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Continue reading →: AI For Good – Book ReviewAs part of my ongoing CPD I am learning more about Artificial Intelligence (AI), and as someone who enjoys reading that gave me another reason to read “AI For Good: Applications in Sustainability, Humanitarian Action, and Health“. Published by Wiley in 2024, and edited by Juan M. Lavista Ferrers (PhD,…
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Continue reading →: Mocking (Python)When I write code I like to include tests. Tests help me to reduce the risk of code breaking changes and give me the reassurance that what I have coded does what I need it to do. I’m currently writing a backend (Django/Python) that serves some APIs and a frontend…
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Continue reading →: Terraforming ProxmoxA blog post looking at using Terraform to deploy a container into Proxmox.
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Continue reading →: JavaScript: json-serverWhen developing code that calls on APIs (Application Programming Interface) it can be a pain having to call the API multiple times just whilst coding the initial call or during testing. NPM (A package manager for Node) has a package that solves this called json-server. It can be installed via:…
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Continue reading →: DevOps: What is DORA?DORA is an acronym for DevOps Research and Assessment. The DORA team carry out research into the DevOps movement and produce “State of DevOps” reports to show what is happening in DevOps across teams across the world. The DORA State of DevOps reports from 2014 onwards can be found at:…
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Continue reading →: DevOps: Muri, Mura, MudaWhen discussing DevOps the Agile principles of Muri, Mura and Muda are key to help identify areas where improvements can be made. Muri Muri is overbudening. Overburdening a system, such as running an engine at its at limits can produces results for a while but it eventually causes burnout. Unlike…
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Continue reading →: LLM – Terminology To HelpMy current learnings around Large Language Models (LLMs) has lead to me running into more acronyms and terms that have either left my memory or are new to me. I decided a blog post was needed to help me keep track. NLP Natural Language Processing. The use of Machine Learning…
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Continue reading →: LLM – Retrieval Augmented Generation (RAG) with Ollama EmbeddingsThe work on the Large Language Model (LLM) bot so far has seen the running of LLM locally using Ollama, a switch in models (from tinyllama to gemma) whilst introducing LangChain and then the switch to LangChain templates. Note: If you skipped the previous blog entry posts, I’m following along with…
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Continue reading →: LLM – Langchain Templates (Python)I finished my previous blog post with the aim of looking at Langchain’s template options. I feel like I was on a similar path during my last post, with defining the initial prompt to be passed each time. However, the Langchain templates allow for easier and more thorough control. Langchain…
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Continue reading →: Interacting with Ollama with Langchain (Python)In my previous blog post I installed Ollama locally so that I could play around with Large Language Models (LLMs). I used Python with requests to do a test of the LLM, but also wrote that there are Ollama Python libraries available. In this blog post I’m taking a look…

