What is an External LLM?
An external LLM allows you to redirect all language processing requests to a service outside of the default provider. This includes:- Self-hosted models (e.g., vLLM, Ollama, TGI).
- Fine-tuned or private models tailored to your specific business logic.
- Third-party providers that support the OpenAI Chat Completions standard (e.g., Together AI, Fireworks, Groq, Anthropic via proxy).
Why Use an External LLM?
| Benefit | Description |
|---|---|
| Customization | Use domain-specific or fine-tuned models for better accuracy. |
| Data Privacy | Keep sensitive data within your own infrastructure or private cloud. |
| Compliance | Meet strict regulatory requirements regarding data residency and auditing. |
| Cost Control | Optimize expenses by choosing providers with competitive pricing or using your own hardware. |
Requirements
To ensure compatibility, your LLM API must implement the OpenAI Chat Completions specification.Core Compatibility
- Endpoint:
POST /chat/completions - Payload: Must accept a
messages: []array. - Streaming: Must support Server-Sent Events (SSE) for real-time interaction.
Optional Features
- Function Calling: Required if your agent needs to trigger external tools.
- Vision: Required for multimodal inputs (e.g., analyzing images).
Setup Options
Option 1: Via Developer Studio
- Navigate to Create New Agent.
- Locate the LLM configuration section.
- Select
Bring your own LLMfrom the Provider dropdown. - Enter your API URL, Model Name, and API Token.

Option 2: Via API
You can define an external LLM by setting theprovider to "custom" within the avatars.config.llm object.