vectara-answer
elk
vectara-answer | elk | |
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13 | 63 | |
217 | 5,108 | |
1.8% | 1.7% | |
8.9 | 9.7 | |
8 days ago | 7 days ago | |
TypeScript | Vue | |
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.
vectara-answer
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Show HN: Quepid now works with vetor search
Hi HN!
I lead product for Vectara (https://vectara.com) and we recently worked with OpenSource connections to both evaluate our new home-grown embedding model (Boomerang) as well as to help users start more quantitatively evaluating these systems on their own data/with their own queries.
OSC maintains a fantastic open source tool, Quepid, and we worked with them to integrate Vectara (and to use it to quantitatively evaluate Boomerang). We're hoping this allows more vector/hybrid players to be more transparent about the quality of their systems and any models they use instead of everyone relying on and gaming a benchmark like BIER.
More details on OSC's eval can be found at https://opensourceconnections.com/blog/2023/10/11/learning-t...
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A Comprehensive Guide for Building Rag-Based LLM Applications
RAG is a very useful flow but I agree the complexity is often overwhelming, esp as you move from a toy example to a real production deployment. It's not just choosing a vector DB (last time I checked there were about 50), managing it, deciding on how to chunk data, etc. You also need to ensure your retrieval pipeline is accurate and fast, ensuring data is secure and private, and manage the whole thing as it scales. That's one of the main benefits of using Vectara (https://vectara.com; FD: I work there) - it's a GenAI platform that abstracts all this complexity away, and you can focus on building your application.
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Do we think about vector dbs wrong?
I agree. my experience is that hybrid search does provide better results in many cases, and is honestly not as easy to implement as may seem at first. In general, getting search right can be complicated today and the common thinking of "hey I'm going to put up a vector DB and use that" is simplistic.
Disclaimer: I'm with Vectara (https://vectara.com), we provide an end-to-end platform for building GenAI products.
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What is a GenAI Platform?
In this article I discuss my long-held belief that it's time we shifted the discussion from "which vector database to use" for GenAI and instead think about "how do we make this whole architecture simpler to use", a focus of GenAI platforms like https://vectara.com
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Comparison of Vector Databases
With Vectara (full disclosure: I work there; https://vectara.com) we provide a simple API to implement applications with Grounded Generation (aka retrieval augmented generation). The embeddings model, the vector store, the retrieval engine and all the other functionality - implemented by the Vectara platform, so you don't have to choose which vector DB to use, which embeddings model to use, and so on. Makes life easy and simple, and you can focus on developing your application.
- Vectara, une bonne alternative à l'ingestion de données par les LLMs
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Train a model based on text from pdfs
You can also use vectara to implement this. Just upload the docs via the indexing API and then run queries via the search API. It tends to be less complicated with Vectara since we take care of many things internally (vectorDB, embeddings, etc). Let me know if I can help further with that.
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ChatGPT-like interface for product search
I found vectara.com but all examples seem to be about feeding text. I'm not super technical so I may be missing something. Please let me know if I need to elaborate further.
- Vectara-Answer
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ChatGPT made everyone realize that we don't want to search, we want answers.
yes agreed that if ChatGPT becomes monetized the same way as Google, then it the fun will be over. We'll have to wait and see. I think though that this innovation is not just applicable to web search or consumer search, and with products like vectara.com providing this type of user experience in the enterprise there is a significant net gain here overall.
elk
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Phanpy: A minimalistic opinionated Mastodon web client
This has lead to a delightful variety of custom clients like https://phanpy.social/ - https://elk.zone/ is another example that I really like.
It's the complete opposite of the Twitter API situation, where they locked their API down and killed the entire ecosystem of third-party clients.
- Elk client for Mastodon is in Preview mode
- Mozilla.social is live and open to registration
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Do we think about vector dbs wrong?
And there are tons of third party clients. I think Tusky is the best one I’ve seen for Android, and there’s an interesting web-based one called Elk that’s very nice. You load up https://elk.zone and then use it as a front-end to sign in to your server.
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BBC on Mastodon: experimenting with distributed and decentralised social media
The answer to that is https://elk.zone atm, a fun and chef's kiss interface (built with nuxt). You can insert elk.zone/ before any Mastodon url. https://phanpy.social is also great, with multi columns even for lists.
A browser plugin (like "Mastodon – Simplified Federation") to follow, favorite, etc. directly on any server has also improved my experience a lot.
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Ask HN: What will it take to get more people using Mastodon more?
Quick! Tell Obama and Taylor Swift about https://elk.zone! They're going to be so excited!
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/r/WorldNews Live Thread: Russian Invasion of Ukraine Day 495, Part 1 (Thread #641)
Also try logging in through https://elk.zone/ if you want to stick with the familiar twitter interface
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Why are reblog/favourite numbers different between platforms?
For me, the boost/reply-numbers using https://elk.zone have been much more reliable than the original app. (It's also the (web)app that convinced me. Mastodon is the real deal.)
- Extraño el internet viejo
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New Mastodon for Android release coming next week [...] new profiles, new settings, new search, and more
Try elk.zone. You can log into the UI with an account from any instance. I use it as my main UI and it looks pretty close to twitter, at least close enough for me.
What are some alternatives?
llama-hub - A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
mjs - Embedded JavaScript engine for C/C++
llm-applications - A comprehensive guide to building RAG-based LLM applications for production.
mastodon - A glitchy but lovable microblogging server
VectorDBBench - A Benchmark Tool for VectorDB
Mastodon - Your self-hosted, globally interconnected microblogging community
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
pinafore - Alternative web client for Mastodon (UNMAINTAINED)
motorhead - 🧠 Motorhead is a memory and information retrieval server for LLMs.
FastHamming - Fast implementation for truncateable extended (127,120) Hamming codes
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
vitest - Next generation testing framework powered by Vite.