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
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
FastAPI has become the go-to Python framework for building APIs quickly — it is fast, well-documented, and generates OpenAPI docs automatically. Paired with Ollama, it gives you a clean way to expose a local LLM as an HTTP API that any client can consume: a web frontend, a mobile app, a CLI tool, or another … Read more
Ansible is the most widely used tool for automating server configuration, and it is a natural fit for deploying Ollama across multiple machines. Whether you are setting up a single GPU workstation, a fleet of developer machines, or a homelab cluster, an Ansible playbook lets you install Ollama, configure it as a service, pull models, … Read more
Rust is an increasingly popular choice for systems programming, CLI tools, and high-performance web services. If you are building a Rust application and want to add local LLM capabilities without a cloud dependency, Ollama exposes a straightforward HTTP API that any Rust HTTP client can call. This guide covers everything from basic chat completions to … Read more
Dart and Flutter have matured into a serious cross-platform development stack. If you are building a Flutter app and want to add AI capabilities without depending on a cloud API — no monthly bill, no data leaving the device or the local network — Ollama gives you a simple HTTP interface that any Dart application … Read more
Kotlin has become the language of choice for Android development and is increasingly popular on the server side thanks to frameworks like Ktor and Spring Boot. If you are building a Kotlin application and want to add local LLM capabilities without routing requests through a cloud API, Ollama is the most straightforward way to do … Read more
Discord has become one of the most popular platforms for developer communities, gaming groups, and hobbyist projects alike. If you’re already running a local LLM with Ollama, building a Discord bot that connects to it is a natural next step — you get a private, free AI assistant available to your entire server, with no … Read more
A practical guide to building Ollama chat interfaces with Gradio: a basic ChatInterface with conversation history, a streaming version using Generator to display tokens as they arrive, a model selector dropdown that reads available Ollama models dynamically, and deployment options including LAN sharing, the Gradio public tunnel, and running as a background service.
A complete guide to evaluating Ollama prompts with Langfuse: self-hosting Langfuse with Docker, wrapping ollama.chat with trace and generation spans that record prompts, responses, and token usage, versioning and A/B testing prompts to compare output quality across versions, recording quality scores from human raters or an automated judge model, and using the Langfuse dashboard alongside Prometheus for comprehensive AI observability.
