Posts Tagged pulumi

Uploading documents to your AI Slackbot in real-time using S3, SQS and Pulumi on AWS

Uploading documents to your AI Slackbot in real-time using S3, SQS and Pulumi on AWS

In the introductory blog post, we learned to Create an AI Slack Bot to Chat with Your Data Using Embedchain, Pulumi on AWS, and continued with Adding data to Pinecone using S3, Embedchain, and Pulumi on AWS for an AI Slack bot. For reference, here’s what our architecture looked like at the end of the second blog post. To follow along, clone the project, git clone https://github.com/catmeme/arti.git or view it on GitHub.

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Adding data to Pinecone using S3, Embedchain and Pulumi on AWS for an AI Slack bot

Adding data to Pinecone using S3, Embedchain and Pulumi on AWS for an AI Slack bot

In the introductory blog post, we learned to Create an AI Slack Bot to Chat with Your Data Using Embedchain, Pulumi on AWS. However, we made a few concessions in the application logic to illustrate the broader picture of what we were able to achieve combining these three technologies. Now that we have a solid foundation for deploying our Slack bot and querying our data, lets begin moving from proof-of-concept to production-ready, iteratively.

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Create an AI Slack Bot to Chat with Your Data Using Embedchain, Pulumi on AWS

Create an AI Slack Bot to Chat with Your Data Using Embedchain, Pulumi on AWS

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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The Pulumi 'Push to start' GitOps Experience

The Pulumi 'Push to start' GitOps Experience

As a skeptic of “quick starts” myself, I approach most marketing promises with a measure of cautious excitement. If the great and powerful algorithm, friends, or a peer brought your attention here, then I invite you to take this one seriously.

Pulumi, with its full support of many general-purpose programming languages, can appear like a chore to get started with. The feeling can haunt seasoned developers as much as practitioners new to infrastructure code.

However, I’ll show you that finding the proverbial easy street is easier than you might believe. The pulumi new developer story just gets sweeter when combined with a few other nice-to-have conveniences.

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Converting Bicep code to Pulumi

Converting Bicep code to Pulumi

Bicep is a DSL developed by Microsoft to simplify the authoring of ARM templates and deploy resources to Azure. Today I will be sharing with you a new Pulumi converter plugin that I have been working on that converts Bicep code to any of the supported Pulumi languages.

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Pulumi CLI now displays time elapsed per resource

Pulumi CLI now displays time elapsed per resource

If you’ve deployed resources to your favorite cloud provider, you have probably found yourself sitting in the console thinking: “I don’t know how long this is going to take.” Then you deploy the resource and think: “When did I even start this?” When using Pulumi, the CLI prints out how long the update took after it ran, but while you’re in the moment, it feels like ages. We’re excited to announce a CLI usability enhancement You can now see how long each of your resources are taking to deploy.

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Snowflake Provider Launch

Snowflake Provider Launch

Snowflake support is here! Pulumi’s new Snowflake Provider gives you the ability to easily set up cloud storage and manage your connections to Snowflake, right alongside the rest of your code.

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