Posts Tagged ai

The integration of artificial intelligence (AI) to improve user experiences is gaining popularity in today’s world. One fascinating application of AI is the creation of chatbots, which can engage users in conversation and provide helpful information or services.

In this blog post, we’ll explore the process of building an AI-powered Slack bot using Embedchain, a Retrieval-Augmented Generation (RAG) framework powered by LangChain. Additionally, we’ll deploy our bot on AWS using Pulumi, a modern infrastructure as code (IaC) platform.

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Building low-code LLM applications just got easier! With Flowise, LocalAI, and Pulumi, you can quickly create, deploy, and manage AI-powered workflows on AWS EKS—without writing complex code.

In this guide, you’ll learn how to:

1. Set up a low-code LLM application using Flowise & LocalAI
2. Deploy it on AWS EKS with Pulumi & TypeScript
3. Create a chatbot workflow and expose it via API

Flowise simplifies LLM orchestration with a drag-and-drop interface, while LocalAI enables local inference without requiring a GPU. Pulumi streamlines cloud infrastructure deployment with just a few lines of code.

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AI is impacting almost every industry today, and for good reason - we are seeing fundamentally new experiences being made possible across a wide variety of products, and a set of new AI capabilities that promise even more incredible change in the near future.

Software development is among the earliest and most prominent fields to realize the benefits of AI, evidenced by the rapid adoption of tools like Github Copilot which is now one of the most heavily adopted developer tools of all time. Developers are benefiting from an incredible increase in their productivity with better scale and faster time to market.

We’re seeing the impacts of AI in the cloud Infrastructure development space in two impactful and complimentary directions:

• 🤖➜☁️: AI is transforming how we author, build and manage cloud infrastructure
• ☁️➜🤖: Cloud infrastructure tooling is changing how we build and deliver AI-based applications

At Pulumi, we’ve already seen profound impacts from AI in both of these directions.

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We all know how easy it is to create, deploy, and manage any cloud infrastructure with Pulumi using your favorite programming language. With the rise of artificial intelligence (AI) more and more developers are working on LLM-powered applications and services. And with this, the need to have the same ease of use for creating, deploying, and managing the infrastructure for these applications is growing.

In this blog post, we will show you how to this can be achieved with combining Pulumi and LangServe.

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Hello, Pulumi Pinecone Provider! 👋

The Pinecone integration with Pulumi offers a native way to manage Pinecone indexes, including the newly-announced serverless indexes. Utilize any of Pulumi’s supported languages to effortlessly create, update, and remove your Pinecone indexes. This integration facilitates the application of Infrastructure as Code principles, helping you to work even more efficiently. Furthermore, this gives you the benefit of tapping into Pulumi’s wide range of providers, offering you a diverse and powerful set of tools to enhance your development work.

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Earlier this year we launched Pulumi AI, a purpose-built AI assistant that can create Infrastructure as Code (IaC) from natural language prompts using Pulumi. Since launch, we’ve seen incredible adoption of Pulumi AI, with over 200,000 questions asked so far and growing fast. Pulumi AI is popular with users new to Pulumi and/or new to the Cloud, but also heavily used by many of the most advanced IaC users and organizations to quickly discover solutions to new problems they need to solve. Over the last few months, we’ve driven major improvements to Pulumi AI through the recently launched Pulumi AI Answers pages with thousands of AI generated answers to common questions, improvements to code generation correctness and performance, and expansion of the languages supported by Pulumi AI.

Today, we are taking the next big step, introducing support for deploying cloud infrastructure directly from Pulumi AI. Going from idea to running cloud infrastructure is just a natural language prompt away!

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The integration of artificial intelligence (AI) with DevOps signals a new era in software development. DevOps possesses unique characteristics and needs that make it exceptionally compatible with AI augmentation. Given that code fundamentally relies on language, and large language models (LLMs) serve as the core of GPT functionality, these models are particularly well-suited for tasks such as code generation. This article unwraps the topics addressed during our “AI: Friends or Foe | AI Talks for DevOps” event in San Francisco.

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The emergence of DevOps revolutionized software development. Now, with AI powered tools like LangChain, these transformations are being accelerated. Unsurprisingly, our distinguished speaker at the launch of Pulumi’s in-person AI Talks, Patrick Debois, who coined the term “DevOps,” has recently tuned into LLM and GenAI Ops using the Langchain framework.

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Earlier this year we introduced Pulumi Insights, a collection of features that bring intelligence to cloud infrastructure using Pulumi. Two key components of that launch were Pulumi AI, a generative AI assistant purpose-built to create cloud infrastructure using natural language, and Pulumi Resource Search, multi-cloud search and analytics across every cloud resource and environment in your organization.

Today, we are excited to bring Pulumi Insights into the pulumi CLI with the new pulumi org search and pulumi ai commands. These commands put AI and resource search at your finger tips right where Pulumi users spend most of their time, in the terminal iterating on their cloud infrastructure.

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The process of taking an idea and turning it into reality has been nothing short of extraordinary since we started innovating with Artificial Intelligence. With this technology, machines learn about and communicate with people, while also helping us in ways we never could have imagined only a few years ago. If you’ve been following along, you might recall our previous article where we used Python and Pulumi to a chatbot API (named katwalk) to the cloud.

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