aljaz/goose
1
0
Fork 0
mirror of https://github.com/aljazceru/goose.git synced 2025-12-17 22:24:21 +01:00
Code Issues Packages Projects Releases Wiki Activity

Add documentation for running with Ramalama local model serving in OCI Containers (#1973)

Browse Source 
Signed-off-by: Adam Miller <admiller@redhat.com>
This commit is contained in:
Adam Miller
2025-06-16 20:58:23 -04:00
committed by GitHub
parent 4a93d42303
commit 3bec469043
1 changed files with 101 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

103
documentation/docs/getting-started/providers.md
View File

@@ -28,6 +28,7 @@ Goose relies heavily on tool calling capabilities and currently works best with
| [GitHub Copilot](https://docs.github.com/en/copilot/using-github-copilot/ai-models) | Access to GitHub Copilot's chat models including gpt-4o, o1, o3-mini, and Claude models. Uses device code authentication flow for secure access. | Uses GitHub device code authentication flow (no API key needed) |
| [Groq](https://groq.com/) | High-performance inference hardware and tools for LLMs. | `GROQ_API_KEY` |
| [Ollama](https://ollama.com/) | Local model runner supporting Qwen, Llama, DeepSeek, and other open-source models. **Because this provider runs locally, you must first [download and run a model](/docs/getting-started/providers#local-llms-ollama).** | `OLLAMA_HOST` |
| [Ramalama](https://ramalama.ai/) | Local model using native [OCI](https://opencontainers.org/) container runtimes, [CNCF](https://www.cncf.io/) tools, and supporting models as OCI artifacts. Ramalama API an compatible alternative to Ollama and can be used with the Goose Ollama provider. Supports Qwen, Llama, DeepSeek, and other open-source models. **Because this provider runs locally, you must first [download and run a model](/docs/getting-started/providers#local-llms-ollama).** | `OLLAMA_HOST` |
| [OpenAI](https://platform.openai.com/api-keys) | Provides gpt-4o, o1, and other advanced language models. Also supports OpenAI-compatible endpoints (e.g., self-hosted LLaMA, vLLM, KServe). **o1-mini and o1-preview are not supported because Goose uses tool calling.** | `OPENAI_API_KEY`, `OPENAI_HOST` (optional), `OPENAI_ORGANIZATION` (optional), `OPENAI_PROJECT` (optional), `OPENAI_CUSTOM_HEADERS` (optional) |
| [OpenRouter](https://openrouter.ai/) | API gateway for unified access to various models with features like rate-limiting management. | `OPENROUTER_API_KEY` |
| [Snowflake](https://docs.snowflake.com/user-guide/snowflake-cortex/aisql#choosing-a-model) | Access the latest models using Snowflake Cortex services, including Claude models. **Requires a Snowflake account and programmatic access token (PAT)**. | `SNOWFLAKE_HOST`, `SNOWFLAKE_TOKEN` |
@@ -275,9 +276,11 @@ To set up Google Gemini with Goose, follow these steps:
</Tabs>
### Local LLMs (Ollama)
### Local LLMs (Ollama or Ramalama)
Ollama provides local LLMs, which requires a bit more set up before you can use it with Goose.
Ollama and Ramalama are both options to provide local LLMs, each which requires a bit more set up before you can use one of them with Goose.
#### Ollama
1. [Download Ollama](https://ollama.com/download).
2. Run any [model supporting tool-calling](https://ollama.com/search?c=tools):
@@ -374,6 +377,102 @@ If you're running Ollama on a different server, you'll have to set `OLLAMA_HOST=
└ Configuration saved successfully
```
#### Ramalama
1. [Download Ramalama](https://github.com/containers/ramalama?tab=readme-ov-file#install).
2. Run any Ollama [model supporting tool-calling](https://ollama.com/search?c=tools) or [GGUF format HuggingFace Model](https://huggingface.co/search/full-text?q=%22tools+support%22+%2B+%22gguf%22&type=model) :
:::warning Limited Support for models without tool calling
Goose extensively uses tool calling, so models without it (e.g. `DeepSeek-r1`) can only do chat completion. If using models without tool calling, all Goose [extensions must be disabled](/docs/getting-started/using-extensions#enablingdisabling-extensions). As an alternative, you can use a [custom DeepSeek-r1 model](/docs/getting-started/providers#deepseek-r1) we've made specifically for Goose.
:::
Example:
```sh
# NOTE: the --runtime-args="--jinja" flag is required for Ramalama to work with the Goose Ollama provider.
ramalama serve --runtime-args="--jinja" ollama://qwen2.5
```
3. In a separate terminal window, configure with Goose:
```sh
goose configure
```
4. Choose to `Configure Providers`
```
┌ goose-configure
│
◆ What would you like to configure?
│ ● Configure Providers (Change provider or update credentials)
│ ○ Toggle Extensions
│ ○ Add Extension
└
```
5. Choose `Ollama` as the model provider since Ramalama is API compatible and can use the Goose Ollama provider
```
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│
◆ Which model provider should we use?
│ ○ Anthropic
│ ○ Databricks
│ ○ Google Gemini
│ ○ Groq
│ ● Ollama (Local open source models)
│ ○ OpenAI
│ ○ OpenRouter
└
```
5. Enter the host where your model is running
:::info Endpoint
For the Ollama provider, if you don't provide a host, we set it to `localhost:11434`. When constructing the URL, we preprend `http://` if the scheme is not `http` or `https`. Since Ramalama's default port to serve on is 8080, we set `OLLAMA_HOST=http://0.0.0.0:8080`
:::
```
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│
◇ Which model provider should we use?
│ Ollama
│
◆ Provider Ollama requires OLLAMA_HOST, please enter a value
│ http://0.0.0.0:8080
└
```
6. Enter the model you have running
```
┌ goose-configure
│
◇ What would you like to configure?
│ Configure Providers
│
◇ Which model provider should we use?
│ Ollama
│
◇ Provider Ollama requires OLLAMA_HOST, please enter a value
│ http://0.0.0.0:8080
│
◇ Enter a model from that provider:
│ qwen2.5
│
◇ Welcome! You're all set to explore and utilize my capabilities. Let's get started on solving your problems together!
│
└ Configuration saved successfully
```
### DeepSeek-R1
Ollama provides open source LLMs, such as `DeepSeek-r1`, that you can install and run locally.