configs
qdrant
configs | qdrant | |
---|---|---|
6 | 141 | |
75 | 17,943 | |
- | 3.4% | |
4.7 | 9.9 | |
about 1 year ago | 6 days ago | |
JavaScript | Rust | |
MIT License | 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.
configs
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Improve your Python code with pre-commit
I was a long time pre-commit fan, just converted to https://trunk.io/ though
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Ask HN: Who is hiring? (February 2023)
Trunk | https://trunk.io | Sr Full Stack / Sr C++ | Full-Time | Remote / Hybrid, SF
Trunk is an a16z funded dev tools startup, redefining software development at scale. We've built three products so far and have plans for more:
* Trunk Check: a universal linter/formatter, available as a CLI, VSCode extension, and CI check;
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Extension to lint and format *every* language
Trunk is also a command line tool, so you can run all these checks on CI, with the same versions of tools you use locally
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Grep one-liners as CI tasks
Tests are a good way to assert an invariant that you expect of your codebase, but as with all things, resolving the error can get a bit tricky/frustrating.
The canonical example in my mind is any kind of autofix-able linter, where there's some kind of patch (or more nuanced autofix) that the linter can generate on-the-spot for you. With a sh_test construct (or any other unit test), you generally find yourself printing out some command that the user can run to fix things, which in a sufficiently large codebase can get really frustrating.
(My company - https://trunk.io - is actually building a universal linter as part of our product offering, and we already have a system to write custom linters with varying levels of sophistication that can plug into both your IDE and CI system.)
- Ultra-clean sane configs for linters, formatters, and more
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?
Anki-Android - AnkiDroid: Anki flashcards on Android. Your secret trick to achieve superhuman information retention.
Milvus - A cloud-native vector database, storage for next generation AI applications
semgrep - Lightweight static analysis for many languages. Find bug variants with patterns that look like source code.
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.
trunk-action - Trunk.io GitHub Action
faiss - A library for efficient similarity search and clustering of dense vectors.
jq - Command-line JSON processor [Moved to: https://github.com/jqlang/jq]
pgvector - Open-source vector similarity search for Postgres
LunarVim - 🌙 LunarVim is an IDE layer for Neovim. Completely free and community driven.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
relay - Sentry event forwarding and ingestion service.
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.