--- title: Workers binding (legacy) description: Reference for the legacy env.AI.autorag() Workers binding used by earlier AI Search instances. image: https://developers.cloudflare.com/dev-products-preview.png --- > Documentation Index > Fetch the complete documentation index at: https://developers.cloudflare.com/ai-search/llms.txt > Use this file to discover all available pages before exploring further. [Skip to content](#%5Ftop) # Workers binding (legacy) The `env.AI.autorag()` binding is the legacy API for AI Search. It will continue to work, but new projects should use the new AI Search bindings instead. For a step-by-step upgrade guide, refer to [Workers binding migration](https://developers.cloudflare.com/ai-search/api/migration/workers-binding/). ### `aiSearch()` This method searches for relevant results from your data source and generates a response using your default model and the retrieved context: JavaScript ``` const answer = await env.AI.autorag("my-autorag").aiSearch({ query: "How do I train a llama to deliver coffee?", model: "@cf/meta/llama-3.3-70b-instruct-fp8-fast", rewrite_query: true, max_num_results: 2, ranking_options: { score_threshold: 0.3, }, reranking: { enabled: true, model: "@cf/baai/bge-reranker-base", }, 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 AI Search Generation model Settings. Defaults to the generation model selected in the AI Search Settings. --- `system_prompt` ` string ` optional The system prompt for generating the answer. --- `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`. `reranking` ` object ` optional Configurations for customizing reranking. Defaults to `{}`. * `enabled` ` boolean ` optional * Enables or disables reranking, which reorders retrieved results based on semantic relevance using a reranking model. Defaults to `false`. * `model` ` string ` optional * The reranking model to use when reranking is enabled. `stream` ` boolean ` optional Returns a stream of results as they are available. Defaults to `false`. `filters` ` object ` optional Narrow down search results based on metadata, like folder and date, so only relevant content is retrieved. For more details, refer to [Metadata filtering](https://developers.cloudflare.com/ai-search/configuration/indexing/metadata/). #### Response This is the response structure without `stream` enabled. ``` { "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": "llama/logistics/llama-logistics.md", "score": 0.45, "attributes": { "modified_date": 1735689600000, "folder": "llama/logistics/" }, "content": [ { "id": "llama001", "type": "text", "text": "Llamas can carry 3 drinks max." } ] }, { "file_id": "llama042", "filename": "llama/llama-commands.md", "score": 0.4, "attributes": { "modified_date": 1735689600000, "folder": "llama/" }, "content": [ { "id": "llama042", "type": "text", "text": "Start with basic commands like 'Espresso Express!' Llamas love alliteration." } ] } ], "has_more": false, "next_page": null } ``` ### `search()` This method searches for results from your corpus and returns the relevant results: JavaScript ``` const answer = await env.AI.autorag("my-autorag").search({ query: "How do I train a llama to deliver coffee?", rewrite_query: true, max_num_results: 2, ranking_options: { score_threshold: 0.3, }, reranking: { enabled: true, model: "@cf/baai/bge-reranker-base", }, }); ``` #### Parameters `messages` ` array ` required An array of message objects. Each message has: * `content` ` string ` \- The search query content. * `role` ` string ` \- The role: `user`, `system`, or `assistant`. --- `ai_search_options` ` object ` optional Per-request overrides for retrieval and model behavior. Supports the following nested options: * `retrieval.filters` ` object ` \- Narrow down search results based on metadata. Refer to [Metadata filtering](https://developers.cloudflare.com/ai-search/configuration/indexing/metadata/) for syntax and examples. * `retrieval.max_num_results` ` number ` \- Maximum number of chunks to return. Defaults to `10`, maximum `50`. * `retrieval.retrieval_type` ` string ` \- One of `vector`, `keyword`, or `hybrid`. * `retrieval.match_threshold` ` number ` \- Minimum similarity score (0-1). Defaults to `0.4`. * `cache.enabled` ` boolean ` \- Override the instance-level cache setting for this request. * `reranking.enabled` ` boolean ` \- Override the instance-level reranking setting for this request. --- For the full list of optional parameters, refer to the [Search API reference](https://developers.cloudflare.com/api/resources/ai%5Fsearch/subresources/instances/methods/search/). #### Response ``` { "object": "vector_store.search_results.page", "search_query": "How do I train a llama to deliver coffee?", "data": [ { "file_id": "llama001", "filename": "llama/logistics/llama-logistics.md", "score": 0.45, "attributes": { "modified_date": 1735689600000, "folder": "llama/logistics/" }, "content": [ { "id": "llama001", "type": "text", "text": "Llamas can carry 3 drinks max." } ] }, { "file_id": "llama042", "filename": "llama/llama-commands.md", "score": 0.4, "attributes": { "modified_date": 1735689600000, "folder": "llama/" }, "content": [ { "id": "llama042", "type": "text", "text": "Start with basic commands like 'Espresso Express!' 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