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---
sidebar_position: 5
slug: /deploy_local_llm
---
# Deploy a local LLM
RAGFlow supports deploying LLMs locally using Ollama or Xinference.
## Ollama
One-click deployment of local LLMs, that is [Ollama](https://github.com/ollama/ollama).
### Install
- [Ollama on Linux](https://github.com/ollama/ollama/blob/main/docs/linux.md)
- [Ollama Windows Preview](https://github.com/ollama/ollama/blob/main/docs/windows.md)
- [Docker](https://hub.docker.com/r/ollama/ollama)
### Launch Ollama
Decide which LLM you want to deploy ([here's a list for supported LLM](https://ollama.com/library)), say, **mistral**:
```bash
$ ollama run mistral
```
Or,
```bash
$ docker exec -it ollama ollama run mistral
```
### Use Ollama in RAGFlow
- Go to 'Settings > Model Providers > Models to be added > Ollama'.
> Base URL: Enter the base URL where the Ollama service is accessible, like, `http://<your-ollama-endpoint-domain>:11434`.
- Use Ollama Models.
## Xinference
Xorbits Inference([Xinference](https://github.com/xorbitsai/inference)) empowers you to unleash the full potential of cutting-edge AI models.
### Install
- [pip install "xinference[all]"](https://inference.readthedocs.io/en/latest/getting_started/installation.html)
- [Docker](https://inference.readthedocs.io/en/latest/getting_started/using_docker_image.html)
To start a local instance of Xinference, run the following command:
```bash
$ xinference-local --host 0.0.0.0 --port 9997
```
### Launch Xinference
Decide which LLM you want to deploy ([here's a list for supported LLM](https://inference.readthedocs.io/en/latest/models/builtin/)), say, **mistral**.
Execute the following command to launch the model, remember to replace `${quantization}` with your chosen quantization method from the options listed above:
```bash
$ xinference launch -u mistral --model-name mistral-v0.1 --size-in-billions 7 --model-format pytorch --quantization ${quantization}
```
### Use Xinference in RAGFlow
- Go to 'Settings > Model Providers > Models to be added > Xinference'.
> Base URL: Enter the base URL where the Xinference service is accessible, like, `http://<your-xinference-endpoint-domain>:9997/v1`.
- Use Xinference Models.
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