For the complete documentation index, see llms.txt. Markdown versions of all docs pages are available by appending .md to any docs URL.
Cerebras
Configuration and setup for Cerebras LLM provider
Configure Cerebras as an LLM provider in agentgateway.
Configuration
Review the following example configuration.# yaml-language-server: $schema=https://agentgateway.dev/schema/config
llm:
models:
- name: "*"
provider: cerebras
params:
apiKey: "$CEREBRAS_API_KEY"
# Optional. If omitted, agentgateway uses the default:
# baseUrl: "https://api.cerebras.ai/v1"| Setting | Description |
|---|---|
name | The model name to match in incoming requests. When a client sends "model": "<name>", the request is routed to this provider. Use * to match any model name. |
provider | The LLM provider, set to cerebras. |
params.model | Optional. If set, this model is used for all requests. If not set, the request must include the model to use. |
params.apiKey | Your Cerebras API key. You can reference environment variables using the $VAR_NAME syntax. |
params.baseUrl | Optional. Overrides the provider base URL. Default: https://api.cerebras.ai/v1. |
Example request
After running agentgateway with the configuration from the previous section, you can send an OpenAI-compatible request to the v1/chat/completions endpoint:
curl -X POST http://localhost:4000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "llama-3.3-70b",
"messages": [{"role": "user", "content": "Hello from Cerebras!"}]
}'Was this page helpful?
