From 4a2cb914d75fb7542f2a757b6fbcc7e60d591434 Mon Sep 17 00:00:00 2001 From: yichuan520030910320 Date: Tue, 15 Jul 2025 22:30:52 -0700 Subject: [PATCH] clean dict --- README.md | 2 +- {tests => test}/sanity_checks/README.md | 0 .../sanity_checks/benchmark_embeddings.py | 0 .../sanity_checks/debug_zmq_issue.py | 0 tests/.DS_Store | Bin 6148 -> 0 bytes .../sanity_checks/test_distance_functions.py | 107 ---------- tests/sanity_checks/test_l2_verification.py | 127 ------------ tests/sanity_checks/test_sanity_check.py | 190 ------------------ 8 files changed, 1 insertion(+), 425 deletions(-) rename {tests => test}/sanity_checks/README.md (100%) rename {tests => test}/sanity_checks/benchmark_embeddings.py (100%) rename {tests => test}/sanity_checks/debug_zmq_issue.py (100%) delete mode 100644 tests/.DS_Store delete mode 100644 tests/sanity_checks/test_distance_functions.py delete mode 100644 tests/sanity_checks/test_l2_verification.py delete mode 100644 tests/sanity_checks/test_sanity_check.py diff --git a/README.md b/README.md index b6e6d2b..003b469 100755 --- a/README.md +++ b/README.md @@ -373,7 +373,7 @@ The script will print the recall and search time for each query, followed by the | System | DPR(2.1M docs) | RPJ-wiki(60M docs) | Chat history(5K messages) | | --------------------- | ---------------- | ---------------- | ---------------- | -| Traditional Vector DB | 3.8 GB | 201 GB | **22.8 MB** | +| Traditional Vector DB | 3.8 GB | 201 GB | 22.8 MB | | **LEANN** | **324 MB** | **6 GB** | **0.78 MB** | | **Reduction** | **91% smaller** | **97% smaller** | **97% smaller** | diff --git a/tests/sanity_checks/README.md b/test/sanity_checks/README.md similarity index 100% rename from tests/sanity_checks/README.md rename to test/sanity_checks/README.md diff --git a/tests/sanity_checks/benchmark_embeddings.py b/test/sanity_checks/benchmark_embeddings.py similarity index 100% rename from tests/sanity_checks/benchmark_embeddings.py rename to test/sanity_checks/benchmark_embeddings.py diff --git a/tests/sanity_checks/debug_zmq_issue.py b/test/sanity_checks/debug_zmq_issue.py similarity index 100% rename from tests/sanity_checks/debug_zmq_issue.py rename to test/sanity_checks/debug_zmq_issue.py diff --git a/tests/.DS_Store b/tests/.DS_Store deleted file mode 100644 index 18e12dd58701f994897ca1f154b1c231bbea3538..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 6148 zcmeHKOHKnZ41IIoRC;RHPZ&?%ybmZ?-&u$v=r3{Jt8J8%)UJjVug z#E8!ZA!JMOa}qo8JZX{`fQ)ZvBVY)iU{e$|dPIkNr?%XAK$N`34eoG)8grcYEc6$L zH1}PsafWMLVl)35S6DADMw7Z(t}ONX<#X?4Q&rPNGo@GY@c4Xixc7AQRmALv5v%!T zM)#Ij=wKii2nK?IVBq@<@Xl5#b__!Y1HnKr@Xmmq4~b2&bZiat(Lt3<0HQvlv(VOB zLSvF+>DU@_h9VY9v{3O9LoA%*$^A;l*3iNsUVMn}{8qe3-ks~G><%dnLk9!FK$n4S z>kjq)KjtsfTjX~`q8AJV1OJQx8B~*M%#ZTB^~2}sU7OfW*;Lf8Rf9si^9W!^&yoE+ dY4b^K`jw8Yp{}CiIh+^|flNrKVBi-Rcm= 0 for score in l2_scores): - print("✅ L2分数都是正数，符合预期") - else: - print("❌ L2分数有负数，可能有问题") - - if all(-1 <= score <= 0 for score in cos_scores): - print("✅ Cosine分数在合理范围内") - else: - print(f"⚠️ Cosine分数超出预期范围: {cos_scores}") - -if __name__ == "__main__": - test_l2_verification() \ No newline at end of file diff --git a/tests/sanity_checks/test_sanity_check.py b/tests/sanity_checks/test_sanity_check.py deleted file mode 100644 index 1c95b8c..0000000 --- a/tests/sanity_checks/test_sanity_check.py +++ /dev/null @@ -1,190 +0,0 @@ -#!/usr/bin/env python3 -""" -Sanity check script for Leann DiskANN backend -Tests different distance functions and embedding models -""" - -import os -import numpy as np -from pathlib import Path -import shutil -import time - -# 导入后端包以触发插件注册 -import sys -sys.path.append('packages/leann-core/src') -sys.path.append('packages/leann-backend-diskann') -sys.path.append('packages/leann-backend-hnsw') - -try: - import leann_backend_diskann - import leann_backend_hnsw - print("INFO: Backend packages imported successfully.") -except ImportError as e: - print(f"WARNING: Could not import backend packages. Error: {e}") - -# 从 leann-core 导入上层 API -from leann.api import LeannBuilder, LeannSearcher - -def test_distance_functions(): - """测试不同的距离函数""" - print("\n=== 测试不同距离函数 ===") - - # 测试数据 - documents = [ - "Machine learning is a powerful technology", - "Deep learning uses neural networks", - "Artificial intelligence transforms industries" - ] - - distance_functions = ["mips", "l2", "cosine"] - - for distance_func in distance_functions: - print(f"\n[测试 {distance_func} 距离函数]") - try: - index_path = f"test_indices/test_{distance_func}.diskann" - if Path(index_path).parent.exists(): - shutil.rmtree(Path(index_path).parent) - - # 构建索引 - builder = LeannBuilder( - backend_name="diskann", - distance_metric=distance_func, - graph_degree=16, - complexity=32 - ) - - for doc in documents: - builder.add_text(doc) - - builder.build_index(index_path) - - # 测试搜索 - searcher = LeannSearcher(index_path, distance_metric=distance_func) - results = searcher.search("neural network technology", top_k=2) - - print(f"✅ {distance_func} 距离函数工作正常") - for i, result in enumerate(results): - print(f" {i+1}. Score: {result['score']:.4f}, Text: {result['text'][:50]}...") - - except Exception as e: - print(f"❌ {distance_func} 距离函数失败: {e}") - -def test_embedding_models(): - """测试不同的embedding模型""" - print("\n=== 测试不同Embedding模型 ===") - - documents = ["AI is transforming the world", "Technology advances rapidly"] - - # 测试不同的embedding模型 - models_to_test = [ - "sentence-transformers/all-mpnet-base-v2", - "sentence-transformers/all-MiniLM-L6-v2", - # "sentence-transformers/distilbert-base-nli-mean-tokens", # 可能不存在 - ] - - for model_name in models_to_test: - print(f"\n[测试 {model_name}]") - try: - index_path = f"test_indices/test_model.diskann" - if Path(index_path).parent.exists(): - shutil.rmtree(Path(index_path).parent) - - # 构建索引 - builder = LeannBuilder( - backend_name="diskann", - embedding_model=model_name, - distance_metric="cosine" - ) - - for doc in documents: - builder.add_text(doc) - - builder.build_index(index_path) - - # 测试搜索 - searcher = LeannSearcher(index_path) - results = searcher.search("artificial intelligence", top_k=1) - - print(f"✅ {model_name} 模型工作正常") - print(f" 结果: {results[0]['text'][:50]}...") - - except Exception as e: - print(f"❌ {model_name} 模型失败: {e}") - -def test_search_correctness(): - """验证搜索结果的正确性""" - print("\n=== 验证搜索结果正确性 ===") - - # 创建有明确相关性的测试文档 - documents = [ - "Python is a programming language used for machine learning", # 与编程相关 - "Dogs are loyal pets that love to play fetch", # 与动物相关 - "Machine learning algorithms can predict future trends", # 与ML相关 - "Cats are independent animals that sleep a lot", # 与动物相关 - "Deep learning neural networks process complex data" # 与ML相关 - ] - - try: - index_path = "test_indices/correctness_test.diskann" - if Path(index_path).parent.exists(): - shutil.rmtree(Path(index_path).parent) - - # 构建索引 - builder = LeannBuilder( - backend_name="diskann", - distance_metric="cosine" - ) - - for doc in documents: - builder.add_text(doc) - - builder.build_index(index_path) - - # 测试相关性查询 - searcher = LeannSearcher(index_path) - - test_queries = [ - ("machine learning programming", [0, 2, 4]), # 应该返回ML相关文档 - ("pet animals behavior", [1, 3]), # 应该返回动物相关文档 - ] - - for query, expected_topics in test_queries: - print(f"\n查询: '{query}'") - results = searcher.search(query, top_k=3) - - print("搜索结果:") - for i, result in enumerate(results): - print(f" {i+1}. ID:{result['id']}, Score:{result['score']:.4f}") - print(f" Text: {result['text'][:60]}...") - - # 简单验证：检查前两个结果是否在预期范围内 - top_ids = [result['id'] for result in results[:2]] - relevant_found = any(id in expected_topics for id in top_ids) - - if relevant_found: - print("✅ 搜索结果相关性正确") - else: - print("⚠️ 搜索结果相关性可能有问题") - - except Exception as e: - print(f"❌ 正确性测试失败: {e}") - -def main(): - print("🔍 Leann DiskANN Sanity Check") - print("=" * 50) - - # 清理旧的测试数据 - if Path("test_indices").exists(): - shutil.rmtree("test_indices") - - # 运行测试 - test_distance_functions() - test_embedding_models() - test_search_correctness() - - print("\n" + "=" * 50) - print("🎉 Sanity check 完成!") - -if __name__ == "__main__": - main() \ No newline at end of file