For the complete documentation index, see llms.txt. Markdown versions of all docs pages are available by appending .md to any docs URL.
Rerank
Send rerank requests through agentgateway using the Cohere-compatible Rerank API.
The Rerank API (/v2/rerank) scores a list of documents against a query and returns the most relevant results in ranked order.
About
Agentgateway supports the Cohere-compatible Rerank API. Use rerank when you already have a candidate set of documents, such as from keyword search or vector search, and want a model to reorder those documents by relevance to a query.
Agentgateway also recognizes /v1/rerank as a rerank route, but /v2/rerank is the Cohere-compatible endpoint.
Route type configuration
In the simplified llm configuration, agentgateway automatically maps /v2/rerank requests to the rerank route type, so no explicit route configuration is required.
# yaml-language-server: $schema=https://agentgateway.dev/schema/config
llm:
models:
- name: "*"
provider: cohere
params:
apiKey: "$COHERE_API_KEY"To configure the route type explicitly, use the binds/listeners/routes format and set the rerank route type in the policies.ai.routes map.
# yaml-language-server: $schema=https://agentgateway.dev/schema/config
binds:
- port: 4000
listeners:
- routes:
- backends:
- ai:
name: cohere
provider:
cohere: {}
policies:
ai:
routes:
"/v2/rerank": "rerank"
backendAuth:
key: "$COHERE_API_KEY"Using the API
Send a request to the /v2/rerank endpoint with a query and candidate documents. The response ranks the documents by relevance.
curl 'http://localhost:4000/v2/rerank' \
--header 'Content-Type: application/json' \
--data '{
"model": "rerank-v3.5",
"query": "What does agentgateway do?",
"documents": [
"agentgateway routes, secures, and observes agent and LLM traffic.",
"A bicycle drivetrain transfers power from pedals to wheels.",
"Vector databases store embeddings for semantic search."
],
"top_n": 2
}'For more information about configuring Cohere, see the Cohere provider guide.