HN user

dmezzetti

861 karma

Founder of NeuML (https://neuml.com)

Creator of txtai (https://github.com/neuml/txtai)

Posts108
Comments343
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hub.docker.com 1y ago

Annotate and Highlight Papers with LLMs

dmezzetti
3pts0
pypi.org 1y ago

Annotate and Highlight Papers with LLMs

dmezzetti
4pts2
pypi.org 1y ago

Show HN: AnnotateAI – Automatically annotate papers using LLMs

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3pts1
pypi.org 1y ago

Show HN: txtai 8.1: Docling integration and Postgres/pgvector schema persistence

dmezzetti
1pts0
pypi.org 1y ago

txtai 8.1 released: Docling integration and Postgres/pgvector schema persistence

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github.com 1y ago

Extractous – Fast Text Extraction for GenAI with Rust and Apache Tika

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2pts0
medium.com 1y ago

Grow your open-source project 2.0

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1pts0
colab.research.google.com 1y ago

Show HN: Analyzing Hugging Face Posts with Graphs and Agents

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1pts0
colab.research.google.com 1y ago

Analyzing Hugging Face Posts with Graphs and Agents

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1pts0
colab.research.google.com 1y ago

Show HN: txtai 8.0 released: an agent framework for minimalists

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pypi.org 1y ago

txtai 8.0 released: an agent framework for minimalists

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3pts1
hub.docker.com 1y ago

Retrieval Augmented Generation (RAG) App for txtai

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2pts0
github.com 1y ago

Model2Vec: Distill a Small Static Model from Any Sentence Transformers Model

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pypi.org 1y ago

txtai 7.5 released: Speech to Speech RAG, new TTS models and Generative Audio

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pypi.org 1y ago

txtai 7.5 released: Speech to Speech RAG, new TTS models and Generative Audio

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pypi.org 1y ago

txtai 7.4 released: embeddings index with platform-independent open data access

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medium.com 1y ago

Analyzing the Stock Market: Add up-to-date market data to LLMs

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medium.com 1y ago

More than chat, explore your own data with GraphRAG

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github.com 1y ago

NLTK version 3.8.2 is no longer available on PyPI

dmezzetti
1pts0
medium.com 1y ago

RAG with Txtai

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2pts0
hub.docker.com 1y ago

Show HN: Open-source GraphRAG Application with your own data

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12pts0
hub.docker.com 1y ago

Show HN: Open-source GraphRAG Application with your own data

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4pts2
neuml.github.io 2y ago

Txtai: Open-source vector search and RAG for minimalists

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249pts55
medium.com 2y ago

RAG made simple without the bloat: How to ground LLMs in reality

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2pts0
pypi.org 2y ago

txtai 7.3 released: Adds new RAG Web Apps and streaming LLM/RAG support

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old.reddit.com 2y ago

BERT Is an LLM?

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2pts1
old.reddit.com 2y ago

LLMs are not the only way

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neuml.github.io 2y ago

Show HN: txtai: open-source, production-focused vector search and RAG

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12pts1
arxiv.org 2y ago

Agentless: Demystifying LLM-Based Software Engineering Agents

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4pts0
medium.com 2y ago

Txtai – A Strong Alternative to ChromaDB and LangChain for Vector Search and RAG

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12pts1
Claude Science 22 days ago

Why does HN let OpenAI and Anthropic basically advertise but it throws down the gauntlet at a small developer like myself when we do "self promotion"?

Top 3 posts as of this moment are all about Claude.

The message here is good. I've now spent over 5 years in the OSS world (https://github.com/neuml). I started by picking a problem I was interested in and checking the work into GitHub. I've been extremely fortunate to have gained a following over the years.

Even with a following, most of the time when you publish it goes into the abyss. Every once in a while something hits but most of the time it takes a lot of patience and resolve. I've had some good visibility over the years from Reddit and Hacker News (though any post I make now on HN is marked as [dead]). It's not always fair and others can "pay" to get the visibility.

I've seen some of the other comments talking about the burden of OSS but I haven't felt that. I set my own agenda and fix what I want to fix. If someone wants to change my priorities that becomes a paid effort.

Companies that consider an open source project a critical part of their infrastructure should sponsor or compensate those projects.

Also when someone finds a bug, the maintainers are under no obligation to fix it or fix it with any timeline or even debug what's going on. If someone wants an immediate response they should provide compensation.

A common misconception is that OSS developers do everything for free. They do what THEY want for free. If YOU want to change their priorities, companies need to compensate for that.

Are multiple LLM queries faster than vector search? Even with the example "dog OR canine" that leads to two LLM inference calls vs one. LLM inference is also more expensive than vector search.

In general RAG != Vector Search though. If a SQL query, grep, full text search or other does the job then by all means. But for relevance-based search, vector search shines.