
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Boost Your Code's Efficiency: Introducing Semantic Cache with Qdrant
I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours.
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Ask HN: Has Anyone Trained a personal LLM using their personal notes?
I'm currently looking to implement locally, using QDrant [1] for instance.
I'm just playing around, but it makes sense to have a runnable example for our users at work too :) [2].
[1]. https://qdrant.tech/
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Show HN: A fast HNSW implementation in Rust
Also compare with qdrant's Rust implementation; they tout their performance. https://github.com/qdrant/qdrant/tree/master/lib/segment/src...
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pgvecto.rs alternatives - qdrant and Weaviate
3 projects | 13 Mar 2024
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Open-source Rust-based RAG
There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb
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Qdrant 1.8.0 - Major Performance Enhancements
For more information, see our release notes. Qdrant is an open source project. We welcome your contributions; raise issues, or contribute via pull requests!
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Perform Image-Driven Reverse Image Search on E-Commerce Sites with ImageBind and Qdrant
Initialize the Qdrant Client with in-memory storage. The collection name will be “imagebind_data” and we will be using cosine distance.
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7 Vector Databases Every Developer Should Know!
Qdrant is an open-source vector search engine optimized for performance and flexibility. It supports both exact and approximate nearest neighbor search, providing a balance between accuracy and speed for various AI and ML applications.
- Ask HN: Who is hiring? (February 2024)
What are some alternatives?
com.openai.unity - A Non-Official OpenAI Rest Client for Unity (UPM)
Milvus - A cloud-native vector database, storage for next generation AI applications
open-product-management - A curated list of product management advice for technical people.
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.
rubyvideo - Indexing all Ruby related videos
faiss - A library for efficient similarity search and clustering of dense vectors.
backlog - My public backlog
pgvector - Open-source vector similarity search for Postgres
redb - An embedded key-value database in pure Rust
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
vespa - AI + Data, online. https://vespa.ai