Sigma Computing’s Post

The products which are productionized are the only ones which generate value. If you are building applications on top of an LLM and want to productionize it then this guide book is of great help. We at KI Reply help iur customers in achieving the same with perfection! Contact Daniel Hummel or Ramakant Agrawal or at apply.ki@reply.de #productionizellm #value #genai #llamaimdex

How to Deploy your LLM App 101 ⚙️ Here’s a fantastic primer by Wenqi Glantz on how to deploy a LlamaIndex app to a full-fledged service on AWS Fargate, with Terraform (HashiCorp) and an automated CI/CD pipeline with GitHub Actions. This is a must read for literally any AI engineer looking to productionize their LLM or RAG application - will save you lots of time in the long run ‼️ The guide walks through every step:  1. Adding Terraform yaml files 2. Adding GitHub Actions workflow to provision a cluster 3. Containerize your LLM app with Docker, Inc 4. Setup secrets in your GitHub repo, propagate to Terraform  5. Integrate deployment into your CI/CD pipeline Blog: https://lnkd.in/gkbXvCgs Repo: https://lnkd.in/gWzPc3wC

Having a proper CI/CD pipeline setup for your application is a key component. One of the most popular CI/CD tools is Github Actions and workflows. The example below from Afaque Umer shows how you can build an app, make a docker image of it and integrate this with a CI/CD pipeline with Github Actions. https://lnkd.in/eWfGZi5f

Having a proper CI/CD pipeline setup for your application is a key component. One of the most popular CI/CD tools is Github Actions and workflows. The example below from Afaque Umer shows how you can build an app, make a docker image of it and integrate this with a CI/CD pipeline with Github Actions. https://lnkd.in/g4sMUrYu

Hey everyone, I'm excited to share the final part of my blog series on how to build a machine learning web app drowsiness detection, I'll show you how to deploy your app to the cloud using Streamlit. You'll learn how to set up your project folder, import your trained Ultralytics model, and deploy for web. By the end of this tutorial, you'll have a fully functional machine learning web app that you can share with the world. Check out the link below and let me know what you think. I hope you enjoyed this series and learned something new. Thanks for reading!

I have successfully completed the lab. Over the course of this lab, I have performed the following tasks: 1- Used a ListView widget 2- Refactored code to use ListView.builder 3-Added notifications to Flutter using a SnackBar widget 4- Declared a new Flutter page 5-Passed data between Flutter pages

Got Bored of multiple IDE's for different computer languages to work? 🥱 Don't want to install many tools to code? 😓 Your system is not supporting multiple applications running simultaneously? 😪 ------- Why Worry..? 🤔 Here we go, Google introducing a new AI based IDE ( Integrated Development Environment ) for cross technologies, without installing any application physically in your device...!🌐 Doesn't it sound awesome...! 😀 Then why late, click the link below, and join the waitlist..! 👇 https://idx.dev/ #projectidx #google #ai #salesforce #java #python #webdevelopment #wcy #ghk #linkedinfamily

#Plotly Dash and Databricks go together like PB&J – they're better together! 🥜🍓 Dash is an effective control panel for the Databricks SDK that enables dynamic, interactive, production-grade data application workflows. In this article from Cal Reynolds, learn how you can leverage the Databricks Jobs API via the Databricks SDK to run an ML workflow in a Databricks notebook, all from a front-end Plotly #Dash web app. https://lnkd.in/gRbzjQj5