ollama/README.md
Leo 2103a5073c
Add Odin Runes, a Feature-Rich Java UI for Ollama, to README (#2440)
* Add Odin Runes to README

Add Odin Runes to README

This commit adds Odin Runes to the "Community Integrations" section of the README. Odin Runes is a Java-based GPT client designed to provide seamless interaction with GPT models, enhancing productivity in prompt engineering and text generation tasks. This addition highlights the integration between Odin Runes and Ollama, offering users the flexibility to leverage large language models locally within their development workflow.

* Update README.md

this commit applies the comments of the reviewer.
2024-03-06 11:57:49 -08:00

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<div align="center">
<img alt="ollama" height="200px" src="https://github.com/jmorganca/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
</div>
# Ollama
[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
Get up and running with large language models locally.
### macOS
[Download](https://ollama.com/download/Ollama-darwin.zip)
### Windows preview
[Download](https://ollama.com/download/OllamaSetup.exe)
### Linux
```
curl -fsSL https://ollama.com/install.sh | sh
```
[Manual install instructions](https://github.com/jmorganca/ollama/blob/main/docs/linux.md)
### Docker
The official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama) `ollama/ollama` is available on Docker Hub.
### Libraries
- [ollama-python](https://github.com/ollama/ollama-python)
- [ollama-js](https://github.com/ollama/ollama-js)
## Quickstart
To run and chat with [Llama 2](https://ollama.com/library/llama2):
```
ollama run llama2
```
## Model library
Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
Here are some example models that can be downloaded:
| Model | Parameters | Size | Download |
| ------------------ | ---------- | ----- | ------------------------------ |
| Llama 2 | 7B | 3.8GB | `ollama run llama2` |
| Mistral | 7B | 4.1GB | `ollama run mistral` |
| Dolphin Phi | 2.7B | 1.6GB | `ollama run dolphin-phi` |
| Phi-2 | 2.7B | 1.7GB | `ollama run phi` |
| Neural Chat | 7B | 4.1GB | `ollama run neural-chat` |
| Starling | 7B | 4.1GB | `ollama run starling-lm` |
| Code Llama | 7B | 3.8GB | `ollama run codellama` |
| Llama 2 Uncensored | 7B | 3.8GB | `ollama run llama2-uncensored` |
| Llama 2 13B | 13B | 7.3GB | `ollama run llama2:13b` |
| Llama 2 70B | 70B | 39GB | `ollama run llama2:70b` |
| Orca Mini | 3B | 1.9GB | `ollama run orca-mini` |
| Vicuna | 7B | 3.8GB | `ollama run vicuna` |
| LLaVA | 7B | 4.5GB | `ollama run llava` |
| Gemma | 2B | 1.4GB | `ollama run gemma:2b` |
| Gemma | 7B | 4.8GB | `ollama run gemma:7b` |
> Note: You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
## Customize a model
### Import from GGUF
Ollama supports importing GGUF models in the Modelfile:
1. Create a file named `Modelfile`, with a `FROM` instruction with the local filepath to the model you want to import.
```
FROM ./vicuna-33b.Q4_0.gguf
```
2. Create the model in Ollama
```
ollama create example -f Modelfile
```
3. Run the model
```
ollama run example
```
### Import from PyTorch or Safetensors
See the [guide](docs/import.md) on importing models for more information.
### Customize a prompt
Models from the Ollama library can be customized with a prompt. For example, to customize the `llama2` model:
```
ollama pull llama2
```
Create a `Modelfile`:
```
FROM llama2
# set the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1
# set the system message
SYSTEM """
You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
"""
```
Next, create and run the model:
```
ollama create mario -f ./Modelfile
ollama run mario
>>> hi
Hello! It's your friend Mario.
```
For more examples, see the [examples](examples) directory. For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation.
## CLI Reference
### Create a model
`ollama create` is used to create a model from a Modelfile.
```
ollama create mymodel -f ./Modelfile
```
### Pull a model
```
ollama pull llama2
```
> This command can also be used to update a local model. Only the diff will be pulled.
### Remove a model
```
ollama rm llama2
```
### Copy a model
```
ollama cp llama2 my-llama2
```
### Multiline input
For multiline input, you can wrap text with `"""`:
```
>>> """Hello,
... world!
... """
I'm a basic program that prints the famous "Hello, world!" message to the console.
```
### Multimodal models
```
>>> What's in this image? /Users/jmorgan/Desktop/smile.png
The image features a yellow smiley face, which is likely the central focus of the picture.
```
### Pass in prompt as arguments
```
$ ollama run llama2 "Summarize this file: $(cat README.md)"
Ollama is a lightweight, extensible framework for building and running language models on the local machine. It provides a simple API for creating, running, and managing models, as well as a library of pre-built models that can be easily used in a variety of applications.
```
### List models on your computer
```
ollama list
```
### Start Ollama
`ollama serve` is used when you want to start ollama without running the desktop application.
## Building
Install `cmake` and `go`:
```
brew install cmake go
```
Then generate dependencies:
```
go generate ./...
```
Then build the binary:
```
go build .
```
More detailed instructions can be found in the [developer guide](https://github.com/jmorganca/ollama/blob/main/docs/development.md)
### Running local builds
Next, start the server:
```
./ollama serve
```
Finally, in a separate shell, run a model:
```
./ollama run llama2
```
## REST API
Ollama has a REST API for running and managing models.
### Generate a response
```
curl http://localhost:11434/api/generate -d '{
"model": "llama2",
"prompt":"Why is the sky blue?"
}'
```
### Chat with a model
```
curl http://localhost:11434/api/chat -d '{
"model": "mistral",
"messages": [
{ "role": "user", "content": "why is the sky blue?" }
]
}'
```
See the [API documentation](./docs/api.md) for all endpoints.
## Community Integrations
### Web & Desktop
- [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
- [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
- [HTML UI](https://github.com/rtcfirefly/ollama-ui)
- [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
- [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
- [Minimalistic React UI for Ollama Models](https://github.com/richawo/minimal-llm-ui)
- [Open WebUI](https://github.com/open-webui/open-webui)
- [Ollamac](https://github.com/kevinhermawan/Ollamac)
- [big-AGI](https://github.com/enricoros/big-AGI/blob/main/docs/config-local-ollama.md)
- [Cheshire Cat assistant framework](https://github.com/cheshire-cat-ai/core)
- [Amica](https://github.com/semperai/amica)
- [chatd](https://github.com/BruceMacD/chatd)
- [Ollama-SwiftUI](https://github.com/kghandour/Ollama-SwiftUI)
- [MindMac](https://mindmac.app)
- [NextJS Web Interface for Ollama](https://github.com/jakobhoeg/nextjs-ollama-llm-ui)
- [Msty](https://msty.app)
- [Chatbox](https://github.com/Bin-Huang/Chatbox)
- [WinForm Ollama Copilot](https://github.com/tgraupmann/WinForm_Ollama_Copilot)
- [NextChat](https://github.com/ChatGPTNextWeb/ChatGPT-Next-Web) with [Get Started Doc](https://docs.nextchat.dev/models/ollama)
- [Odin Runes](https://github.com/leonid20000/OdinRunes)
### Terminal
- [oterm](https://github.com/ggozad/oterm)
- [Ellama Emacs client](https://github.com/s-kostyaev/ellama)
- [Emacs client](https://github.com/zweifisch/ollama)
- [gen.nvim](https://github.com/David-Kunz/gen.nvim)
- [ollama.nvim](https://github.com/nomnivore/ollama.nvim)
- [ollama-chat.nvim](https://github.com/gerazov/ollama-chat.nvim)
- [ogpt.nvim](https://github.com/huynle/ogpt.nvim)
- [gptel Emacs client](https://github.com/karthink/gptel)
- [Oatmeal](https://github.com/dustinblackman/oatmeal)
- [cmdh](https://github.com/pgibler/cmdh)
- [tenere](https://github.com/pythops/tenere)
- [llm-ollama](https://github.com/taketwo/llm-ollama) for [Datasette's LLM CLI](https://llm.datasette.io/en/stable/).
- [ShellOracle](https://github.com/djcopley/ShellOracle)
### Database
- [MindsDB](https://github.com/mindsdb/mindsdb/blob/staging/mindsdb/integrations/handlers/ollama_handler/README.md)
### Package managers
- [Pacman](https://archlinux.org/packages/extra/x86_64/ollama/)
- [Helm Chart](https://artifacthub.io/packages/helm/ollama-helm/ollama)
### Libraries
- [LangChain](https://python.langchain.com/docs/integrations/llms/ollama) and [LangChain.js](https://js.langchain.com/docs/modules/model_io/models/llms/integrations/ollama) with [example](https://js.langchain.com/docs/use_cases/question_answering/local_retrieval_qa)
- [LangChainGo](https://github.com/tmc/langchaingo/) with [example](https://github.com/tmc/langchaingo/tree/main/examples/ollama-completion-example)
- [LangChain4j](https://github.com/langchain4j/langchain4j) with [example](https://github.com/langchain4j/langchain4j-examples/tree/main/ollama-examples/src/main/java)
- [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/ollama.html)
- [LangChain4j](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-ollama)
- [LiteLLM](https://github.com/BerriAI/litellm)
- [OllamaSharp for .NET](https://github.com/awaescher/OllamaSharp)
- [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
- [Ollama-rs for Rust](https://github.com/pepperoni21/ollama-rs)
- [Ollama4j for Java](https://github.com/amithkoujalgi/ollama4j)
- [ModelFusion Typescript Library](https://modelfusion.dev/integration/model-provider/ollama)
- [OllamaKit for Swift](https://github.com/kevinhermawan/OllamaKit)
- [Ollama for Dart](https://github.com/breitburg/dart-ollama)
- [Ollama for Laravel](https://github.com/cloudstudio/ollama-laravel)
- [LangChainDart](https://github.com/davidmigloz/langchain_dart)
- [Semantic Kernel - Python](https://github.com/microsoft/semantic-kernel/tree/main/python/semantic_kernel/connectors/ai/ollama)
- [Haystack](https://github.com/deepset-ai/haystack-integrations/blob/main/integrations/ollama.md)
- [Elixir LangChain](https://github.com/brainlid/langchain)
- [Ollama for R - rollama](https://github.com/JBGruber/rollama)
- [Ollama-ex for Elixir](https://github.com/lebrunel/ollama-ex)
- [Ollama Connector for SAP ABAP](https://github.com/b-tocs/abap_btocs_ollama)
### Mobile
- [Enchanted](https://github.com/AugustDev/enchanted)
- [Maid](https://github.com/Mobile-Artificial-Intelligence/maid)
### Extensions & Plugins
- [Raycast extension](https://github.com/MassimilianoPasquini97/raycast_ollama)
- [Discollama](https://github.com/mxyng/discollama) (Discord bot inside the Ollama discord channel)
- [Continue](https://github.com/continuedev/continue)
- [Obsidian Ollama plugin](https://github.com/hinterdupfinger/obsidian-ollama)
- [Logseq Ollama plugin](https://github.com/omagdy7/ollama-logseq)
- [NotesOllama](https://github.com/andersrex/notesollama) (Apple Notes Ollama plugin)
- [Dagger Chatbot](https://github.com/samalba/dagger-chatbot)
- [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot)
- [Ollama Telegram Bot](https://github.com/ruecat/ollama-telegram)
- [Hass Ollama Conversation](https://github.com/ej52/hass-ollama-conversation)
- [Rivet plugin](https://github.com/abrenneke/rivet-plugin-ollama)
- [Llama Coder](https://github.com/ex3ndr/llama-coder) (Copilot alternative using Ollama)
- [Obsidian BMO Chatbot plugin](https://github.com/longy2k/obsidian-bmo-chatbot)
- [Copilot for Obsidian plugin](https://github.com/logancyang/obsidian-copilot)
- [Obsidian Local GPT plugin](https://github.com/pfrankov/obsidian-local-gpt)
- [Open Interpreter](https://docs.openinterpreter.com/language-model-setup/local-models/ollama)
- [twinny](https://github.com/rjmacarthy/twinny) (Copilot and Copilot chat alternative using Ollama)
- [Wingman-AI](https://github.com/RussellCanfield/wingman-ai) (Copilot code and chat alternative using Ollama and HuggingFace)
- [Page Assist](https://github.com/n4ze3m/page-assist) (Chrome Extension)