`Hybrid` search combines the results of a vector search and a keyword (BM25F) search by fusing the two result sets. The [fusion method](#change-the-fusion-method) and the [relative weights](#balance-keyword-and-vector-search) are configurable. :::callout{intent="tip" title="Prefer natural language queries?"} The [Query Agent](query-agent.md) translates plain English questions into optimized Weaviate queries automatically - no manual query construction needed. Cloud only ::: ## Basic hybrid search Combine the results of a vector search and a keyword search. The search uses a single query string. :::code-group{sync="languages"} ```python title="Python" {2} jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid(query="food", limit=3) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "food" limit := 3 q := client.GraphQL().Get(). WithClassName(className). WithFields(graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}). WithHybrid(client.GraphQL().HybridArgumentBuilder().WithQuery(query)). WithLimit(limit) result, err := q.Do(ctx) ``` ```java title="Java" {4} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid( "food", q -> q.limit(3) ); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {3-4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {5-7} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "food" } ) { question answer } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "a closer grocer", "question": "A nearer food merchant" }, { "answer": "Famine", "question": "From the Latin for \"hunger\", it's a period when food is extremely scarce" }, { "answer": "Tofu", "question": "A popular health food, this soybean curd is used to make a variety of dishes & an ice cream substitute" } ] } } } ``` ::: ## Named vectors A hybrid search on a collection that has [named vectors](../reference-configuration/collections.md#multiple-vector-embeddings-named-vectors) must specify a `target` vector. Weaviate uses the query vector to search the target vector space. :::code-group{sync="languages"} ```python title="Python" {2-6} reviews = client.collections.use("WineReviewNV") response = reviews.query.hybrid( query="A French Riesling", target_vector="title_country", limit=3 ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" {4} const myNVCollection = client.collections.use('WineReviewNV'); const result = await myNVCollection.query.hybrid('a sweet German white wine', { targetVector: 'title_country', limit: 2, }) for (let object of result.objects) { console.log(JSON.stringify(object.properties, null, 2)); } ``` ```java title="Java" ``` ```csharp title="C#" {2-5} var reviews = client.Collections.Use("WineReviewNV"); var response = await reviews.Query.Hybrid( vectors: v => v.NearText(["A French Riesling"]).TargetVectorsMinimum("title_country"), limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {5-8} { Get { WineReviewNV( limit: 2 hybrid: { targetVectors: ["title_country"] query: "A French Riesling" } ) { title review_body country } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json ``` ::: ## Explain the search results To see the object rankings, set the `explain score` field in your query. The search rankings are part of the object metadata. Weaviate uses the score to order the search results. :::code-group{sync="languages"} ```python title="Python" {7,13} from weaviate.classes.query import MetadataQuery jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", alpha=0.5, return_metadata=MetadataQuery(score=True, explain_score=True), limit=3, ) for o in response.objects: print(o.properties) print(o.metadata.score, o.metadata.explain_score) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "food" limit := 3 result, err := client.GraphQL().Get(). WithClassName(className). WithFields( graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}, graphql.Field{Name: "_additional", Fields: []graphql.Field{{Name: "score"}, {Name: "explainScore"}}}, ). WithHybrid(client.GraphQL().HybridArgumentBuilder().WithQuery(query)). WithLimit(limit). Do(ctx) ``` ```java title="Java" {4,9-10} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("food", q -> q.alpha(0.5f) .returnMetadata(Metadata.SCORE, Metadata.EXPLAIN_SCORE) .limit(3)); for (var o : response.objects()) { System.out.println(o.properties()); System.out .println(o.queryMetadata().score() + " " + o.queryMetadata().explainScore()); } ``` ```csharp title="C#" {5,12-14} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", alpha: 0.5f, returnMetadata: MetadataOptions.Score | MetadataOptions.ExplainScore, limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); Console.WriteLine( $"Score: {o.Metadata.Score}, Explain Score: {o.Metadata.ExplainScore}" ); } ``` ```graphql title="GraphQL" {11-14} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "food" } ) { question answer _additional { score explainScore } } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "_additional": { "explainScore": "(bm25)\n(hybrid) Document df958a90-c3ad-5fde-9122-cd777c22da6c contributed 0.003968253968253968 to the score\n(hybrid) Document df958a90-c3ad-5fde-9122-cd777c22da6c contributed 0.012295081967213115 to the score", "score": "0.016263336" }, "answer": "a closer grocer", "question": "A nearer food merchant" }, { "_additional": { "explainScore": "(vector) [0.0223698 -0.02752683 -0.0061537363 0.0023812135 -0.00036100898 -0.0078375945 -0.018505432 -0.037500713 -0.0042215516 -0.012620432]... \n(hybrid) Document ec776112-e651-519d-afd1-b48e6237bbcb contributed 0.012096774193548387 to the score", "score": "0.012096774" }, "answer": "Famine", "question": "From the Latin for \"hunger\", it's a period when food is extremely scarce" }, { "_additional": { "explainScore": "(vector) [0.0223698 -0.02752683 -0.0061537363 0.0023812135 -0.00036100898 -0.0078375945 -0.018505432 -0.037500713 -0.0042215516 -0.012620432]... \n(hybrid) Document 98807640-cd16-507d-86a1-801902d784de contributed 0.011904761904761904 to the score", "score": "0.011904762" }, "answer": "Tofu", "question": "A popular health food, this soybean curd is used to make a variety of dishes & an ice cream substitute" } ] } } } ``` ::: ## Balance keyword and vector search Hybrid search results can favor the keyword component or the vector component. To change the relative weights of the keyword and vector components, set the `alpha` value in your query. - An `alpha` of `1` is a pure vector search. - An `alpha` of `0` is a pure keyword search. If you do not set `alpha`, the effective weighting depends on your client. See [Alpha parameter](../search/hybrid-search.md#alpha-parameter). :::code-group{sync="languages"} ```python title="Python" {4} jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", alpha=0.25, limit=3, ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "food" limit := 3 alpha := float32(0.25) result, err := client.GraphQL().Get(). WithClassName(className). WithFields(graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}). WithHybrid(client.GraphQL().HybridArgumentBuilder(). WithQuery(query). WithAlpha(alpha), ). WithLimit(limit). Do(ctx) ``` ```java title="Java" {4} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("food", q -> q .alpha(0.25f) .limit(3)); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", alpha: 0.25f, limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {7} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "food" alpha: 0.25 } ) { question answer } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "a closer grocer", "question": "A nearer food merchant" }, { "answer": "food stores (supermarkets)", "question": "This type of retail store sells more shampoo & makeup than any other" }, { "answer": "cake", "question": "Devil's food & angel food are types of this dessert" } ] } } } ``` ::: ## Change the fusion method `Relative Score Fusion` is the default fusion method starting in `v1.24`. - To use the keyword and vector search relative scores instead of the search rankings, use `Relative Score Fusion`. - To use [`autocut`](../apis/graphql-additional-operators.md#autocut) with the `hybrid` operator, use `Relative Score Fusion`. :::code-group{sync="languages"} ```python title="Python" {1,6} from weaviate.classes.query import HybridFusion jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", fusion_type=HybridFusion.RELATIVE_SCORE, limit=3, ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "food" limit := 3 fusionType := "relativeScoreFusion" result, err := client.GraphQL().Get(). WithClassName(className). WithFields(graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}). WithHybrid(client.GraphQL().HybridArgumentBuilder(). WithQuery(query). WithFusionType(graphql.FusionType(fusionType)), ). WithLimit(limit). Do(ctx) ``` ```java title="Java" {4} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("food", q -> q .fusionType(FusionType.RELATIVE_SCORE) .limit(3)); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", fusionType: HybridFusion.RelativeScore, limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {7} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "food" fusionType: relativeScoreFusion } ) { question answer } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "a closer grocer", "question": "A nearer food merchant" }, { "answer": "food stores (supermarkets)", "question": "This type of retail store sells more shampoo & makeup than any other" }, { "answer": "cake", "question": "Devil's food & angel food are types of this dessert" } ] } } } ``` ::: :::accordion{title="Additional information"} For a discussion of fusion methods, see [this blog post](https://weaviate.io/blog/hybrid-search-fusion-algorithms) and [this reference page](../apis/graphql-search-operators.md#fusion-algorithms). ::: ## Keyword search operators :::callout{intent="info" title="Added in `v1.31`"} ::: Keyword (BM25) search operators define how many of the query [tokens](#tokenization) must match, and whether they must all match within a single searched property. The options are `or` (default), `and`, and `and_cross` (available from `v1.38.8`). The keyword leg of a hybrid query accepts the same operators as a standalone keyword search. For `and_cross`, which matches every token across the searched properties combined, see [BM25 search: `and_cross`](bm25.md#and_cross). ### `or` With the `or` operator, the search returns objects that contain at least `minimumOrTokensMatch` of the tokens in the search string. :::code-group{sync="languages"} ```python title="Python" {1,5-6} from weaviate.classes.query import BM25Operator jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="Australian mammal cute", bm25_operator=BM25Operator.or_(minimum_match=2), limit=3, ) for o in response.objects: print(o.properties) ``` ```typescript title="JS/TS" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```java title="Java" {4} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid( "Australian mammal cute", c -> c.searchOperator(SearchOperator.or(2)) .limit(3)); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {3-4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "Australian mammal cute", bm25Operator: new BM25Operator.Or(MinimumMatch: 1), limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```python title="GraphQL" {7-10} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "Australian mammal cute" bm25SearchOperator: { operator: Or, minimumOrTokensMatch: 2 } } ) { question answer } } } ``` ::: ### `and` With the `and` operator, the search returns objects where all tokens in the search string appear together within a single searched property. :::code-group{sync="languages"} ```python title="Python" {1,5-6} from weaviate.classes.query import BM25Operator jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="Australian mammal cute", bm25_operator=BM25Operator.and_(), # Each result must include all tokens (e.g. "australian", "mammal", "cute") limit=3, ) for o in response.objects: print(o.properties) ``` ```typescript title="JS/TS" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```java title="Java" {4-6} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid( "Australian mammal cute" // .bm25Operator(BM25Operator.and()) // Each result must include all tokens // (e.g. "australian", "mammal", "cute") // .limit(3) ); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {3-4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "Australian mammal cute", bm25Operator: new BM25Operator.And(), // Each result must include all tokens limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```python title="GraphQL" {7-9} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "Australian mammal cute" bm25SearchOperator: { operator: And, } } ) { question answer } } } ``` ::: ## Specify keyword search properties The keyword search portion of hybrid search can be directed to only search a subset of object properties. This does not affect the vector search portion. :::code-group{sync="languages"} ```python title="Python" {4} jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", query_properties=["question"], alpha=0.25, limit=3, ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "food" limit := 3 alpha := float32(0.25) properties := []string{"question"} result, err := client.GraphQL().Get(). WithClassName(className). WithFields(graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}). WithHybrid(client.GraphQL().HybridArgumentBuilder(). WithQuery(query). WithAlpha(alpha). WithProperties(properties), ). WithLimit(limit). Do(ctx) ``` ```java title="Java" {4} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("food", q -> q .queryProperties("question") .alpha(0.25f) .limit(3)); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", queryProperties: ["question"], alpha: 0.25f, limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {7} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "food" properties: ["question"] alpha: 0.25 } ) { question answer } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "a closer grocer", "question": "A nearer food merchant" }, { "answer": "cake", "question": "Devil's food & angel food are types of this dessert" }, { "answer": "honey", "question": "The primary source of this food is the Apis mellifera" } ] } } } ``` ::: ## Set weights on property values Specify the relative value of an object's `properties` in the keyword search. Higher values increase the property's contribution to the search score. :::code-group{sync="languages"} ```python title="Python" {4} jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", query_properties=["question^2", "answer"], alpha=0.25, limit=3, ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "food" limit := 3 alpha := float32(0.25) properties := []string{"question^2", "answer"} result, err := client.GraphQL().Get(). WithClassName(className). WithFields(graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}). WithHybrid(client.GraphQL().HybridArgumentBuilder(). WithQuery(query). WithAlpha(alpha). WithProperties(properties), ). WithLimit(limit). Do(ctx) ``` ```java title="Java" {4} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("food", q -> q .queryProperties("question^2", "answer") .alpha(0.25f) .limit(3)); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", queryProperties: ["question^2", "answer"], alpha: 0.25f, limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {7} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "food" properties: ["question^2", "answer"] alpha: 0.25 } ) { question answer } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "a closer grocer", "question": "A nearer food merchant" }, { "answer": "cake", "question": "Devil's food & angel food are types of this dessert" }, { "answer": "food stores (supermarkets)", "question": "This type of retail store sells more shampoo & makeup than any other" } ] } } } ``` ::: ## Specify a search vector The vector component of hybrid search can use a query string or a query vector. To specify a query vector instead of a query string, provide a query vector (for the vector search) and a query string (for the keyword search) in your query. :::code-group{sync="languages"} ```python title="Python" {6} query_vector = [-0.02] * 1536 # Some vector that is compatible with object vectors jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", vector=query_vector, alpha=0.25, limit=3, ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "food" limit := 3 //Create a vector 384 dimensions long // Define the length of the slice length := 384 // Initialize the slice with the specified length values := make([]float32, length) // Fill the slice with values for i := 0; i < length; i++ { values[i] = 0.1 * float32(i+1) } vector := values result, err := client.GraphQL().Get(). WithClassName(className). WithFields(graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}). WithHybrid(client.GraphQL().HybridArgumentBuilder(). WithQuery(query). WithVector(vector), ). WithLimit(limit). Do(ctx) ``` ```java title="Java" {9} float[] queryVector = new float[1536]; // Some vector that is compatible with object vectors for (int i = 0; i < queryVector.length; i++) { queryVector[i] = -0.02f; } CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("food", q -> q // .nearVector(NearVector.of(queryVector)) .alpha(0.25f) .limit(3)); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {6} var queryVector = Enumerable.Repeat(-0.02f, 1536).ToArray(); var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", vectors: queryVector, alpha: 0.25f, limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {7} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "food" vector: [0.013085687533020973, -0.00777443777769804, 0.005439540836960077, -0.021052561700344086, -0.02164270170032978, -0.006985447835177183, -0.018974246457219124, -0.025260508060455322, -0.0013630924513563514, -0.03597281128168106, 0.027993107214570045, 0.01635710895061493, -0.02948128432035446, 0.009159981273114681, -0.0026780758053064346, 0.001033544773235917, 0.04051431640982628, 0.001919554895721376, 0.024952609091997147, -0.01960287243127823, 0.0001997531799133867, 0.031405650079250336, 0.021142365410923958, -0.007954045198857784, -0.0008338918560184538, -0.0040572043508291245, 7.381747127510607e-05, -0.019051222130656242, 0.004942412953823805, -0.01888444274663925, 0.028121398761868477, 0.004631306976079941, -0.031559597700834274, -0.003143130801618099, 0.01867917738854885, -0.024208521470427513, 0.0056351847015321255, -0.019333461299538612, -0.0012756941141560674, 0.01737060956656933, 0.020128866657614708, -0.007755194325000048, -0.0071329823695123196, -0.007761608809232712, -0.0074986121617257595, 0.00579554820433259, 0.002782312221825123, 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-0.001111321267671883, -0.027582576498389244, -0.0024455483071506023, -0.021655529737472534, -0.007505026645958424, -0.009429392404854298, -0.016177501529455185, 0.0072484444826841354, 0.017139684408903122, 0.014561034739017487, 0.007075251545757055, -0.02289995364844799, 0.006411345209926367, 0.018768981099128723, 0.0026347774546593428, -0.008871326223015785, -0.03989851847290993, 0.008204213343560696, 0.013060029596090317, -0.03299646079540253, -0.015536046586930752, 0.02464471198618412, -0.02894246205687523, -0.006485112942755222, 0.008768693543970585, 0.016831785440444946, 0.035664912313222885, -0.0032938728109002113, 0.022425275295972824, -0.02050090953707695, -0.00025557982735335827, 0.013239637017250061, -0.016652178019285202, 0.004143801052123308, -0.0032072763424366713, -0.025273337960243225] } ) { question answer } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "Risotto", "question": "From the Italian word for rice, it's a rice dish cooked with broth & often grated cheese" }, { "answer": "arrabiata", "question": "Italian for \"angry\", it describes a pasta sauce spiced up with plenty of chiles" }, { "answer": "Fettucine Alfredo", "question": "Ribbon-shaped noodles, sweet butter, cream, parmesan cheese & black pepper make up this pasta dish" } ] } } } ``` ::: ## Vector search parameters You can specify [vector similarity search](similarity.md) parameters similar to [near text](similarity.md#search-with-text) or [near vector](similarity.md#search-with-a-vector) searches, such as `group by` and `move to` / `move away`. An equivalent `distance` [threshold for vector search](similarity.md#set-a-similarity-threshold) can be specified with the `max vector distance` parameter. :::code-group{sync="languages"} ```python title="Python" {6-10} from weaviate.classes.query import HybridVector, Move, HybridFusion jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="California", max_vector_distance=0.4, # Maximum threshold for the vector search component vector=HybridVector.near_text( query="large animal", move_away=Move(force=0.5, concepts=["mammal", "terrestrial"]), ), alpha=0.75, limit=5, ) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```java title="Java" {14-15} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var intermediateResponse = jeopardy.query .nearText("large animal", c -> c.moveAway(0.5f, from -> from.concepts("mammal", "terrestrial"))) .objects() .get(0) .vectors() .getDefaultSingle(); var response = jeopardy.query.hybrid("California", q -> q .maxVectorDistance(0.4f) .nearVector(NearVector.of(intermediateResponse)) .alpha(0.75f) .limit(5)); ``` ```csharp title="C#" {5-10} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "California", maxVectorDistance: 0.4f, vectors: v => v.NearText( "large animal", moveAway: new Move(force: 0.5f, concepts: ["mammal", "terrestrial"]) ), alpha: 0.75f, limit: 5 ); ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "Rhinoceros", "points": 400, "question": "The \"black\" species of this large horned mammal can grasp twigs with its upper lip" }, { "answer": "the hippopotamus", "points": 400, "question": "Close relative of the pig, though its name means \"river horse\"" }, { "answer": "buffalo", "points": 400, "question": "Animal that was the main staple of the Plains Indians economy" }, { "answer": "California", "points": 200, "question": "Its state animal is the grizzly bear, & the state tree is a type of redwood" }, { "answer": "California", "points": 200, "question": "This western state sent its first refrigerated trainload of oranges back east February 14, 1886" } ] } } } ``` ::: ## Hybrid search thresholds The only available search threshold is `max vector distance`, which will set the maximum allowable distance for the vector search component. :::code-group{sync="languages"} ```python title="Python" {6} from weaviate.classes.query import HybridVector, Move, HybridFusion jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="California", max_vector_distance=0.4, # Maximum threshold for the vector search component alpha=0.75, limit=5, ) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```java title="Java" {4} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("California", q -> q .maxVectorDistance(0.4f) // Maximum threshold for the vector search component .alpha(0.75f) .limit(5)); ``` ```csharp title="C#" {4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "California", maxVectorDistance: 0.4f, // Maximum threshold for the vector search component alpha: 0.75f, limit: 5 ); ``` ::: ## Group results Define criteria to group search results. :::code-group{sync="languages"} ```python title="Python" # Grouping parameters group_by = GroupBy( prop="round", # group by this property objects_per_group=3, # maximum objects per group number_of_groups=2, # maximum number of groups ) # Query jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( alpha=0.75, query="California", group_by=group_by ) for grp_name, grp_content in response.groups.items(): print(grp_name, grp_content.objects) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```java title="Java" // Query CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("California", q -> q.alpha(0.75f), GroupBy.property("round", // group by this property 2, // maximum number of groups 3 // maximum objects per group )); response.groups().forEach((groupName, group) -> { System.out.println(group.name() + " " + group.objects()); }); ``` ```csharp title="C#" // Query var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "California", alpha: 0.75f, groupBy: new GroupByRequest("round") // group by this property { NumberOfGroups = 2, // maximum number of groups ObjectsPerGroup = 3, // maximum objects per group } ); foreach (var group in response.Groups.Values) { Console.WriteLine($"{group.Name} {JsonSerializer.Serialize(group.Objects)}"); } ``` ::: :::accordion{title="Example response"} The response is like this: ``` 'Jeopardy!' 'Double Jeopardy!' ``` ::: ## `limit` & `offset` Use `limit` to set a fixed maximum number of objects to return. Optionally, use `offset` to paginate the results. :::code-group{sync="languages"} ```python title="Python" {4-5} jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", limit=3, offset=1 ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "safety" limit := 3 result, err := client.GraphQL().Get(). WithClassName(className). WithFields( graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}, graphql.Field{Name: "_additional", Fields: []graphql.Field{{Name: "score"}}}, ). WithHybrid(client.GraphQL().HybridArgumentBuilder().WithQuery(query)). WithLimit(limit). Do(ctx) ``` ```java title="Java" {4-5} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("food", q -> q .limit(3) .offset(1) ); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {4-5} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", limit: 3, offset: 1 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {7} { Get { JeopardyQuestion( hybrid: { query: "safety" } limit: 3 ) { question answer _additional { score } } } } ``` ::: ## Limit result groups To limit results to groups with similar distances from the query, use the [`autocut`](../apis/graphql-additional-operators.md#autocut) filter. Specify the `Relative Score Fusion` ranking method when you use autocut with hybrid search. :::callout{intent="info"} Autocut requires `Relative Score Fusion` method because it uses actual similarity scores to detect cutoff points. Autocut shouldn't be used with `Ranked Fusion` as this fusion method relies on ranking positions, not similarity scores. To learn more about the different fusion algorithms, visit the [search operators reference page](../apis/graphql-search-operators.md#fusion-algorithms). ::: :::code-group{sync="languages"} ```python title="Python" {6-7} from weaviate.classes.query import HybridFusion jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", fusion_type=HybridFusion.RELATIVE_SCORE, auto_limit=1 ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "safety" autocut := 1 result, err := client.GraphQL().Get(). WithClassName(className). WithFields( graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}, graphql.Field{Name: "_additional", Fields: []graphql.Field{{Name: "score"}}}, ). WithHybrid(client.GraphQL().HybridArgumentBuilder().WithQuery(query)). WithAutocut(autocut). Do(ctx) ``` ```java title="Java" ``` ```csharp title="C#" {4-5} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", fusionType: HybridFusion.RelativeScore, autoLimit: 1 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {7} { Get { JeopardyQuestion( hybrid: { query: "safety" } autocut: 1 ) { question answer _additional { score } } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "Guards", "question": "Life, Security, Shin", "_additional": { "score": "0.75" }, }, # ... trimmed for brevity ] } } } ``` ::: ## Filter results To narrow your search results, use a [`filter`](../apis/graphql-filters.md). :::code-group{sync="languages"} ```python title="Python" {1-2,7} from weaviate.classes.query import Filter jeopardy = client.collections.use("JeopardyQuestion") response = jeopardy.query.hybrid( query="food", filters=Filter.by_property("round").equal("Double Jeopardy!"), limit=3, ) for o in response.objects: print(o.properties) ``` ```typescript title="JavaScript/TypeScript" const jeopardy = client.collections.use('JeopardyQuestion'); ``` ```go title="Go" ctx := context.Background() className := "JeopardyQuestion" query := "food" limit := 3 filter := filters.Where(). WithPath([]string{"round"}). WithOperator(filters.Equal). WithValueString("Double Jeopardy!") result, err := client.GraphQL().Get(). WithClassName(className). WithFields(graphql.Field{Name: "question"}, graphql.Field{Name: "answer"}, graphql.Field{Name: "round"}). WithHybrid(client.GraphQL().HybridArgumentBuilder().WithQuery(query)). WithWhere(filter). WithLimit(limit). Do(ctx) ``` ```java title="Java" {4} CollectionHandle> jeopardy = client.collections.use("JeopardyQuestion"); var response = jeopardy.query.hybrid("food", q -> q .filters(Filter.property("round").eq("Double Jeopardy!")) .limit(3)); for (var o : response.objects()) { System.out.println(o.properties()); } ``` ```csharp title="C#" {4} var jeopardy = client.Collections.Use("JeopardyQuestion"); var response = await jeopardy.Query.Hybrid( "food", filters: Filter.Property("round").IsEqual("Double Jeopardy!"), limit: 3 ); foreach (var o in response.Objects) { Console.WriteLine(JsonSerializer.Serialize(o.Properties)); } ``` ```graphql title="GraphQL" {8-12} { Get { JeopardyQuestion( limit: 3 hybrid: { query: "food" } where: { path: ["round"] operator: Equal valueText: "Double Jeopardy!" } ) { question answer round } } } ``` ::: :::accordion{title="Example response"} The output is like this: ```json { "data": { "Get": { "JeopardyQuestion": [ { "answer": "food stores (supermarkets)", "question": "This type of retail store sells more shampoo & makeup than any other", "round": "Double Jeopardy!" }, { "answer": "Tofu", "question": "A popular health food, this soybean curd is used to make a variety of dishes & an ice cream substitute", "round": "Double Jeopardy!" }, { "answer": "gastronomy", "question": "This word for the art & science of good eating goes back to Greek for \"belly\"", "round": "Double Jeopardy!" } ] } } } ``` ::: ### Tokenization Weaviate converts filter terms into tokens. The default tokenization is `word`. The `word` tokenizer keeps alphanumeric characters, lowercase them and splits on whitespace. It converts a string like "Test\_domain\_weaviate" into "test", "domain", and "weaviate". For details and additional tokenization methods, see [Tokenization](../reference-configuration/collections.md#tokenization). ## Soft-rank with Boost :::callout{intent="info" title="Added in `v1.38`"} ::: Hybrid queries accept an optional `boost` argument that promotes or demotes matching documents without removing them. This is useful for biasing results by recency, popularity, a soft filter, or another property. The boost runs once over the **fused** hybrid result. The BM25 and vector sub-search legs do not see the boost themselves. Hybrid's own `alpha` blend runs first, and the boost rescores the fused candidate pool on top. See [Boost](boost.md) for the supported condition types (filter, property value, time decay, numeric decay), curve choices, blending semantics, and depth tuning. ## Diversity selection (MMR) :::callout{intent="info" title="Added in `v1.38.6`"} ::: Hybrid search fuses a keyword result set and a vector result set, which often means the top of the fused list is a cluster of near-duplicates. **Maximal Marginal Relevance (MMR)** reranks that list to balance relevance with diversity, so that each selected object adds something new to the result set. Diversity selection runs after fusion. Both search legs run first, their results are fused with the configured `alpha` and fusion method, and the diversity pass then picks a diverse subset of the fused candidates. :::code-group{sync="languages"} ```python title="Python" {10-13} from weaviate.classes.query import Diversity collection = client.collections.get("MMRDemo") # Fuse the keyword and vector results into 20 candidates, then select 5 diverse results response = collection.query.hybrid( query="Question", vector=base_vec, limit=20, diversity_selection=Diversity.mmr( limit=5, balance=0.5, ), ) for o in response.objects: print(o.properties["question"]) ``` ::: Important notes: - **Top-level only**: set diversity selection on the hybrid query itself. Setting it on a sub-search is rejected with an error. - **Two limits**: the query's top-level `limit` is the candidate window that gets diversified, and the diversity `limit` is the number of results returned. The diversity `limit` must be at least `1` and no larger than the query `limit`. - **Ordering**: results come back in MMR order, not fused-score order. - **Pagination**: `offset` moves the candidate window, so it must advance by the query `limit`, not by the number of returned objects. Weaviate does not validate this, and getting it wrong silently repeats some objects across pages while skipping others. See [Pagination](similarity.md#pagination). - **Not supported**: multi-vector collections. Weaviate rejects these queries with an error. For the parameters, the relevance and diversity trade-off, and vector search examples, see [Diversity selection (MMR)](similarity.md#diversity-selection-mmr). ## Related pages - [Connect to Weaviate](../connect-to-weaviate/index.md) - [API References: Search operators # Hybrid](../apis/graphql-search-operators.md#hybrid) - About [hybrid fusion algorithms](https://weaviate.io/blog/hybrid-search-fusion-algorithms). - For search using the GraphQL API, see [GraphQL API](../apis/graphql-get.md). ## Questions and feedback Have a question or feedback? Here's how to reach us. ::::card-grid :::card{title="Community Forum" href="https://forum.weaviate.io/c/support" icon="messages-square"} Ask questions and connect with other developers on our **Community forum**. ::: :::card{title="Support" href="/guides/support-overview" icon="life-buoy"} Weaviate Cloud user or customer? Find the right channel on the **Support page**. ::: :::: ## Related pages - [Agents](./agents-index.md) - [AI-assisted Weaviate code generation](./ai-assisted-vibe-coding-index.md) - [APIs](./apis-index.md) - [Authorization and authentication](./authorization-and-authentication-index.md) - [Benchmarks](./benchmarks-index.md) - [Best practices](./best-practices-index.md) - [Client libraries](./clients-index.md) - [Client Libraries / SDKs](./client-libraries-index.md) - [Cloud](./cloud-index.md) - [Cloud account management](./cloud-account-management-index.md) # Agent Instructions This portal answers questions programmatically. To receive a synthesized, source-cited answer instead of crawling page by page, append the `?ask=` query parameter to any page URL on this site: /guides/quickstart?ask=how+do+I+authenticate Optional parameters: - `&goal=` steers the answer toward your objective (e.g. `&goal=write+a+python+client`). - `&version=