> ## Documentation Index
> Fetch the complete documentation index at: https://docs.unpage.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# LLM Configuration

The LLM plugin allows you to configure which Large Language Model (LLM) Unpage uses for its [Agents](/concepts/agents) and other AI-powered features.

Unpage uses [LiteLLM](https://github.com/BerriAI/litellm) as its LLM provider interface, which supports multiple model providers including OpenAI, Anthropic, and Amazon Bedrock.

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  <Accordion title="MCP Tools" icon="wrench">
    No MCP tools are currently available for this plugin.
  </Accordion>
</AccordionGroup>

## Configuration

You can configure the LLM plugin using the `unpage configure` command, which will guide you through selecting a provider and model.

```bash theme={null}
$ uv run unpage configure
```

Alternatively, you can manually edit your Unpage config file at `~/.unpage/profiles/<profile_name>/config.yaml`:

```yaml theme={null}
plugins:
  # ...
  llm:
    enabled: true
    settings:
      model: "openai/gpt-4o"  # Provider/model format
      api_key: "your-api-key"
      temperature: 0          # 0-1, lower is more deterministic
      max_tokens: 8192        # Maximum output tokens
      cache: true             # Enable response caching
```

### Model Selection

The LLM plugin supports the following model providers and recommended models:

#### OpenAI

```yaml theme={null}
model: "openai/gpt-4o"           # Fast, intelligent, flexible GPT model (recommended)
model: "openai/gpt-4o-mini"      # Fast, affordable small model for focused tasks
```

You'll need an [OpenAI API key](https://platform.openai.com/api-keys) to use these models.

#### Anthropic

```yaml theme={null}
model: "anthropic/claude-4-sonnet-20250514"  # High intelligence and balanced performance (recommended)
model: "anthropic/claude-4-opus-20250514"    # Highest level of intelligence and capability
```

You'll need an [Anthropic API key](https://console.anthropic.com/settings/keys) to use these models.

#### Amazon Bedrock

```yaml theme={null}
model: "bedrock/us.anthropic.claude-sonnet-4-20250514-v1:0"  # US region, Claude 4 Sonnet (recommended)
model: "bedrock/us.anthropic.claude-opus-4-20250514-v1:0"    # US region, Claude 4 Opus
model: "bedrock/eu.anthropic.claude-sonnet-4-20250514-v1:0"  # EU region, Claude 4 Sonnet
model: "bedrock/eu.anthropic.claude-opus-4-20250514-v1:0"    # EU region, Claude 4 Opus
```

For Amazon Bedrock models, you'll need [Amazon Bedrock API key](https://docs.aws.amazon.com/bedrock/latest/userguide/api-keys.html). If not set, the plugin will default to the AWS credentials in your environment using the AWS SDK credential provider discovery. We default to `us-east-1` region if no region is set in the environment.

### Advanced Configuration

The LLM plugin uses sensible defaults for most settings:

* `temperature`: 0 (most deterministic responses)
* `max_tokens`: Set to the model's maximum context length
* `cache`: true (enables response caching for efficiency)

You can adjust these settings in your config file based on your specific requirements.

## Supported Models

In addition to the recommended models listed above, the LLM plugin supports all models supported by LiteLLM. You can view the full list of supported models in the [LiteLLM documentation](https://docs.litellm.ai/docs/providers).

To use a model not included in the interactive configuration, directly edit your config.yaml file with the appropriate provider/model string format.

## Environment Variables

You can also configure the LLM plugin using environment variables:

* `OPENAI_API_KEY`: For OpenAI models
* `ANTHROPIC_API_KEY`: For Anthropic models
* `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`: For Amazon Bedrock models
* `AWS_REGION` or `AWS_DEFAULT_REGION`: Region for Amazon Bedrock (defaults to `us-east-1`)