Alternatives
Products that do what ai-embed-search does
Local semantic search engine with transformer embeddings.
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Hi there! When Supabase announced their recent hackathon, I thought it was a good time to build something to learn more about so many of the new AI models and tech out there. From the different techniques of embedding documents to the future RAG. With the rise of short form content with TikTok and Youtube. A lot more knowledge is in videos than ever before. Finding specific answers within millions of videos can be difficult for any one person to go through. So the question is if there is Google that indexes text on website making it easier to find based on the context of on your question,…
2023 · avse.vercel.app
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I have spent several years working on search engines in the backend and have now utilized that experience to develop a fuzzy search library for the frontend. It's fast, accurate and can be used for all languages. It should be easy to integrate into your Javascript / Typescript projects. If you test it and find any edge cases that did not work for you please let me know. The implementation is based on 3-grams by the book, augmented with a novel trick of sorting the characters within the 3-grams for enhanced accuracy. For a detailed explanation you may refer to my related blog post at…
2024 · github.com
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Sep 2025 · github.com
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Hi folks! I created a frontend-only live semantic search engine based on transformers.js and sentence-transformers/all-MiniLM-L6-v2. Simply pour in your text and a query term. Hit enter and watch the search engine in action! It's highly customizable and stores the embeddings in a variable so that consecutive runs are very fast. You can tweak the segment length to reduce computation time or get get more precise results. I would be very happy to discuss some more usage ideas or receive PRs for improvements. Introduction blog post:…
2023 · geo.rocks
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I wrote this tool to get familiar with CLIP model, I know many people have written similar tools with CLIP before, but I'm new to machine learning and writing a classic tool helps my study. The unusual thing with my version is, it is in pure Node.js, with the power of node-mlx, a Node.js machine learning framework. The repo in the link is mostly about implementing indexing and CLI, the code of the model implementation lives as a Node.js module: https://github.com/frost-beta/clip . Hope this helps other learners!
2024 · github.com
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Inspekt▲98AI-powered API proxy for automated debugging and security
Mar 2026 · inspekt-api.vercel.app
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2024 · webcrumbs.org
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Hey HN, we're excited to show you client-vector-search, a client-side library that helps you embed, store, search, and cache vectors in your browser or node env. We needed it at https://searchbase.app and that's why we've built it. with it you get: 1. easy setup: you only need to add 5 lines of code to build a semantic search 2. no embedding api needed: you don't need an api and have to pay for it unless ure scaling up millions 3. faster search: modern hardware is better than cheap cloud computers (0.5vCPUs) 4. zero latency: no back-and-forth with server-side 5. easy integration…
2023 · clientvectorsearch.com
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Dear HN Community, I am a long time fan and first-time contributor. I just launched a developer focused semantic search platform and wanted to share it with the community. The idea is simple: upload structured or unstructured documents, select the fields you want to index and tag as metadata, and instantly get a clean search API you can use in your own app. Here is what it currently supports: - Manage your own tenants and projects - Upload .json and .txt files (support for .pdf, .docx, .xlsx, .yml, etc. coming soon) - Expose 3 APIs: search, upload document (embeddings), and delete document -…
2025 · aisearch.vpuna.com
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Hey everyone! I’m excited to announce the release of my last project, MiniSearch. I admire Perplexity.ai, Phind.com, You.com, Bing, Bard and all these search engines integrated with AI chatbots. And as a curious developer, I took the chance and created my own version. Using Web-LLM and Transformers.js to provide browser-based text-generation models on desktop and mobile, I built a minimalist self-hosted search app on which an AI analyses the results, comments on them and responds to your query summarising the info. In the backend, it still queries a real search engine, but besides that,…
2023 · huggingface.co
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If you've ever used CTRL+F on websites or documentation, you'll love this functionality.
2024 · github.com
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Hey HN, We’ve been heads-down building MOSS - a semantic memory layer that brings AI-powered search and personalization fully on-device (No cloud | No latency | No data leaving the user’s device) We just launched a live demo showing MOSS running entirely in-browser, performing lightning-fast semantic search over local in-browser VectorDB. This unlocks a new class of privacy-first, hybrid AI experiences that work even without a server connection. If you’re curious about: - how to run AI search right inside the browser - the technical challenges behind on-device vector search - why we believe…
2025 · twitter.com
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Hey HN! We just released a new library for building LLM-powered applications: @axflow/models. It is part of a larger suite of libraries we're developing for TypeScript developers working with generative AI. This library provides the simplest APIs for 1) invoking the most popular LLM and embedding models (openai, anthropic, cohere, huggingface, etc.) 2) streaming LLM responses to clients, including augmenting the streams with additional arbitrary data and 3) building client-side applications with React hooks. @axflow/models has zero dependencies and is built using only the…
2023 · docs.axflow.dev
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