?? ? ? ?? ?? ???? ?? ??? ??(NLP) ? ?? ??? ??? ?????. ?? ??????? ??? ??? ???? ?? ?? ??(???)? ?? ???? "??"? ?????. ? ???? OpenAI ???, Go ? PostgreSQL? pgVector ??? ???? ?? ?? ?? ??? ??? ??? ?????.

????? ??????

???? ??? ???? ???(?? ?? ???)? ??? ???? ????. ? ??? ??? ??? ????? ?? ??? ? ???? ?? ??????. PostgreSQL(pgVector ??? ??)? ?? ??????? ???? ?????? ??? ??? ??? ???? ??? ? ????.

PostgreSQL? pgVector? ???? ??? ??????

pgVector? PostgreSQL? ?? ??? ??? ???? ?? ???? ?????. ?? ?? ??? ??? ? ????.

• ???? ?? ?? ??
• ?????? ??? ??? ?? ?? ??
• ?? SQL? ???? ?? ??

? ??

1. OpenAI? ??? API? ???? ?? ???? ?? ????? ?????.
2. PgVector ??? ???? PostgreSQL? ??? ???? ?????.
3. ???? ???? ???????? ??? ?? ??? ??? ????.

????

• ?????(1.19 ??).
• PostgreSQL? ???? ?? ????(?? ?? ???).
• PostgreSQL? pgVector ??? ?????. (?? ??? pgVector? GitHub ???? ?????.)
• ???? ??? OpenAI API ????.

?? ???? ?? postgres/pgVector ? Docker ?? ??? ??? Makefile???.

pgvector:
    @docker run -d \
        --name pgvector \
        -e POSTGRES_USER=admin \
        -e POSTGRES_PASSWORD=admin \
        -e POSTGRES_DB=vectordb \
        -v pgvector_data:/var/lib/postgresql/data \
        -p 5432:5432 \
        pgvector/pgvector:pg17
psql:
    @psql -h localhost -U admin -d vectordb

pgVector? ???? ??? ?????. ?? ?? PostgreSQL ????????:

CREATE EXTENSION IF NOT EXISTS vector;

?? ??

package main

import (
    "context"
    "fmt"
    "log"
    "os"
    "strings"

    "github.com/jackc/pgx/v5/pgxpool"
    "github.com/joho/godotenv"
    "github.com/sashabaranov/go-openai"
)

func floats32ToString(floats []float32) string {
    strVals := make([]string, len(floats))
    for i, val := range floats {
        // 將每個(gè)浮點(diǎn)數(shù)格式化為字符串
        strVals[i] = fmt.Sprintf("%f", val)
    }

    // 使用逗號(hào) + 空格連接它們
    joined := strings.Join(strVals, ", ")

    // pgvector 需要方括號(hào)表示法才能輸入向量，例如 [0.1, 0.2, 0.3]
    return "[" + joined + "]"
}

func main() {
    // 加載環(huán)境變量
    err := godotenv.Load()
    if err != nil {
        log.Fatal("加載 .env 文件出錯(cuò)")
    }

    // 創(chuàng)建連接池
    dbpool, err := pgxpool.New(context.Background(), os.Getenv("DATABASE_URL"))
    if err != nil {
        fmt.Fprintf(os.Stderr, "無(wú)法創(chuàng)建連接池：%v\n", err)
        os.Exit(1)
    }
    defer dbpool.Close()

    // 1. 確保已啟用 pgvector 擴(kuò)展
    _, err = dbpool.Exec(context.Background(), "CREATE EXTENSION IF NOT EXISTS vector;")
    if err != nil {
        log.Fatalf("創(chuàng)建擴(kuò)展失?。?v\n", err)
        os.Exit(1)
    }

    // 2. 創(chuàng)建表（如果不存在）
    createTableSQL := `
    CREATE TABLE IF NOT EXISTS documents (
        id SERIAL PRIMARY KEY,
        content TEXT,
        embedding vector(1536)
    );
    `
    _, err = dbpool.Exec(context.Background(), createTableSQL)
    if err != nil {
        log.Fatalf("創(chuàng)建表失?。?v\n", err)
    }

    // 3. 創(chuàng)建索引（如果不存在）
    createIndexSQL := `
    CREATE INDEX IF NOT EXISTS documents_embedding_idx
    ON documents USING ivfflat (embedding vector_l2_ops) WITH (lists = 100);
    `
    _, err = dbpool.Exec(context.Background(), createIndexSQL)
    if err != nil {
        log.Fatalf("創(chuàng)建索引失敗：%v\n", err)
    }

    // 4. 初始化 OpenAI 客戶(hù)端
    apiKey := os.Getenv("OPENAI_API_KEY")
    if apiKey == "" {
        log.Fatal("未設(shè)置 OPENAI_API_KEY")
    }
    openaiClient := openai.NewClient(apiKey)

    // 5. 插入示例文檔
    docs := []string{
        "PostgreSQL 是一個(gè)先進(jìn)的開(kāi)源關(guān)系數(shù)據(jù)庫(kù)。",
        "OpenAI 提供基于 GPT 的模型來(lái)生成文本嵌入。",
        "pgvector 允許將嵌入存儲(chǔ)在 Postgres 數(shù)據(jù)庫(kù)中。",
    }

    for _, doc := range docs {
        err = insertDocument(context.Background(), dbpool, openaiClient, doc)
        if err != nil {
            log.Printf("插入文檔“%s”失?。?v\n", doc, err)
        }
    }

    // 6. 查詢(xún)相似性
    queryText := "如何在 Postgres 中存儲(chǔ)嵌入？"
    similarDocs, err := searchSimilarDocuments(context.Background(), dbpool, openaiClient, queryText, 5)
    if err != nil {
        log.Fatalf("搜索失?。?v\n", err)
    }

    fmt.Println("=== 最相似的文檔 ===")
    for _, doc := range similarDocs {
        fmt.Printf("- %s\n", doc)
    }
}

// insertDocument 使用 OpenAI API 為 `content` 生成嵌入，并將其插入 documents 表中。
func insertDocument(ctx context.Context, dbpool *pgxpool.Pool, client *openai.Client, content string) error {
    // 1) 從 OpenAI 獲取嵌入
    embedResp, err := client.CreateEmbeddings(ctx, openai.EmbeddingRequest{
        Model: openai.AdaEmbeddingV2, // "text-embedding-ada-002"
        Input: []string{content},
    })
    if err != nil {
        return fmt.Errorf("CreateEmbeddings API 調(diào)用失敗：%w", err)
    }

    // 2) 將嵌入轉(zhuǎn)換為 pgvector 的方括號(hào)字符串
    embedding := embedResp.Data[0].Embedding // []float32
    embeddingStr := floats32ToString(embedding)

    // 3) 插入 PostgreSQL
    insertSQL := `
        INSERT INTO documents (content, embedding)
        VALUES (, ::vector)
    `
    _, err = dbpool.Exec(ctx, insertSQL, content, embeddingStr)
    if err != nil {
        return fmt.Errorf("插入文檔失?。?w", err)
    }

    return nil
}

// searchSimilarDocuments 獲取用戶(hù)查詢(xún)的嵌入，并根據(jù)向量相似性返回前 k 個(gè)相似的文檔。
func searchSimilarDocuments(ctx context.Context, pool *pgxpool.Pool, client *openai.Client, query string, k int) ([]string, error) {
    // 1) 通過(guò) OpenAI 獲取用戶(hù)查詢(xún)的嵌入
    embedResp, err := client.CreateEmbeddings(ctx, openai.EmbeddingRequest{
        Model: openai.AdaEmbeddingV2, // "text-embedding-ada-002"
        Input: []string{query},
    })
    if err != nil {
        return nil, fmt.Errorf("CreateEmbeddings API 調(diào)用失敗：%w", err)
    }

    // 2) 將 OpenAI 嵌入轉(zhuǎn)換為 pgvector 的方括號(hào)字符串格式
    queryEmbedding := embedResp.Data[0].Embedding // []float32
    queryEmbeddingStr := floats32ToString(queryEmbedding)
    // 例如 "[0.123456, 0.789012, ...]"

    // 3) 構(gòu)建按向量相似性排序的 SELECT 語(yǔ)句
    selectSQL := fmt.Sprintf(`
        SELECT content
        FROM documents
        ORDER BY embedding <-> '%s'::vector
        LIMIT %d;
    `, queryEmbeddingStr, k)

    // 4) 運(yùn)行查詢(xún)
    rows, err := pool.Query(ctx, selectSQL)
    if err != nil {
        return nil, fmt.Errorf("查詢(xún)文檔失?。?w", err)
    }
    defer rows.Close()

    // 5) 讀取匹配的文檔
    var contents []string
    for rows.Next() {
        var content string
        if err := rows.Scan(&content); err != nil {
            return nil, fmt.Errorf("掃描行失?。?w", err)
        }
        contents = append(contents, content)
    }
    if err = rows.Err(); err != nil {
        return nil, fmt.Errorf("行迭代錯(cuò)誤：%w", err)
    }

    return contents, nil
}

??

PostgreSQL, Go ? pgVector? OpenAI ???? ?? ?? ?? ?????? ??? ?? ??? ???? ?????. ???? ??? ???? ?????? ??? ?? ?????? ??? ???? ??? ?? ???? ??? ??? ?? ???? ?????.

? ??? ??? ??? ?? ???? ????, ???? ?? ??? ???, ???? ??? ??? ??? ?????. ??? ?? ???? ???? ???? ???????.

? ??? OpenAI, Go ? PostgreSQL? ???? ?? ?? ?? ?? ??(pgVector)? ?? ?????. ??? ??? PHP ??? ????? ?? ?? ??? ?????!