Execute a pesquisa híbrida com a MongoDB Vector Search e a MongoDB Search

Os estágios $rankFusion e $scoreFusion estão disponíveis como recursos de pré-visualização. Para saber mais, consulte Recursos de visualização.

Este tutorial demonstra uma pesquisa híbrida que é uma agregação de pesquisa de texto completo e pesquisa semântica para os mesmos critérios da query. Embora o texto completo seja eficaz para encontrar correspondências exatas para termos de query, a pesquisa semântica oferece o benefício adicional de identificar documentos semanticamente semelhantes, mesmo que os documentos não contenham o termo de query exato. Isso garante que correspondências sinônimas e contextualmente semelhantes também sejam incluídas nos resultados combinados de ambos os métodos de pesquisa.

Por outro lado, se você tiver tokens para nomes próprios ou palavras-chave específicas em seu conjunto de dados que não espera que sejam considerados no treinamento de um modelo de incorporação no mesmo contexto em que são usados em seu conjunto de dados, sua pesquisa vetorial poderá se beneficiar da combinação com uma pesquisa de texto completo.

Você também pode definir pesos para cada método de pesquisa por query. Com base no fato de os resultados da pesquisa de texto completo ou semântica serem mais relevantes e apropriados para uma query, você pode aumentar o peso desse método de pesquisa por query.

Sobre o tutorial

Este tutorial demonstra como executar uma pesquisa híbrida combinando queries do MongoDB Vector Search e do MongoDB Search na collection sample_mflix.embedded_movies, que contém detalhes sobre filmes, para obter resultados de pesquisa unificados. Especificamente, este tutorial orienta você pelas seguintes etapas:

Crie um índice do MongoDB Vector Search no campo plot_embedding_voyage_3_large . Este campo contém incorporações vetoriais que representam o resumo da trama de um filme.
Crie um índice do MongoDB Search no title campo na coleção sample_mflix.embedded_movies. Este campo contém o nome do filme como uma string de texto.
Execute uma consulta que use fusão de classificação recíproca para combinar os resultados de uma consulta $vectorSearch no campo plot_embedding_voyage_3_large e uma consulta { $search } no campo title .

Pré-requisitos

Antes de começar, conclua os pré-requisitos comuns. Você deve ter o acesso ao projeto para criar índices do MongoDB Vector Search e do MongoDB Project Data Access Admin Search.

Crie os índices Vector Search do MongoDB e Search do MongoDB

Esta seção demonstra como criar os seguintes índices nos campos na collection sample_mflix.embedded_movies :

Um índice MongoDB Vector Search no campo plot_embedding_voyage_3_large para executar queries vetoriais nesse campo.
Um índice do MongoDB Search no campo title para executar a pesquisa de texto completo nesse campo.

Procedimento

Conecte-se ao cluster do Atlas usando `mongosh`.

Para saber mais, consulte Conectar-se a um cluster via mongosh.

Alterne para o banco de dados que contém a collection para a qual você deseja criar o índice.

use sample_mflix

switched to db sample_mflix

Defina o índice do MongoDB Vector Search .

Execute o seguinte comando. Esta definição de índice indexa o campo plot_embedding_voyage_3_large como o campo Vector Search do MongoDB ao executar query da coleção.

1 db.embedded_movies.createSearchIndex(
2   "hybrid-vector-search", 
3   "vectorSearch", 
4   {
5     "fields": [
6       {
7         "type": "vector",
8         "path": "plot_embedding_voyage_3_large",
9         "numDimensions": 2048,
10         "similarity": "dotProduct"
11       }
12     ]
13   }
14 );

Defina o índice de pesquisa do MongoDB .

A seguinte definição de índice indexa automaticamente todos os campos indexáveis dinamicamente na collection.

1 db.embedded_movies.createSearchIndex(
2   "hybrid-full-text-search", 
3   "search", 
4   {
5     "mappings": {
6       "dynamic": true
7     }
8   }
9 );

Execute uma query combinada de pesquisa semântica e pesquisa de texto completo usando `$rankFusion`

Esta seção demonstra como executar query dos dados da sample_mflix.embedded_movies coleção para runas plot_embedding_voyage_3_large nos title campos e usando os $vectorSearch estágios de pipeline e dentro do $search $rankFusion estágio para reordenar as documentos nos resultados. A $rankFusion etapa garante que os documentos que aparecem em ambas as pesquisas apareçam no topo dos resultados combinados.

Procedimento

Configure as incorporações a serem usadas na consulta.

Crie um arquivo denominado query-embeddings.js.

Copie e cole as seguintes incorporações no arquivo.

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Salve e feche o arquivo.

Conecte-se ao seu cluster usando o `mongosh`.

Abra o mongosh em uma janela do terminal e conecte ao seu cluster. Para obter instruções detalhadas sobre a conexão, consulte Conectar-se a um cluster via mongosh.

Use o banco de dados `sample_mflix`.

Execute o seguinte comando no prompt mongosh:

use sample_mflix

switched to db sample_mflix

Carregue as incorporações para usar na query.

Execute o seguinte comando para carregar as incorporações após substituir <path-to-file> pelo caminho absoluto para o arquivo embeddings.js:

load('/<path-to-file>/embeddings.js');

Para verificar se as incorporações foram carregadas com sucesso, execute o seguinte comando:

STAR_WARS_EMBEDDING.length

Execute as seguintes queries do MongoDB Search na `embedded_movies` collection.

1 db.embedded_movies.aggregate([
2   {
3     $rankFusion: {
4       input: {
5         pipelines: {
6           vectorPipeline: [
7             {
8               "$vectorSearch": {
9                 "index": "hybrid-vector-search",
10                 "path": "plot_embedding_voyage_3_large",
11                 "queryVector": STAR_WARS_EMBEDDING,
12                 "numCandidates": 100,
13                 "limit": 20
14               }
15             }
16           ],
17           fullTextPipeline: [
18             {
19               "$search": {
20                 "index": "hybrid-full-text-search",
21                 "phrase": {
22                   "query": "star wars",
23                   "path": "title"
24                 }
25               }
26             },
27             { "$limit": 20 }
28           ]
29         }
30       },
31       combination: {
32         weights: {
33           vectorPipeline: 0.5,
34           fullTextPipeline: 0.5
35         }
36       },
37       "scoreDetails": true
38     }
39   },
40   {
41     "$project": {
42       _id: 1,
43       title: 1,
44       plot: 1,
45       scoreDetails: {"$meta": "scoreDetails"}
46     }
47   },
48   {
49     "$limit": 10
50   }
51 ]);

[
  {
    _id: ObjectId('573a1397f29313caabce68f6'),
    plot: "Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader.",
    title: 'Star Wars: Episode IV - A New Hope',
    scoreDetails: {
      value: 0.01626123744050767,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'fullTextPipeline',
          rank: 2,
          weight: 0.5,
          value: 2.9571781158447266,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 1,
          weight: 0.5,
          value: 0.7987099885940552,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcf0f5f'),
    plot: 'Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory.',
    title: 'Star Wars: Episode I - The Phantom Menace',
    scoreDetails: {
      value: 0.015527202696196438,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'fullTextPipeline',
          rank: 2,
          weight: 0.5,
          value: 2.9571781158447266,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 7,
          weight: 0.5,
          value: 0.7771433591842651,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1397f29313caabce77d9'),
    plot: 'After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke.',
    title: 'Star Wars: Episode V - The Empire Strikes Back',
    scoreDetails: {
      value: 0.015504807692307693,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'fullTextPipeline',
          rank: 4,
          weight: 0.5,
          value: 2.712062358856201,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 5,
          weight: 0.5,
          value: 0.7810181975364685,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1397f29313caabce8cdb'),
    plot: 'After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force.',
    title: 'Star Wars: Episode VI - Return of the Jedi',
    scoreDetails: {
      value: 0.015388257575757576,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'fullTextPipeline',
          rank: 4,
          weight: 0.5,
          value: 2.712062358856201,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 6,
          weight: 0.5,
          value: 0.7782549858093262,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13c0f29313caabd62f62'),
    plot: 'Anakin Skywalker and Ahsoka Tano must rescue the kidnapped son of Jabba the Hutt, but political intrigue complicates their mission.',
    title: 'Star Wars: The Clone Wars',
    scoreDetails: {
      value: 0.015141165755919854,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'fullTextPipeline',
          rank: 1,
          weight: 0.5,
          value: 3.609658718109131,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 12,
          weight: 0.5,
          value: 0.7561323642730713,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcf124d'),
    plot: 'As the Clone Wars near an end, the Sith Lord Darth Sidious steps out of the shadows, at which time Anakin succumbs to his emotions, becoming Darth Vader and putting his relationships with Obi-Wan and Padme at risk.',
    title: 'Star Wars: Episode III - Revenge of the Sith',
    scoreDetails: {
      value: 0.014854753521126762,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'fullTextPipeline',
          rank: 4,
          weight: 0.5,
          value: 2.712062358856201,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 11,
          weight: 0.5,
          value: 0.756283700466156,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcf1258'),
    plot: 'Ten years after initially meeting, Anakin Skywalker shares a forbidden romance with Padmè, while Obi-Wan investigates an assassination attempt on the Senator and discovers a secret clone army crafted for the Jedi.',
    title: 'Star Wars: Episode II - Attack of the Clones',
    scoreDetails: {
      value: 0.014391447368421052,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'fullTextPipeline',
          rank: 4,
          weight: 0.5,
          value: 2.712062358856201,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 16,
          weight: 0.5,
          value: 0.7400004267692566,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1398f29313caabce9091'),
    plot: "A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule.",
    title: 'Dune',
    scoreDetails: {
      value: 0.008064516129032258,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'fullTextPipeline', rank: 0, weight: 0.5 },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 2,
          weight: 0.5,
          value: 0.7947750091552734,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1397f29313caabce6f53'),
    plot: 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...',
    title: 'Message from Space',
    scoreDetails: {
      value: 0.007936507936507936,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'fullTextPipeline', rank: 0, weight: 0.5 },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 3,
          weight: 0.5,
          value: 0.7913960218429565,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139df29313caabcfa90b'),
    plot: 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...',
    title: 'Message from Space',
    scoreDetails: {
      value: 0.007936507936507936,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'fullTextPipeline', rank: 0, weight: 0.5 },
        {
          inputPipelineName: 'vectorPipeline',
          rank: 3,
          weight: 0.5,
          value: 0.7913960218429565,
          details: []
        }
      ]
    }
  }
]

Sobre a query

A query de amostra recupera os resultados de pesquisa classificados da pesquisa semântica e da pesquisa de texto completo e atribui uma pontuação de classificação recíproca aos documentos nos resultados com base na posição deles na array de resultados. A pontuação de classificação recíproca é calculada usando a seguinte fórmula:

1.0/{document position in the results + constant value}

Em seguida, a query soma as pontuações de ambas as pesquisas para cada documento, classifica os documentos com base na pontuação combinada e ordena os documentos para retornar um único resultado. O valor da constante é sempre 60.

Pesos de query

A consulta de exemplo define os seguintes pesos para os pipelines para influenciar a contribuição de classificação desses pipelines para a pontuação final:

vectorPipeline = 0.5
fullTextPipeline = 0.5

Você pode ajustar os pesos para dar mais importância a um método de pesquisa. Observe que um número menor proporciona maior peso.

A pontuação de classificação recíproca ponderada é calculada usando a seguinte fórmula:

weight x reciprocal rank

scoreDetails.value exibe a pontuação bruta desse pipeline antes de ser ponderada e combinada por meio da fusão de classificação recíproca. scoreDetails.details.value mostra a pontuação de classificação recíproca ponderada.

Estágios de query

O exemplo de query usa a etapa $rankFusion para executar as consultas semânticas e de texto completo de forma independente, remover duplicações e combinar os resultados da query de entrada em um conjunto final de resultados ordenados. Ele retorna um conjunto ordenado de documentos com base nas classificações que aparecem nos pipelines de entrada e nos pesos dos pipelines. Especificamente, esse estágio usa os seguintes pipelines de entrada:

vectorPipeline

Este pipeline contém a query $vectorSearch. Ela pesquisa o campo plot_embedding_voyage_3_large pela string star wars especificada como incorporação vetorial no campo queryVector da query. A query usa o modelo de incorporação voyage-3-large da Voyage AI, que é o mesmo modelo usado para as incorporações no campo plot_embedding_voyage_3_large. A query também especifica uma pesquisa para até 100 vizinhos mais próximos e limita os resultados somente a 20 documentos. Essa etapa retorna os documentos classificados da pesquisa semântica nos resultados.

fullTextPipeline

O pipeline contém os seguintes estágios:

$search para pesquisar filmes que contenham o termo star wars no campo title. Esse estágio retorna os documentos classificados da pesquisa de texto completo nos resultados.
$limit para limitar a saída do estágio $search a apenas 20 resultados.

A query de exemplo usa os seguintes estágios para combinar os resultados da pesquisa semântica e de texto e retornar uma única lista classificada de documentos nos resultados:

`$project`	Inclui somente os seguintes campos nos resultados: `_id` `title` `plot` `scoreDetails`
`$limit`	Limita a saída a apenas `10` resultados.

Execute uma query combinada de pesquisa semântica e pesquisa de texto completo usando `$scoreFusion`

Esta seção demonstra como executar query dos dados da sample_mflix.embedded_movies coleção para runas plot_embedding_voyage_3_large nos title campos e usando os $vectorSearch estágios de pipeline e dentro do $search $scoreFusion estágio para reordenar as documentos nos resultados com base em suas pontuações combinadas. O $scoreFusion estágio usa expressões matemáticas para combinar as pontuações de um documento e influenciar a posição do documento nos resultados.

Procedimento

Configure as incorporações a serem usadas na consulta.

Crie um arquivo denominado query-embeddings.js.

Copie e cole as seguintes incorporações no arquivo.

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Salve e feche o arquivo.

Conecte-se ao seu cluster usando o `mongosh`.

Abra o mongosh em uma janela do terminal e conecte ao seu cluster. Para obter instruções detalhadas sobre a conexão, consulte Conectar-se a um cluster via mongosh.

Use o banco de dados `sample_mflix`.

Execute o seguinte comando no prompt mongosh:

use sample_mflix

switched to db sample_mflix

Carregue as incorporações para usar na query.

Execute o seguinte comando para carregar as incorporações após substituir <path-to-file> pelo caminho absoluto para o arquivo embeddings.js:

load('/<path-to-file>/embeddings.js');

Para verificar se as incorporações foram carregadas com sucesso, execute o seguinte comando:

STAR_WARS_EMBEDDING.length

Execute as seguintes queries do MongoDB Search na `embedded_movies` collection.

1 db.embedded_movies.aggregate( [
2    {
3       $scoreFusion: {
4          input: {
5             pipelines: {
6                searchOne: [
7                   {
8                      "$vectorSearch": {
9                         "index": "hybrid-vector-search",
10                         "path": "plot_embedding_voyage_3_large",
11                         "queryVector": STAR_WARS_EMBEDDING,
12                         "numCandidates": 100,
13                         "limit": 20
14                      }
15                   }
16                ],
17                searchTwo: [
18                   {
19                      "$search": {
20                         "index": "hybrid-full-text-search",
21                         "text": {
22                            "query": "star wars",
23                            "path": "title"
24                         }
25                      }
26                   },
27                ]
28             },
29             normalization: "sigmoid"
30          },
31          combination: {
32             method: "expression",
33             expression: {
34                $sum: [
35                  {$multiply: [ "$$searchOne", 10]}, "$$searchTwo"
36                ]
37             }
38          },
39          "scoreDetails": true
40       }
41    },
42    {
43       "$project": {
44          _id: 1,
45          title: 1,
46          plot: 1,
47          scoreDetails: {"$meta": "scoreDetails"}
48       }
49    },
50    { $limit: 10 }
51 ] )

[
  {
    _id: ObjectId('573a1397f29313caabce68f6'),
    plot: "Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader.",
    title: 'Star Wars: Episode IV - A New Hope',
    scoreDetails: {
      value: 7.847857250621068,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7987099885940552,
          weight: 1,
          value: 0.6896984675751023,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 2.9629626274108887,
          weight: 1,
          value: 0.950872574870045,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcf0f5f'),
    plot: 'Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory.',
    title: 'Star Wars: Episode I - The Phantom Menace',
    scoreDetails: {
      value: 7.801513736063318,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7771433591842651,
          weight: 1,
          value: 0.6850641161193273,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 2.9629626274108887,
          weight: 1,
          value: 0.950872574870045,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1397f29313caabce77d9'),
    plot: 'After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke.',
    title: 'Star Wars: Episode V - The Empire Strikes Back',
    scoreDetails: {
      value: 7.797042499608402,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7810181975364685,
          weight: 1,
          value: 0.6858995173201419,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 2.7174296379089355,
          weight: 1,
          value: 0.9380473264069833,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13c0f29313caabd62f62'),
    plot: 'Anakin Skywalker and Ahsoka Tano must rescue the kidnapped son of Jabba the Hutt, but political intrigue complicates their mission.',
    title: 'Star Wars: The Clone Wars',
    scoreDetails: {
      value: 7.79454790938817,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7561323642730713,
          weight: 1,
          value: 0.6805134398691156,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 4.537533760070801,
          weight: 1,
          value: 0.989413510697013,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1397f29313caabce8cdb'),
    plot: 'After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force.',
    title: 'Star Wars: Episode VI - Return of the Jedi',
    scoreDetails: {
      value: 7.7910863426550625,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7782549858093262,
          weight: 1,
          value: 0.6853039016248079,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 2.7174296379089355,
          weight: 1,
          value: 0.9380473264069833,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcf124d'),
    plot: 'As the Clone Wars near an end, the Sith Lord Darth Sidious steps out of the shadows, at which time Anakin succumbs to his emotions, becoming Darth Vader and putting his relationships with Obi-Wan and Padme at risk.',
    title: 'Star Wars: Episode III - Revenge of the Sith',
    scoreDetails: {
      value: 7.743510743539187,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.756283700466156,
          weight: 1,
          value: 0.6805463417132204,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 2.7174296379089355,
          weight: 1,
          value: 0.9380473264069833,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcf1258'),
    plot: 'Ten years after initially meeting, Anakin Skywalker shares a forbidden romance with Padmè, while Obi-Wan investigates an assassination attempt on the Senator and discovers a secret clone army crafted for the Jedi.',
    title: 'Star Wars: Episode II - Attack of the Clones',
    scoreDetails: {
      value: 7.708006822019003,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7400004267692566,
          weight: 1,
          value: 0.676995949561202,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 2.7174296379089355,
          weight: 1,
          value: 0.9380473264069833,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1398f29313caabce9091'),
    plot: "A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule.",
    title: 'Dune',
    scoreDetails: {
      value: 6.888556969451009,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7947750091552734,
          weight: 1,
          value: 0.6888556969451008,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 0,
          weight: 1,
          value: 0
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1397f29313caabce6f53'),
    plot: 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...',
    title: 'Message from Space',
    scoreDetails: {
      value: 6.8813100491486825,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7913960218429565,
          weight: 1,
          value: 0.6881310049148682,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 0,
          weight: 1,
          value: 0
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139df29313caabcfa90b'),
    plot: 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...',
    title: 'Message from Space',
    scoreDetails: {
      value: 6.8813100491486825,
      description: 'the value calculated by combining the scores (either normalized or raw) across input pipelines from which this document is output from:',
      normalization: 'sigmoid',
      combination: {
        method: 'custom expression',
        expression: "{ string: { $sum: [ { $multiply: [ '$$searchOne', 10 ] }, '$$searchTwo' ] } }"
      },
      details: [
        {
          inputPipelineName: 'searchOne',
          inputPipelineRawScore: 0.7913960218429565,
          weight: 1,
          value: 0.6881310049148682,
          details: []
        },
        {
          inputPipelineName: 'searchTwo',
          inputPipelineRawScore: 0,
          weight: 1,
          value: 0
        }
      ]
    }
  }
]

Sobre a query

A query de exemplo recupera os resultados da pesquisa pontuada das pesquisas semântica e de texto completo e aplica a expressão sigmoid para normalizar a pontuação antes de combinar os resultados. Em seguida, ele combina a pontuação dos pipelines em uma única pontuação agregada para cada documento.

Pesos de query

A query de amostra aplica pesos às pontuações do pipeline de entrada normalizadas ao combinar os resultados. Ele aplica os pesos utilizando uma expressão de agregação customizada. Neste exemplo, a query usa a expressão $multiply para multiplicar a pontuação do pipeline searchOne por 10. Isso garante que os resultados deste pipeline contribuam mais para a pontuação final do que os resultados do pipeline searchTwo. Em seguida, ele usa o operador de agregação $sum para adicionar as pontuações dos dois estágios do pipeline.

Final Score = ($$searchOne * 10) + $$searchTwo

Observação

Se você combinar os resultados da query usando uma expressão (combination.method: expression), não será possível usar peso em sua query. Recomendamos usar $multiply conforme demonstrado na query de exemplo anterior.

Estágios de query

A query de amostra usa o estágio $scoreFusion para executar as queries semânticas e de texto completo de forma independente e, em seguida, deduplicar e combinar os resultados da query de entrada em um conjunto de resultados de pontuação final. Ele retorna um conjunto de documentos com base na pontuação combinada de seus pipelines de entrada e nos pesos de combinação. Especificamente, este estágio utiliza os seguintes pipelines de entrada:

vectorPipeline

Este pipeline contém a query. Ele pesquisa $vectorSearch no plot_embedding_voyage_3_large campo as strings de conflito especificadas como incorporações vetoriais no queryVector campo da query. A consulta usa o voyage-3-large modelo de incorporação da Voyage AI, que é o mesmo modelo usado para as incorporações no plot_embedding_voyage_3_large campo. A consulta também especifica uma pesquisa para 100 até vizinhos mais próximos e limita os resultados 20 somente para documentos. Este estágio retorna os documentos pontuados da pesquisa semântica.

fullTextPipeline

O pipeline contém os seguintes estágios:

$search para pesquisar filmes que contenham o termo star wars no title campo. Este estágio retorna os documentos pontuados da pesquisa de texto completo.
$limit para limitar a saída do estágio $search a apenas 20 resultados.

A query de exemplo usa os seguintes estágios para retornar os resultados da pesquisa semântica e de texto como uma única lista de documentos com pontuação:

`$project`	Inclui somente os seguintes campos nos resultados: `_id` `title` `plot` `scoreDetails`
`$limit`	Limita a saída a apenas `10` resultados.

Voltar

Pesquisa híbrida

Pesquisa vetorial combinada

1	db.embedded_movies.createSearchIndex(
2	"hybrid-vector-search",
3	"vectorSearch",
4	{
5	"fields": [
6	{
7	"type": "vector",
8	"path": "plot_embedding_voyage_3_large",
9	"numDimensions": 2048,
10	"similarity": "dotProduct"
11	}
12	]
13	}
14	);

1	db.embedded_movies.createSearchIndex(
2	"hybrid-full-text-search",
3	"search",
4	{
5	"mappings": {
6	"dynamic": true
7	}
8	}
9	);

1	db.embedded_movies.aggregate([
2	{
3	$rankFusion: {
4	input: {
5	pipelines: {
6	vectorPipeline: [
7	{
8	"$vectorSearch": {
9	"index": "hybrid-vector-search",
10	"path": "plot_embedding_voyage_3_large",
11	"queryVector": STAR_WARS_EMBEDDING,
12	"numCandidates": 100,
13	"limit": 20
14	}
15	}
16	],
17	fullTextPipeline: [
18	{
19	"$search": {
20	"index": "hybrid-full-text-search",
21	"phrase": {
22	"query": "star wars",
23	"path": "title"
24	}
25	}
26	},
27	{ "$limit": 20 }
28	]
29	}
30	},
31	combination: {
32	weights: {
33	vectorPipeline: 0.5,
34	fullTextPipeline: 0.5
35	}
36	},
37	"scoreDetails": true
38	}
39	},
40	{
41	"$project": {
42	_id: 1,
43	title: 1,
44	plot: 1,
45	scoreDetails: {"$meta": "scoreDetails"}
46	}
47	},
48	{
49	"$limit": 10
50	}
51	]);

1	db.embedded_movies.aggregate( [
2	{
3	$scoreFusion: {
4	input: {
5	pipelines: {
6	searchOne: [
7	{
8	"$vectorSearch": {
9	"index": "hybrid-vector-search",
10	"path": "plot_embedding_voyage_3_large",
11	"queryVector": STAR_WARS_EMBEDDING,
12	"numCandidates": 100,
13	"limit": 20
14	}
15	}
16	],
17	searchTwo: [
18	{
19	"$search": {
20	"index": "hybrid-full-text-search",
21	"text": {
22	"query": "star wars",
23	"path": "title"
24	}
25	}
26	},
27	]
28	},
29	normalization: "sigmoid"
30	},
31	combination: {
32	method: "expression",
33	expression: {
34	$sum: [
35	{$multiply: [ "$$searchOne", 10]}, "$$searchTwo"
36	]
37	}
38	},
39	"scoreDetails": true
40	}
41	},
42	{
43	"$project": {
44	_id: 1,
45	title: 1,
46	plot: 1,
47	scoreDetails: {"$meta": "scoreDetails"}
48	}
49	},
50	{ $limit: 10 }
51	] )

Sobre o tutorial

Pré-requisitos

Crie os índices Vector Search do MongoDB e Search do MongoDB

Procedimento

Conecte-se ao cluster do Atlas usando mongosh.

Alterne para o banco de dados que contém a collection para a qual você deseja criar o índice.

Defina o índice do MongoDB Vector Search .

Defina o índice de pesquisa do MongoDB .

Execute uma query combinada de pesquisa semântica e pesquisa de texto completo usando $rankFusion

Procedimento

Configure as incorporações a serem usadas na consulta.

Conecte-se ao seu cluster usando o mongosh.

Use o banco de dados sample_mflix.

Carregue as incorporações para usar na query.

Execute as seguintes queries do MongoDB Search na embedded_movies collection.

Sobre a query

Pesos de query

Estágios de query

Execute uma query combinada de pesquisa semântica e pesquisa de texto completo usando $scoreFusion

Procedimento

Configure as incorporações a serem usadas na consulta.

Conecte-se ao seu cluster usando o mongosh.

Use o banco de dados sample_mflix.

Carregue as incorporações para usar na query.

Execute as seguintes queries do MongoDB Search na embedded_movies collection.

Sobre a query

Pesos de query

Observação

Estágios de query

Conecte-se ao cluster do Atlas usando `mongosh`.

Execute uma query combinada de pesquisa semântica e pesquisa de texto completo usando `$rankFusion`

Conecte-se ao seu cluster usando o `mongosh`.

Use o banco de dados `sample_mflix`.

Execute as seguintes queries do MongoDB Search na `embedded_movies` collection.

Execute uma query combinada de pesquisa semântica e pesquisa de texto completo usando `$scoreFusion`

Conecte-se ao seu cluster usando o `mongosh`.

Use o banco de dados `sample_mflix`.

Execute as seguintes queries do MongoDB Search na `embedded_movies` collection.