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ネイティブ 再ランク付けを始める

重要

ネイティブ 再ランク付けはプレビュー機能として利用できます。機能および関連するドキュメントは、プレビュー期間中にいつでも変更される可能性があります。したがって、本番環境でこの機能を使用することは推奨されません。現時点では、この機能のカスタマーデータは使用してモデルを訓練することはありません。詳しくは、「 プレビュー機能 」を参照してください。

$rerank集計ステージでは、Voyage AI再ランク付けモデルを使用して入力ドキュメントの順序付けを行い、クエリへの関連性でソートされた同じドキュメントを返します。 $rerankステージは集計パイプラインのどこにでも表示できます。

$rerank クエリを実行するためにインデックスを作成する必要はありません。ただし、 MongoDB、コレクションにMongoDB ベクトル検索またはMongoDB Searchインデックスを作成する必要がある $vectorSearch$search$rankFusion、または $scoreFusion ステージの後に $rerank を使用することを推奨しています。

このクイックスタートでは、 sample_mflix$rerank データセットに対するクエリで 集計ステージを使用して、Atlas でネイティブ 再ランク付けを有効にして使用する方法を示します。

始める前に、次のタスクを完了してください。

の使用に関する互換性と要件の詳細については、「$rerank 考慮事項 」を参照してください。

ネイティブ 再ランク付けを開始するには、次の手順に従います。

1
  1. まだ表示されていない場合は、希望するプロジェクトを含む組織を選択しますナビゲーション バーのOrganizationsメニュー

  2. まだ表示されていない場合は、ナビゲーション バーのProjectsメニューから目的のプロジェクトを選択します。

  3. サイドバーで、 アイコンを Project Overview の横にあるをクリックします。

[ Project Settings ]ページが表示されます。

  1. [Native Reranking] セクションまで下にスクロールし、Enable Native RerankingOn に切り替えます。

  2. [Confirm] をクリックします。

2

次のクエリでは、$rerank ステージを使用して、マーシャルのクエリに最も関連する上位 10 行の映画を検索します。

  1. sample_mflixデータベースに切り替えます。

    use sample_mflix
  2. ネイティブ 再ランク付け クエリを実行します。

    次のクエリは、 $rerankステージを使用して、rerank-2.5 モデルを使用してパフォーマンス のクエリに最も関連する映画を返します。クエリは、マーシャリングの訓練とイベントに関する映画を優先します。次のパイプラインステージを使用します。

    パイプラインステージ
    説明

    ドキュメントをフィルタリングして、fullplotフィールドが string 型のドキュメントのみを含めます。

    ドキュメントを releasedフィールドの降順で並べ替え、確実に順序付けます。

    rerank-2.5 リランク モデルを使用して、クエリに一致するようにドキュメントを並べ替えます。 numDocsToRerank パラメーターは、再ランク付けを考慮するドキュメントの最大数を指定します。 path パラメーターは、再ランク付けに使用するフィールドを指定します。

    ドキュメントに rerankScore という名前のフィールドを追加します。

    出力を10ドキュメントに制限します。

    結果のドキュメントから、titlefullplotrerankScore 以外のすべてのフィールドを除外します。

    1db.embedded_movies.aggregate([
    2 {
    3 "$match": {
    4 "fullplot": { "$exists": true, "$type": "string" }
    5 }
    6 },
    7 {
    8 "$sort": { "released": -1 }
    9 },
    10 {
    11 "$rerank": {
    12 "model": "rerank-2.5",
    13 "query": {
    14 "text": "martial arts; prioritize films about martial arts training and tournaments"
    15 },
    16 "path": "fullplot",
    17 "numDocsToRerank": 100
    18 }
    19 },
    20 {
    21 "$addFields": {
    22 "rerankScore": { "$meta": "score" }
    23 }
    24 },
    25 { "$limit": 10 },
    26 {
    27 "$project": {
    28 "_id": 0,
    29 "title": 1,
    30 "fullplot": 1,
    31 "rerankScore": 1
    32 }
    33 }
    34])
    [
    {
    title: 'Ti mene nosis',
    fullplot: 'No treason, no surrender.',
    rerankScore: 0.5986876487731934
    },
    {
    title: 'The Real Miyagi',
    fullplot: 'The life of the greatest karate master of a generation.',
    rerankScore: 0.5986876487731934
    },
    {
    title: 'Peter Pan Live!',
    fullplot: 'A live telecast of the beloved J. M. Barrie story.',
    rerankScore: 0.5986876487731934
    },
    {
    title: "Why Don't You Play in Hell?",
    fullplot: 'A renegade film crew becomes embroiled with a yakuza clan feud.',
    rerankScore: 0.5986876487731934
    },
    {
    fullplot: "A French police magistrate spends years trying to take down one of the country's most powerful drug rings.",
    title: 'The Connection',
    rerankScore: 0.5986876487731934
    },
    {
    title: 'Anomalisa',
    fullplot: "Charlie Kaufman's first stop-motion film about a man crippled by the mundanity of his life.",
    rerankScore: 0.5986876487731934
    },
    {
    title: 'The Master Plan',
    fullplot: 'Charles Ingvar Jènsson gathers three criminals to take vengeance upon the people who killed his uncle.',
    rerankScore: 0.5986876487731934
    },
    {
    title: 'Redeemer',
    fullplot: 'A former hit-man for a drug cartel becomes a vigilante to pay for his sins and find redemption.',
    rerankScore: 0.5986876487731934
    },
    {
    title: 'Rise of the Legend',
    fullplot: 'An orphan, whose father has been killed by dark power, attempts to bring justice back to the town.',
    rerankScore: 0.5986876487731934
    },
    {
    title: 'Darkness on the Edge of Town',
    fullplot: 'A troubled teenage sharpshooter decides to avenge the death of her estranged sister after she is found murdered in a public bathroom.',
    rerankScore: 0.5986876487731934
    }
    ]
3

MongoDB、$rerank $vectorSearch$search、 、$rankFusion 、または$scoreFusion ステージの後に を使用することを推奨しています。そのためには、コレクションにMongoDB ベクトル検索とMongoDB Searchインデックスを作成して、 ステージと$vectorSearch $searchステージを実行します。

$vectorSearch$searchこのクイックスタートの ステージと ステージを使用するサンプルクエリを試すには、コレクションにMongoDB ベクトル検索とMongoDB Searchインデックスを作成する必要があります。

プロット_埋め込み_ストレージ_4_LargeフィールドにMongoDB ベクトル検索インデックスを作成します。

インデックスを作成するには、以下の手順を実行します。

  1. サイドバーの Search & Vector Search をクリックします。

  2. [Create Index] をクリックします。

  3. インデックス構成を開始します。

    • インデックスタイプとして Vector Search を選択します。

    • インデックスの名前として「vector_index」と入力します。

    • sample_mflix.embedded_movies コレクションを選択します。

    • エディターのタイプとして JSON Editor を選択します。

  4. Next をクリックし、 JSONエディターに次のインデックス定義を貼り付けます。

    ``plot_ embedded_voice_4_Large``フィールドのインデックス。
    {
    "fields": [
    {
    "type": "vector",
    "path": "plot_embedding_voyage_4_large",
    "numDimensions": 2048,
    "similarity": "dotProduct"
    }
    ]
    }
  5. [Next をクリックし、[Create Index] をクリックします。

``fillプロット``フィールドにMongoDB Searchインデックスを作成します。

インデックスを作成するには、以下の手順を実行します。

  1. サイドバーの Search & Vector Search をクリックします。

  2. [Create Index] をクリックします。

  3. インデックス構成を開始します。

    • インデックスタイプとして Search を選択します。

    • インデックスの名前として「search_index」と入力します。

    • sample_mflix.embedded_movies コレクションを選択します。

    • エディターのタイプとして JSON Editor を選択します。

  4. Next をクリックし、 JSONエディターに次のインデックス定義を貼り付けます。

    動的にインデックス付け可能なフィールドの 動的インデックス 。
    {
    "mappings": {
    "dynamic": true
    }
    }
  5. [Next をクリックし、[Create Index] をクリックします。

4
  1. mongoshを使用してクラスターに接続します。

  2. クエリで使用する埋め込みを保存するには、embeddings.js という名前のファイルを作成します。

  3. 次の埋め込みをコピーしてファイルに貼り付けます。

    クエリタームの埋め込み。
    MARTIAL_ARTS_EMBEDDINGS=[0.02218237891793251, -0.007462590467184782, -0.01691064052283764, 0.0072914301417768, -0.011365045793354511, -0.045186325907707214, -6.846413452876732e-05, -0.0034916705917567015, 0.009995763190090656, 0.025742514058947563, -0.002481824718415737, -0.0029268416110426188, 0.0023106643930077553, -0.04135233536362648, -0.019717669114470482, -0.024510158225893974, -0.008729176595807076, -0.001048356993123889, 0.01033808384090662, 0.008900336921215057, -0.00797607097774744, 0.03258892521262169, 0.00766798248514533, 0.010406548157334328, 0.04107847809791565, -0.020128455013036728, -0.03833991289138794, 0.018348386511206627, -0.01533596497029066, 0.042995475232601166, 0.020813096314668655, -0.0016260230913758278, -0.004364588297903538, -0.011159653775393963, -0.03436899557709694, 0.010817333124577999, -0.0008900337270461023, -0.012118151411414146, -0.0156782865524292, 0.04381704330444336, -0.013350505381822586, 0.003851107321679592, -0.00010537057823967189, 0.011638902127742767, -0.002978189615532756, 0.019033027812838554, 0.006675252690911293, -0.013624361716210842, -0.03806605562567711, -0.003936687484383583, -0.029028791934251785, -0.025742514058947563, 0.023962445557117462, 0.010611940175294876, -0.005614058580249548, -0.009584978222846985, -0.012049687094986439, -0.0004000872722826898, 0.015815213322639465, 0.0032006981782615185, -0.03505363687872887, -0.009448050521314144, -0.0468294657766819, -0.002892609452828765, -0.029439575970172882, -0.012734328396618366, 0.0030124217737466097, 0.001891321619041264, -0.00422766013070941, -0.001283702440559864, -0.0006332932389341295, 0.011433510109782219, -0.01622599922120571, 0.03409513831138611, -0.011228117160499096, -0.04354318603873253, 0.00015083503967616707, 0.018759172409772873, 0.012528936378657818, -0.0176637452095747, 0.016089070588350296, -0.03067192994058132, -0.0005776660982519388, -0.013418969698250294, 0.009653442539274693, 0.03039807453751564, -0.008181463927030563, 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-0.007907606661319733, -0.005956379231065512, 0.026016369462013245, -0.013145113363862038, -0.026564082130789757, 0.007325661834329367, -0.04135233536362648, 0.02368859015405178, 0.0036457150708884, -0.036970630288124084, -0.06107000634074211, 0.005271737929433584, 0.013761290349066257, 0.01615753397345543, 0.009653442539274693, 0.024784015491604805, 0.029028791934251785, -0.002516056876629591, 0.02190852165222168, 0.016773711889982224, -0.026701010763645172, 0.023003948852419853, 0.00398803548887372, 0.019854597747325897, -0.012871257029473782, -0.005442898254841566, -0.005819451063871384, 0.009653442539274693, -0.02218237891793251, 0.008968801237642765, -0.0291657205671072, -0.0176637452095747, -0.021497737616300583, 0.0002513917279429734, 0.007736446801573038, -0.0043474724516272545, 0.0046213287860155106, 0.014719787985086441, 0.010064227506518364, -0.04710332304239273, 0.03217814117670059, -0.028070293366909027, -0.006743717007339001, -0.010269619524478912, 0.010132691822946072, 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  4. sample_mflixデータベースに切り替えます。

    use sample_mflix
  5. 埋め込みをmongosh にロードします。

    load('embeddings.js');
5

次のクエリでは、$rerank ステージと ステージの後に$vectorSearch $searchステージを使用して、プロモーダルのクエリに最も関連する上位 10 行の映画を検索します。

$vectorSearch の後に $rerank を実行します。

次のクエリでは、$vectorSearch ステージを使用して、アクションのクエリに最も関連する映画を一致させます。次に、クエリは ステージを使用してドキュメントの順序を変更し、Compass$rerank のスタイルと照合に焦点を当てます。次のパイプラインステージを使用します。

パイプラインステージ
説明

埋め込みモデルを使用して、クエリ テキスト パフォーマンス パフォーマンスのベクトル検索を実行します。 voyage-4-largenumCandidatesパラメーターは、再ランク付けを考慮するドキュメントの最大数を指定します。

結果のドキュメントから、titlefullplotvectorScore 以外のすべてのフィールドを除外します。

ドキュメントをフィルタリングして、fullplotフィールドが string 型のドキュメントのみを含めます。

rerank-2.5 リランク モデルを使用して、クエリに一致するようにドキュメントを並べ替えます。 numDocsToRerank パラメーターは、再ランク付けするドキュメントの最大数を指定します。 path パラメーターは、再ランク付けに使用するフィールドを指定します。

ドキュメントに rerankScore という名前のフィールドを追加します。

出力を10ドキュメントに制限します。

結果のドキュメントから、titlefullplotrerankScore 以外のすべてのフィールドを除外します。

1db.embedded_movies.aggregate([
2 {
3 "$vectorSearch": {
4 "index": "vector_index",
5 "path": "plot_embedding_voyage_4_large",
6 "queryVector": MARTIAL_ARTS_EMBEDDINGS,
7 "numCandidates": 100,
8 "limit": 100
9 }
10 },
11 {
12 "$project": {
13 "_id": 0,
14 "title": 1,
15 "fullplot": 1,
16 "vectorScore": { "$meta": "vectorSearchScore" }
17 }
18 },
19 {
20 "$match": {
21 "fullplot": { "$exists": true, "$type": "string" }
22 }
23 },
24 {
25 "$rerank": {
26 "model": "rerank-2.5",
27 "query": {
28 "text": "martial arts; focus on combat styles and fight choreography"
29 },
30 "path": "fullplot",
31 "numDocsToRerank": 100
32 }
33 },
34 {
35 "$addFields": {
36 "rerankScore": { "$meta": "score" }
37 }
38 },
39 { "$limit": 10 },
40 {
41 "$project": {
42 "_id": 0,
43 "title": 1,
44 "fullplot": 1,
45 "vectorScore": 1,
46 "rerankScore": 1
47 }
48 }
49])
[
{
title: 'The Real Miyagi',
fullplot: 'The life of the greatest karate master of a generation.',
vectorScore: 0.7579228281974792,
rerankScore: 0.5986876487731934
},
{
title: 'Kung Fu Killer',
fullplot: 'A Caucasian monk in Shanghai infiltrates the underworld to find the killers of his spiritual female Grandmaster.',
vectorScore: 0.7047170996665955,
rerankScore: 0.5986876487731934
},
{
title: 'Dragon Tiger Gate',
fullplot: 'Three young martial arts masters emerge from the back streets of Hong Kong to help the powerless fight injustice.',
vectorScore: 0.7224205732345581,
rerankScore: 0.5986876487731934
},
{
title: 'Pistol Opera',
fullplot: 'The No. 3 assassin of Japan is given the chance to usurp No. 1 and take their place.',
vectorScore: 0.6872181296348572,
rerankScore: 0.5986876487731934
},
{
title: 'Once Upon a Time in Shanghai',
fullplot: 'A laborer moves to Shanghai in the hope of becoming rich. But ends up using his kung fu skills to survive.',
vectorScore: 0.6834211349487305,
rerankScore: 0.5986876487731934
},
{
title: 'Yasmine',
fullplot: "A young woman who lives with her strict father works to become a a champion at Silat, Brunei's version of kung fu.",
vectorScore: 0.7219811677932739,
rerankScore: 0.5986876487731934
},
{
title: 'Best of the Best',
fullplot: 'Team USA gets rid of personal ghosts while fighting Team Korea in Taekwondo championship. "Adversity overcome" formula with excellent fighting scenes.',
vectorScore: 0.6988193988800049,
rerankScore: 0.5986876487731934
},
{
title: 'Dragon Strike',
fullplot: 'The adventures of a restless martial arts student called Dragon, who, while constantly pursuing a girl, gets involved in the affairs of a gang of thieves.',
vectorScore: 0.7163552641868591,
rerankScore: 0.5986876487731934
},
{
title: 'Legendary Weapons of China',
fullplot: "A band of killers from an ailing kung fu and magic society are sent on a manhunt for a former member of the society, whose bad mouthing threatens it's existence.",
vectorScore: 0.7019355893135071,
rerankScore: 0.5986876487731934
},
{
title: 'The Touch',
fullplot: 'A sister and brother, the last heirs of a family of acrobats, are called upon by a Buddhist monk sect to retrieve an artifact that their ancestors have protected throughout the ages.',
vectorScore: 0.6897575855255127,
rerankScore: 0.5986876487731934
}
]

$search の後に $rerank を実行します。

次のクエリは、$search ステージを使用して、クエリ テキスト $rerankパフォーマンス の全文検索を実行します。次に、クエリは ステージを使用してドキュメントの順序を変更し、プロットのプロットを優先します。次のパイプラインステージを使用します。

パイプラインステージ
説明

クエリ テキスト パフォーマンスの全文検索を実行します。

ステージの出力を$search 100ドキュメントに制限します。

結果のドキュメントから、titlefullplotsearchScore 以外のすべてのフィールドを除外します。

ドキュメントをフィルタリングして、fullplotフィールドが string 型のドキュメントのみを含めます。

rerank-2.5 リランク モデルを使用して、クエリに一致するようにドキュメントを並べ替えます。 numDocsToRerank パラメーターは、再ランク付けするドキュメントの最大数を指定します。 path パラメーターは、再ランク付けに使用するフィールドを指定します。

ドキュメントに rerankScore という名前のフィールドを追加します。

出力を10ドキュメントに制限します。

結果のドキュメントから、titlefullplotrerankScore 以外のすべてのフィールドを除外します。

1db.embedded_movies.aggregate([
2 {
3 "$search": {
4 "index": "search_index",
5 "text": {
6 "query": "martial arts",
7 "path": "fullplot"
8 }
9 }
10 },
11 {
12 "$limit": 100
13 },
14 {
15 "$project": {
16 "_id": 0,
17 "title": 1,
18 "fullplot": 1,
19 "searchScore": { "$meta": "searchScore" }
20 }
21 },
22 {
23 "$match": {
24 "fullplot": { "$exists": true, "$type": "string" }
25 }
26 },
27 {
28 "$rerank": {
29 "model": "rerank-2.5",
30 "query": {
31 "text": "martial arts; prioritize movie plots about martial arts competition and training"
32 },
33 "path": "fullplot",
34 "numDocsToRerank": 100
35 }
36 },
37 {
38 "$addFields": {
39 "rerankScore": { "$meta": "score" }
40 }
41 },
42 { "$limit": 10 },
43 {
44 "$project": {
45 "_id": 0,
46 "title": 1,
47 "fullplot": 1,
48 "searchScore": 1,
49 "rerankScore": 1
50 }
51 }
52])
[
{
title: 'Dragon Tiger Gate',
fullplot: 'Three young martial arts masters emerge from the back streets of Hong Kong to help the powerless fight injustice.',
searchScore: 5.30598258972168,
rerankScore: 0.5986876487731934
},
{
title: 'Dragon Strike',
fullplot: 'The adventures of a restless martial arts student called Dragon, who, while constantly pursuing a girl, gets involved in the affairs of a gang of thieves.',
searchScore: 5.074832439422607,
rerankScore: 0.5986876487731934
},
{
title: 'Here Comes the Boom',
fullplot: 'A high school biology teacher looks to become a successful mixed-martial arts fighter in an effort to raise money to prevent extra-curricular activities from being axed at his cash-strapped school.',
searchScore: 4.862981796264648,
rerankScore: 0.5986876487731934
},
{
title: 'Here Comes the Boom',
fullplot: 'A high school biology teacher looks to become a successful mixed-martial arts fighter in an effort to raise money to prevent extra-curricular activities from being axed at his cash-strapped school.',
searchScore: 4.862981796264648,
rerankScore: 0.5986876487731934
},
{
title: 'Vampire Effect',
fullplot: "It's a high-kicking battle on the dark side when an ace vampire slayer and his beautiful sidekicks wage the ultimate martial-arts showdown with one of the most dangerous of the undead.",
searchScore: 4.862981796264648,
rerankScore: 0.5986876487731934
},
{
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',
searchScore: 2.3932719230651855,
rerankScore: 0.5986876487731934
},
{
title: 'The Last Dragon',
fullplot: 'In New York City, a young man searches for the "master" to obtain the final level of martial arts mastery known as the glow. Along the way, he must fight an evil martial arts expert and rescue a beautiful singer from an obsessed music promoter.',
searchScore: 5.777412414550781,
rerankScore: 0.5986876487731934
},
{
title: 'SPL: Kill Zone',
fullplot: 'Chan, an articulate senior detective nearing the end of his career, is taking care of the daughter of a witness killed by ruthless crime lord Po. Martial arts expert Ma is set to take over as head of the crime unit, replacing Chan who wants an early retirement.',
searchScore: 4.463685035705566,
rerankScore: 0.5986876487731934
},
{
title: 'Fighter in the Wind',
fullplot: 'A young Korean man arrives in Japan near the end of World War II with hopes of being a fighter pilot, but ends up on the streets battling racism, organized crime, occupying American servicemen, and his own fear of failure as a martial artist. (Korean with English subtitles)',
searchScore: 2.2145204544067383,
rerankScore: 0.5986876487731934
},
{
title: "Bruce Lee: A Warrior's Journey",
fullplot: "Legendary martial artist Bruce Lee is the subject of this thoughtful documentary by Lee aficionado John Little. Using interviews, behind-the-scenes footage and action sequences from Lee's last (unfinished) film, Game of Death, Little paints a textured, complex portrait of the world's most famous action hero.",
searchScore: 2.2390332221984863,
rerankScore: 0.5986876487731934
}
]

ネイティブ 再ランク付けの詳細については、次のリソースを参照してください。