Ollama’s default settings are conservative — designed to work on a wide range of hardware without crashing, not to extract peak performance from yours. If you’re getting fewer tokens per second than you expected, or the model is loading slowly, or you’re hitting memory pressure that prevents you from running your preferred model, there’s a … Read more
AI agent frameworks — systems where multiple LLM-backed agents collaborate on tasks, use tools, and produce coordinated outputs — have matured significantly, and both CrewAI and AutoGen work well with Ollama as the local inference backend. Running agents locally means zero API costs for long multi-step agent runs, no rate limits when agents make many … Read more
AI agent frameworks let you build systems where multiple LLM-powered agents collaborate on complex tasks — one agent researches, another writes, a third reviews, and an orchestrator coordinates the whole thing. CrewAI and AutoGen are two of the most popular frameworks for this, and both support Ollama as the local inference backend. Running agents locally … Read more
Ollama exposes an OpenAI-compatible API at http://localhost:11434/v1. This is one of its most useful and underappreciated features — any application, library, or tool built for the OpenAI API can be pointed at your local Ollama instance with two changes: the base URL and the model name. No code changes to the actual logic, no switching … Read more
Streamlit and Gradio are Python libraries that let you build web interfaces for AI applications in a few dozen lines of code. Both are excellent choices for wrapping an Ollama model in a shareable, polished UI — without writing HTML, CSS, or JavaScript. Whether you’re building a demo to share with colleagues, a personal tool … Read more
Once you have Ollama running, the question becomes: what front-end do you actually talk to your models through? The terminal is fine for quick tests, but for daily use you want a proper chat interface — conversation history, model switching, file uploads, and a UI you’d actually want to spend time in. LibreChat and SillyTavern … Read more
Make (formerly Integromat) is a cloud-based visual automation platform — similar to Zapier but with more powerful data transformation capabilities and a better visual workflow builder. While Make runs in the cloud and its scenarios execute on Make’s servers, it can call local services via webhooks, and with a bit of network configuration it can … Read more
AnythingLLM is one of the most polished all-in-one local AI applications available. Unlike Flowise or Dify, which require configuration and technical knowledge to set up properly, AnythingLLM is designed to work well out of the box: install it, connect it to Ollama, upload some documents, and you have a working private AI assistant with document … Read more
If you live in Neovim or Emacs, you probably don’t want to leave your editor to use an AI assistant. Both editors have mature plugin ecosystems with multiple Ollama-backed AI options — some simple chat interfaces, some more ambitious coding assistants with inline completion and code actions. This guide covers the best options for each … Read more
Flowise and Dify are two of the most capable no-code platforms for building AI applications with local models. Both connect to Ollama, both let you build RAG pipelines and chatbots visually, and both run self-hosted with no data leaving your infrastructure. But they have meaningfully different approaches and strengths — this guide covers what each … Read more
