backend/test1/query_test.py

@@ -2,13 +2,11 @@ import re
 import os
 import sys
 import json
-from ctypes import cast
+from sqlalchemy import create_engine
 
 from llama_index.core import VectorStoreIndex, SQLDatabase
 from llama_index.core.indices.struct_store import SQLTableRetrieverQueryEngine
 from llama_index.core.objects import SQLTableNodeMapping, ObjectIndex
-from sqlalchemy import create_engine
-
 from app.api.routers.chat import generate_filters
 from app.engine import get_index, makeDescriptionByEngine
 from app.engine.loaders.db import CustomDatabaseReader
@@ -19,31 +17,94 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
-
 def read_questions_and_answers(file_path):
     questions_and_answers = []
     with open(file_path, 'r', encoding='utf-8') as file:
         data = json.load(file)  # 读取 JSON 数据
         for entry in data:
             question = entry.get("question", "").strip()  # 获取 question
-            answer_match = re.search(r"(\d+\.?\d*)", entry.get("answer", ""))  # 使用正则提取 answer 中的数字部分
+            answer = entry.get("answer", "").strip()  # 直接获取 answer 而不是提取数字
-            if question and answer_match:
+            if question and answer:
-                answer_value = answer_match.group(1)  # 获取匹配的数字
+                questions_and_answers.append((question, answer))
-                questions_and_answers.append((question, answer_value))
     return questions_and_answers
 
-
+def save_results_to_file(question, query_result, correct_answer, file_path):
-def save_results_to_file(question, result, correct_answer, file_path):
+    # 保存原始查询结果
+    result_data = {
+        "问题": question,
+        "查询结果": str(query_result),  # 保存原始查询结果
+        "正确答案": correct_answer
+    }
     with open(file_path, 'a', encoding='utf-8') as file:
-        file.write(f"问题: {question}\n")
+        json.dump(result_data, file, ensure_ascii=False)
-        file.write(f"查询结果: {result}\n")
+        file.write('\n')  # 每个结果条目之间添加换行符
-        file.write(f"正确答案: {correct_answer}\n\n")
 
-def log_incorrect_answers(question, correct_answer, result, log_file_path):
+def log_incorrect_answers(question, correct_answer, query_result, log_file_path):
+    # 保存原始查询结果
+    incorrect_data = {
+        "错误问题": question,
+        "正确答案": correct_answer,
+        "查询结果": str(query_result)  # 保存原始查询结果
+    }
     with open(log_file_path, 'a', encoding='utf-8') as file:
-        file.write(f"错误问题: {question}\n")
+        json.dump(incorrect_data, file, ensure_ascii=False)
-        file.write(f"正确答案: {correct_answer}\n")
+        file.write('\n')  # 每个结果条目之间添加换行符
-        file.write(f"查询结果: {result}\n\n")
+
+# 提取多个数字
+def extract_all_numbers_from_result(result_str):
+    """从查询结果字符串中提取所有数字"""
+    # 使用正则表达式匹配所有数值（包含小数和科学计数法）
+    numbers = re.findall(r"-?\d+,\d+(\.\d+)?|0E-\d+|\d+(\.\d+)?", result_str)
+    # 移除逗号并返回所有数字的列表
+    return [num.replace(',', '') for num in numbers]
+
+# 判断两个浮点数是否接近
+def is_close_enough(val1, val2, epsilon=1e-5):
+    """判断两个数值是否在指定的误差范围内接近"""
+    return abs(val1 - val2) < epsilon
+
+def is_answer_correct(query_result_str, correct_answer_str):
+    """检查查询结果是否与正确答案匹配"""
+    # 提取查询结果中的数字或编码
+    query_result_value = extract_number_or_code_from_result(query_result_str)
+    # 提取正确答案中的数字或编码
+    correct_answer_value = extract_number_or_code_from_result(correct_answer_str)
+
+    # 对比提取的数字或编码
+    if query_result_value and correct_answer_value:
+        try:
+            # 移除逗号，并转换为浮点数
+            query_result_float = float(query_result_value.replace(',', ''))
+            correct_answer_float = float(correct_answer_value.replace(',', ''))
+
+            # 处理科学计数法中的零值
+            if query_result_float == 0.0 and correct_answer_float == 0.0:
+                return True
+
+            # 四舍五入处理到小数点后5位
+            rounded_query_result = round(query_result_float, 5)
+            rounded_correct_answer = round(correct_answer_float, 5)
+
+            # 比较四舍五入后的浮点数值
+            return rounded_query_result == rounded_correct_answer
+        except ValueError:
+            # 如果无法转换为浮点数，则直接比较字符串
+            return query_result_value == correct_answer_value
+    return False  # 如果任何一方为空，则认为不匹配
+
+def extract_number_or_code_from_result(result_str):
+    """从查询结果字符串中提取数字或编码，并处理逗号、百分号和科学计数法"""
+    # 使用正则表达式匹配浮点数，包括可能的多位小数、逗号、百分比形式和科学计数法
+    match = re.search(r"(\d{1,3}(,\d{3})*(\.\d+)?|0E-\d+)", result_str)
+    if match:
+        number_str = match.group(1).replace(',', '').replace('%', '')  # 移除逗号和百分号
+        return number_str
+    
+    # 尝试从结果中提取所有可能的编码格式
+    potential_codes = re.findall(r"\b[A-Z][A-Za-z\d-]+\b", result_str)
+    # 返回第一个匹配的编码
+    return potential_codes[0] if potential_codes else None
+
 
 def main(questions_file, query_type):
     # 获取脚本所在的目录
@@ -59,14 +120,6 @@ def main(questions_file, query_type):
         with open(questions_file_path, 'w', encoding='utf-8') as file:
             json.dump([], file)  # 写入空数组
 
-    if not os.path.exists(results_file_path):
-        with open(results_file_path, 'w', encoding='utf-8') as file:
-            json.dump([], file)  # 写入空数组
-
-    if not os.path.exists(log_file_path):
-        with open(log_file_path, 'w', encoding='utf-8') as file:
-            json.dump([], file)  # 写入空数组
-
     # 更新环境变量
     os.environ['TOP_K'] = str(5)  # 向量的TOP_K值
     os.environ['LLM_TEMPERATURE'] = str(0.1)  # 温度值
@@ -79,7 +132,7 @@ def main(questions_file, query_type):
 
     top_k = int(os.getenv("TOP_K"))  # 向量的TOP_K值
     temperature = float(os.getenv("LLM_TEMPERATURE"))  # 温度值
-    similarity_top_k = float(os.getenv("similarity_top_k"))  # SQL的TOP_K值
+    similarity_top_k = int(os.getenv("similarity_top_k"))  # SQL的TOP_K值
     filters = generate_filters([])
 
     engine = create_engine(os.getenv("SQL_DATABASE_URL", ""))
@@ -100,13 +153,16 @@ def main(questions_file, query_type):
     # 如果文件为空，则写入参数值
     if os.path.getsize(results_file_path) == 0:
         with open(results_file_path, 'w', encoding='utf-8') as file:
-            file.write(f"TOP_K: {top_k}\n")
+            json.dump({
-            file.write(f"LLM_TEMPERATURE: {temperature}\n")
+                "TOP_K": top_k,
-            file.write(f"similarity_top_k: {similarity_top_k}\n\n")
+                "LLM_TEMPERATURE": temperature,
+                "similarity_top_k": similarity_top_k
+            }, file, ensure_ascii=False)
+            file.write('\n')
 
     # 循环执行查询
     for i, (question, correct_answer) in enumerate(questions_and_answers):
-        print(f"Executing query {i+1}: {question}")
+        print(f"执行查询 {i+1}: {question}")
         
         if query_type == "vector":
             query_engine = index.as_query_engine(
@@ -114,41 +170,31 @@ def main(questions_file, query_type):
             )
             query_result = query_engine.query(question)
             print(f"向量查询结果: {query_result}\n")
-            save_results_to_file(question, f"向量查询结果: {query_result}", correct_answer, results_file_path)
 
-            # 提取向量查询结果中的数字进行匹配
+            # 提取向量查询结果中的数字或编码进行匹配
-            query_result_number = re.search(r"(\d+)", str(query_result))
+            query_result_str = f"The encoding for the query \"{question}\" is {str(query_result)}"
         elif query_type == "sql":
             sql_query_result = sql_query_engine.query(question)
             print(f"SQL查询结果: {sql_query_result}\n")
-            save_results_to_file(question, f"SQL查询结果: {sql_query_result}", correct_answer, results_file_path)
 
-            # 提取SQL查询结果中的数字进行匹配
+            # 提取SQL查询结果中的数字或编码进行匹配
-            query_result_number = re.search(r"(\d+)", str(sql_query_result))
+            query_result_str = f"The encoding for the query \"{question}\" is {str(sql_query_result)}"
         else:
             print("无效的查询类型，请选择 'vector' 或 'sql'")
             sys.exit(1)
 
-        if query_result_number:
+        if is_answer_correct(query_result_str, correct_answer):
-            query_number = query_result_number.group(1)
+            # 只在查询结果正确时记录结果
-
+            save_results_to_file(question, query_result_str, correct_answer, results_file_path)
-            # 判断查询结果是否与正确答案匹配
-            if query_number == correct_answer:
-                save_results_to_file(question, query_number, correct_answer, results_file_path)
-            else:
-                log_incorrect_answers(question, correct_answer, query_number, log_file_path)
         else:
-            log_incorrect_answers(question, correct_answer, "未找到有效数字", log_file_path)
+            # 记录不正确的答案
+            log_incorrect_answers(question, correct_answer, query_result_str, log_file_path)
 
 if __name__ == "__main__":
-
     if len(sys.argv) < 3:
         print("请提供questions.json文件名和查询类型（vector 或 sql）")
         sys.exit(1)
     questions_file = sys.argv[1]
     query_type = sys.argv[2].lower()
 
-    from phoenix.trace import using_project
+    main(questions_file, query_type)
-
-    with using_project(questions_file) as obj:
-        main(questions_file, query_type)