Alternatives
Products that do what I'm a pastor/dev and built a 200M token generative Bible does
- 1LC
Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
2023 · github.com
- 2IB
Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
Apr 2026 · github.com
- 3
- 4BT
Built an auditable AI (Bible) translation pipeline: Hebrew/Greek source packets -> verse JSON with notes rolling up to chapters, books, and testaments. Final texts compiled with metrics (TTR, n-grams). This is the first full-text example as far as I know (Gen Z bible doesn't count). There are hallucinations and issues, but the overall quality surprised me. LLMs have a lot of promise translating and rendering 'accessible' more ancient texts. The technology has a lot of benefit for the faithful, that I think is only beginning to be explored.
Jan 2026 · biblexica.com
- 5BS
Introducing Biblos, a simple tool for semantic search and summarization of Bible passages. Leveraging Chroma for vector search with BAAI BGE embeddings, semantically find related verses across the Bible. The tool employs Anthropic's Claude LLM model for generating high-quality summaries of retrieved passages, contextualizing your search topic. Built on a Retrieval Augmented Generation (RAG) architecture, the app implements a simple Streamlit Web UI using Python. Deployed using render.com, the app is available at https://biblos.app Note: Search by just topic/keywords, e.g.…
2023 · github.com
- 6BA
Made this in a free evening. Index an permissive license translation of the Bible (WEB) into a RAG database to allow returning passages of similar semantic meaning. Lots of fun. For example, "more money more problems" returns Ecclesiastes 5:9-13 which, I'll just say, is spot on.. "Moreover the profit of the earth is for all. The king profits from the field. He who loves silver shall not be satisfied with silver, nor he who loves abundance, with increase. This also is vanity. When goods increase, those who eat them are increased; and what advantage is there to its owner, except to feast on…
Jun 2026 · crosscanon.com
- 7IM
Hi HN, I am Jiayuan, and I'm here to introduce a tool we've been building over the past few months: Devv (https://devv.ai). In simple terms, it is an AI-powered search engine specifically designed for developers. Now, you might ask, with so many AI search engines already available—Perplexity, You.com, Phind, and several open-source projects—why do we need another one? We all know that Generative Search Engines are built on RAG (Retrieval-Augmented Generation)[1] combined with Large Language Models (LLMs). Most of the products mentioned above use indexes from general search engines…
2024 · devv.ai
- 8AL
Nov 2025 · github.com
- 9RB
I rebuilt Biblos, my semantic Bible search app, to run entirely in your browser. No more server costs. The main challenge was fitting an accurate text embedding model into browsers. Last year's version cost $20 monthly to host. The new version runs free on Vercel and searches 31k Bible verses without sending data to any server. I pre-compute embeddings for all 31,000 Bible verses offline using BGE-large-en-v1.5. Each verse becomes a 1024-dimensional vector stored as JSON, compressed into ZIP files by book. When you visit the site, your browser downloads Transformers.js and the BGE model. The…
Oct 2025 · biblos.app
- 10GD
We're a team of three friends who have been working with forms and Open Source for a decade, and we joined forces together to create something where we can apply all of our experience. We recently released GolemUI, an Open Source library to generate forms dynamically from JSON definitions, with a typed layer to simplify authoring. This library has a lot to offer. These are the main characteristics: 1. A JSON engine. The form is governed by a JSON definition that you can store in a DB, version, diff, or generate it with LLMs as a validated JSON. 2. We provide also 28 headless components (and…
Jul 2026 · golemui.com
- 11AD
I created a daily game where you get a random Bible verse and try to identify the book (e.g. "Psalms", "Genesis", "Luke") in as few guesses as possible. I have absolutely no clue how I got the idea, other than the fact that I grew up in the Orthodox Church and all my other coding projects have been faith-related (a terrible mobile app (1) and slightly broken Byzantine chant website (2) ). I'm a relatively new developer and I've been hungry for a project to build that people will actually use and share around, so I hoped this would fit the bill. Sure enough, friends and family have been…
Jan 2026 · bibdle.com
- 12CA
Synthetic data generation is an essential step in training and evaluating LLMs/Agents/RAG pipelines, but tooling around this is still lacking. We're introducing Curator, an open-source library designed to streamline the data curation process. While there are many libraries to prompt LLMs, the semantics of generating synthetic data is different from prompting. For example, we need to process a large number of prompts (sometimes in millions or more) while accepting some failures, utilize several stages of prompting, incorporate human feedback, and filter out bad data using verifiers…
2025 · github.com
- 13AT
Hey HN! Erik here from banana.dev We’ve trained a small(ish) language model on structured extraction, and today we’re launching a playground for it at https://anythingtojson.com. Give it a try! This model continues our work on structured generation, following last week’s launch of Fructose[1], a python client for strongly-typed LLM responses. There seem to be two distinct halves of the problem intended to be solved by Fructose and structured generation: 1. the reasoning ability of the model, such as performing chain of thought, creative acts, and natural language tasks. In a way,…
2024 · anythingtojson.com
- 14IP
To be specific, the content is generated by a GPT-2 based model. https://amzn.to/2TCc0v2 Let me know if you have any questions :-)
2020
- 15SB
Hey HN! My brothers and I have worked on this for the last 2 weeks. We use OpenAI's `text-embedding-ada-002` model to embed queries and a vector database to search for similar verses / blocks of verses. We'd like to see what you think and appreciate any feedback!
2023 · siliconscripture.org
- 16IB
I use AI while reading the Bible and I suspect others do too. It's helpful whether you're struggling with the Elizabethan English, or want added context/want to know what theologians say about a passage. So I thought, why not make the AI come to you? TIA for any feedback!
2025 · scripturia.com
- 17
- 18EA
2024 · barneyhill.com
- 19
AI-powered Bible study. Any verse, deeply understood.
Jul 2026 · scriptureinsight.site
- 20
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- 22CE
Hi all, I open sourced my toy project that runs Generative AI models LOCALLY in the side panel of a Chrome extension. The Chrome extension uses Transformers.js to run models in browser under the hood. I've integrated and tested these models so far. \1. LLM: Llama 3, Phi 3.5, Qwen 2.5, SmolLM2 \2. Reasoning: DeepSeek R1 \3. Multimodal LLM: Janus \4. Speech-to-Text: Whisper On an M1 MacBook, DeepSeek R1 1.5B runs at ~30 tokens/sec If you're interested in, you can download the extension from chrome web store or clone my github repository. \1. chrome web store:…
2025 · github.com
- 23TP
2016 · dodecaglotta.com
- 24ET
This is a simple text editor, made using gtkmm 3 and llama.cpp, that allows you to explore the possible continuations (ranked by descending probability) that an LLM would output after each token. I was quite surprised that there didn't seem to be a tool like that out there yet, so I decided to make my own. Source is on Github (https://github.com/blackhole89/autopen), though the code is still in a very rough shape.
2024 · youtube.com
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