qdrant
google-search-results-nodejs
qdrant | google-search-results-nodejs | |
---|---|---|
141 | 57 | |
17,943 | 73 | |
3.4% | - | |
9.9 | 2.7 | |
7 days ago | 5 months ago | |
Rust | JavaScript | |
Apache License 2.0 | MIT License |
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.
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)
google-search-results-nodejs
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Google Search Parameters (2024 Guide)
The Google Search URL parameters are important to understand whether you are maximizing the conversion rate in your ad groups and optimizing your cost per click(CPC) rates in Google Analytics for your ad campaigns, improving your SEO(Search Engine Optimization) metrics for your e-commerce business, or collecting data for your social media project. Using custom parameters for your search will affect the Search Engine Result Page (SERP) data significantly in your favor. SerpApi unlocks the power of SERP data to you with minimal effort, the fastest response times, and in the most complete form.
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How to Create LCEL Chains in LangChain
A SERP API key set in the SERP_API_KEY variable.
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Ask HN: Who is hiring? (March 2024)
SerpApi | https://serpapi.com | Junior-to-Senior Fullstack Engineer | Illustrator and Graphic Designer | Based in Austin, TX but remote-first structure | Full-time | ONSITE or FULLY REMOTE | $150K - 180K a year 1099 for US or local avg + 20% for outside the US
SerpApi is the leading API to scrape and parse search engine results. We deeply support Google, Google Maps, Google Images, Bing, Baidu, and a lot more.
Our current stack is Ruby, Rails, MongoDB, and React.JS. We are looking for more Junior and Senior FullStack Engineers.
We have an awesome work environment: We are a remote first company (before Covid!). We do continuous integration, continuous deployments, code reviews, code pairings, profit sharing, and most of communication is async via GitHub.
We value super strongly transparency, do open books, have a public roadmap, and contribute to the EFF.
Apply at: https://serpapi.com/careers
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Ask HN: Who is hiring? (February 2024)
SerpApi | https://serpapi.com | Junior-to-Senior Fullstack Engineer | Illustrator and Graphic Designer | Based in Austin, TX but remote-first structure | Full-time | ONSITE or FULLY REMOTE | $150K - 180K a year 1099 for US or local avg + 20% for outside the US
SerpApi is the leading API to scrape and parse search engine results. We deeply support Google, Google Maps, Google Images, Bing, Baidu, and a lot more.
Our current stack is Ruby, Rails, MongoDB, and React.JS.
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How to Automate Processes with CrewAI
This code needs two API keys: one for the OpenAI API (GPT-4 is used by the CrewAI "Agents" by default) and one for the SerpAPI (you can create an account for free).
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Scraping the full snippet from Google search result
Sign up for free at SerpApi.
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What is SERP? Meaning, Use Cases and Approaches
SERPApi: SERPApi is a powerful tool that provides developers with an easy and efficient way to extract search engine results page (SERP) data using API.
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Why doesn't anyone seem to care about knowledge cut-off dates?
Assuming privacy is not a concern for coding questions, you can use the following web search APIs to augment your LLM's knowledge - Google's web search API: https://serpapi.com/ - You.com's web-search API: https://api.you.com/ - Metaphor's web-search API: https://platform.metaphor.systems/ - StackExchange question search API: https://api.stackexchange.com/docs/advanced-search
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For RoR, see in production every method call, parameter and return value
I run a large Rails application (https://serpapi.com), and the issues that would be solved with the type system would be close to nil.
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Comparing Types of Databases: A Real-World Benchmark Analysis
SerpApi is an API for scraping Google and other search engines with fast, easy, and complete solutions. Our team is tackling a challenge within our operational database where we house a Locations collection featuring predefined data structures. We aim to offer these locations to clients reliably and allow them to utilize these in their searches with SerpApi's Google Search API, demonstrating the interconnected functionality of various types of databases. You may register to claim free credits to try out our products
What are some alternatives?
Milvus - A cloud-native vector database, storage for next generation AI applications
google-maps-services-js - Node.js client library for Google Maps API Web Services
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.
body-parser - Node.js body parsing middleware
faiss - A library for efficient similarity search and clustering of dense vectors.
TeleAPI - 🚀 The useful library to simplify your work with Telegram Bot API
pgvector - Open-source vector similarity search for Postgres
S3 Server - Zenko CloudServer, an open-source Node.js implementation of the Amazon S3 protocol on the front-end and backend storage capabilities to multiple clouds, including Azure and Google.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
gtrans
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
clauneck - A tool for scraping emails, social media accounts, and much more information from websites using Google Search Results.