Joe McElroy

598 posts

Joe McElroy

Joe McElroy

@phoey1

engineering @elastic. working on @searchkit. Github https://t.co/cyMFUPZHNH

London UK Katılım Kasım 2008
233 Takip Edilen149 Takipçiler
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Joe McElroy
Joe McElroy@phoey1·
Searchkit: React Components for elasticsearch. Make fast usable searches quick! searchkit.co
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Joe McElroy
Joe McElroy@phoey1·
@JesseCohenInv I don’t think this leaves people jobless for those who want to work. It should be viewed as entry level roles disappear because the bar is higher. We will also have a higher ceiling to excel.
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Joe McElroy
Joe McElroy@phoey1·
@JesseCohenInv We need to stop viewing AI as a replacement for the worker and start seeing it as the treadmill. It’s raising the floor of what a human needs to do, but it’s also providing the gym for them to get that strong before they even start.
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Jesse Cohen
Jesse Cohen@JesseCohenInv·
Anthropic CEO Dario Amodei warns: “50% of entry-level white-collar jobs could be disrupted within the next 1–5 years.” From law to finance to consulting, he says that AI is capable of handling a wide range of knowledge work.
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Joe McElroy
Joe McElroy@phoey1·
@johtani_en @xeraa Hey Jun, could you tell me steps you did where you encountered the issue? Happy for this to be in a DM :)
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Jun Ohtani(Ver. en)
Jun Ohtani(Ver. en)@johtani_en·
@xeraa It is basicaly fine. But the search-lab pages are buggy unfortunately...
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Jun Ohtani(Ver. en)
Jun Ohtani(Ver. en)@johtani_en·
Um, I clicked the link to the search lab page on Elastic web site, then it shows always 404 page... Because of the language selector... I always edit the URL on my browser...
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Joe McElroy retweetledi
LangChain
LangChain@LangChain·
🦜🏁Self Query Template (@elastic) Often times documents come with really useful metadata! But how can you best take advantage of this metadata when doing RAG? 🤔 Self-query is one way to do so. This converts a 🗨️natural language query into one piece that is embedded and compared via cosine similarity, just as in naive RAG. But then a "metadata filter" is also extracted, that can be applied to metadata present in the vectorstore ❓This is useful because often times a query may not only refer to semantic meaning, but could also reference some of the metadata For example: "what is a movie about aliens from the year 1980" 👽 While "aliens" may be a semantic query, "year == 1980" is not, this is an explicit filter that should be applied Most vectorstores allow for some metadata filters, so this can be used with most of them Check out our recent template which does this for ElasticSearch: github.com/langchain-ai/l… This is an example "query construction" - check out @RLanceMartin's awesome post on this from earlier in the week: blog.langchain.dev/query-construc…
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Derek Cheung
Derek Cheung@derekcheungsa·
@llama_index @elastic @phoey1 This is a great addition! I see in the example the retrieval says it did not find the context info for the question. Is there anything missing in the retrieval parameters
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LlamaIndex 🦙
LlamaIndex 🦙@llama_index·
LlamaIndex + @elastic 🚀 This has been a highly requested feature (a lot of our users are using Elasticsearch!) HUGE shoutout to @phoey1 for making this happen. - Vector/text/hybrid search - Metadata + metadata filtering - es_filters - And more! gpt-index.readthedocs.io/en/stable/exam…
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LangChain
LangChain@LangChain·
The latest and greatest in 🦜🔗: 🧠 @neural_internet Bittensor LLM ⚡ DashVector store 🤖 @zep_ai vector store ♻️ @elastic search self-querying retriever a 🧵:
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LangChain
LangChain@LangChain·
♻️ @elastic search self-querying retriever Combine the power of the Elasticsearch vector store with LangChain’s query constructor chain to create a self-querying retriever. Huge s/o to @phoey1 for continuing to add Elasticsearch features to 🦜🔗! Docs: python.langchain.com/docs/modules/d…
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Philipp Krenn
Philipp Krenn@xeraa·
more #elasticsearch integrations coming your way :) PS: we'll also have LangChain at our upcoming ElasticON AI event in san francisco: elastic.co/events/elastic…
LangChain@LangChain

🤹 New @elastic vector store @phoey1 has done a huge revamp and added a new Elasticsearch-backed vector store, allowing for a number of new index / query strategies. Try it out: ``from langchain.vectorstores import ElasticsearchStore`` Docs: python.langchain.com/docs/integrati…

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LangChain
LangChain@LangChain·
New in 🦜🔗==0.0.265! 3 new model wrappers and vector store improvements: 🐾 Ernie chat model 🚅 @berriai LiteLLM chat model support 🪄 @neuralmagic DeepSparse LLM 🤹 Major @elastic vector store improvements a 🧵:
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LangChain
LangChain@LangChain·
🤹 New @elastic vector store @phoey1 has done a huge revamp and added a new Elasticsearch-backed vector store, allowing for a number of new index / query strategies. Try it out: ``from langchain.vectorstores import ElasticsearchStore`` Docs: python.langchain.com/docs/integrati…
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Benjamin Trent
Benjamin Trent@benwtrent·
This is why optimization tasks are addictive! Getting some nice improvements for vector search in Apache Lucene 9.7. github.com/erikbern/ann-b…
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Shay Banon
Shay Banon@kimchy·
Why we designed, in the last couple of years, Elasticsearch and Lucene vector database implementation the way we did, and where we are heading elastic.co/fr/blog/vector…
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Shay Banon
Shay Banon@kimchy·
I ❤️Lucene. Like so many times before (real time search, doc values, bm25, bkd, compressions, …), we are actively investing in making Apache Lucene also a great Vector Database elastic.co/blog/accelerat…
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Doug Turnbull
Doug Turnbull@softwaredoug·
If I don’t say it enough, this is a fantastic resource lnkd.in/gX6c8fqA
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