mljourney

Jupyter Notebook is the standard environment for data science, machine learning research, and exploratory Python work. Connecting it to Ollama gives you an interactive local AI assistant that understands your code and data — you can ask questions about dataframes, generate visualisation code, explain statistical results, and iterate on analysis with a local LLM, all … Read more

PDFs are everywhere — research papers, contracts, reports, invoices, technical manuals. Being able to summarise, extract information from, and query a PDF using a local LLM means you can process sensitive documents without sending them to a cloud API. This guide walks through building a complete local PDF processing pipeline in Python: extracting text, handling … Read more

Django is the most popular Python web framework, and adding local LLM capabilities to a Django application is straightforward with Ollama. Whether you want an AI-powered chat endpoint, automatic content summarisation, intelligent search, or document analysis, Ollama provides a local HTTP API you can call from anywhere in a Django project — views, models, management … Read more

Open WebUI’s Pipelines feature is one of its most powerful and underused capabilities. Pipelines let you intercept every message that flows through Open WebUI — before it reaches the model and after the model responds — and run custom Python logic at each stage. You can use this to add RAG retrieval, apply content filters, … Read more

Bash is the glue language of Linux and macOS systems, and Ollama’s HTTP API is simple enough to call with nothing more than curl. This means you can integrate a local LLM into shell scripts, cron jobs, aliases, and pipelines without installing any additional tools or language runtimes. This guide covers the essential patterns for … Read more

A terminal user interface gives you the interactivity of a chat application without leaving the command line. Building one for Ollama means you get a keyboard-driven, full-screen local AI assistant that starts in milliseconds, requires no browser, and works over SSH. This guide walks through building a polished TUI chat application in Python using the … Read more

Scala is a powerful language that sits at the intersection of object-oriented and functional programming, widely used for data engineering, distributed systems, and backend services. Ollama exposes a simple HTTP API that any Scala HTTP client can call, and Scala’s strong type system lets you model the request and response shapes precisely with case classes. … Read more

Emacs is one of the oldest and most extensible editors in existence, and its Lisp-based extension system makes it a surprisingly capable platform for local AI integration. Connecting Emacs to Ollama gives you AI assistance that runs entirely on your own hardware — inline completions, multi-turn chat, code explanation, and documentation generation — all without … Read more

Neovim has become the editor of choice for a significant portion of the developer community, and its Lua-based plugin ecosystem makes it surprisingly capable as a local AI coding assistant. By connecting Neovim to Ollama, you get code completions, inline chat, and documentation generation that run entirely on your own hardware — no GitHub Copilot … Read more

Haskell is an unusual choice for AI integration work — but that is part of what makes it interesting. Its strong type system, purely functional model, and lazy evaluation make it excellent for building reliable data pipelines, and Ollama’s simple HTTP API is easy to call from any language with an HTTP client. This guide … Read more