Python: fix Bing grounding & custom search content generation (#12760)

### Motivation and Context

The same `agent_content_generation` method is used to handle both
`bing_grounding` and `bing_custom_search` tool calls; however, the
method expected that the dicts on the underlying types were named the
same - which they aren't. They have their respective names, as shown
above.

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### Description

Fix Bing content generation based on the instance we're dealing with.
- Add unit tests.
- Closes #12746

<!-- Describe your changes, the overall approach, the underlying design.
These notes will help understanding how your code works. Thanks! -->

### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [X] The code builds clean without any errors or warnings
- [X] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [X] I didn't break anyone 😄

Author: moonbox3

python/semantic_kernel/agents/azure_ai/agent_content_generation.py

@@ -18,6 +18,7 @@
     RequiredMcpToolCall,
     RunStep,
     RunStepAzureAISearchToolCall,
+    RunStepBingCustomSearchToolCall,
     RunStepBingGroundingToolCall,
     RunStepDeltaCodeInterpreterImageOutput,
     RunStepDeltaCodeInterpreterLogOutput,
@@ -283,16 +284,26 @@ def generate_function_result_content(
 
 @experimental
 def generate_bing_grounding_content(
-    agent_name: str, bing_tool_call: "RunStepBingGroundingToolCall"
+    agent_name: str, bing_tool_call: "RunStepBingGroundingToolCall | RunStepBingCustomSearchToolCall"
 ) -> ChatMessageContent:
-    """Generate function result content related to a Bing Grounding Tool."""
+    """Generate function result content related to a Bing Grounding Tool or Bing Custom Search Tool."""
     message_content: ChatMessageContent = ChatMessageContent(role=AuthorRole.ASSISTANT, name=agent_name)  # type: ignore
+
+    # Extract tool details based on the specific tool type
+    if isinstance(bing_tool_call, RunStepBingGroundingToolCall):
+        tool_details = bing_tool_call.bing_grounding
+    elif isinstance(bing_tool_call, RunStepBingCustomSearchToolCall):
+        tool_details = bing_tool_call.bing_custom_search
+    else:
+        # This should never happen with proper typing, but provides safety
+        raise TypeError(f"Unsupported Bing tool call type: {type(bing_tool_call)}")
+
     message_content.items.append(
         FunctionCallContent(
             id=bing_tool_call.id,
             name=bing_tool_call.type,
             function_name=bing_tool_call.type,
-            arguments=bing_tool_call.bing_grounding,
+            arguments=tool_details,
         )
     )
     return message_content
@@ -464,21 +475,27 @@ def generate_streaming_function_content(
 def generate_streaming_bing_grounding_content(
     agent_name: str, step_details: "RunStepDeltaToolCallObject"
 ) -> StreamingChatMessageContent | None:
-    """Generate StreamingChatMessageContent for Bing Grounding tool calls, filtering out empty results."""
+    """Generate StreamingChatMessageContent for Bing Grounding and Bing Custom Search tool calls."""
     if not step_details.tool_calls:
         return None
 
     items: list[FunctionCallContent] = []
     for index, tool in enumerate(step_details.tool_calls):
-        if tool.type != "bing_grounding":
+        if tool.type not in ("bing_grounding", "bing_custom_search"):
             continue
 
-        arguments = tool.get("bing_grounding", {}) or {}
-        requesturl = arguments.get("requesturl", "")
-        response_metadata = arguments.get("response_metadata", None)
+        # Extract tool details based on the specific tool type
+        if tool.type == "bing_grounding":
+            tool_details = tool.get("bing_grounding", {})
+        elif tool.type == "bing_custom_search":
+            tool_details = tool.get("bing_custom_search", {})
+        else:
+            continue
+
+        request_url = tool_details.get("requesturl", None)
+        response_metadata = tool_details.get("response_metadata", None)
 
-        # Only skip if BOTH are missing/empty
-        if requesturl == "" and response_metadata is None:
+        if not request_url and not response_metadata:
             continue
 
         items.append(
@@ -487,7 +504,7 @@ def generate_streaming_bing_grounding_content(
                 index=index,
                 name=tool.type,
                 function_name=tool.type,
-                arguments=arguments,
+                arguments=tool_details,
             )
         )
 

python/semantic_kernel/agents/azure_ai/agent_thread_actions.py

@@ -16,6 +16,7 @@
     ResponseFormatJsonSchemaType,
     RunStep,
     RunStepAzureAISearchToolCall,
+    RunStepBingCustomSearchToolCall,
     RunStepBingGroundingToolCall,
     RunStepCodeInterpreterToolCall,
     RunStepDeltaChunk,
@@ -340,11 +341,12 @@ def sort_key(step: RunStep):
                                     | AgentsNamedToolChoiceType.BING_CUSTOM_SEARCH
                                 ):
                                     logger.debug(
-                                        f"Entering tool_calls (bing_grounding) for run [{run.id}], agent "
-                                        f" `{agent.name}` and thread `{thread_id}`"
+                                        f"Entering tool_calls (bing_grounding/bing_custom_search) for run [{run.id}], "
+                                        f"agent `{agent.name}` and thread `{thread_id}`"
                                     )
-                                    bing_call: RunStepBingGroundingToolCall = cast(
-                                        RunStepBingGroundingToolCall, tool_call
+                                    # Handle both Bing grounding and custom search tool calls
+                                    bing_call: RunStepBingGroundingToolCall | RunStepBingCustomSearchToolCall = cast(
+                                        RunStepBingGroundingToolCall | RunStepBingCustomSearchToolCall, tool_call
                                     )
                                     content = generate_bing_grounding_content(
                                         agent_name=agent.name, bing_tool_call=bing_call

python/tests/unit/agents/azure_ai_agent/test_agent_content_generation.py

@@ -28,6 +28,8 @@
     MessageTextUrlCitationDetails,
     RequiredFunctionToolCall,
     RunStep,
+    RunStepBingCustomSearchToolCall,
+    RunStepBingGroundingToolCall,
     RunStepDeltaFunction,
     RunStepDeltaFunctionToolCall,
     RunStepDeltaToolCallObject,
@@ -38,6 +40,7 @@
 
 from semantic_kernel.agents.azure_ai.agent_content_generation import (
     generate_annotation_content,
+    generate_bing_grounding_content,
     generate_code_interpreter_content,
     generate_function_call_content,
     generate_function_result_content,
@@ -407,3 +410,53 @@ def test_generate_code_interpreter_content():
 def test_generate_streaming_code_interpreter_content_no_calls():
     step_details = type("Details", (), {"tool_calls": None})
     assert generate_streaming_code_interpreter_content("my_agent", step_details) is None
+
+
+def test_generate_bing_grounding_content():
+    """Test generate_bing_grounding_content with RunStepBingGroundingToolCall."""
+    bing_grounding_tool_call = RunStepBingGroundingToolCall(
+        id="call_gvgTmSL4hgdxWP4O7LLnwMlt",
+        bing_grounding={
+            "requesturl": "https://api.bing.microsoft.com/v7.0/search?q=search",
+            "response_metadata": "{'market': 'en-US', 'num_docs_retrieved': 5, 'num_docs_actually_used': 5}",
+        },
+    )
+
+    msg = generate_bing_grounding_content("my_agent", bing_grounding_tool_call)
+
+    assert len(msg.items) == 1
+    assert msg.role == AuthorRole.ASSISTANT
+    assert isinstance(msg.items[0], FunctionCallContent)
+    assert msg.items[0].id == "call_gvgTmSL4hgdxWP4O7LLnwMlt"
+    assert msg.items[0].name == "bing_grounding"
+    assert msg.items[0].function_name == "bing_grounding"
+    assert msg.items[0].arguments["requesturl"] == "https://api.bing.microsoft.com/v7.0/search?q=search"
+    assert msg.items[0].arguments["response_metadata"] == (
+        "{'market': 'en-US', 'num_docs_retrieved': 5, 'num_docs_actually_used': 5}"
+    )
+
+
+def test_generate_bing_custom_search_content():
+    """Test generate_bing_grounding_content with RunStepBingCustomSearchToolCall."""
+    bing_custom_search_tool_call = RunStepBingCustomSearchToolCall(
+        id="call_abc123def456ghi",
+        bing_custom_search={
+            "query": "semantic kernel python",
+            "custom_config_id": "config_123",
+            "search_results": "{'num_results': 10, 'top_result': 'Microsoft Semantic Kernel'}",
+        },
+    )
+
+    msg = generate_bing_grounding_content("my_agent", bing_custom_search_tool_call)
+
+    assert len(msg.items) == 1
+    assert msg.role == AuthorRole.ASSISTANT
+    assert isinstance(msg.items[0], FunctionCallContent)
+    assert msg.items[0].id == "call_abc123def456ghi"
+    assert msg.items[0].name == "bing_custom_search"
+    assert msg.items[0].function_name == "bing_custom_search"
+    assert msg.items[0].arguments["query"] == "semantic kernel python"
+    assert msg.items[0].arguments["custom_config_id"] == "config_123"
+    assert msg.items[0].arguments["search_results"] == (
+        "{'num_results': 10, 'top_result': 'Microsoft Semantic Kernel'}"
+    )