Built-in Providers

Built-in LLM Providers

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

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 for full documentation on each provider, credentials, and named configurations.

Built-in Memory Provider

Use Runflow’s managed memory backend:

import { RunflowMemoryProvider } from '@runflow-ai/sdk';

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

Next Steps

LLM Providers

Configure and use LLM providers

Memory Provider

Learn about memory providers

Knowledge Provider

Learn about knowledge providers

LLM Providers Memory Provider Interface

Getting Started

CLI

Core Concepts

Real-World Examples

Advanced

Configuration

Extending Runflow

Help & Support

Built-in Providers

Built-in LLM Providers

Built-in Memory Provider

Next Steps

LLM Providers

Memory Provider

Knowledge Provider

​Built-in LLM Providers

​Built-in Memory Provider

​Next Steps

LLM Providers

Memory Provider

Knowledge Provider

Built-in LLM Providers

Built-in Memory Provider

Next Steps