Reviewable
qdrant
Reviewable | qdrant | |
---|---|---|
3 | 140 | |
125 | 17,943 | |
0.8% | 3.4% | |
9.1 | 9.9 | |
8 days ago | 3 days ago | |
Handlebars | Rust | |
- | Apache License 2.0 |
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.
Reviewable
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Ask HN: Who is hiring? (February 2023)
https://github.com/Reviewable/Reviewable/tree/master/careers
Reviewable is a very small, bootstrapped business that sells our code review software to some of the largest companies around. We've been around long enough to be much more stable than your average startup, yet stayed small enough to avoid crippling bureaucracy — everybody reports directly to the founder/CEO. We're engineer-centric and fully remote. However, we prefer hiring US residents and offer the usual benefits: health and dental insurance, 401(k) plans with company contributions, unlimited vacation, etc. We've built a company and a codebase where we enjoy working day-to-day and hope that you will too!
We're looking for a backend generalist with a love for problem-solving with algorithms and data structures!
Apply at https://github.com/Reviewable/Reviewable/tree/master/careers
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Ask HN: Who is hiring? (November 2022)
Reviewable | Bay Area, CA, USA or Remote | Full Time | Generalist / Backend Developers | Typescript | https://reviewable.io/
https://github.com/Reviewable/Reviewable/tree/master/careers
Reviewable is a very small, bootstrapped business that sells our code review software to some of the largest companies around. We've been around long enough to be much more stable than your average startup, yet stayed small enough to avoid crippling bureaucracy — everybody reports directly to the founder/CEO. We're engineer-centric and fully remote. However, we prefer hiring US residents and offer the usual benefits: health and dental insurance, 401(k) plans with company contributions, unlimited vacation, etc. We've built a company and a codebase where we enjoy working day-to-day and hope that you will too!
Apply at https://github.com/Reviewable/Reviewable/tree/master/careers
- Show HN: Crocodile Code Review
qdrant
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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)
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Step-by-Step Guide to Building LLM Applications with Ruby (Using Langchain and Qdrant)
Qdrant serves as a vector database, optimized for handling high-dimensional data typically found in AI and ML applications. It's designed for efficient storage and retrieval of vectors, making it an ideal solution for managing the data produced and consumed by AI models like Mistral 7B. In our setup, Qdrant handles the storage of vectors generated by the language model, facilitating quick and accurate retrievals.