''' | |
''' | |
##TODO: | |
import sqlite3 | |
import pandas as pd | |
## run the following function to set up a dedicated database using SQLite. | |
def construct_db(data_file=None): | |
excel_file = "/Users/yunshi/Downloads/360Data/Data Center/Working-On Task/演讲与培训/2023ChatGPT/Coding/Text2SQL/模拟数据.csv" # Replace with your actual file path | |
df = pd.read_csv(excel_file) | |
print('df:', df.head()) | |
conn = sqlite3.connect('myexcelDB.db') # Replace 'mydatabase.db' with your desired name | |
# Create a cursor object to execute SQL commands | |
cursor = conn.cursor() | |
##NOTE: Insert data from DataFrame into the table. 注意这里的if_exists选项,考虑是否要覆盖原始内容。这里如果需要指定index,那么就需要指定index_label,且index=False,否则会选择默认的index,这样就会产生duplicate错误。 | |
df.to_sql('table01', conn, if_exists='replace', index=False, index_label="产品ID") | |
return None | |
def llm_query(sql_command): | |
# Connect to the database (or create it if it doesn't exist) | |
conn = sqlite3.connect('./myexcelDB.db') # Replace 'myexcelDB.db' with your desired name | |
# Create a cursor object to execute SQL commands | |
cursor = conn.cursor() | |
## SQL command | |
cursor.execute(sql_command) | |
query_result = cursor.fetchall() # Fetch all rows as a list of tuples | |
# print('query_result:', query_result) | |
## 将列名也取出来。 | |
column_names = [description[0] for description in cursor.description] | |
query_df = pd.DataFrame(query_result, columns=column_names) | |
# query_df.set_index("产品ID", inplace=True) | |
print('query_df:', query_df) | |
return query_df | |
# llm_query("SELECT * FROM table01 WHERE 宽度 > 300") ## sample function call. | |
# construct_db() | |
# sql = "SELECT 产品ID FROM table01 WHERE 长度 > 50" | |
# res = llm_query(sql) | |
# res |