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I've only used ollama over cli. As per the parent poster -- do you know if there are advantages over ollama for CLI use? Have you used both?
by n8henrie 2y ago
I've only used ollama over cli. As per the parent poster -- do you know if there are advantages over ollama for CLI use? Have you used both?
- dannyobrien 2y agoI haven't used Ollama, but from what I've seen, it seems to operate at a different level of abstraction compared to `llm`. I use `llm` to access both remote and local models through its plugin ecosystem[1]. One of the plugins allows you to use Ollama-served local models. This means you can use the same CLI interface with Ollama[2], as well as with OpenAI, Gemini, Anthropic, llamafile, llamacpp, mlc, and others. I select different models for different purposes. Recently, I've switched my default from OpenAI to Anthropic quite seamlessly. [1] - https://llm.datasette.io/en/stable/plugins/directory.html#plugin-directory https://llm.datasette.io/en/stable/plugins/directory.html#pl... [2] - https://github.com/taketwo/llm-ollama https://github.com/taketwo/llm-ollama
- awwaiid 2y agoThe llm CLI is much more unixy, letting you pipe data in and out easily. It can use hosted and local models, including ollama.
- simonw 2y agoOllama can’t talk to OpenAI / Anthropic / etc. LLM gives you a single interface that can talk to both hosted and local models. It also logs everything you do to a SQLite database, which is great for further analysis. I use LLM and Ollama together quite a bit, because Ollama are really good at getting new models working and their server keeps those models in memory between requests.
- wrsh07 2y agoYou can run llamafile as a server, too, right? Still need to download gguf files if you don't use one of their premade binaries, but if you haven't set up llm to hit the running llamafile server I'm sure that's easy to do