feat: Add nl2sql tool to run and execute sql queries in databases

src/crewai_tools/tools/nl2sql/nl2sql_tool.py

@@ -0,0 +1,74 @@
+from typing import Any, Union
+
+from crewai_tools import BaseTool
+from pydantic import Field
+from sqlalchemy import create_engine, text
+from sqlalchemy.orm import sessionmaker
+
+
+class NL2SQL(BaseTool):
+    name: str = "NL2SQL"
+    description: str = "Converts natural language to SQL queries and executes them."
+    db_uri: str = Field(
+        title="Database URI",
+        description="The URI of the database to connect to.",
+    )
+    tables: list = []
+    columns: dict = {}
+
+    def model_post_init(self, __context: Any) -> None:
+        data = {}
+        tables = self._fetch_available_tables()
+
+        for table in tables:
+            table_columns = self._fetch_all_available_columns(table["table_name"])
+            data[f'{table["table_name"]}_columns'] = table_columns
+
+        self.tables = tables
+        self.columns = data
+
+    def _fetch_available_tables(self):
+        return self.execute_sql(
+            "SELECT table_name FROM information_schema.tables WHERE table_schema = 'public';"
+        )
+
+    def _fetch_all_available_columns(self, table_name: str):
+        return self.execute_sql(
+            f"SELECT column_name, data_type FROM information_schema.columns WHERE table_name = '{table_name}';"
+        )
+
+    def _run(self, sql_query: str):
+        try:
+            data = self.execute_sql(sql_query)
+        except Exception:
+            data = (
+                f"Based on these tables {self.tables} and columns {self.columns}, "
+                "you can create SQL queries to retrieve data from the database."
+                f"Get the original request {sql_query} and try to create a SQL query that retrieves the requested data."
+            )
+
+        return data
+
+    def execute_sql(self, sql_query: str) -> Union[list, str]:
+        engine = create_engine(self.db_uri)
+        Session = sessionmaker(bind=engine)
+        session = Session()
+
+        try:
+            result = session.execute(text(sql_query))
+            session.commit()
+
+            if result.returns_rows:
+                columns = result.keys()
+                data = [dict(zip(columns, row)) for row in result.fetchall()]
+                return data
+            else:
+                return f"Query {sql_query} executed successfully"
+
+        except Exception as e:
+            session.rollback()
+            print(f"SQL execution error: {e}")
+            raise e
+
+        finally:
+            session.close()