knowledge/tests/service/test_trunks_service.py

import regex
from pathlib import Path

import pytest
from service.trunks_service import TrunksService
from model.trunks_model import Trunks
from sqlalchemy.exc import IntegrityError

@pytest.fixture(scope="module")
def trunks_service():
    return TrunksService()

@pytest.fixture
def test_trunk_data():
    return {
        "content": """测试""",
        "file_path": "test_path.pdf",
        "type": "default"
    }

class TestTrunksServiceCRUD:
    def test_create_and_get_trunk(self, trunks_service, test_trunk_data):
        # 测试创建和查询
        created = trunks_service.create_trunk(test_trunk_data)
        assert created.id is not None

    def test_update_trunk(self, trunks_service, test_trunk_data):
        trunk = trunks_service.create_trunk(test_trunk_data)
        updated = trunks_service.update_trunk(trunk.id, {"content": "更新内容"})
        assert updated.content == "更新内容"

    def test_delete_trunk(self, trunks_service, test_trunk_data):
        trunk = trunks_service.create_trunk(test_trunk_data)
        assert trunks_service.delete_trunk(trunk.id)
        assert trunks_service.get_trunk_by_id(trunk.id) is None

class TestSearchOperations:
    def test_vector_search2(self, trunks_service):
        page = 1
        limit = 100
        file_path = '急诊医学（第2版'
        while True:
            results = trunks_service.paginated_search_by_type_and_filepath(
                {'pageNo': page, 'limit': limit, 'type': 'trunk', 'file_path': file_path})
            if not results['data']:
                break
            for record in results['data']:
                print(f"{record['id']}{record['type']}{record['title']}{record['file_path']}")
                if record['type'] != 'trunk' or file_path not in record['file_path']:
                    print('出现异常数据')
                    break

                page_no = self.get_page_no(record['content'], trunks_service, file_path)
                if page_no is None:
                    print(f"{record['id']}找到page_no: {page_no}")
                    continue
                trunks_service.update_trunk(record['id'], {'page_no': page_no})
            page += 1

    def test_vector_search(self, trunks_service):
        page = 1
        limit = 100
        file_path='trunk2'
        while True:
            results = trunks_service.paginated_search_by_type_and_filepath({'pageNo': page, 'limit': limit, 'type': 'trunk', 'file_path': file_path})
            if not results['data']:
                break
            for record in results['data']:
                print(f"{record['id']}{record['type']}{record['title']}{record['file_path']}")
                if record['type'] != 'trunk' or file_path not in record['file_path']:
                    print('出现异常数据')
                    break

                page_no = self.get_page_no(record['content'],trunks_service,file_path)
                if page_no is None:
                    print(f"{record['id']}找到page_no: {page_no}")
                    continue
                trunks_service.update_trunk(record['id'], {'page_no': page_no})
            page += 1

    def get_page_no(self, text: str, trunks_service,file_path:str) -> int:
        results = trunks_service.search_by_vector(text,1000,type='page',file_path=file_path,conversation_id="1111111aaaa")
        sentences = self.split_text(text)
        count = 0
        for r in results:
            #将r["content"]的所有空白字符去掉
            content = regex.sub(r'[^\w\d\p{L}]', '', r["content"])
            count+=1
            match_count = 0
            length = len(sentences)/2
            for sentence in sentences:
                sentence = regex.sub(r'[^\w\d\p{L}]', '', sentence)
                if sentence in content:
                    match_count += 1
                    if match_count >= 2:
                        return r["page_no"]

    def test_match_trunk(self,trunks_service) -> int:
        must_matchs = ['心肌梗死']
        keywords = [ '概述']
        text = '''- 主要病因：
1. 冠状动脉粥样硬化（占90%以上）
2. 冠状动脉栓塞（如房颤血栓脱落）
3. 冠状动脉痉挛（可卡因滥用等）
- 危险因素：
1. 吸烟（RR=2.87）
2. 高血压（RR=2.50）
3. LDL-C≥190mg/dL（RR=4.48）
- 遗传因素：
家族性高胆固醇血症（OMIM#143890）'''
        text = regex.sub(r'[^\w\d\p{L}]', '', text)
        results = trunks_service.search_by_vector(text,1000,distance=0.72,type='trunk')
        print(f"原结果: {results[0]["meta_header"]}")
        print(results[0]["content"])
        max_match_count = 0
        best_match = None
        for r in results:
            if all(must_match in r["content"] or must_match in r["meta_header"] for must_match in must_matchs):
                match_count = sum(keyword in r["content"] for keyword in keywords)
                if match_count > max_match_count:
                    max_match_count = match_count
                    best_match = r
                elif best_match is None and max_match_count == 0:
                    best_match = r
        if best_match:
            print(f"最佳匹配: {best_match["title"]}")
            print(best_match["content"])
        return best_match
           
    def split_text(self, text):
        """将文本分割成句子"""
        print(text)
        # 使用常见的标点符号作为分隔符
        delimiters = ['!', '?', '。', '！', '？', '\n', ';', '。', '；']
        sentences = [text]
        for delimiter in delimiters:
            new_sentences = []
            for sentence in sentences:
                parts = sentence.split(delimiter)
                new_sentences.extend([part + delimiter if i < len(parts) - 1 else part for i, part in enumerate(parts)])
            sentences = [s.strip() for s in new_sentences if s.strip()]
        
        # 合并短句子
        merged_sentences = []
        buffer = ""
        for sentence in sentences:
            buffer += " " + sentence if buffer else sentence
            if len(buffer) >= 10:
                merged_sentences.append(buffer)
                buffer = ""
        if buffer:
            merged_sentences.append(buffer)
        
        # 打印最终句子
        for i, sentence in enumerate(merged_sentences):
            print(f"句子{i+1}: {sentence.replace(" ","").replace("\u2003", "").replace("\u2002", "").replace("\u2009", "").replace("\n", "").replace("\r", "")}")
        
        return merged_sentences
class TestExceptionCases:
    def test_duplicate_id(self, trunks_service, test_trunk_data):
        with pytest.raises(IntegrityError):
            trunk1 = trunks_service.create_trunk(test_trunk_data)
            test_trunk_data["id"] = trunk1.id
            trunks_service.create_trunk(test_trunk_data)

    def test_invalid_vector_dimension(self, trunks_service, test_trunk_data):
        with pytest.raises(ValueError):
            invalid_data = test_trunk_data.copy()
            invalid_data["embedding"] = [0.1]*100
            trunks_service.create_trunk(invalid_data)

@pytest.fixture
def trunk_factory():
    class TrunkFactory:
        @staticmethod
        def create(**overrides):
            defaults = {
                "content": "工厂内容",
                "file_path": "factory_path.pdf",
        "type": "default"
            }
            return {**defaults, **overrides}
    return TrunkFactory()


class TestBatchCreateFromDirectory:
    def test_batch_create_from_directory(self, trunks_service):
        # 使用现有目录路径
        base_path = Path(r'E:\project\vscode\《急诊医学（第2版）》')
        
        # 遍历目录并创建trunk
        created_ids = []
        for txt_path in base_path.glob('**/*_split_*.txt'):
            relative_path = txt_path.relative_to(base_path.parent.parent)
            with open(txt_path, 'r', encoding='utf-8') as f:
                trunk_data = {
                    "content": f.read(),
                    "file_path": str(relative_path).replace('\\', '/')
                }
                trunk = trunks_service.create_trunk(trunk_data)
                created_ids.append(trunk.id)

        # 验证数据库记录
        for trunk_id in created_ids:
            db_trunk = trunks_service.get_trunk_by_id(trunk_id)
            assert db_trunk is not None
            assert ".txt" in db_trunk.file_path
            assert "_split_" in db_trunk.file_path
            assert len(db_trunk.content) > 0