π Implement semantic search in #Postgres in 15 minutes.
π Use pgml and pgvector extensions
π’ Convert text to embeddings
βοΈ Measure vector similarity
π Optimize with HNSW indexes
http://dlvr.it/TFZyW0
π Implement semantic search in #Postgres in 15 minutes.
π Use pgml and pgvector extensions
π’ Convert text to embeddings
βοΈ Measure vector similarity
π Optimize with HNSW indexes
http://dlvr.it/TFZyW0
How to build a better search engine for @ycombinator job listings π§ π»
Our guide shows you how to:
Powered by @runtrellis & the @postgresml SDK, Korvus
π Tutorial: http://dlvr.it/TF9Dx3 π» π» π»
PostgresML now supports Llama 3.2 π¦
π¦ Free for all Serverless Database users
π Bring models to your data, not vice versa
β¨ Smaller models, bigger capabilities
Read on in the blog: [http://dlvr.it/TDlpqs
Ever wondered how RAG works inside a database?
Check out our latest chatbot β‘οΈ
It performs RAG over all of Wikipedia, using open-source models directly in Postgres.
β¨Full RAG workflow in one SQL query
πIn-database processing
π100% open-source
Try it: http://dlvr.it/TDgLwF
π postgresml-django
Seamlessly integrate ML/AI with #django ORM
β¨ Automatic in-database embeddings
π Vector similarity search
π§ ML-powered Django projects
Try it now, let us know what you think.
http://dlvr.it/TD4N31
Check out what @sudowrite pulled off with their RAG stack:
β‘οΈ Whipped up a prototype in just 3 hours
πNow crunching 1M+ calls/hour like it's nothing
π Doing all this fancy AI stuff inside their Postgres DB
Get the details here π [http://dlvr.it/TCRY5B
Too many enterprise AI/ML apps are out of date before they launch, and unmaintainable long term. π
Why?
Complex data pipelines. Isn't there a better way?
β¬οΈ
http://dlvr.it/TBd1Ps
Want to see how devs are using PostgresML? π¦
Check out this great rundown from @Krishnaik06 β¬οΈ
http://dlvr.it/TBX8JF
RAG Retrieval Speed Showdown π
We conducted a hands-on speed comparison of the most popular RAG retrieval systems.
π Dive into our full blog post to get the details and analysis.
http://dlvr.it/TBJyNK
"Open source AI is important, not because of some pedantic definition by some pseudo-official body like OSI β itβs important because of the power and incentive structures that pervade our society."
Read on in our blog β‘οΈ
http://dlvr.it/TB2B9v
Excited to announce meta-llama-3.1 support in PostgresML Cloud! π¦ + π¦
Get the details on our blog β‘οΈ
http://dlvr.it/T9zdFY
Learn how to do RAG in Python...on Postgres. With @NeuralNine
β‘οΈ http://dlvr.it/T9myN5
RAG in a single query. On Postgres. That's Korvus.
Our new open-source RAG pipeline combines the entire RAG workflow - from embedding to text generation - into a single DB query...one query to rule them all βοΈ No SQL necessary. Python, JS, or Rust.
β‘οΈ http://dlvr.it/T9QlcK
PGML + DBT = β€οΈ
Are you a data engineer looking to incorporate NLP into your data workflow? Check out this tutorial on getting up and running quickly and easily using DBT and PostgresML.
http://dlvr.it/T96mg4
Rather than shipping the entire vector back to an application like a normal vector database, PostgresML includes all the algorithms needed to compute results internally.
Learn more β‘οΈ
http://dlvr.it/T91syY
Swap OpenAI with any open-source model β‘οΈ
http://dlvr.it/T8pFYp
How to generate LLM embeddings with open source models from Hugging Face π€
http://dlvr.it/T8jLsF
How to create a semantic search engine with nothing but SQL β‘οΈ
Introducing Unified RAG β a practical solution to the pitfalls of typical LLM apps.
http://dlvr.it/T8DnHV
Introducing Unified RAG β a practical solution to the pitfalls of typical LLM apps.
http://dlvr.it/T8DkkX
How to build a Django app -- with the spicy addition πΆοΈ of semantic search -- powered by embedding models running inside your PostgreSQL database.
http://dlvr.it/T8B9T6
10 minutes to RAG | A step-by-step video tutorial π¦
http://dlvr.it/T87cyr
In-database ML represents a strategic shift to leverage data more effectively. By enabling MLOPs directly within the DB, more orgs can make AI apps that are more efficient, effective and reactive to real-time data changes.
http://dlvr.it/T851Vz
Moving from AWS β‘οΈ GCP with minimal downtime
4 lessons learned from our cloud migration
http://dlvr.it/T7z026
Serverless LLMs don't work. Bringing your models in-database is the answer.
postgresml.org/blog/serverl...
π¦ + π¦
We are excited to announce the official release of our Rust SDK, now available on crates.io.
http://dlvr.it/T7wYY6