feat: add migrations, test scripts, and utility tools
- Add database migrations (006-028) for face recognition, identity, file_uuid - Add test scripts for ASR, face, search, processing - Add portal frontend (Tauri) - Add config, benchmark, and monitoring utilities - Add model checkpoints and pretrained model references
This commit is contained in:
Warren
227
test_search_comparison.rs
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227
test_search_comparison.rs
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use anyhow::{Context, Result};
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use momentry_core::core::db::{Database, PostgresDb, QdrantDb};
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use momentry_core::Embedder;
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use std::env;
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use std::time::Instant;
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#[derive(Debug)]
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struct SearchComparison {
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query: String,
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bm25_results: usize,
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qdrant_results: usize,
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bm25_top_score: f32,
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qdrant_top_score: f32,
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bm25_time_ms: u128,
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qdrant_time_ms: u128,
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overlap_count: usize,
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}
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fn print_results(
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query: &str,
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bm25_results: &[momentry_core::core::db::postgres_db::Bm25Result],
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qdrant_results: &[momentry_core::core::db::SearchResult],
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limit: usize,
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) {
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println!("\n=== 查詢: '{}' ===", query);
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println!(
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"BM25 結果 (共 {} 筆，顯示前 {} 筆):",
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bm25_results.len(),
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limit.min(bm25_results.len())
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);
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for (i, r) in bm25_results.iter().take(limit).enumerate() {
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println!(
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" {}. {} (uuid: {}, chunk_id: {})",
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i + 1,
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r.text.chars().take(60).collect::<String>(),
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r.uuid,
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r.chunk_id
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);
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println!(
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" 分數: {:.4}, 時間: {:.1}-{:.1}s, 類型: {}",
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r.bm25_score, r.start_time, r.end_time, r.chunk_type
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);
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}
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println!(
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"\nQdrant 向量搜尋結果 (共 {} 筆，顯示前 {} 筆):",
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qdrant_results.len(),
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limit.min(qdrant_results.len())
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);
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for (i, r) in qdrant_results.iter().take(limit).enumerate() {
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println!(" {}. uuid: {}, chunk_id: {}", i + 1, r.uuid, r.chunk_id);
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println!(" 分數: {:.4}", r.score);
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}
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// 計算重疊
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let bm25_ids: Vec<String> = bm25_results
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.iter()
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.map(|r| format!("{}-{}", r.uuid, r.chunk_id))
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.collect();
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let qdrant_ids: Vec<String> = qdrant_results
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.iter()
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.map(|r| format!("{}-{}", r.uuid, r.chunk_id))
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.collect();
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let overlap: Vec<&String> = bm25_ids
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.iter()
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.filter(|id| qdrant_ids.contains(id))
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.collect();
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println!(
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"\n結果重疊: {}/{} (BM25 與 Qdrant 共同返回)",
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overlap.len(),
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bm25_results.len().max(qdrant_results.len())
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);
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if !overlap.is_empty() {
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println!("重疊的 chunk IDs: {:?}", overlap);
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}
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}
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#[tokio::main]
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async fn main() -> Result<()> {
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// 設定環境變數
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env::set_var("RUST_LOG", "info");
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env::set_var("QDRANT_URL", "http://localhost:6333");
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env::set_var("QDRANT_API_KEY", "Test3200Test3200Test3200");
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env::set_var("QDRANT_COLLECTION", "momentry_rule1");
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println!("=== BM25 與 Qdrant 搜尋比較測試 ===\n");
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// 初始化元件
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println!("初始化元件...");
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let embedder = Embedder::new("nomic-embed-text-v2-moe:latest".to_string());
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let pg = PostgresDb::init()
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.await
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.context("Failed to initialize PostgreSQL database")?;
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let qdrant = QdrantDb::new();
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// 測試查詢清單
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let test_queries = vec![
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// 英文查詢
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("telephone", Some("384b0ff44aaaa1f1")), // Charade 電影
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("money", Some("384b0ff44aaaa1f1")),
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("gold", Some("384b0ff44aaaa1f1")),
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// 中文查詢
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("工作", Some("9760d0820f0cf9a7")), // ExaSAN 影片
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("加快速度", Some("9760d0820f0cf9a7")),
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("聲音", Some("9760d0820f0cf9a7")),
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// 全域查詢（無 uuid 限制）
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("computer", None),
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("technology", None),
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];
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let limit = 10;
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let mut comparisons = Vec::new();
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for (query_str, uuid_opt) in test_queries {
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let query = query_str.to_string();
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let uuid = uuid_opt.map(|s| s.to_string());
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println!(
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"\n🔍 測試查詢: '{}' {}",
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query,
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uuid_opt
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.map(|u| format!("(uuid: {})", u))
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.unwrap_or_default()
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);
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// BM25 搜尋
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let bm25_start = Instant::now();
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let bm25_results = pg.search_bm25(&query, uuid_opt, limit).await?;
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let bm25_time = bm25_start.elapsed();
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// Qdrant 向量搜尋
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let qdrant_start = Instant::now();
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let query_vector = embedder.embed_query(&query).await?;
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let qdrant_results = if let Some(ref uuid) = uuid {
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qdrant.search_in_uuid(&query_vector, uuid, limit).await?
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} else {
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qdrant.search(&query_vector, limit).await?
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};
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let qdrant_time = qdrant_start.elapsed();
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// 計算重疊
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let bm25_ids: Vec<String> = bm25_results
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.iter()
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.map(|r| format!("{}-{}", r.uuid, r.chunk_id))
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.collect();
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let qdrant_ids: Vec<String> = qdrant_results
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.iter()
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.map(|r| format!("{}-{}", r.uuid, r.chunk_id))
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.collect();
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let overlap_count = bm25_ids.iter().filter(|id| qdrant_ids.contains(id)).count();
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// 儲存比較結果
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let comparison = SearchComparison {
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query: query.clone(),
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bm25_results: bm25_results.len(),
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qdrant_results: qdrant_results.len(),
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bm25_top_score: bm25_results.first().map(|r| r.bm25_score).unwrap_or(0.0),
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qdrant_top_score: qdrant_results.first().map(|r| r.score).unwrap_or(0.0),
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bm25_time_ms: bm25_time.as_millis(),
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qdrant_time_ms: qdrant_time.as_millis(),
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overlap_count,
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};
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comparisons.push(comparison);
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// 顯示詳細結果
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print_results(&query, &bm25_results, &qdrant_results, 5);
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// 顯示效能比較
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println!("\n⏱️ 效能比較:");
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println!(" BM25 搜尋時間: {}ms", bm25_time.as_millis());
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println!(
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" Qdrant 搜尋時間: {}ms (含向量嵌入時間)",
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qdrant_time.as_millis()
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);
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}
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// 顯示總結比較表
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println!("\n📊 搜尋比較總結");
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println!(
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"{:<15} {:<6} {:<6} {:<8} {:<8} {:<6} {:<6} {:<6}",
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"查詢", "BM25數", "QD數", "BM25分", "QD分", "BM25ms", "QDms", "重疊"
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);
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println!("{}", "-".repeat(80));
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for comp in &comparisons {
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println!(
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"{:<15} {:<6} {:<6} {:<8.4} {:<8.4} {:<6} {:<6} {:<6}/{}",
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&comp.query[..15.min(comp.query.len())],
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comp.bm25_results,
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comp.qdrant_results,
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comp.bm25_top_score,
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comp.qdrant_top_score,
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comp.bm25_time_ms,
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comp.qdrant_time_ms,
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comp.overlap_count,
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comp.bm25_results.max(comp.qdrant_results)
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);
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}
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// 分析統計
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let total_queries = comparisons.len();
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let bm25_faster = comparisons
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.iter()
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.filter(|c| c.bm25_time_ms < c.qdrant_time_ms)
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.count();
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let avg_overlap = comparisons
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.iter()
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.map(|c| c.overlap_count as f32 / c.bm25_results.max(c.qdrant_results).max(1) as f32)
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.sum::<f32>()
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/ total_queries as f32
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* 100.0;
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println!("\n📈 統計分析:");
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println!(" • 總測試查詢數: {}", total_queries);
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println!(
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" • BM25 較快的查詢: {}/{} ({:.1}%)",
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bm25_faster,
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total_queries,
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bm25_faster as f32 / total_queries as f32 * 100.0
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);
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println!(" • 平均結果重疊率: {:.1}%", avg_overlap);
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Ok(())
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}
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