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LLM plugin providing access to models running on an Ollama server
| Date | Stars |
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| 2026-08-05 | 370 |
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| 2026-11-04 | 374 |
Today
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# llm-ollama [](https://pypi.org/project/llm-ollama/) [](https://github.com/taketwo/llm-ollama/releases) [](https://github.com/taketwo/llm-ollama/actions/workflows/test.yml) [](https://github.com/taketwo/llm-ollama/blob/main/LICENSE) [LLM](https://llm.datasette.io/) plugin providing access to models running on an [Ollama](https://ollama.ai) server. ## Installation Install this plugin in the same environment as [LLM](https://llm.datasette.io/). ```bash llm install llm-ollama ``` ## Quickstart By default, the plugin connects to a local Ollama server. Ensure the server is running and has some models available. Alternatively, the plugin can connect to a remote or managed Ollama cloud server; see [Connecting to Ollama server](#connecting-to-ollama-server) for configuration instructions. The plugin automatically discovers all models available on the server and registers them with LLM. To see the list of models and their capabilities, run: ```bash llm ollama models ``` ```bash model digest capabilities gemma3:latest c0494fe00251 completion, vision gpt-oss:120b-cloud 569662207105 completion, tools, thinking mxbai-embed-large:latest 468836162de7 embedding qwen3:4b 2bfd38a7daaf completion, tools, thinking ``` Once registered, models are available for prompting, chatting, and embedding under their Ollama names prefixed with `ollama/`. Assuming you have `gemma3:latest` available, you can run a prompt using: ```bash llm -m ollama/gemma3:latest 'How much is 2+2?' ``` The plugin automatically creates shorter aliases for models that have `:latest` in the name, so the previous command is equivalent to running: ```bash llm -m ollama/gemma3 'How much is 2+2?' ``` To start an interactive chat session instead of a one-shot prompt, run: ```bash llm chat -m ollama/gemma3 ``` ```bash Chatting with ollama/gemma3:latest Type 'exit' or 'quit' to exit Type '!multi' to enter multiple lines, then '!end' to finish Type '!edit' to open your default editor and modify the prompt Type '!fragment <my_fragment> [<another_fragment> ...]' to insert one or more fragments > ``` ## Features ### Attachments Models that report the `vision` capability accept images, and models that report `audio` accept WAV and MP3 audio, using the [LLM attachments](https://llm.datasette.io/en/stable/usage.html#attachments) option: ```bash llm -m ollama/llava "Describe this image" -a https://static.simonwillison.net/static/2024/pelicans.jpg llm -m ollama/gemma4:e2b "Transcribe this recording" -a recording.mp3 ``` ### Tools Ollama models with [tools support](https://ollama.com/search?c=tools) can make use of [LLM tools](https://llm.datasette.io/en/stable/tools.html) passed to them: ```bash llm -m ollama/llama3.2 -T llm_time 'What is the time?' --td ``` The plugin also registers `ollama_web_search` and `ollama_web_fetch` tools that wrap the [web search API](https://docs.ollama.com/web-search) provided by `ollama.com`. These tools augment models with the latest information to reduce hallucinations and improve accuracy. To use these tools, an API key must be configured (see [Ollama cloud](#ollama-cloud)). ### Embeddings The plugin supports [LLM embeddings](https://llm.datasette.io/en/stable/embeddings/cli.html) with models that report the `embedding` capability, such as `mxbai-embed-large`: ```bash llm embed -m ollama/mxbai-embed-large -i README.md ``` By default, the input will be truncated from the end to fit within the context length. This behavior can be changed by setting `OLLAMA_EMBED_TRUNCATE=no` environment variable. In such cases,
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:154cea094fa04855, llm:description: 'LLM plugin providing access to models running on an Ollama server' (repository description)
matched fp:154cea094fa04855, llm:description: 'LLM plugin providing access to models running on an Ollama server' (repository description)
matched fp:154cea094fa04855, llm:description: 'LLM plugin providing access to models running on an Ollama server' (repository description)