Você pode combinar queries do MongoDB Vector Search e do MongoDB Search em uma pesquisa híbrida para obter resultados unificados.
Este tutorial demonstra como executar uma pesquisa híbrida na coleção sample_mflix.embedded_movies, que contém detalhes sobre filmes. Especificamente, este tutorial orienta você pelas seguintes etapas:
Crie um índice de pesquisa vetorial MongoDB no campo
plot_embedding_voyage_4_large. Este campo contém embeddings de vetor (de 2048 dimensões criados usando o modelo de embeddingvoyage-4-largeda Voyage AI) que representam o resumo do enredo de um filme.Crie um índice de pesquisa do MongoDB na coleção
sample_mflix.embedded_movies.Execute uma query para combinar os resultados de uma query
$vectorSearche de uma query$searchusando as seguintes técnicas:Impulsionamento semântica
Fusão de classificação recíproca
Score Fusion
Por que pesquisa híbrida?
Uma pesquisa híbrida é uma agregação de diferentes métodos de pesquisa, como uma pesquisa de texto completo e semântica, para os mesmos critérios de 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.
Você pode aplicar as seguintes técnicas para realizar uma pesquisa híbrida:
Técnica | Impulsionamento semântica | Fusão de classificação recíproca | Fusão de pontuação relativa | |||
Propósito | Melhora a precisão dos resultados da pesquisa de texto completo, aumentando os documentos que correspondem à pesquisa vetorial. Útil ao recuperar conjuntos de resultados muito grandes. | Combina resultados de diferentes métodos de pesquisa em um único conjunto de resultados classificados calculando a classificação recíproca dos documentos nos resultados. | Combina resultados de diferentes métodos de pesquisa em um único conjunto de resultados classificados calculando a pontuação dos documentos nos resultados. | |||
Método de classificação |
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Método de pontuação | Aumenta a pontuação de resultados de texto completo para documentos que correspondem aos resultados da pesquisa vetorial pela pontuação ponderada da pesquisa vetorial. | Calcula a pontuação usando a seguinte fórmula: Em seguida, para cada método de pesquisa, aplique diferentes pesos ( | Calcula a pontuação usando a seguinte fórmula: | |||
Recursos de pesquisa |
| Suporta o processamento adicional de resultados em estágios de agregação subsequentes, como | Suporta o processamento adicional de resultados em estágios de agregação subsequentes, como | |||
Saída | Conjunto de resultados único que contém documentos de | Conjunto de resultados único que contém documentos de ambos os métodos de pesquisa. | Conjunto de resultados único que contém documentos de ambos os métodos de pesquisa. |
Pré-requisitos
Antes de começar, você deve ter o seguinte:
Um Atlas cluster com MongoDB versão v8.0 ou superior.
Observação
Certifique-se de que seu Atlas cluster tenha memória suficiente para armazenar índices do MongoDB Search e do MongoDB Vector Search e executar queries de alto desempenho.
Os dados sample_mflix carregados em seu Atlas cluster.
mongoshpara executar queries em seu Atlas cluster:Project Data Access Adminacesso ao projeto para criar índices do MongoDB Vector Search e do MongoDB 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 pesquisa vetorial no campo
plot_embedding_voyage_4_largepara executar query vetoriais nesse campo.Um índice do MongoDB Search que indexa dinamicamente todos os campos indexáveis dinamicamente para executar a pesquisa de texto completo nesses campos.
1
Conecte ao cluster utilizando mongosh.
Para saber mais, consulte Conectar-se a um cluster via mongosh.
2
3
Defina o índice do MongoDB Vector Search .
Execute o seguinte comando. Esta definição de índice indexa o campo plot_embedding_voyage_4_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_4_large", 9 "numDimensions": 2048, 10 "similarity": "dotProduct" 11 } 12 ] 13 } 14 );
Executar as query de pesquisa híbrida
Esta seção demonstra como consultar os dados na coleção sample_mflix.embedded_movies de charming animal nos campos plot_embedding_voyage_4_large e fullplot usando os estágios de pipeline $vectorSearch e $search, respectivamente. A query aprimora a relevância das queries $search aumentando as pontuações de texto completo usando pontuações $vectorSearch para os mesmos documentos.
Query de impulsionamento semântica
1
Crie o arquivo para as incorporações.
Crie um arquivo denominado
query-embeddings.js.touch query-embeddings.js Copie e cole as seguintes incorporações no arquivo.
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2
Conecte-se ao seu cluster usando 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.
3
Use o banco de dados sample_mflix.
Execute o seguinte comando no prompt mongosh:
use sample_mflix
switched to db sample_mflix
4
5
Execute as seguintes queries do MongoDB Search na coleção embedded_movies.
1 vectorWeight = 1; 2 vectorCutoff = 0.7; 3 numResults = 20; 4 numCandidates = numResults * 10; 5 6 // Execute the vector search 7 vectorResults = db.embedded_movies.aggregate([ 8 { 9 $vectorSearch: { 10 "index": "hybrid-vector-search", 11 "path": "plot_embedding_voyage_4_large", 12 "queryVector": CHARMING_ANIMAL_EMBEDDING, 13 "numCandidates": numCandidates, 14 "limit": numResults 15 } 16 }, 17 { 18 $project: { 19 "_id": 1, 20 "title": 1, 21 "fullplot": 1, 22 "vectorScore": { $meta: "vectorSearchScore" } 23 } 24 }, 25 { 26 $match: { 27 "vectorScore": { $gte: vectorCutoff } 28 } 29 } 30 ]).toArray(); 31 32 // Create a map for fast lookup 33 vectorScoresMap = {}; 34 vectorResults.forEach(result => { 35 vectorScoresMap[result._id] = result.vectorScore * vectorWeight; 36 }); 37 38 // Execute the text search with boosting based just on ID 39 textResults = db.embedded_movies.aggregate([ 40 { 41 $search: { 42 "index": "hybrid-full-text-search", 43 "compound": { 44 "should": [ 45 { 46 "text": { 47 "query": "charming animal", 48 "path": "fullplot", 49 "fuzzy": {} 50 } 51 }, 52 ...Object.keys(vectorScoresMap).map(id => ({ 53 "equals": { 54 "path": "_id", 55 "value": id, 56 "score": { boost: { value: vectorScoresMap[id] } } 57 } 58 })) 59 ] 60 } 61 } 62 }, 63 { 64 $limit: 20 65 }, 66 { 67 $project: { 68 "_id": 1, 69 "title": 1, 70 "fullplot": 1, 71 "score": { $meta: "searchScore" } 72 } 73 } 74 ]).toArray();
[ { _id: ObjectId('573a13a3f29313caabd0d0a8'), fullplot: "Dr. John Dolittle the beloved doctor is back, but this time around he plays cupid to bumbling circus bear Archie as he's so smitten by a Pacific Western bear female, Ava. Dr. Dolittle must help a group of forest creatures to save their forest. But with the aid of his mangy, madcap animal friends, Dr. Dolittle must teach Archie the ways of true romance in time to save his species and his home before their habit is gone. So John held a meeting for every animal in the forest to not give up without a fight no matter what kind of animal expression they have and everyone agrees to do it and save their home.", title: 'Dr. Dolittle 2', score: 3.2186570167541504 }, { _id: ObjectId('573a13c5f29313caabd71215'), title: 'The Bannen Way', fullplot: 'A slick, sexy, action-packed show about Neal Bannen, a charming con-man with a police chief for a father, a mob boss for an uncle and a weakness for beautiful women, who wants to turn his life around and leave the criminal lifestyle forever.', score: 3.066267967224121 }, { _id: ObjectId('573a1394f29313caabce074d'), title: 'Perri', fullplot: 'This True Life Fantasy follows and shows how the life of a female squirrel, Perri, in the forest is filled with danger and fraught with peril. When not fleeing her natural enemy, the Marten, Perri finds time to fall in love with her prince-charming male squirrel.', score: 3.0323688983917236 }, { _id: ObjectId('573a139af29313caabcf0e1d'), title: 'Wild America', fullplot: 'Three brothers - Marshall, Marty and Mark dream of becoming naturalists and portraying animal life of America. One summer their dream comes true, they travel through America, filming alligators, bears and moose.', score: 2.9388742446899414 }, { _id: ObjectId('573a13e3f29313caabdc08f2'), title: 'Bang Bang', fullplot: "A chance encounter of the unassuming bank receptionist Harleen Sahni with the charming yet mysterious Rajveer Nanda, results in an on-rush of ditched planes, car chases, shoot-outs, bombing raids and general global mayhem. But as the transcontinental chase ensues with Rajveer convincing Harleen that he's the good guy, can she really trust him, and will trust matter when the bullets start flying?", score: 2.7579541206359863 }, { _id: ObjectId('573a1393f29313caabcdbe7c'), fullplot: "In this charming film based on the popular L. Frank Baum stories, Dorothy and her dog Toto are caught in a tornado's path and somehow end up in the land of Oz. Here she meets some memorable friends and foes in her journey to meet the Wizard of Oz who everyone says can help her return home and possibly grant her new friends their goals of a brain, heart and courage.", title: 'The Wizard of Oz', score: 2.703585147857666 }, { _id: ObjectId('573a1397f29313caabce80f6'), title: 'Gauche the Cellist', fullplot: 'A cellist in a small orchestra receives help from animals to help him practice his music.', score: 2.692498207092285 }, { _id: ObjectId('573a13bcf29313caabd55f51'), title: 'The Missing Lynx', fullplot: "A group of animals look for a way off of an eccentric billionaire's own personal Noah's Ark.", score: 2.6747734546661377 }, { _id: ObjectId('573a1397f29313caabce8aac'), title: 'The Grey Fox', fullplot: `Old West highwayman Bill Miner, known to Pinkertons as "The Gentleman Bandit," is released in 1901 after 33 years in prison, a genial and charming old man. He goes to Washington to live and work with his sister's family. But the world has changed much while he has been away, and he just can't adjust. So he goes to Canada and returns to the only thing familiar to him -- robbery (with stagecoaches changed to trains).`, score: 2.651318073272705 }, { _id: ObjectId('573a13c7f29313caabd75624'), fullplot: 'Extraordinary teen John Smith (Pettyfer) is a fugitive on the run from ruthless enemies sent to destroy him. Changing his identity, moving from town to town with his guardian Henri (Olyphant), John is always the new kid with no ties to his past. In the small Ohio town he now calls home, John encounters unexpected, life-changing events-his first love (Agron), powerful new abilities and a connection to the others who share his incredible destiny.', title: 'I Am Number Four', score: 2.6149134635925293 }, { _id: ObjectId('573a1392f29313caabcdb48b'), title: 'Snow White and the Seven Dwarfs', fullplot: 'The first, and by far most memorable full-length animated feature from the Disney Studios, "Snow White and the Seven Dwarfs" may have been superseded technically by many of the films that followed it. But its simple story of a charming little princess saved from the evil deeds of her wicked stepmother, the queen, by a group of seven adorable dwarfs made history when it was first released in December, 1937 and has since become an incomparable screen classic.', score: 2.6010334491729736 }, { _id: ObjectId('573a13b4f29313caabd4070d'), title: 'Paragraph 78', fullplot: 'This is a wonderful movie about a group of men frontier the Nashville area who like to make puppets out of real animals', score: 2.573139190673828 }, { _id: ObjectId('573a1393f29313caabcdc6e9'), title: 'Tom Dick and Harry', fullplot: "Working girl/telephone operator Janie is engaged to conservative, dull, but very reliable car salesman Tom, who offers her a safe, stable marriage. Then she meets unconventional slacker Harry, a philosophical car mechanic without much ambition although she does hear bells when they kiss. Through Harry, the fickle Janie meets Dick, a handsome and charming millionaire playboy, who embodies her greatest romantic fantasies, and after a champagne-filled overnight flight to Chicago, she thinks she's met her dream man, but has she?", score: 2.5526208877563477 }, { _id: ObjectId('573a13acf29313caabd28039'), title: 'The Science of Sleep', fullplot: 'Following the death of his father in Mexico, Stèphane Miroux, a shy insecure young man, agrees to come to Paris to draw closer to his widowed mother Christine. He lands a boring job at a calendar-making firm and falls in love with his charming neighbor Stèphanie. But conquering her is no bed of roses for the young man and the only solution he finds to put up with the difficulties he is going through is escape into a dream world...', score: 2.5526208877563477 }, { _id: ObjectId('573a13b3f29313caabd3b4e1'), fullplot: `Manny the woolly mammoth, Sid the sloth, Diego the saber-toothed tiger, and the hapless prehistoric squirrel/rat known as Scrat are still together and enjoying the perks of their now melting world. Manny may be ready to start a family, but nobody has seen another mammoth for a long time; Manny thinks he may be the last one. That is, until he miraculously finds Ellie, the only female mammoth left in the world. Their only problems: They can't stand each other--and Ellie somehow thinks she's a possum! Ellie comes with some excess baggage in the form of her two possum "brothers"-- Crash and Eddie, a couple of daredevil pranksters and cocky, loud-mouthed troublemakers. Manny, Sid and Diego quickly learn that the warming climate has one major drawback: A huge glacial dam holding off oceans of water is about to break, threatening the entire valley. The only chance of survival lies at the other end of the valley. So our three heroes, along with Ellie, Crash and Eddie, form the most unlikely family--in any "Age"-- as they embark on a mission across an ever-changing, increasingly dangerous landscape towards their salvation.`, title: 'Ice Age: The Meltdown', score: 2.518824338912964 }, { _id: ObjectId('573a1395f29313caabce1b5f'), title: 'Hatari!', fullplot: `John Wayne and his ensemble cast cavort over the African landscape filling orders from zoos for wild animals. Bruce Cabot plays "the Indian", a womanizing sharpshooter who is gored by a rhino in the opening scenes of the film. This becomes a running theme through the movie; their bad luck in catching rhinos, and provides the climactic ending chase. While Bruce is in the hospital, Elsa Martinelli shows up as a woman photographer from a Swiss zoo, and John wants to send her packing. She strongarms the Duke into letting her stay by promising that her zoo will buy most of their animals this season if she's allowed to go along on the hunts and take photos. Hardy Kruger, Gerard Blain, Michelle Girardon and Valentin de Vargas round out the group. They traipse over the African landscape capturing animals; Elsa also has a running gag where she collects baby elephants as the movie goes along. In the end she's acquired three of them.`, score: 2.4652297496795654 }, { _id: ObjectId('573a13c5f29313caabd6e7a4'), title: 'Merantau', fullplot: `In Minangkabau, West Sumatera, Yuda a skilled practitioner of Silat Harimau is in the final preparations to begin his "Merantau" a century's old rites-of-passage to be carried out by the community's young men that will see him leave the comforts of his idyllic farming village and make a name for himself in the bustling city of Jakarta. After a series of setbacks leave Yuda homeless and uncertain about his new future, a chance encounter results in him defending the orphaned Astri from becoming the latest victim of a European human trafficking ring led by the wildly psychotic, Ratger and his right-hand man Lars. With Ratger injured in the mèlèe and seeking both his "merchandise" and bloody retribution, Yuda's introduction to this bustling city is a baptism of fire as he is forced to go on the run with Astri and her younger brother Adit as all the pimps and gangsters that inhabit the night hound the streets chasing their every step. With escape seemingly beyond their grasp, Yuda has no choice but to face his attackers in an adrenaline charged, jaw-dropping finale.`, score: 2.4573898315429688 }, { _id: ObjectId('573a1398f29313caabceaddd'), title: 'Dead Heat', fullplot: 'Roger Mortis and Doug Bigelow are cops that are chasing crooks that are dead serious about crime. Or should I say they are chasing dead crooks perpetrating serious crimes? Seems some nutcase has learned how to bring back the dead and is sending them on crime sprees. Now these indestructable goons are in the way of officers Mortis and Bigelow. To even things up, when Mortis is killed (in the line of duty, of course) he gets a jump start from the Resurrection machine and takes the fight to the zombie bad guys.', score: 2.398913860321045 }, { _id: ObjectId('573a1393f29313caabcde3af'), title: 'Mighty Joe Young', fullplot: `In Africa, the girl Jill Young trades a baby gorilla with two natives and raises the animal. Twelve years later, the talkative and persuasive promoter Max O'Hara organizes a safari to Africa with the Oklahoma cowboy Gregg to bring attractions to his new night-club in Hollywood. They capture several lions and out of blue, they see a huge gorilla nearby their camping and they try to capture the animal. However, the teenager Jill Young stops the men that intended to kill her gorilla. Max seduces Jill with a fancy life in Hollywood and she signs a contract with him where the gorilla Joseph "Joe" Young would be the lead attraction. Soon she realizes that her dream is a nightmare to Joe and she asks Max to return to Africa. However he persuades her to stay a little longer in the show business. But when three alcoholic costumers give booze to Joe, the gorilla destroys the spot and is sentenced by the justice to be sacrificed. Will Jill, Gregg and Max succeed in saving Joe?`, score: 2.3978404998779297 }, { _id: ObjectId('573a13c7f29313caabd75592'), fullplot: 'FBI agent Malcolm Turner and his son, Trent, go undercover at an all-girls performing arts school after Trent witnesses a murder. Posing as Big Momma and Charmaine, they must find the murderer before he finds them.', title: 'Big Mommas: Like Father, Like Son', score: 2.3933444023132324 } ]
Sobre a query
A query de amostra aumenta os $search resultados com base nas $vectorSearch pontuações de resultados para retornar os documentos mais relevantes. Para o aumento semântica, você executa as seguintes etapas:
Execute a consulta
$vectorSearch.Use um valor acima do solicitado para especificar o número de candidatos a mais do que o limite especificado a ser considerado. A solicitação over permite que você realize o seguinte:
Inclua um grande número e um amplo repositório de documentos a serem considerados na pesquisa inicial.
Refine a computação de pontuação nos estágios subsequentes.
A query usa o seguinte cálculo para determinar o número de candidatos a considerar durante a pesquisa vetorial:
numCandidates = limit * over request Os resultados são filtrados com base em um limite de pontuação mínima (
vectorCutoff).Escale a pontuação da pesquisa vetorial para ajustar a influencia dos resultados da pesquisa vetorial na pontuação e na classificação de documentos.
Use o parâmetro
vectorWeightpara definir o peso e multiplicar as pontuações da pesquisa vetorial pelovectorWeight. Isso controla a importância dos resultados da pesquisa vetorial e garante que somente os documentos mais semanticamente relevantes sejam considerados.Execute a
$searchquery e aumente a pontuação dos documentos que correspondem aos resultados da pesquisa vetorial.
A query de amostra define as seguintes variáveis:
vectorWeightpara adicionar peso à pontuação do vetor de pesquisa, com um número menor fornecendo maior peso.vectorCutoffpara definir a pontuação mínima do vetor para que o resultado seja impulsionado.numResultspara especificar o número desejado de resultados de pesquisanumCandidatespara calcular o número de candidatos a considerar durante a pesquisa inicial. Ele calcula o número de candidatos usando a seguinte fórmula:numCandidates = numResults x overRequestFactor
A query de exemplo usa os seguintes estágios do pipeline para realizar uma pesquisa semântica na coleção e recuperar a classificação recíproca dos documentos nos resultados:
Pesquisa no campo | |
Pesquisa filmes que contenham o termo charming animal no campo fullplot. Para os documentos nos resultados que correspondem ao |
Query de fusão de classificação recíproca
Você pode executar uma query que 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. Para saber mais sobre a técnica de fusão de classificação recíproca e como executar uma query de fusão de classificação recíproca, consulte Executar pesquisa vetorial híbrida e pesquisa de texto completo.
Query de fusão de pontuação relativa
Você pode executar uma query que 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 dos pipelines em uma única pontuação agregada para cada documento. Para saber mais sobre a técnica de fusão de pontuação e como executar uma query de fusão de pontuação, consulte Executar pesquisa híbrida vetorial e de texto completo.