Ollama tutorial: setup, terminal chat and Python apps

This Tamil tutorial introduces Ollama as a runtime for downloaded language models, then moves from terminal chat to a custom Python application. The installation section points to the macOS, Linux and Windows downloads. Installation and initial model downloads require internet access; the demonstrated local models can subsequently run offline.

The terminal walkthrough covers pulling and running a model, listing downloads, checking loaded models and removing them. Llama 3.2 answers a sample question. A custom localhost chat interface then switches between Llama 3.2 and Gemma 2, showing their different answers to the same API question.

The Python section follows Ollama's API documentation through Libraries → Python to the official repository. The presenter discusses pip installation, imports and the chat response's model and messages arguments, then compares that example with the application's integration file. He explains the changes needed for its model picker. This is an integration walkthrough with a working app, rather than a line-by-line lesson or a complete application-building exercise.

The final discussion covers memory, storage, response speed and maintaining downloaded models. Hardware suggestions and the slower responses are the presenter's observations, rather than fixed requirements or a general benchmark. He presents local models as useful for learning and prototyping, while cautioning that small models should not be expected to match every cloud service.