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REST API

This guide will instruct you through how to use the AutoRAG REST API to make a query to your AutoRAG.

Prerequisite: Get AutoRAG API token

You need an API token with the AutoRAG - Read and AutoRAG Edit permissions to use the REST API. To create a new token:

  1. Log in to the Cloudflare dashboard and select your account.
  2. Go to AI > AutoRAG and select your AutoRAG.
  3. Select Use AutoRAG then select API.
  4. Select Create an API Token.
  5. Review the prefilled information then select Create API Token.
  6. Select Copy API Token and save that value for future use.

This REST API searches for relevant results from your data source and generates a response using the model and the retrieved relevant context:

Terminal window
curl https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/autorag/rags/{AUTORAG_NAME}/ai-search \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer {API_TOKEN}" \
-d '{
"query": "How do I train a llama to deliver coffee?",
"model": @cf/meta/llama-3.3-70b-instruct-sd,
"rewrite_query": true,
"max_num_results": 10,
"ranking_options": {
"score_threshold": 0.6
},
"stream": true,
}'

Parameters

query string required

The input query.

model string optional

The text-generation model that is used to generate the response for the query. For a list of valid options, check the AutoRAG Generation model Settings. Defaults to the generation model selected in the AutoRAG Settings.

rewrite_query boolean optional

Rewrites the original query into a search optimized query to improve retrieval accuracy. Defaults to false.

max_num_results number optional

The maximum number of results that can be returned from the Vectorize database. Defaults to 10. Must be between 1 and 50.

ranking_options object optional

Configurations for customizing result ranking. Defaults to {}.

  • score_threshold number optional
    • The minimum match score required for a result to be considered a match. Defaults to 0. Must be between 0 and 1.

streaming object optional

Returns a stream of results as they are available. Defaults to false.

Response

This is the response structure without stream enabled.

{
"success": true,
"result": {
"object": "vector_store.search_results.page",
"search_query": "How do I train a llama to deliver coffee?",
"response": "To train a llama to deliver coffee:\n\n1. **Build trust** — Llamas appreciate patience (and decaf).\n2. **Know limits** — Max 3 cups per llama, per `llama-logistics.md`.\n3. **Use voice commands** — Start with \"Espresso Express!\"\n4.",
"data": [
{
"file_id": "llama001",
"filename": "docs/llama-logistics.md",
"score": 0.98,
"attributes": {},
"content": [
{
"id": "llama001",
"type": "text",
"text": "Llamas can carry 3 drinks max."
}
]
},
{
"file_id": "llama042",
"filename": "docs/llama-commands.md",
"score": 0.95,
"attributes": {},
"content": [
{
"id": "llama042",
"type": "text",
"text": "Start with basic commands like 'Espresso Express!' Llamas love alliteration."
}
]
},
],
"has_more": false,
"next_page": null
}
}

This REST API searches for results from your data source and returns the relevant results:

Terminal window
curl https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/autorag/rags/{AUTORAG_NAME}/search \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer {API_TOKEN}" \
-d '{
"query": "How do I train a llama to deliver coffee?",
"rewrite_query": true,
"max_num_results": 10,
"ranking_options": {
"score_threshold": 0.6
},
}'

Parameters

query string required

The input query.

rewrite_query boolean optional

Rewrites the original query into a search optimized query to improve retrieval accuracy. Defaults to false.

max_num_results number optional

The maximum number of results that can be returned from the Vectorize database. Defaults to 10. Must be between 1 and 50.

ranking_options object optional

Configurations for customizing result ranking. Defaults to {}.

  • score_threshold number optional
    • The minimum match score required for a result to be considered a match. Defaults to 0. Must be between 0 and 1.

Response

{
"success": true,
"result": {
"object": "vector_store.search_results.page",
"search_query": "How do I train a llama to deliver coffee?",
"data": [
{
"file_id": "llama001",
"filename": "docs/llama-logistics.md",
"score": 0.98,
"attributes": {},
"content": [
{
"id": "llama001",
"type": "text",
"text": "Llamas can carry 3 drinks max."
}
]
},
{
"file_id": "llama042",
"filename": "docs/llama-commands.md",
"score": 0.95,
"attributes": {},
"content": [
{
"id": "llama042",
"type": "text",
"text": "Start with basic commands like 'Espresso Express!' Llamas love alliteration."
}
]
},
],
"has_more": false,
"next_page": null
}
}