Client-side vector search with Transformers.js

Hacker News

I've updated my Bible exploration tool to run entirely in the browser using Transformers.js. Key features: - Semantic search over the entire text using BAAI/bge-large-en-v1.5 embeddings - Client-side vector similarity search, no server required - Web UI built with HTML, Tailwind CSS, and vanilla JavaScript - Displays top search results with similarity scores - Hosted for free on Vercel, no server required! This is an evolution of my previous Biblos project, now optimized to run client-side only. - https://github.com/dssjon/biblos-js - https://biblos.app

Visit product View on Hacker NewsJun 25, 2024

Share card

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Client-Side WASM Vector Search56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Client-Side WASM Vector Search

Hacker News5

Marqo – Vectorless Vector Search77%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Marqo – Vectorless Vector Search

Hacker News62

jist.in, displaying gist contents by client-side js for legibility41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

jist.in, displaying gist contents by client-side js for legibility

Hacker News1

SQLite-Vector – Vector search for SQLite, now Apache 2.066%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

SQLite-Vector – Vector search for SQLite, now Apache 2.0

Hacker News2

Client Vector Search – Embeddings and Semantic Search with 5 Lines87%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Client Vector Search – Embeddings and Semantic Search with 5 Lines

Hacker News11

Facets – client-side faceted search43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Facets – client-side faceted search

Hacker News4

C+

C++ virtual_vec vector implementation47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

C++ virtual_vec vector implementation

Hacker News39

C+

C++23 constexpr n-dimensional Euclidean vector56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

C++23 constexpr n-dimensional Euclidean vector

Hacker News1

Asteroid, an alternative js client for Meteor62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Asteroid, an alternative js client for Meteor

Hacker News5

Quepid now works with vector search50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Quepid now works with vector search

Hacker News2

Browse all products Analyze your launch