Explore{}

You can explore the search graph based on the semantic meaning of the data concepts in a Weaviate using the GraphQL Explore{} function. Search results are based on given data, meta data and the Contextionary used in Weaviate.

Explore{} query structure and syntax

The Explore{} function is always defined based on the following principle:

{
  Explore (
    limit: <Int>,               # The maximum amount of objects to return
    nearText: {                 # Either this or 'nearVector' is required
      concepts: [<String>]!,   # Required - An array of search items. If the text2vec-contextionary is the vectorization module, the concepts should be present in the Contextionary.
      certainty: <Float>,      # Minimal level of certainty, computed by normalized distance
      moveTo: {                # Optional - Giving directions to the search
        concepts: [<String>]!, # List of search items
        force: <Float>!        # The force to apply for a particular movement. Must be between 0 (no movement) and 1 (largest possible movement).
      },
      moveAwayFrom: {          # Optional - Giving directions to the search
        concepts: [<String>]!, # List of search items
        force: <Float>!        # The force to apply for a particular movement. Must be between 0 (no movement) and 1 (largest possible movement).
      }
    },
    nearVector: {              # Either this or 'nearText' is required
      vector: [<Float>]!,      # Required - An array of search items, which length should match the vector space
      certainty: <Float>       # Minimal level of certainty, computed by normalized distance
    }
  ) {
    beacon
    certainty                # certainty value based on a normalized distance calculation
    className
  }
}

An example query:

GraphQL

  {
  Explore (
    nearVector: {
      vector: [-0.36840257,0.13973749,-0.28994447,-0.18607682,0.20019795,0.15541431,-0.42353877,0.30262852,0.2724561,0.07069917,0.4877447,0.038771532,0.64523,-0.15907241,-0.3413626,-0.026682584,-0.63310874,-0.33411884,0.082939014,0.30305764,0.045918174,-0.21439327,-0.5005205,0.6210859,-0.2729049,-0.51221114,0.09680918,0.094923325,-0.15688285,-0.07325482,0.6588305,0.0523736,-0.14173415,-0.27428055,0.25526586,0.057506185,-0.3103442,0.028601522,0.124522656,0.66984487,0.12160647,-0.5090515,-0.540393,-0.39546522,-0.2201204,0.34625968,-0.21068871,0.21132985,0.048714135,0.09043683,0.3176081,-0.056684002,-0.12117501,-0.6591976,-0.26731065,0.42615625,0.33333477,-0.3240578,-0.18771006,0.2328068,-0.17239179,-0.33583146,-0.6556605,-0.10608161,-0.5135395,-0.25123677,-0.23004892,0.7036331,0.04456794,0.41253626,0.27872285,-0.28226635,0.11927197,-0.4677766,0.4343466,-0.17538455,0.10621233,0.95815116,0.23587844,-0.006406698,-0.10512518,-1.1125883,-0.37921682,0.040789194,0.676718,0.3369762,0.040712647,0.580487,0.20063736,-0.021220192,-0.09071747,-0.0023735985,0.30007777,-0.039925132,0.4035474,-0.2518212,-0.17846306,0.12371392,-0.0703354,-0.3752431,-0.652917,0.5952828,1.3426708,-0.08167235,-0.38515738,0.058423538,-0.08100355,-0.192886,0.3745164,-0.23291737,0.33326542,-0.6019264,-0.42822492,-0.6524583,-0.15210791,-0.5073593,0.022548754,-0.058033653,-0.47369233,-0.30890635,0.6338296,0.0017854869,0.1954949,0.99348027,-0.26558784,-0.058124136,1.149388,0.02915948,0.013422121,0.25484946,-0.030017598,-0.23879935,0.053123385,-0.36463016,-0.0024245526,0.1202083,-0.45966506,-0.34140104,-0.08484162,-0.03537422,-0.2817959,0.25044164,-0.5060605,0.1252808,-0.032539487,0.110069446,-0.20679846,-0.46421885,-0.4141739,0.26994973,-0.070687145,0.16862138,-0.20162229,0.22199251,-0.2771402,0.23653336,0.16585203,-0.08286354,-0.15343396,0.23893964,-0.7453282,-0.16549355,-0.1947069,0.46136436,0.22064126,0.28654936,-0.038697664,0.037633028,-0.80988157,0.5094175,-0.0920082,0.25405347,-0.64169943,0.43366328,-0.2999211,-0.4090591,0.11957859,0.00803617,-0.0433745,0.12818244,0.28464508,-0.31760025,0.16558012,-0.33553946,-0.3943465,0.59569097,-0.6524206,0.3683173,-0.60456693,0.2046492,0.46010277,0.24695799,0.2946015,0.11376746,-0.027988048,0.03749422,-0.16577742,0.23407385,-0.0231737,-0.023245076,0.08752677,0.2299883,0.35467404,0.046193745,-0.39828986,0.21079691,0.38396686,-0.0018698421,0.16047359,-0.057517264,-0.203534,0.23438136,-0.84250915,0.22371331,0.0058325706,0.30733636,0.19518353,-0.108008966,0.6509316,0.070131645,-0.24023099,0.28779706,0.2326336,0.07004021,-0.45955566,0.20426086,-0.37472793,-0.049604423,0.4537271,0.6133582,-1.0527759,-0.5472505,0.15193434,0.5296606,-0.11560251,0.07279209,0.40557706,0.2505283,0.24490519,0.017602902,-0.004647707,0.16608049,0.12576887,0.118216865,0.4403996,0.39552462,-0.22196701,-0.061155193,0.03693534,-0.4022908,0.3842317,-0.0831345,0.01930883,0.3446575,-0.2167439,-0.23994556,-0.09370326,-0.3671856,0.044011243,0.017895095,-0.019855855,-0.16416992,0.17858285,0.31287143,0.38368022,-0.006513525,0.45780763,-0.23027879,0.108570844,-0.4449492,-0.035763215,0.03818417,0.040017277,-0.17022872,-0.2622464,0.65610534,0.16720143,0.2515769,-0.23535803,0.62484455,0.16771325,-0.62404263,0.19176348,-0.72786695,0.18485649,-0.30914405,-0.3230534,-0.24064465,0.28841522,0.39792386,0.15618932,0.03928854,0.18277727,-0.101632096,0.1868196,-0.33366352,0.086561844,0.48557812,-0.6198209,-0.07978742]
    }
  ) {
    beacon
    certainty // only supported if distance==cosine
    distance  // always supported
    className
  }
}

Python

  import weaviate

client = weaviate.Client("http://localhost:8080")

explore_articles_query = """
  {
    Explore (
      nearVector: {
        vector: [-0.36840257,0.13973749,-0.28994447,-0.18607682,0.20019795,0.15541431,-0.42353877,0.30262852,0.2724561,0.07069917,0.4877447,0.038771532,0.64523,-0.15907241,-0.3413626,-0.026682584,-0.63310874,-0.33411884,0.082939014,0.30305764,0.045918174,-0.21439327,-0.5005205,0.6210859,-0.2729049,-0.51221114,0.09680918,0.094923325,-0.15688285,-0.07325482,0.6588305,0.0523736,-0.14173415,-0.27428055,0.25526586,0.057506185,-0.3103442,0.028601522,0.124522656,0.66984487,0.12160647,-0.5090515,-0.540393,-0.39546522,-0.2201204,0.34625968,-0.21068871,0.21132985,0.048714135,0.09043683,0.3176081,-0.056684002,-0.12117501,-0.6591976,-0.26731065,0.42615625,0.33333477,-0.3240578,-0.18771006,0.2328068,-0.17239179,-0.33583146,-0.6556605,-0.10608161,-0.5135395,-0.25123677,-0.23004892,0.7036331,0.04456794,0.41253626,0.27872285,-0.28226635,0.11927197,-0.4677766,0.4343466,-0.17538455,0.10621233,0.95815116,0.23587844,-0.006406698,-0.10512518,-1.1125883,-0.37921682,0.040789194,0.676718,0.3369762,0.040712647,0.580487,0.20063736,-0.021220192,-0.09071747,-0.0023735985,0.30007777,-0.039925132,0.4035474,-0.2518212,-0.17846306,0.12371392,-0.0703354,-0.3752431,-0.652917,0.5952828,1.3426708,-0.08167235,-0.38515738,0.058423538,-0.08100355,-0.192886,0.3745164,-0.23291737,0.33326542,-0.6019264,-0.42822492,-0.6524583,-0.15210791,-0.5073593,0.022548754,-0.058033653,-0.47369233,-0.30890635,0.6338296,0.0017854869,0.1954949,0.99348027,-0.26558784,-0.058124136,1.149388,0.02915948,0.013422121,0.25484946,-0.030017598,-0.23879935,0.053123385,-0.36463016,-0.0024245526,0.1202083,-0.45966506,-0.34140104,-0.08484162,-0.03537422,-0.2817959,0.25044164,-0.5060605,0.1252808,-0.032539487,0.110069446,-0.20679846,-0.46421885,-0.4141739,0.26994973,-0.070687145,0.16862138,-0.20162229,0.22199251,-0.2771402,0.23653336,0.16585203,-0.08286354,-0.15343396,0.23893964,-0.7453282,-0.16549355,-0.1947069,0.46136436,0.22064126,0.28654936,-0.038697664,0.037633028,-0.80988157,0.5094175,-0.0920082,0.25405347,-0.64169943,0.43366328,-0.2999211,-0.4090591,0.11957859,0.00803617,-0.0433745,0.12818244,0.28464508,-0.31760025,0.16558012,-0.33553946,-0.3943465,0.59569097,-0.6524206,0.3683173,-0.60456693,0.2046492,0.46010277,0.24695799,0.2946015,0.11376746,-0.027988048,0.03749422,-0.16577742,0.23407385,-0.0231737,-0.023245076,0.08752677,0.2299883,0.35467404,0.046193745,-0.39828986,0.21079691,0.38396686,-0.0018698421,0.16047359,-0.057517264,-0.203534,0.23438136,-0.84250915,0.22371331,0.0058325706,0.30733636,0.19518353,-0.108008966,0.6509316,0.070131645,-0.24023099,0.28779706,0.2326336,0.07004021,-0.45955566,0.20426086,-0.37472793,-0.049604423,0.4537271,0.6133582,-1.0527759,-0.5472505,0.15193434,0.5296606,-0.11560251,0.07279209,0.40557706,0.2505283,0.24490519,0.017602902,-0.004647707,0.16608049,0.12576887,0.118216865,0.4403996,0.39552462,-0.22196701,-0.061155193,0.03693534,-0.4022908,0.3842317,-0.0831345,0.01930883,0.3446575,-0.2167439,-0.23994556,-0.09370326,-0.3671856,0.044011243,0.017895095,-0.019855855,-0.16416992,0.17858285,0.31287143,0.38368022,-0.006513525,0.45780763,-0.23027879,0.108570844,-0.4449492,-0.035763215,0.03818417,0.040017277,-0.17022872,-0.2622464,0.65610534,0.16720143,0.2515769,-0.23535803,0.62484455,0.16771325,-0.62404263,0.19176348,-0.72786695,0.18485649,-0.30914405,-0.3230534,-0.24064465,0.28841522,0.39792386,0.15618932,0.03928854,0.18277727,-0.101632096,0.1868196,-0.33366352,0.086561844,0.48557812,-0.6198209,-0.07978742]
      }
    ) {
      beacon
      certainty // only supported if distance==cosine
      distance  // always supported
      className
    }
  }
"""

query_result = client.query.raw(explore_articles_query)
print(query_result)

Javascript

  const weaviate = require("weaviate-client");

const client = weaviate.client({
  scheme: 'http',
  host: 'localhost:8080',
});

client.graphql
      .explore()
      .withNearVector({vector:[-0.36840257,0.13973749,-0.28994447,-0.18607682,0.20019795,0.15541431,-0.42353877,0.30262852,0.2724561,0.07069917,0.4877447,0.038771532,0.64523,-0.15907241,-0.3413626,-0.026682584,-0.63310874,-0.33411884,0.082939014,0.30305764,0.045918174,-0.21439327,-0.5005205,0.6210859,-0.2729049,-0.51221114,0.09680918,0.094923325,-0.15688285,-0.07325482,0.6588305,0.0523736,-0.14173415,-0.27428055,0.25526586,0.057506185,-0.3103442,0.028601522,0.124522656,0.66984487,0.12160647,-0.5090515,-0.540393,-0.39546522,-0.2201204,0.34625968,-0.21068871,0.21132985,0.048714135,0.09043683,0.3176081,-0.056684002,-0.12117501,-0.6591976,-0.26731065,0.42615625,0.33333477,-0.3240578,-0.18771006,0.2328068,-0.17239179,-0.33583146,-0.6556605,-0.10608161,-0.5135395,-0.25123677,-0.23004892,0.7036331,0.04456794,0.41253626,0.27872285,-0.28226635,0.11927197,-0.4677766,0.4343466,-0.17538455,0.10621233,0.95815116,0.23587844,-0.006406698,-0.10512518,-1.1125883,-0.37921682,0.040789194,0.676718,0.3369762,0.040712647,0.580487,0.20063736,-0.021220192,-0.09071747,-0.0023735985,0.30007777,-0.039925132,0.4035474,-0.2518212,-0.17846306,0.12371392,-0.0703354,-0.3752431,-0.652917,0.5952828,1.3426708,-0.08167235,-0.38515738,0.058423538,-0.08100355,-0.192886,0.3745164,-0.23291737,0.33326542,-0.6019264,-0.42822492,-0.6524583,-0.15210791,-0.5073593,0.022548754,-0.058033653,-0.47369233,-0.30890635,0.6338296,0.0017854869,0.1954949,0.99348027,-0.26558784,-0.058124136,1.149388,0.02915948,0.013422121,0.25484946,-0.030017598,-0.23879935,0.053123385,-0.36463016,-0.0024245526,0.1202083,-0.45966506,-0.34140104,-0.08484162,-0.03537422,-0.2817959,0.25044164,-0.5060605,0.1252808,-0.032539487,0.110069446,-0.20679846,-0.46421885,-0.4141739,0.26994973,-0.070687145,0.16862138,-0.20162229,0.22199251,-0.2771402,0.23653336,0.16585203,-0.08286354,-0.15343396,0.23893964,-0.7453282,-0.16549355,-0.1947069,0.46136436,0.22064126,0.28654936,-0.038697664,0.037633028,-0.80988157,0.5094175,-0.0920082,0.25405347,-0.64169943,0.43366328,-0.2999211,-0.4090591,0.11957859,0.00803617,-0.0433745,0.12818244,0.28464508,-0.31760025,0.16558012,-0.33553946,-0.3943465,0.59569097,-0.6524206,0.3683173,-0.60456693,0.2046492,0.46010277,0.24695799,0.2946015,0.11376746,-0.027988048,0.03749422,-0.16577742,0.23407385,-0.0231737,-0.023245076,0.08752677,0.2299883,0.35467404,0.046193745,-0.39828986,0.21079691,0.38396686,-0.0018698421,0.16047359,-0.057517264,-0.203534,0.23438136,-0.84250915,0.22371331,0.0058325706,0.30733636,0.19518353,-0.108008966,0.6509316,0.070131645,-0.24023099,0.28779706,0.2326336,0.07004021,-0.45955566,0.20426086,-0.37472793,-0.049604423,0.4537271,0.6133582,-1.0527759,-0.5472505,0.15193434,0.5296606,-0.11560251,0.07279209,0.40557706,0.2505283,0.24490519,0.017602902,-0.004647707,0.16608049,0.12576887,0.118216865,0.4403996,0.39552462,-0.22196701,-0.061155193,0.03693534,-0.4022908,0.3842317,-0.0831345,0.01930883,0.3446575,-0.2167439,-0.23994556,-0.09370326,-0.3671856,0.044011243,0.017895095,-0.019855855,-0.16416992,0.17858285,0.31287143,0.38368022,-0.006513525,0.45780763,-0.23027879,0.108570844,-0.4449492,-0.035763215,0.03818417,0.040017277,-0.17022872,-0.2622464,0.65610534,0.16720143,0.2515769,-0.23535803,0.62484455,0.16771325,-0.62404263,0.19176348,-0.72786695,0.18485649,-0.30914405,-0.3230534,-0.24064465,0.28841522,0.39792386,0.15618932,0.03928854,0.18277727,-0.101632096,0.1868196,-0.33366352,0.086561844,0.48557812,-0.6198209,-0.07978742]})
      .withFields('beacon certainty className')
      .do()
      .then(res => {
        console.log(res)
      })
      .catch(err => {
        console.error(err)
      });

  package main

import (
  "context"
  "fmt"

  "github.com/semi-technologies/weaviate-go-client/v4/weaviate"
  "github.com/semi-technologies/weaviate-go-client/v4/weaviate/graphql"
)

func main() {
  cfg := weaviate.Config{
    Host:   "localhost:8080",
    Scheme: "http",
  }
  client := weaviate.New(cfg)

  vector := []float32{-0.36840257, 0.13973749, -0.28994447, -0.18607682, 0.20019795, 0.15541431, -0.42353877, 0.30262852, 0.2724561, 0.07069917, 0.4877447, 0.038771532, 0.64523, -0.15907241, -0.3413626, -0.026682584, -0.63310874, -0.33411884, 0.082939014, 0.30305764, 0.045918174, -0.21439327, -0.5005205, 0.6210859, -0.2729049, -0.51221114, 0.09680918, 0.094923325, -0.15688285, -0.07325482, 0.6588305, 0.0523736, -0.14173415, -0.27428055, 0.25526586, 0.057506185, -0.3103442, 0.028601522, 0.124522656, 0.66984487, 0.12160647, -0.5090515, -0.540393, -0.39546522, -0.2201204, 0.34625968, -0.21068871, 0.21132985, 0.048714135, 0.09043683, 0.3176081, -0.056684002, -0.12117501, -0.6591976, -0.26731065, 0.42615625, 0.33333477, -0.3240578, -0.18771006, 0.2328068, -0.17239179, -0.33583146, -0.6556605, -0.10608161, -0.5135395, -0.25123677, -0.23004892, 0.7036331, 0.04456794, 0.41253626, 0.27872285, -0.28226635, 0.11927197, -0.4677766, 0.4343466, -0.17538455, 0.10621233, 0.95815116, 0.23587844, -0.006406698, -0.10512518, -1.1125883, -0.37921682, 0.040789194, 0.676718, 0.3369762, 0.040712647, 0.580487, 0.20063736, -0.021220192, -0.09071747, -0.0023735985, 0.30007777, -0.039925132, 0.4035474, -0.2518212, -0.17846306, 0.12371392, -0.0703354, -0.3752431, -0.652917, 0.5952828, 1.3426708, -0.08167235, -0.38515738, 0.058423538, -0.08100355, -0.192886, 0.3745164, -0.23291737, 0.33326542, -0.6019264, -0.42822492, -0.6524583, -0.15210791, -0.5073593, 0.022548754, -0.058033653, -0.47369233, -0.30890635, 0.6338296, 0.0017854869, 0.1954949, 0.99348027, -0.26558784, -0.058124136, 1.149388, 0.02915948, 0.013422121, 0.25484946, -0.030017598, -0.23879935, 0.053123385, -0.36463016, -0.0024245526, 0.1202083, -0.45966506, -0.34140104, -0.08484162, -0.03537422, -0.2817959, 0.25044164, -0.5060605, 0.1252808, -0.032539487, 0.110069446, -0.20679846, -0.46421885, -0.4141739, 0.26994973, -0.070687145, 0.16862138, -0.20162229, 0.22199251, -0.2771402, 0.23653336, 0.16585203, -0.08286354, -0.15343396, 0.23893964, -0.7453282, -0.16549355, -0.1947069, 0.46136436, 0.22064126, 0.28654936, -0.038697664, 0.037633028, -0.80988157, 0.5094175, -0.0920082, 0.25405347, -0.64169943, 0.43366328, -0.2999211, -0.4090591, 0.11957859, 0.00803617, -0.0433745, 0.12818244, 0.28464508, -0.31760025, 0.16558012, -0.33553946, -0.3943465, 0.59569097, -0.6524206, 0.3683173, -0.60456693, 0.2046492, 0.46010277, 0.24695799, 0.2946015, 0.11376746, -0.027988048, 0.03749422, -0.16577742, 0.23407385, -0.0231737, -0.023245076, 0.08752677, 0.2299883, 0.35467404, 0.046193745, -0.39828986, 0.21079691, 0.38396686, -0.0018698421, 0.16047359, -0.057517264, -0.203534, 0.23438136, -0.84250915, 0.22371331, 0.0058325706, 0.30733636, 0.19518353, -0.108008966, 0.6509316, 0.070131645, -0.24023099, 0.28779706, 0.2326336, 0.07004021, -0.45955566, 0.20426086, -0.37472793, -0.049604423, 0.4537271, 0.6133582, -1.0527759, -0.5472505, 0.15193434, 0.5296606, -0.11560251, 0.07279209, 0.40557706, 0.2505283, 0.24490519, 0.017602902, -0.004647707, 0.16608049, 0.12576887, 0.118216865, 0.4403996, 0.39552462, -0.22196701, -0.061155193, 0.03693534, -0.4022908, 0.3842317, -0.0831345, 0.01930883, 0.3446575, -0.2167439, -0.23994556, -0.09370326, -0.3671856, 0.044011243, 0.017895095, -0.019855855, -0.16416992, 0.17858285, 0.31287143, 0.38368022, -0.006513525, 0.45780763, -0.23027879, 0.108570844, -0.4449492, -0.035763215, 0.03818417, 0.040017277, -0.17022872, -0.2622464, 0.65610534, 0.16720143, 0.2515769, -0.23535803, 0.62484455, 0.16771325, -0.62404263, 0.19176348, -0.72786695, 0.18485649, -0.30914405, -0.3230534, -0.24064465, 0.28841522, 0.39792386, 0.15618932, 0.03928854, 0.18277727, -0.101632096, 0.1868196, -0.33366352, 0.086561844, 0.48557812, -0.6198209, -0.07978742}

  withNearVector := client.GraphQL().NearVectorArgBuilder().
    WithVector(vector)

  result, err := client.GraphQL().Explore().
    WithFields(
      graphql.Beacon, 
      graphql.Certainty,  # only supported if distance==cosine
      graphql.Distance    # always supported
      graphql.ClassName).
    WithNearVector(withNearVector).
    Do(context.Background())

  if err != nil {
    panic(err)
  }
  fmt.Printf("%v", result)
}

Java

  package technology.semi.weaviate;

import technology.semi.weaviate.client.Config;
import technology.semi.weaviate.client.WeaviateClient;
import technology.semi.weaviate.client.base.Result;
import technology.semi.weaviate.client.v1.graphql.model.ExploreFields;
import technology.semi.weaviate.client.v1.graphql.model.GraphQLResponse;
import technology.semi.weaviate.client.v1.graphql.query.argument.NearVectorArgument;

public class App {
  public static void main(String[] args) {
    Config config = new Config("http", "localhost:8080");
    WeaviateClient client = new WeaviateClient(config);
    ExploreFields[] fields = new ExploreFields[]{
      ExploreFields.CERTAINTY,  // only supported if distance==cosine
      ExploreFields.DISTANCE,   // always supported
      ExploreFields.BEACON, 
      ExploreFields.CLASS_NAME
    };

    Float[] vector = new Float[]{-0.36840257f,0.13973749f,-0.28994447f,-0.18607682f,0.20019795f,0.15541431f,-0.42353877f,0.30262852f,0.2724561f,0.07069917f,0.4877447f,0.038771532f,0.64523f,-0.15907241f,-0.3413626f,-0.026682584f,-0.63310874f,-0.33411884f,0.082939014f,0.30305764f,0.045918174f,-0.21439327f,-0.5005205f,0.6210859f,-0.2729049f,-0.51221114f,0.09680918f,0.094923325f,-0.15688285f,-0.07325482f,0.6588305f,0.0523736f,-0.14173415f,-0.27428055f,0.25526586f,0.057506185f,-0.3103442f,0.028601522f,0.124522656f,0.66984487f,0.12160647f,-0.5090515f,-0.540393f,-0.39546522f,-0.2201204f,0.34625968f,-0.21068871f,0.21132985f,0.048714135f,0.09043683f,0.3176081f,-0.056684002f,-0.12117501f,-0.6591976f,-0.26731065f,0.42615625f,0.33333477f,-0.3240578f,-0.18771006f,0.2328068f,-0.17239179f,-0.33583146f,-0.6556605f,-0.10608161f,-0.5135395f,-0.25123677f,-0.23004892f,0.7036331f,0.04456794f,0.41253626f,0.27872285f,-0.28226635f,0.11927197f,-0.4677766f,0.4343466f,-0.17538455f,0.10621233f,0.95815116f,0.23587844f,-0.006406698f,-0.10512518f,-1.1125883f,-0.37921682f,0.040789194f,0.676718f,0.3369762f,0.040712647f,0.580487f,0.20063736f,-0.021220192f,-0.09071747f,-0.0023735985f,0.30007777f,-0.039925132f,0.4035474f,-0.2518212f,-0.17846306f,0.12371392f,-0.0703354f,-0.3752431f,-0.652917f,0.5952828f,1.3426708f,-0.08167235f,-0.38515738f,0.058423538f,-0.08100355f,-0.192886f,0.3745164f,-0.23291737f,0.33326542f,-0.6019264f,-0.42822492f,-0.6524583f,-0.15210791f,-0.5073593f,0.022548754f,-0.058033653f,-0.47369233f,-0.30890635f,0.6338296f,0.0017854869f,0.1954949f,0.99348027f,-0.26558784f,-0.058124136f,1.149388f,0.02915948f,0.013422121f,0.25484946f,-0.030017598f,-0.23879935f,0.053123385f,-0.36463016f,-0.0024245526f,0.1202083f,-0.45966506f,-0.34140104f,-0.08484162f,-0.03537422f,-0.2817959f,0.25044164f,-0.5060605f,0.1252808f,-0.032539487f,0.110069446f,-0.20679846f,-0.46421885f,-0.4141739f,0.26994973f,-0.070687145f,0.16862138f,-0.20162229f,0.22199251f,-0.2771402f,0.23653336f,0.16585203f,-0.08286354f,-0.15343396f,0.23893964f,-0.7453282f,-0.16549355f,-0.1947069f,0.46136436f,0.22064126f,0.28654936f,-0.038697664f,0.037633028f,-0.80988157f,0.5094175f,-0.0920082f,0.25405347f,-0.64169943f,0.43366328f,-0.2999211f,-0.4090591f,0.11957859f,0.00803617f,-0.0433745f,0.12818244f,0.28464508f,-0.31760025f,0.16558012f,-0.33553946f,-0.3943465f,0.59569097f,-0.6524206f,0.3683173f,-0.60456693f,0.2046492f,0.46010277f,0.24695799f,0.2946015f,0.11376746f,-0.027988048f,0.03749422f,-0.16577742f,0.23407385f,-0.0231737f,-0.023245076f,0.08752677f,0.2299883f,0.35467404f,0.046193745f,-0.39828986f,0.21079691f,0.38396686f,-0.0018698421f,0.16047359f,-0.057517264f,-0.203534f,0.23438136f,-0.84250915f,0.22371331f,0.0058325706f,0.30733636f,0.19518353f,-0.108008966f,0.6509316f,0.070131645f,-0.24023099f,0.28779706f,0.2326336f,0.07004021f,-0.45955566f,0.20426086f,-0.37472793f,-0.049604423f,0.4537271f,0.6133582f,-1.0527759f,-0.5472505f,0.15193434f,0.5296606f,-0.11560251f,0.07279209f,0.40557706f,0.2505283f,0.24490519f,0.017602902f,-0.004647707f,0.16608049f,0.12576887f,0.118216865f,0.4403996f,0.39552462f,-0.22196701f,-0.061155193f,0.03693534f,-0.4022908f,0.3842317f,-0.0831345f,0.01930883f,0.3446575f,-0.2167439f,-0.23994556f,-0.09370326f,-0.3671856f,0.044011243f,0.017895095f,-0.019855855f,-0.16416992f,0.17858285f,0.31287143f,0.38368022f,-0.006513525f,0.45780763f,-0.23027879f,0.108570844f,-0.4449492f,-0.035763215f,0.03818417f,0.040017277f,-0.17022872f,-0.2622464f,0.65610534f,0.16720143f,0.2515769f,-0.23535803f,0.62484455f,0.16771325f,-0.62404263f,0.19176348f,-0.72786695f,0.18485649f,-0.30914405f,-0.3230534f,-0.24064465f,0.28841522f,0.39792386f,0.15618932f,0.03928854f,0.18277727f,-0.101632096f,0.1868196f,-0.33366352f,0.086561844f,0.48557812f,-0.6198209f,-0.07978742f};

    NearVectorArgument nearVector = NearVectorArgument.builder().
      vector(vector).build();

    Result<GraphQLResponse> result = client.graphQL().explore()
      .withFields(fields)
      .withNearVector(nearVector)
      .run();
    if (result.hasErrors()) {
      System.out.println(result.getError());
      return;
    }
    System.out.println(result.getResult());
  }
}

curl

  $ echo '{ 
  "query": "{
    Explore (
      nearVector: {
        vector: [-0.36840257,0.13973749,-0.28994447,-0.18607682,0.20019795,0.15541431,-0.42353877,0.30262852,0.2724561,0.07069917,0.4877447,0.038771532,0.64523,-0.15907241,-0.3413626,-0.026682584,-0.63310874,-0.33411884,0.082939014,0.30305764,0.045918174,-0.21439327,-0.5005205,0.6210859,-0.2729049,-0.51221114,0.09680918,0.094923325,-0.15688285,-0.07325482,0.6588305,0.0523736,-0.14173415,-0.27428055,0.25526586,0.057506185,-0.3103442,0.028601522,0.124522656,0.66984487,0.12160647,-0.5090515,-0.540393,-0.39546522,-0.2201204,0.34625968,-0.21068871,0.21132985,0.048714135,0.09043683,0.3176081,-0.056684002,-0.12117501,-0.6591976,-0.26731065,0.42615625,0.33333477,-0.3240578,-0.18771006,0.2328068,-0.17239179,-0.33583146,-0.6556605,-0.10608161,-0.5135395,-0.25123677,-0.23004892,0.7036331,0.04456794,0.41253626,0.27872285,-0.28226635,0.11927197,-0.4677766,0.4343466,-0.17538455,0.10621233,0.95815116,0.23587844,-0.006406698,-0.10512518,-1.1125883,-0.37921682,0.040789194,0.676718,0.3369762,0.040712647,0.580487,0.20063736,-0.021220192,-0.09071747,-0.0023735985,0.30007777,-0.039925132,0.4035474,-0.2518212,-0.17846306,0.12371392,-0.0703354,-0.3752431,-0.652917,0.5952828,1.3426708,-0.08167235,-0.38515738,0.058423538,-0.08100355,-0.192886,0.3745164,-0.23291737,0.33326542,-0.6019264,-0.42822492,-0.6524583,-0.15210791,-0.5073593,0.022548754,-0.058033653,-0.47369233,-0.30890635,0.6338296,0.0017854869,0.1954949,0.99348027,-0.26558784,-0.058124136,1.149388,0.02915948,0.013422121,0.25484946,-0.030017598,-0.23879935,0.053123385,-0.36463016,-0.0024245526,0.1202083,-0.45966506,-0.34140104,-0.08484162,-0.03537422,-0.2817959,0.25044164,-0.5060605,0.1252808,-0.032539487,0.110069446,-0.20679846,-0.46421885,-0.4141739,0.26994973,-0.070687145,0.16862138,-0.20162229,0.22199251,-0.2771402,0.23653336,0.16585203,-0.08286354,-0.15343396,0.23893964,-0.7453282,-0.16549355,-0.1947069,0.46136436,0.22064126,0.28654936,-0.038697664,0.037633028,-0.80988157,0.5094175,-0.0920082,0.25405347,-0.64169943,0.43366328,-0.2999211,-0.4090591,0.11957859,0.00803617,-0.0433745,0.12818244,0.28464508,-0.31760025,0.16558012,-0.33553946,-0.3943465,0.59569097,-0.6524206,0.3683173,-0.60456693,0.2046492,0.46010277,0.24695799,0.2946015,0.11376746,-0.027988048,0.03749422,-0.16577742,0.23407385,-0.0231737,-0.023245076,0.08752677,0.2299883,0.35467404,0.046193745,-0.39828986,0.21079691,0.38396686,-0.0018698421,0.16047359,-0.057517264,-0.203534,0.23438136,-0.84250915,0.22371331,0.0058325706,0.30733636,0.19518353,-0.108008966,0.6509316,0.070131645,-0.24023099,0.28779706,0.2326336,0.07004021,-0.45955566,0.20426086,-0.37472793,-0.049604423,0.4537271,0.6133582,-1.0527759,-0.5472505,0.15193434,0.5296606,-0.11560251,0.07279209,0.40557706,0.2505283,0.24490519,0.017602902,-0.004647707,0.16608049,0.12576887,0.118216865,0.4403996,0.39552462,-0.22196701,-0.061155193,0.03693534,-0.4022908,0.3842317,-0.0831345,0.01930883,0.3446575,-0.2167439,-0.23994556,-0.09370326,-0.3671856,0.044011243,0.017895095,-0.019855855,-0.16416992,0.17858285,0.31287143,0.38368022,-0.006513525,0.45780763,-0.23027879,0.108570844,-0.4449492,-0.035763215,0.03818417,0.040017277,-0.17022872,-0.2622464,0.65610534,0.16720143,0.2515769,-0.23535803,0.62484455,0.16771325,-0.62404263,0.19176348,-0.72786695,0.18485649,-0.30914405,-0.3230534,-0.24064465,0.28841522,0.39792386,0.15618932,0.03928854,0.18277727,-0.101632096,0.1868196,-0.33366352,0.086561844,0.48557812,-0.6198209,-0.07978742]
      }
    ) {
      beacon
      certainty  // only supported if distance==cosine
      distance   // always supported
      className
    }
  }"
}' | curl \
    -X POST \
    -H 'Content-Type: application/json' \
    -d @- \
    http://localhost:8080/v1/graphql

🟢 Click here to try out this graphql example in the Weaviate Console.

The result might look like this:

{
  "data": {
    "Explore": [
      {
        "beacon": "weaviate://localhost/7e9b9ffe-e645-302d-9d94-517670623b35",
        "certainty": 0.975523,
        "className": "Publication"
      }
    ]
  },
  "errors": null
}

CamelCase interpretation

Weaviate’s vectorization module text2vec-contextionary splits words based on CamelCase. For example, if a user wants to explore for the iPhone (the Apple device) they should use iphone rather than iPhone because the latter will be interpreted as [i, phone].

Explore filter arguments

Concepts

Strings written in the Concepts array are your fuzzy search terms. An array of concepts is required to set in the Explore query, and all words in this array should be present in the Contextionary.

There are three ways to define the concepts array argument in the Explore filter.

["New York Times"] = one vector position is determined based on the occurrences of the words
["New", "York", "Times"] = all concepts have a similar weight.
["New York", "Times"] = a combination of the two above.

A practical example would be: concepts: ["beatles", "John Lennon"]

Distance

You can set a maximum allowed distance, which will be used to determine which data results to return. The interpretation of the value of the distance field depends on the distance metric used.

If the distance metric is cosine you can also use certainty instead of distance. Certainty normalizes the distance in a range of 0..1, where 0 reprents a perfect opposite (cosine distance of 2) and 1 represents vectors with an identical angle (cosine distance of 0). Certainty is not available on non-cosine distance metrics.

Moving

Because pagination is not possible in multidimensional storage, you can improve your results with additional explore functions which can move away from semantic concepts or towards semantic concepts. E.g., if you look for the concept ‘New York Times’ but don’t want to find the city New York, you can use the moveAwayFrom{} function by using the words ‘New York’. This is also a way to exclude concepts and to deal with negations (not operators in similar query languages). Concepts in the moveAwayFrom{} filter are not per definition excluded from the result, but the resulting concepts are further away from the concepts in this filter.

Additional filters

Explore{} functions can be extended with search filters (both semantic filters as traditional filters). Because the filters work on multiple core functions (like Aggregate{}) there is a specific documentation page dedicated to filters.

More Resources

If you can’t find the answer to your question here, please look at the:

Frequently Asked Questions. Or,
Knowledge base of old issues. Or,
For questions: Stackoverflow. Or,
For issues: Github. Or,
Ask your question in the Slack channel: Slack.

Edit on Github

Explore{} query structure and syntax
Explore filter arguments
- Concepts
- Additional filters
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