Feat(graphql): Add vector support to graphql #9074
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…ch based on vector indexes (#48) - [Float] data type with an @Embedding directive in GraphQL is mapped to "VFLOAT" data type in dgraph - @Embedding directive is allowed only for [Float] data type - Add querySimilar<Type> query that performs similarity search based on HNSW (vector) indexes for types with fields having @Embedding directive - querySimilar<Type> accepts 3 arguments 1. id - unique id for the object to run similarity search on. 2. <predicate> - An enum of embedding predicates defined in the type to base the search on 3. <topK> - number of nearest neighbors to return
…62) Description: If topK argument in querySimilar* queries is a graphql variable dgraph reported a panic as topK was explicitly cast as int. The fix instead uses fmt.Sprintf("%v", topK) where topK is of type interface{}. This works for when topK is passed as an int literal or a graphql variable. Fixes: HYP-328
… searches (#60) Description: If the vector parameter in a similar_to function call is a variable that evaluates to NULL then we report it as a parsing (syntax) error. The fix, instead of reporting a parsing error, returns an empty result. Closes: HYP-302 --------- Co-authored-by: Bill Province <[email protected]>
Description: Made the embedding parameeter, by, to be NonNull for `querySimilar<Type>ById `& `querySimilar<Type>ByEmbedding ` queries. This fixes the backend panic. However, the postman client fails to show the dropdown as in the input for the parameter. It shows it as a simple text input box. The client, while editing the query text in the editor pane shows valid enum values as part of the autocomplete feature. Fixes: HYP-336
…69) Description: This PR adds support for specifying @search directive with search options (vector index options) The fix is not backward compatible. Earlier searchArgs in @search directive were expected to be Enum of index types. Arguments are expected to be strings now of the following form. `@search(by: [String!])` where each string element in the array is of the form `<searchArg> := <searchType> [ ( <searchOptions> ) ]` searchOptions are optional. ``` ``` <searchOptions> := <searchOption> , <searchOption>, ... <searchOption> := <optionName><COLON><SPACE><optionValue> ``` ``` For example: `product_vector: [Float!] @hm_embedding @search(by: ["hnsw(metric: euclidian, exponent: 6)"])` Fixes: HYP-313
…_distance field was getting clobbered (#77) Description: ``` querySimilar<Type> queries defined a new derived type "<Type>WithDistance" with a new field hm_distance. However, if <Type> had any lists, hm_distance was getting clobbered by an "<ListFieldName>Aggregate" being added to <Type> The fix essentially does away with the derived type <Type>WithDistance as the resultType for querySimilar<Type> queries. Instead, we add <embeddingFieldName>Distance field for each embedding in the <Type> definition itself. This would make it easy to add support for filters on embeddings. ``` Fixes: HYP-447
…ch-filter (#79) This change adds filter agrument to querySimilarById & querySimilarByEmbedding queries. The filter argument is used as a "post-vector-serach-filter" to filter out nodes returned by the vector search. Fixes: HYP-334
…#82) Description: Computes hm_distance based on the HNSW index metric ('euclidian', 'dotproduct', 'cosine') Euclidian - (v1 - v2) dot (v1 - v2) Dot product - v1 dot v2 Cosine - (v1 dot v2) / ((v1 dot v1) * (v2 dot v2)) Fixes: HYP-477
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@harshil-goel Defining a field in graphql type as the bellow doesn't work: embedding: [Float!] @embedding @search(by: ["hnsw(exponent: 4, metric: euclidian)"]) |
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Adds support for vector predicate in GraphQL. Introduced new queries like similar_to() in graphql