add database dir.

app.py

@@ -3,7 +3,7 @@ import pandas as pd
 import sys
 import os
 
-from utils.tools import get_kb, get_schema, get_tables, get_meaning
+from utils.tools import get_kb, get_schema, get_tables, get_meaning, execute_sqlite_query
 
 @gr.mcp.tool()
 def get_all_databases() -> list:
@@ -141,7 +141,41 @@ def meaning_query(db_name, table_name):
     if len(result) == 0:
         return pd.DataFrame({"message": ["沒有找到相關欄位意義"]})
     
-    return result
+    return pd.DataFrame(result)
+
+def execute_sqlite(db_name: str, query: str):
+    """
+    Execute an SQL query on a specified SQLite database and return results.
+
+    This function allows direct SQL query execution on the selected database,
+    returning either the query results or error messages in a standardized format.
+
+    Args:
+        db_name (str): The name of the database to execute the query against. Must not be empty.
+        query (str): The SQL query to execute. Must not be empty.
+
+    Returns:
+        pandas.DataFrame: If query executes successfully, returns DataFrame with query results.
+                         If query fails or parameters are missing, returns error message in DataFrame.
+
+    Example:
+        >>> result = execute_sqlite("sales_db", "SELECT * FROM customers LIMIT 10")
+        >>> print(result)
+        # Returns DataFrame with first 10 rows from customers table
+    """
+    if not db_name or not query:
+        return pd.DataFrame({"message": ["請選擇資料庫和SQL"]})
+    
+    result = execute_sqlite_query(db_name, query)
+    
+    if len(result) == 0:
+        return pd.DataFrame({"message": ["沒有找到相關資料"]})
+    
+    if result['success']:
+        return pd.DataFrame(result['data'], columns=result['columns'])
+    else:
+        return pd.DataFrame({"message": [result['error']]})
+
 
 # 建立 Gradio 界面
 with gr.Blocks(title="資料庫查詢工具") as demo:
@@ -188,6 +222,15 @@ with gr.Blocks(title="資料庫查詢工具") as demo:
         # 當資料庫選擇變更時，更新資料表下拉選單
         # meaning_db.change(update_tables, inputs=meaning_db, outputs=meaning_table)
         meaning_search.click(meaning_query, inputs=[meaning_db, meaning_table], outputs=meaning_result)
+
+    with gr.Tab("sqlite SQL 執行"):
+        with gr.Row():
+            sql_db = gr.Dropdown(choices=all_dbs, label="選擇資料庫", value=all_dbs[0] if all_dbs else None)
+            sql_query  = gr.Textbox(label="sqlite SQL")
+        sql_exec = gr.Button("執行 SQL")
+        sql_result = gr.DataFrame(label="查詢結果")
+        sql_exec.click(execute_sqlite, inputs=[sql_db, sql_query], outputs=sql_result)
+
 # 啟動 Gradio 應用程式
 if __name__ == "__main__":
     demo.launch(mcp_server=True, server_name="0.0.0.0",allowed_paths=["/"], share=True)

database/alien_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e160643c9abb43ba69917532f2654637e677460df25678f9daecdefb416046ed
+size 2371584

database/archeology_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b525a54561e866f12cb373e5d3588ffcfdda13f59966cd9e3e28bb2633b21fdd
+size 2547712

database/credit_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c1ba8d05ed529c159792070b45734c90698200ee28e11d07586a2f17eddfd87b
+size 1306624

database/cross_db_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d7e40379640260a2a16fb014b9af240a2d187de9223470f05ac92c390ec5e657
+size 1261568

database/crypto_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:49103c15d930b290298ac52e2f965877f3caacde6c5269c6c798e596b4c7a5e1
+size 2969600

database/cybermarket_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:23153eba8d258ef4846257326c4481850d7632bc2efdbe2b2236efa00d316922
+size 4231168

database/disaster_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a6ded0fe31d3baef51295aee4a94ad5f21af77a2d6e226b64ad217e466617e09
+size 2097152

database/fake_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a2c6888064e47d82fcf7d47fd0d4bafa5f3ac20569f87b1c98db2e5d2ff9f96
+size 2666496

database/gaming_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:830ff704c00442b83d243f1e96dc79441436b20b7afbd20b15bccad5052f54ec
+size 1388544

database/insider_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5a340024cb8022f819874086bef2a409074e7f15018d3a8dc9c6d0387d796bae
+size 1486848

database/mental_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:64c03a0f0857cd017eed8193df3069e2d0f42e5eeac10fcb03c7918ecec6470f
+size 1470464

database/museum_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4bc022713669f1cab2736e453a012f53eea396e9b94457e744c858cc034d1fb3
+size 2019328

database/news_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3d7163ee93932af7e33ecf46e4ef2c98e9bd8132c3f3ed4c434670feeb441142
+size 1716224

database/polar_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6d351808b75c7adfb9d073741345ab2368eeb0accc53369977b531764f54fe8d
+size 2740224

database/robot_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aef0e7b7134f891da0ae5621638abb12229accd916fb0c7fb2691a66223c05c4
+size 2179072

database/solar_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d143744388100c33eaf7330af84dc71321fc7c317332961e4129196fd66cbc27
+size 2215936

database/vaccine_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2aaf3f42a086d2a70365390bde5db91682fcc842c27febad665f3fe14f0bd402
+size 1290240

database/virtual_template.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d963a35900ac10f5b4a12cdf672ed999742fcf2b04b704e52411c6a1af2acd77
+size 2551808

pyproject.toml

@@ -1,12 +1,9 @@
 [project]
-name = "newsagent"
+name = "LiveSQLBench-Lite-MCP"
 version = "0.1.0"
 description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
-    "bs4>=0.0.2",
     "gradio[mcp]>=5.33.1",
-    "litellm>=1.74.1",
-    "smolagents[litellm,mcp]>=1.20.0",
 ]

requirements.txt

@@ -1,3 +1 @@
 gradio[mcp]
-bs4
-smolagents[litellm,mcp]

utils/tools.py

@@ -1,4 +1,10 @@
 import pandas as pd
+import sqlite3
+import os.path
+import gradio as gr
+import os
+import shutil
+import uuid
 
 
 kb_df = pd.read_csv("./data/kb.csv")
@@ -27,7 +33,72 @@ def get_meaning(db_name, table_name):
     result = result[['column_name', 'meaning']]
     return result
 
+def execute_sqlite_query(db_name, query):
+    """
+    執行 SQLite 查詢並返回結果
+    
+    參數:
+        db_name (str): 數據庫名稱
+        query (str): SQL 查詢字符串
+        
+    返回:
+        dict: 包含查詢結果或錯誤信息的字典
+            成功時: {'success': True, 'columns': 列名列表, 'data': 查詢結果}
+            失敗時: {'success': False, 'error': 錯誤信息}
+    """
+    
+    db_path = f"./database/{db_name}_template.sqlite"
+    
+    # 檢查數據庫文件是否存在
+    if not os.path.exists(db_path):
+        return {'success': False, 'error': f"數據庫文件不存在: {db_path}"}
+    
+    uid = uuid.uuid4()
+    tmp_db_file = f'/tmp/{uid}_{os.path.basename(db_path)}'
+    shutil.copy(db_path, tmp_db_file)
+
+    try:
+        # 連接到 SQLite 數據庫
+        conn = sqlite3.connect(tmp_db_file)
+        cursor = conn.cursor()
+        
+        # 執行查詢
+        cursor.execute(query)
+        
+        # 獲取結果
+        rows = cursor.fetchall()
+        
+        # 獲取列名
+        columns = [description[0] for description in cursor.description] if cursor.description else []
+        
+        # 關閉連接
+        conn.close()
+
+        os.remove(tmp_db_file)
+        return {
+            'success': True,
+            'columns': columns,
+            'data': rows
+        }
+        
+    except sqlite3.Error as e:
+        # 捕獲 SQLite 錯誤
+        os.remove(tmp_db_file)
+        return {
+            'success': False,
+            'error': str(e)
+        }
+    except Exception as e:
+        # 捕獲其他錯誤
+        os.remove(tmp_db_file)
+        return {
+            'success': False,
+            'error': f"執行查詢時發生錯誤: {str(e)}"
+        }
+
 get_kb('solar', 'PP')
 get_schema('solar', 'alerts')
 get_tables('solar')
 get_meaning('solar', 'alerts')
+result = execute_sqlite_query('solar', 'SELECT * from test')
+print(result)