| [Amazon Bedrock](https://aws.amazon.com/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](https://www.anthropic.com/) | Offers Claude, an advanced AI model for natural language tasks. | `ANTHROPIC_API_KEY` |
| [Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-services/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](https://www.databricks.com/) | Unified data analytics and AI platform for building and deploying models. | `DATABRICKS_HOST`, `DATABRICKS_TOKEN` |
| [Gemini](https://ai.google.dev/gemini-api/docs) | Advanced LLMs by Google with multimodal capabilities (text, images). | `GOOGLE_API_KEY` |
| [GCP Vertex AI](https://cloud.google.com/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](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` |
| [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) |
| [OpenRouter](https://openrouter.ai/) | API gateway for unified access to various models with features like rate-limiting management. | `OPENROUTER_API_KEY` |
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.
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.
For enterprise OpenAI deployments with governance:
```sh
OPENAI_API_KEY=your-api-key
OPENAI_ORGANIZATION=org-id123
OPENAI_PROJECT=compliance-approved
```
</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.
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
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.
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}`
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](https://ollama.com/michaelneale/deepseek-r1-goose) 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](https://ollama.com/download).
2. In a terminal window, run the following command to install the custom DeepSeek-r1 model:
```sh
ollama run michaelneale/deepseek-r1-goose
```
<Tabs groupId="interface">
<TabItem value="cli" label="Goose CLI" default>
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
```
</TabItem>
<TabItem value="ui" label="Goose Desktop">
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.
</TabItem>
</Tabs>
---
If you have any questions or need help with a specific provider, feel free to reach out to us on [Discord](https://discord.gg/block-opensource) or on the [Goose repo](https://github.com/block/goose).
