add planner db agent to planner docstring

Author: CTY-git

patchwork/common/multiturn_strategy/planning_strategy.py

@@ -86,6 +86,42 @@ def __init__(
         executor_tool_set: dict[str, Tool],
         example_json: Union[str, dict[str, Any]] = '{"output":"output text"}',
     ):
+        """
+        Use this like this::
+
+            class DatabaseAgent(Step, input_class=DatabaseAgentInputs, output_class=DatabaseAgentOutputs):
+                 def __init__(self, inputs):
+                     super().__init__(inputs)
+
+                     llm_client = AioLlmClient.create_aio_client(inputs)
+
+                     data = inputs.get("prompt_value", {})
+                     self.task = mustache_render(inputs["task"], data)
+
+                     db_dialect = inputs["db_dialect"]
+                     self.planner = PlanningStrategy(
+                         llm_client,
+                         planner_system_prompt=f'''\\
+            You are a {db_dialect} database query planning assistant. You are tasked to plan the steps to assist with the provided task.
+            You will not execute the steps in the plan. The user will do that instead.
+            The first step of the plan should be as follows:
+            1. Tell me all tables currently available.
+                        After the list of table names is provided, get the DDL of the tables that is relevant.
+                        Your steps should be clear and concise like the following example:
+            1. Tell me the column descriptions of the table `orders`.
+            2. Execute the SQL Query: `SELECT * FROM orders`
+                        After every step, you will be asked to edit the plan so feel free to plan 1 step at a time.
+            ''',
+                        executor_system_prompt=f'''\\
+            You are a {db_dialect} database query execution assistant. You will be provided instructions on what to do.
+            ''',
+                    )
+
+                def run(self) -> dict:
+                    planner_response = self.planner.run(self.task, 10)
+                    return {**planner_response, **self.planner.usage()}
+
+        """
         self.planner = Agent(
             llm_client,
             name="Planner",

patchwork/steps/DatabaseAgent/DatabaseAgent.py

@@ -48,39 +48,3 @@ def __init__(self, inputs):
     def run(self) -> dict:
         result = self.agentic_strategy.execute(limit=10)
         return {**result, **self.agentic_strategy.usage()}
-
-
-# class DatabaseAgent(Step, input_class=DatabaseAgentInputs, output_class=DatabaseAgentOutputs):
-#     def __init__(self, inputs):
-#         super().__init__(inputs)
-#
-#         llm_client = AioLlmClient.create_aio_client(inputs)
-#
-#         data = inputs.get("prompt_value", {})
-#         self.task = mustache_render(inputs["task"], data)
-#
-#         db_dialect = inputs["db_dialect"]
-#         self.planner = PlanningStrategy(
-#             llm_client,
-#             planner_system_prompt=f"""\
-# You are a {db_dialect} database query planning assistant. You are tasked to plan the steps to assist with the provided task.
-# You will not execute the steps in the plan. The user will do that instead.
-# The first step of the plan should be as follows:
-# 1. Tell me all tables currently available.
-#
-# After the list of table names is provided, get the DDL of the tables that is relevant.
-#
-# Your steps should be clear and concise like the following example:
-# 1. Tell me the column descriptions of the table `orders`.
-# 2. Execute the SQL Query: `SELECT * FROM orders`
-#
-# After every step, you will be asked to edit the plan so feel free to plan 1 step at a time.
-# """,
-#             executor_system_prompt=f"""\
-# You are a {db_dialect} database query execution assistant. You will be provided instructions on what to do.
-# """,
-#         )
-#
-#     def run(self) -> dict:
-#         planner_response = self.planner.run(self.task, 10)
-#         return {**planner_response, **self.planner.usage()}