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.
A practical guide to generating git commit messages with Ollama: reading staged diffs with git diff –cached, a conventional commits format prompt with low temperature, a prepare-commit-msg git hook that prepends AI suggestions as editable comments, and an interactive CLI tool with accept, edit, regenerate, and quit options for full control over every commit.
A complete guide to composing Ollama with other services in Docker Compose: a full stack with Ollama, Open WebUI, FastAPI, and pgvector Postgres, a model init container, CPU-only variant, FastAPI Dockerfile and client using the compose service hostname, health checks with service_healthy dependency condition, and essential compose commands for managing models and containers.
A practical guide to email drafting with a local LLM: a basic draft_email function with tone and length parameters, subject line generation, drafting replies to existing emails with intent specification, batch personalisation of email templates for multiple recipients with company and role context, and a reference of effective tone and style prompt parameters for reliably varied email outputs.
A practical guide to LLM pretraining data pipelines: language identification with FastText, heuristic quality filtering using character-to-word ratios, symbol ratios, and repeated line detection, perplexity-based filtering with KenLM to catch templated and garbled text, MinHash LSH deduplication with datasketch, exact substring deduplication with suffix arrays, building a full pipeline with HuggingFace datatrove including Gopher and C4 quality filters, training a fastText classifier for quality scoring, and balancing the data mix across web, books, and code sources.
