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

# Built-in Providers

> Use Runflow's built-in LLM, memory, and knowledge providers

## Built-in LLM Providers

Runflow comes with 8 built-in LLM provider integrations. Configure them in the portal and use in code:

```typescript theme={null}
import { openai, anthropic, bedrock, groq, gemini, xai, custom } from '@runflow-ai/sdk';

model: openai('gpt-4o')              // OpenAI
model: anthropic('claude-sonnet-4-6')          // Anthropic
model: bedrock('anthropic.claude-3-5-sonnet-20241022-v2:0')  // AWS Bedrock
model: groq('llama-3.3-70b-versatile')         // Groq
model: gemini('gemini-2.5-flash')              // Google Gemini
model: xai('grok-4-1-fast-non-reasoning')      // xAI (Grok)
model: custom('llama3', 'Ollama Local')        // Any OpenAI-compatible API
```

Azure OpenAI is also supported — use `openai()` with a `providerName` pointing to your Azure configuration.

See [LLM Providers](/providers/llm-provider) for full documentation on each provider, credentials, and named configurations.

## Built-in Memory Provider

Use Runflow's managed memory backend:

```typescript theme={null}
import { RunflowMemoryProvider } from '@runflow-ai/sdk';

const memory = new Memory({
  provider: new RunflowMemoryProvider(apiClient),
  maxTurns: 10,
});
```

## Next Steps

<CardGroup cols={2}>
  <Card title="LLM Providers" icon="microchip" href="/providers/llm-provider">
    Configure and use LLM providers
  </Card>

  <Card title="Memory Provider" icon="brain" href="/providers/memory-provider">
    Learn about memory providers
  </Card>

  <Card title="Knowledge Provider" icon="database" href="/providers/knowledge-provider">
    Learn about knowledge providers
  </Card>
</CardGroup>