Vmodak/pdm aiq agent

.gitignore

@@ -32,3 +32,9 @@ RAG/notebooks/langchain/data/save_embedding
 
 # IntelliJ's project specific settings file
 .idea
+
+# Environment variables
+.env
+
+# egg-info directories
+**/egg-info

industries/manufacturing/backup/golden_plot_generator/__init__.py

@@ -0,0 +1 @@
+# Golden Plot Generator - Independent plotting system for evaluation 

industries/manufacturing/backup/golden_plot_generator/database/connector.py

@@ -0,0 +1,45 @@
+"""
+Direct SQLite database connector for golden plot generation.
+No dependencies on the agentic framework.
+"""
+import sqlite3
+import pandas as pd
+import os
+from typing import Optional
+
+class DatabaseConnector:
+    def __init__(self, db_path: str = "../PredM_db/nasa_turbo.db"):
+        self.db_path = db_path
+
+    def execute_query(self, sql_query: str) -> Optional[pd.DataFrame]:
+        """
+        Execute SQL query and return results as pandas DataFrame.
+
+        Args:
+            sql_query (str): SQL query to execute
+
+        Returns:
+            pd.DataFrame or None: Query results
+        """
+        try:
+            if not os.path.exists(self.db_path):
+                raise FileNotFoundError(f"Database not found at: {self.db_path}")
+
+            with sqlite3.connect(self.db_path) as conn:
+                df = pd.read_sql_query(sql_query, conn)
+                return df
+
+        except Exception as e:
+            print(f"Error executing query: {e}")
+            print(f"SQL Query: {sql_query}")
+            return None
+
+    def get_table_info(self, table_name: str) -> Optional[pd.DataFrame]:
+        """Get table schema information."""
+        sql = f"PRAGMA table_info({table_name})"
+        return self.execute_query(sql)
+
+    def list_tables(self) -> Optional[pd.DataFrame]:
+        """List all tables in the database."""
+        sql = "SELECT name FROM sqlite_master WHERE type='table'"
+        return self.execute_query(sql)