The **chat** endpoint is one of two ways to generate text from an LLM with Ollama. At a high level you provide the endpoint an array of objects with a role and content specified. Then with each output and prompt, you add more of those role/content objects, which builds up the history.
With the **generate** endpoint, you need to provide a `prompt`. But with **chat**, you provide `messages`. And the resulting stream of responses includes a `message` object with a `content` field.
The final JSON object doesn't provide the full content, so you will need to build the content yourself.
In the **main** function, we collect `user_input` and add it as a message to our messages and that is passed to the chat function. And the output is added as another message.
## Next Steps
In this example, all generations are kept. You might want to experiment with summarizing everything older than 10 conversations to enable longer history with less context being used.