Use Cases
External LLM configuration is ideal for:- Custom models: Use fine-tuned or specialized language models
- Data control: Route LLM requests through your own infrastructure or preferred providers
- Regulatory compliance: Meet specific data residency requirements
Requirements
Your external LLM API must implement a single endpoint following the OpenAI-compatible Chat Completions API format. At minimum, the endpoint must support:- Standard chat completion requests with
messagesarray - Streaming responses with server-sent events
Using Popular Providers
Many LLM providers offer OpenAI-compatible endpoints that work out of the box: xAI (Grok): Get API key- Base URL:
https://api.x.ai/v1 - Models:
grok-4,grok-3-beta,grok-code-fast-1
- Base URL:
https://generativelanguage.googleapis.com/v1beta/openai - Models:
gemini-2.0-flash,gemini-1.5-pro,gemini-1.5-flash
Using these providers may incur additional costs based on their pricing models.
Configuration
You can configure external LLMs through our API. Dashboard support is planned for a future release.- Register your LLM API with the Create External API Configuration endpoint
- Reference the configuration when creating an agent with the Create Agent endpoint
Complete Example
See our external LLM example for full implementation including API registration, agent creation, and optional deployment of a compatible LLM API.Next Steps
External LLM Example
Complete implementation with deployment scripts
API: Create External API Configuration
Register external LLM APIs
API: Create Agent
Configure external LLMs for managed agents
Back to Managed Agents
Return to managed agents overview