Tag · 11 posts
#python
Dapr Workflow: code that picks up where it left off
Lots of the work I see in projects is a chain of steps: fetch a document, convert it, call a model, write the result somewhere. You write it as a background job that reads from a queue, and it works fine until the process restarts halfway through a 300-page PDF or a model call times…
aiGoogle’s A2A: taking a closer look
In the previous post, I talked about options to build multi-agent solutions. The last option used Google’s A2A. A2A provides a wrapper around your agent, basically a JSON-RPC API, that standardizes how you talk to your agent. In this post we take a closer look at the basics of A2A with simple synchronous message exchange.…
aiToken consumption in Microsoft’s Graph RAG
In the previous post, we discussed Microsoft’s Graph RAG implementation. In this post, we will take a look at token consumption to query the knowledge graph, both for local and global queries. Note: this test was performed with gpt-4o. A few days after this blog post, OpenAI released gpt-4o-mini. Initital tests with gpt-4o-mini show that…
aiEmbedding flows created with Microsoft Prompt Flow in your own applications
A while ago, I wrote about creating your first Prompt Flow in Visual Studio Code. In this post, we will embed such a flow in a Python application built with Streamlit. The application allows you to search for images based on a description. Check the screenshot below: There are a few things we need to…
aiFast chat bot creation with the OpenAI Assistants API and the Microsoft Bot Framework SDK
This post is part of a series of blog posts about the Azure OpenAI Assistants API. Here are the previous posts: Part 1: introduction Part 2: using tools Part 3: retrieval In all of those posts, we demonstrated the abilities of the Azure OpenAI Assistants API in a Python notebook. In this post, we will…
aiRetrieval with the Azure OpenAI Assistants API
In two previous blog posts, I wrote an introduction to the Azure OpenAI Assistants API and how to work with custom functions. In this post, we will take a look at an assistant that can answer questions about documents. We will create an HR Assistant that has access to an HR policy document. In addition,…
aiA look at the Azure OpenAI Assistants API
Introduction A while ago, I looked at the OpenAI Assistants API. In February of 2024, Microsoft have released their Assistants API in public preview. It works in the same way as the OpenAI Assistants API while being able to use it with Azure OpenAI models, deployed to a region of your choice. The goal of…
aiUse Azure OpenAI Add your data vector search from code
In the previous post, we looked at using Azure OpenAI Add your data from the Azure OpenAI Chat Playground. It is an easy-to-follow wizard to add documents to a storage account and start asking questions about them. From the playground, you can deploy a chat app to an Azure web app and you are good…
aiStep-by-Step Guide: How to Build Your Own Chatbot with the ChatGPT API
In this blog post, we will be discussing how to build your own chat bot using the ChatGPT API. It’s worth mentioning that we will be using the OpenAI APIs directly and not the Azure OpenAI APIs, and the code will be written in Python. A crucial aspect of creating a chat bot is maintaining…
aiA quick look at Azure App Configuration and the Python Provider
When developing an application, it is highly likely that it needs to be configured with all sorts of settings. A simple list of key/value pairs is usually all you need. Some of the values can be read by anyone (e.g., a public URL) while some values should be treated as secrets (e.g., a connection string).…
automationWriting a Kubernetes operator with Kopf
In today’s post, we will write a simple operator with Kopf, which is a Python framework created by Zalando. A Kubernetes operator is a piece of software, running in Kubernetes, that does something application specific. To see some examples of what operators are used for, check out operatorhub.io. Our operator will do something simple in…
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