goose/documentation/docs/getting-started/providers.md

sidebar_position, title

sidebar_position	title
2	Configure LLM Provider

import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

Supported LLM Providers

Goose is compatible with a wide range of LLM providers, allowing you to choose and integrate your preferred model.

:::tip Model Selection Goose relies heavily on tool calling capabilities and currently works best with Anthropic's Claude 3.5 Sonnet and OpenAI's GPT-4o (2024-11-20) model. Berkeley Function-Calling Leaderboard can be a good guide for selecting models. :::

Available Providers

Provider	Description	Parameters
Amazon Bedrock	Offers a variety of foundation models, including Claude, Jurassic-2, and others. AWS environment variables must be set in advance, not configured through goose configure	AWS_PROFILE, or AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION, ...
Anthropic	Offers Claude, an advanced AI model for natural language tasks.	ANTHROPIC_API_KEY, ANTHROPIC_HOST (optional)
Azure OpenAI	Access Azure-hosted OpenAI models, including GPT-4 and GPT-3.5.	AZURE_OPENAI_API_KEY, AZURE_OPENAI_ENDPOINT, AZURE_OPENAI_DEPLOYMENT_NAME
Databricks	Unified data analytics and AI platform for building and deploying models.	DATABRICKS_HOST, DATABRICKS_TOKEN
Gemini	Advanced LLMs by Google with multimodal capabilities (text, images).	GOOGLE_API_KEY
GCP Vertex AI	Google Cloud's Vertex AI platform, supporting Gemini and Claude models. Credentials must be configured in advance. Follow the instructions at https://cloud.google.com/vertex-ai/docs/authentication.	GCP_PROJECT_ID, GCP_LOCATION and optional GCP_MAX_RETRIES (6), GCP_INITIAL_RETRY_INTERVAL_MS (5000), GCP_BACKOFF_MULTIPLIER (2.0), GCP_MAX_RETRY_INTERVAL_MS (320_000).
Groq	High-performance inference hardware and tools for LLMs.	GROQ_API_KEY
Ollama	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.	OLLAMA_HOST
OpenAI	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	API gateway for unified access to various models with features like rate-limiting management.	OPENROUTER_API_KEY

Configure Provider

To configure your chosen provider or see available options, run goose configure in the CLI or visit the Provider Settings page in the Goose Desktop.

1. Run the following command:

```sh
goose configure
```

2. Select `Configure Providers` from the menu and press Enter.

```

┌ goose-configure │ ◆ What would you like to configure? │ ● Configure Providers (Change provider or update credentials) │ ○ Toggle Extensions │ ○ Add Extension └

3. Choose a model provider and press Enter.

┌ goose-configure │ ◇ What would you like to configure? │ Configure Providers │ ◆ Which model provider should we use? │ ● Anthropic (Claude and other models from Anthropic) │ ○ Databricks │ ○ Google Gemini │ ○ Groq │ ○ Ollama │ ○ OpenAI │ ○ OpenRouter └

4. Enter your API key (and any other configuration details) when prompted

┌ goose-configure │ ◇ What would you like to configure? │ Configure Providers │ ◇ Which model provider should we use? │ Anthropic │ ◆ Provider Anthropic requires ANTHROPIC_API_KEY, please enter a value │
└

  </TabItem>
  <TabItem value="ui" label="Goose Desktop">
  **To update your LLM provider and API key:** 
  1. Click `...` in the upper right corner
  2. Click `Settings`
  3. Next to `Models`, click `Browse`
  4. Click `Configure` in the upper right corner
  4. Press the `+` button next to the provider of your choice
  5. Add additional configurations (API key, host, etc) then press `submit`

  **To change provider model**
  1. Click `...` in the upper right corner
  2. Click `Settings`
  3. Next to `Models`, click `Browse`
  4. Scroll down to `Add Model` 
  5. Select a Provider from drop down menu
  6. Enter Model name
  7. Press `+ Add Model`

  You can explore more models by selecting a `provider` name under `Browse by Provider`. A link will appear, directing you to the provider's website. Once you've found the model you want, return to step 6 and paste the model name.
  </TabItem>

</Tabs>

## Using Custom OpenAI Endpoints

Goose supports using custom OpenAI-compatible endpoints, which is particularly useful for:
- Self-hosted LLMs (e.g., LLaMA, Mistral) using vLLM or KServe
- Private OpenAI-compatible API servers
- Enterprise deployments requiring data governance and security compliance
- OpenAI API proxies or gateways

### Configuration Parameters

| Parameter | Required | Description |
|-----------|----------|-------------|
| `OPENAI_API_KEY` | Yes | Authentication key for the API |
| `OPENAI_HOST` | No | Custom endpoint URL (defaults to api.openai.com) |
| `OPENAI_ORGANIZATION` | No | Organization ID for usage tracking and governance |
| `OPENAI_PROJECT` | No | Project identifier for resource management |
| `OPENAI_CUSTOM_HEADERS` | No | Additional headers to include in the request. Can be set via environment variable, configuration file, or CLI, in the format `HEADER_A=VALUE_A,HEADER_B=VALUE_B`. |

### Example Configurations

<Tabs groupId="deployment">
  <TabItem value="vllm" label="vLLM Self-Hosted" default>
    If you're running LLaMA or other models using vLLM with OpenAI compatibility:
    ```sh
    OPENAI_HOST=https://your-vllm-endpoint.internal
    OPENAI_API_KEY=your-internal-api-key
    ```
  </TabItem>
  <TabItem value="kserve" label="KServe Deployment">
    For models deployed on Kubernetes using KServe:
    ```sh
    OPENAI_HOST=https://kserve-gateway.your-cluster
    OPENAI_API_KEY=your-kserve-api-key
    OPENAI_ORGANIZATION=your-org-id
    OPENAI_PROJECT=ml-serving
    ```
  </TabItem>
  <TabItem value="enterprise" label="Enterprise OpenAI">
    For enterprise OpenAI deployments with governance:
    ```sh
    OPENAI_API_KEY=your-api-key
    OPENAI_ORGANIZATION=org-id123
    OPENAI_PROJECT=compliance-approved
    ```
  </TabItem>
  <TabItem value="custom-headers" label="Custom Headers">
    For OpenAI-compatible endpoints that require custom headers:
    ```sh
    OPENAI_API_KEY=your-api-key
    OPENAI_ORGANIZATION=org-id123
    OPENAI_PROJECT=compliance-approved
    OPENAI_CUSTOM_HEADERS="X-Header-A=abc,X-Header-B=def"
    ```
  </TabItem>
</Tabs>

### Setup Instructions

<Tabs groupId="interface">
  <TabItem value="cli" label="Goose CLI" default>
    1. Run `goose configure`
    2. Select `Configure Providers`
    3. Choose `OpenAI` as the provider
    4. Enter your configuration when prompted:
       - API key
       - Host URL (if using custom endpoint)
       - Organization ID (if using organization tracking)
       - Project identifier (if using project management)
  </TabItem>
  <TabItem value="ui" label="Goose Desktop">
    1. Click `...` in the upper right corner
    2. Click `Settings`
    3. Next to `Models`, click the `browse` link
    4. Click the `configure` link in the upper right corner
    5. Press the `+` button next to OpenAI
    6. Fill in your configuration details:
       - API Key (required)
       - Host URL (for custom endpoints)
       - Organization ID (for usage tracking)
       - Project (for resource management)
    7. Press `submit`
  </TabItem>
</Tabs>

:::tip Enterprise Deployment
For enterprise deployments, you can pre-configure these values using environment variables or configuration files to ensure consistent governance across your organization.
:::

## Using Goose for Free

Goose is a free and open source AI agent that you can start using right away, but not all supported [LLM Providers][providers] provide a free tier. 

Below, we outline a couple of free options and how to get started with them.

:::warning Limitations
These free options are a great way to get started with Goose and explore its capabilities. However, you may need to upgrade your LLM for better performance.
:::


### Google Gemini
Google Gemini provides a free tier. To start using the Gemini API with Goose, you need an API Key from [Google AI studio](https://aistudio.google.com/app/apikey).

To set up Google Gemini with Goose, follow these steps:

<Tabs groupId="interface">
  <TabItem value="cli" label="Goose CLI" default>
    1. Run: 
    ```sh
    goose configure
    ```
    2. Select `Configure Providers` from the menu.
    3. Follow the prompts to choose `Google Gemini` as the provider.
    4. Enter your API key when prompted.
    5. Enter the Gemini model of your choice.

    ```
    ┌   goose-configure
    │
    ◇ What would you like to configure?
    │ Configure Providers
    │
    ◇ Which model provider should we use?
    │ Google Gemini
    │
    ◇ Provider Google Gemini requires GOOGLE_API_KEY, please enter a value
    │▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪▪
    │    
    ◇ Enter a model from that provider:
    │ gemini-2.0-flash-exp
    │
    ◇ Hello! You're all set and ready to go, feel free to ask me anything!
    │
    └ Configuration saved successfully
    ```
    
  </TabItem>
  <TabItem value="ui" label="Goose Desktop">
  **To update your LLM provider and API key:** 

    1. Click on the three dots in the top-right corner.
    2. Select `Provider Settings` from the menu.
    2. Choose `Google Gemini` as provider from the list.
    3. Click Edit, enter your API key, and click `Set as Active`.

  </TabItem>
</Tabs>


### Local LLMs (Ollama)

Ollama provides local LLMs, which requires a bit more set up before you can use it with Goose.

1. [Download Ollama](https://ollama.com/download). 
2. Run any [model supporting tool-calling](https://ollama.com/search?c=tools):

:::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
ollama run qwen2.5

3. In a separate terminal window, configure with Goose:

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

┌   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 Ollama, 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. If you're running Ollama on port 80 or 443, you'll have to set OLLMA_HOST=http://host:{port} :::

┌   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://localhost:11434
└

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://localhost:11434
│
◇  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. Note that the native DeepSeek-r1 model doesn't support tool calling, however, we have a custom model you can use with Goose.

:::warning Note that this is a 70B model size and requires a powerful device to run smoothly. :::

1. Download and install Ollama from ollama.com.
2. In a terminal window, run the following command to install the custom DeepSeek-r1 model:

ollama run michaelneale/deepseek-r1-goose

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

```
┌   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

```
┌   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://localhost:11434
└
```

6. Enter the installed model from above

```
┌   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://localhost:11434  
│    
◇  Enter a model from that provider:
│  michaelneale/deepseek-r1-goose
│
◇  Welcome! You're all set to explore and utilize my capabilities. Let's get started on solving your problems together!
│
└  Configuration saved successfully
```

3. Click `...` in the top-right corner. 4. Navigate to `Settings` -> `Browse Models` -> and select `Ollama` from the list. 5. Enter `michaelneale/deepseek-r1-goose` for the model name.

---

If you have any questions or need help with a specific provider, feel free to reach out to us on Discord or on the Goose repo.