set results to "" empty string if the response from genie is None

integrations/langchain/src/databricks_langchain/genie.py

@@ -37,19 +37,20 @@ def _query_genie_as_agent(input, genie_space_id, genie_agent_name):
         return {"messages": [AIMessage(content="")]}
 
 
+class GenieToolInput(BaseModel):
+    question: str = Field(description="question to ask the agent")
+    summarized_chat_history: str = Field(
+        description="summarized chat history to provide the agent context of what may have been talked about. "
+        "Say 'No history' if there is no history to provide."
+    )
+
+
 def GenieTool(genie_space_id: str, genie_agent_name: str, genie_space_description: str):
     from langchain_core.tools import BaseTool
     from langchain_core.callbacks.manager import CallbackManagerForToolRun
 
     genie = Genie(genie_space_id)
 
-    class GenieToolInput(BaseModel):
-        question: str = Field(description="question to ask the agent")
-        summarized_chat_history: str = Field(
-            description="summarized chat history to provide the agent context of what may have been talked about. "
-            "Say 'No history' if there is no history to provide."
-        )
-
     class GenieQuestionToolWithTrace(BaseTool):
         name: str = f"{genie_agent_name}_details"
         description: str = genie_space_description
@@ -70,7 +71,7 @@ def _run(
             response = genie.ask_question_with_details(message)
             if response:
                 return response.response, response
-            return "no results from room", None
+            return "", None
 
     tool_with_details = GenieQuestionToolWithTrace()
 

integrations/langchain/tests/test_genie.py

@@ -2,10 +2,13 @@
 
 from langchain_core.messages import AIMessage
 
+from databricks_ai_bridge.genie import GenieResult
 from databricks_langchain.genie import (
     GenieAgent,
     _concat_messages_array,
     _query_genie_as_agent,
+    GenieTool,
+    GenieToolInput,
 )
 
 
@@ -69,3 +72,43 @@ def test_create_genie_agent(MockRunnableLambda):
 
     # Check that the partial function is created with the correct arguments
     MockRunnableLambda.assert_called()
+
+
+@patch("databricks_langchain.genie.Genie")
+def test_create_genie_tool(MockGenie):
+    mock_genie = MockGenie.return_value
+    mock_genie.ask_question_with_details.return_value = GenieResult(
+        description=None, sql_query=None, response="It is sunny."
+    )
+
+    agent = GenieTool("space-id", "Genie", "Description")
+
+    assert agent.name == "Genie"
+    assert agent.args_schema == GenieToolInput
+    assert agent.description == "Description"
+    assert (
+        agent.invoke({"question": "What is the weather?", "summarized_chat_history": "No history"})
+        == "It is sunny."
+    )
+
+    assert mock_genie.ask_question_with_details.call_count == 1
+
+
+@patch("databricks_langchain.genie.Genie")
+def test_create_genie_tool_no_response(MockGenie):
+    mock_genie = MockGenie.return_value
+    mock_genie.ask_question_with_details.return_value = None
+
+    agent = GenieTool("space-id", "Genie", "Description")
+
+    assert agent.name == "Genie"
+    assert agent.args_schema == GenieToolInput
+    assert agent.description == "Description"
+    assert (
+            agent.invoke({"question": "What is the weather?", "summarized_chat_history": "No history"})
+            == ""
+    )
+
+    assert mock_genie.ask_question_with_details.call_count == 1
+
+