diff --git a/examples/ai_modinput_app/bin/agentic_weather.py b/examples/ai_modinput_app/bin/agentic_weather.py
index 768688c2..54856c56 100644
--- a/examples/ai_modinput_app/bin/agentic_weather.py
+++ b/examples/ai_modinput_app/bin/agentic_weather.py
@@ -20,6 +20,8 @@
 from _collections_abc import dict_items
 from typing import final, override
 
+from splunklib.ai.messages import AIMessage, ContentBlock, TextBlock
+
 # ! NOTE: This insert is only needed for splunk-sdk-python CI/CD to work.
 # ! Remove this if you're modifying this example locally.
 sys.path.insert(0, "/splunklib-deps")
@@ -95,9 +97,9 @@ def stream_events(self, inputs: InputDefinition, ew: EventWriter) -> None:
                     weather_events += list(reader)
 
                 for weather_event in weather_events:
-                    weather_event["human_readable"] = asyncio.run(
-                        self.invoke_agent(weather_event)
-                    )
+                    result = asyncio.run(self.invoke_agent(weather_event))
+                    weather_event["human_readable"] = self.parse_content(result)
+
                     logger.debug(f"{weather_event=}")
 
                     event = Event(
@@ -112,7 +114,7 @@ def stream_events(self, inputs: InputDefinition, ew: EventWriter) -> None:
 
             logger.debug(f"Finishing enrichment for {input_name} at {csv_file_path}")
 
-    async def invoke_agent(self, weather_event: dict[str, str | int]) -> str:
+    async def invoke_agent(self, weather_event: dict[str, str | int]) -> AIMessage:
         if not self.service:
             raise AssertionError("No Splunk connection available")
 
@@ -127,7 +129,27 @@ async def invoke_agent(self, weather_event: dict[str, str | int]) -> str:
                 data=weather_event,
             )
             logger.debug(f"{response=}")
-            return response.final_message.content
+            return response.final_message
+
+    def _parse_content_block(self, block: str | ContentBlock) -> str | None:
+        match block:
+            case TextBlock():
+                return block.text
+            case str():
+                return block
+            case _:
+                return None
+
+    def parse_content(self, message: AIMessage) -> str:
+        """Parses the content from AIMessage and builds a single string our of it"""
+        if isinstance(message.content, str):
+            return message.content
+
+        return " ".join(
+            parsed_block
+            for block in message.content
+            if (parsed_block := self._parse_content_block(block))
+        )
 
 
 if __name__ == "__main__":
diff --git a/splunklib/ai/engines/langchain.py b/splunklib/ai/engines/langchain.py
index 76fa100b..08e67fa7 100644
--- a/splunklib/ai/engines/langchain.py
+++ b/splunklib/ai/engines/langchain.py
@@ -77,7 +77,9 @@
     AgentResponse,
     AIMessage,
     BaseMessage,
+    ContentBlock,
     HumanMessage,
+    OpaqueBlock,
     OutputT,
     StructuredOutputCall,
     StructuredOutputMessage,
@@ -87,6 +89,7 @@
     SubagentStructuredResult,
     SubagentTextResult,
     SystemMessage,
+    TextBlock,
     ToolCall,
     ToolFailureResult,
     ToolMessage,
@@ -951,7 +954,7 @@ async def awrap_tool_call(
         return LC_ToolMessage(
             name=_normalize_agent_name(call.name),
             tool_call_id=call.id,
-            content=content,
+            content=_map_content_to_langchain(content),
             status=status,
             artifact=sdk_result,
         )
@@ -1085,7 +1088,10 @@ def _convert_model_response_to_model_result(
     # This invariant is asserted via ModelResponse.__post_init__
     assert len(resp.message.structured_output_calls) <= 1
 
-    lc_message = LC_AIMessage(content=resp.message.content)
+    lc_message = LC_AIMessage(
+        content=_map_content_to_langchain(resp.message.content),
+        additional_kwargs=resp.message.extras or {},
+    )
     # This field can't be set via __init__()
     lc_message.tool_calls = [_map_tool_call_to_langchain(c) for c in resp.message.calls]
 
@@ -1160,7 +1166,7 @@ def _convert_tool_message_to_lc(
         name=name,
         tool_call_id=message.call_id,
         status=status,
-        content=content,
+        content=_map_content_to_langchain(content),
         artifact=artifact,
     )
 
@@ -1243,9 +1249,10 @@ def _convert_model_result_from_lc(model_response: LC_ModelCallResult) -> ModelRe
         ai_message = model_response
         structured_response = None
 
+    additional_kwargs = cast(dict[str, Any], ai_message.additional_kwargs)
     return ModelResponse(
         message=AIMessage(
-            content=ai_message.content.__str__(),
+            content=_map_content_from_langchain(ai_message.content),  # pyright: ignore[reportUnknownArgumentType]
             calls=[
                 _map_tool_call_from_langchain(tc)
                 for tc in ai_message.tool_calls
@@ -1260,6 +1267,7 @@ def _convert_model_result_from_lc(model_response: LC_ModelCallResult) -> ModelRe
                 for tc in ai_message.tool_calls
                 if tc["name"].startswith(TOOL_STRATEGY_TOOL_PREFIX)
             ],
+            extras=additional_kwargs,
         ),
         structured_output=structured_response,
     )
@@ -1433,7 +1441,10 @@ def _agent_as_tool(agent: BaseAgent[OutputT]) -> StructuredTool:
 
     async def invoke_agent(
         message: HumanMessage, thread_id: str | None
-    ) -> tuple[OutputT | str, SubagentStructuredResult | SubagentTextResult]:
+    ) -> tuple[
+        OutputT | str | list[str | ContentBlock],
+        SubagentStructuredResult | SubagentTextResult,
+    ]:
         result = await agent.invoke([message], thread_id=thread_id)
 
         if agent.output_schema:
@@ -1452,13 +1463,19 @@ async def invoke_agent(
 
             async def _run(  # pyright: ignore[reportRedeclaration]
                 content: str, thread_id: str
-            ) -> tuple[OutputT | str, SubagentStructuredResult | SubagentTextResult]:
+            ) -> tuple[
+                OutputT | str | list[str | ContentBlock],
+                SubagentStructuredResult | SubagentTextResult,
+            ]:
                 return await invoke_agent(HumanMessage(content=content), thread_id)
         else:
 
             async def _run(  # pyright: ignore[reportRedeclaration]
                 content: str,
-            ) -> tuple[OutputT | str, SubagentStructuredResult | SubagentTextResult]:
+            ) -> tuple[
+                OutputT | str | list[str | ContentBlock],
+                SubagentStructuredResult | SubagentTextResult,
+            ]:
                 return await invoke_agent(HumanMessage(content=content), None)
 
         return StructuredTool.from_function(
@@ -1471,7 +1488,10 @@ async def _run(  # pyright: ignore[reportRedeclaration]
 
     async def invoke_agent_structured(
         content: BaseModel, thread_id: str | None
-    ) -> tuple[OutputT | str, SubagentStructuredResult | SubagentTextResult]:
+    ) -> tuple[
+        OutputT | str | list[str | ContentBlock],
+        SubagentStructuredResult | SubagentTextResult,
+    ]:
         result = await agent.invoke_with_data(
             instructions="Follow the system prompt.",
             data=content.model_dump(),
@@ -1492,7 +1512,10 @@ async def invoke_agent_structured(
 
         async def _run(
             **kwargs: Any,  # noqa: ANN401
-        ) -> tuple[OutputT | str, SubagentStructuredResult | SubagentTextResult]:
+        ) -> tuple[
+            OutputT | str | list[str | ContentBlock],
+            SubagentStructuredResult | SubagentTextResult,
+        ]:
             content: BaseModel = kwargs["content"]
             thread_id: str = kwargs["thread_id"]
             return await invoke_agent_structured(content, thread_id)
@@ -1512,7 +1535,10 @@ async def _run(
 
         async def _run(
             **kwargs: Any,  # noqa: ANN401
-        ) -> tuple[OutputT | str, SubagentStructuredResult | SubagentTextResult]:
+        ) -> tuple[
+            OutputT | str | list[str | ContentBlock],
+            SubagentStructuredResult | SubagentTextResult,
+        ]:
             content = InputSchema(**kwargs)
             return await invoke_agent_structured(content, None)
 
@@ -1564,11 +1590,66 @@ def _map_tool_call_to_langchain(call: ToolCall | SubagentCall) -> LC_ToolCall:
     return LC_ToolCall(id=call.id, name=name, args=args)
 
 
+def _map_content_from_langchain(
+    content: str | list[str | dict[str, Any]],
+) -> str | list[str | ContentBlock]:
+    if isinstance(content, str):
+        return content
+
+    result_content = [_map_content_block_from_langchain(b) for b in content]
+
+    return result_content
+
+
+def _map_content_block_from_langchain(
+    block: str | dict[str, Any],
+) -> str | ContentBlock:
+    if isinstance(block, str):
+        return block
+
+    match block.get("type"):
+        case "text":
+            return TextBlock(
+                text=block["text"],
+                extras=block.get("extras"),
+            )
+        case _:
+            # NOTE: we return data we're not handling
+            # as opaque content blocks so they
+            # are preserved and sent back to the LLM
+            return OpaqueBlock(data=block)
+
+
+def _map_content_to_langchain(
+    content: str | list[str | ContentBlock],
+) -> str | list[str | dict[str, Any]]:
+    if isinstance(content, str):
+        return content
+
+    result_content = [_map_content_block_to_langchain(b) for b in content]
+
+    return result_content
+
+
+def _map_content_block_to_langchain(block: str | ContentBlock) -> str | dict[str, Any]:
+    if isinstance(block, str):
+        return block
+
+    match block:
+        case TextBlock():
+            result: dict[str, Any] = {"type": "text", "text": block.text}
+            if block.extras:
+                result["extras"] = block.extras
+            return result
+        case OpaqueBlock():
+            return block.data
+
+
 def _map_message_from_langchain(message: LC_BaseMessage) -> BaseMessage:
     match message:
         case LC_AIMessage():
             return AIMessage(
-                content=message.content.__str__(),
+                content=_map_content_from_langchain(message.content),  # pyright: ignore[reportUnknownArgumentType]
                 calls=[
                     _map_tool_call_from_langchain(tc)
                     for tc in message.tool_calls
@@ -1583,6 +1664,7 @@ def _map_message_from_langchain(message: LC_BaseMessage) -> BaseMessage:
                     for tc in message.tool_calls
                     if tc["name"].startswith(TOOL_STRATEGY_TOOL_PREFIX)
                 ],
+                extras=cast(dict[str, Any], message.additional_kwargs),
             )
         case LC_HumanMessage():
             return HumanMessage(content=message.content.__str__())
@@ -1597,7 +1679,10 @@ def _map_message_from_langchain(message: LC_BaseMessage) -> BaseMessage:
 def _map_message_to_langchain(message: BaseMessage) -> LC_AnyMessage:
     match message:
         case AIMessage():
-            lc_message = LC_AIMessage(content=message.content)
+            lc_message = LC_AIMessage(
+                content=_map_content_to_langchain(message.content),
+                additional_kwargs=message.extras or {},
+            )
             # This field can't be set via constructor
             lc_message.tool_calls = [
                 _map_tool_call_to_langchain(c) for c in message.calls
diff --git a/splunklib/ai/messages.py b/splunklib/ai/messages.py
index 04db32b6..bdacfb93 100644
--- a/splunklib/ai/messages.py
+++ b/splunklib/ai/messages.py
@@ -21,6 +21,31 @@
 from splunklib.ai.tools import ToolType
 
 
+@dataclass(frozen=True)
+class TextBlock:
+    """Plain text content block returned by a model."""
+
+    text: str
+    # TODO: should we have the id here as well?
+    # Provider-specific extras (e.g. Gemini thought signature on text blocks).
+    extras: dict[str, Any] | None = field(default=None)
+
+
+@dataclass(frozen=True)
+class OpaqueBlock:
+    """Content block of an unrecognized or unsupported type.
+
+    The raw provider dict is preserved in `data` so it can be sent back
+    to the model unchanged on subsequent calls.
+    """
+
+    data: dict[str, Any]
+
+
+# Type alias for all content block variants.
+ContentBlock = TextBlock | OpaqueBlock
+
+
 @dataclass(frozen=True)
 class ToolCall:
     name: str
@@ -85,12 +110,15 @@ class AIMessage(BaseMessage):
     """
 
     role: Literal["assistant"] = field(default="assistant", init=False)
-    content: str
+    content: str | list[str | ContentBlock]
 
     calls: Sequence[ToolCall | SubagentCall]
     structured_output_calls: Sequence[StructuredOutputCall] = field(
         default_factory=tuple
     )
+    # Backend-specific metadata (e.g. provider additional_kwargs) not
+    # representable in the standard fields. Opaque to callers.
+    extras: dict[str, Any] | None = field(default=None)
 
 
 @dataclass(frozen=True)
@@ -120,7 +148,7 @@ class SubagentTextResult:
     Returned by subagent calls that don't have an output schema.
     """
 
-    content: str
+    content: str | list[str | ContentBlock]
 
 
 @dataclass(frozen=True)
diff --git a/tests/ai_testlib.py b/tests/ai_testlib.py
index 631fd16f..7c77ba4e 100644
--- a/tests/ai_testlib.py
+++ b/tests/ai_testlib.py
@@ -1,4 +1,7 @@
 from typing import override
+from warnings import warn
+
+from splunklib.ai.messages import AIMessage, ContentBlock, SubagentTextResult, TextBlock
 from splunklib.ai.model import PredefinedModel
 from tests.ai_test_model import InternalAIModel, TestLLMSettings, create_model
 from tests.testlib import SDKTestCase
@@ -18,6 +21,27 @@ def setUp(self) -> None:
                 app.delete()
                 self.restart_splunk()
 
+    def _parse_content_block(self, block: str | ContentBlock) -> str | None:
+        match block:
+            case TextBlock():
+                return block.text
+            case str():
+                return block
+            case _:
+                warn(f"Skipping OpaqueBlock when parsing the AIMessage.content")
+                return None
+
+    def parse_content(self, message: AIMessage | SubagentTextResult) -> str:
+        """Parses the content from AIMessage and builds a single string our of it"""
+        if isinstance(message.content, str):
+            return message.content
+
+        return " ".join(
+            parsed_block
+            for block in message.content
+            if (parsed_block := self._parse_content_block(block))
+        )
+
     @property
     def test_llm_settings(self) -> TestLLMSettings:
         client_id: str = self.opts.kwargs["internal_ai_client_id"]
diff --git a/tests/integration/ai/test_agent.py b/tests/integration/ai/test_agent.py
index 1f9ea591..1d0b8ab8 100644
--- a/tests/integration/ai/test_agent.py
+++ b/tests/integration/ai/test_agent.py
@@ -64,7 +64,12 @@ async def test_agent_with_openai_round_trip(self):
                 ]
             )
 
-            response = result.final_message.content.strip().lower().replace(".", "")
+            response = (
+                self.parse_content(result.final_message)
+                .strip()
+                .lower()
+                .replace(".", "")
+            )
             assert result.structured_output is None, (
                 "The structured output should not be populated"
             )
@@ -152,7 +157,7 @@ class Person(BaseModel):
 
             response = result.structured_output
 
-            last_message = result.final_message.content
+            last_message = self.parse_content(result.final_message)
 
             assert type(response) == Person, "Response is not of type Person"
             assert response.name != "", "Name field is empty"
@@ -220,7 +225,7 @@ class NicknameGeneratorInput(BaseModel):
             )
             assert subagent_message, "No subagent message found in response"
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Chris-zilla" in response, "Agent did generate valid nickname"
 
     @pytest.mark.asyncio
@@ -264,7 +269,7 @@ async def test_subagent_without_input_schema(self):
             assert first_ai_message.calls[0].args.lower() == "chris"
             assert first_ai_message.calls[0].thread_id is None, "unexpected thread_id"
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Chris-zilla" in response, "Agent did generate valid nickname"
 
     @pytest.mark.asyncio
@@ -305,7 +310,7 @@ class Person(BaseModel):
                 ]
             )
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Chris-zilla" in response, "Agent did generate valid nickname"
 
     # TODO: unskip the test once we switch to a better model
diff --git a/tests/integration/ai/test_agent_mcp_tools.py b/tests/integration/ai/test_agent_mcp_tools.py
index ac2dd880..ecbf4fde 100644
--- a/tests/integration/ai/test_agent_mcp_tools.py
+++ b/tests/integration/ai/test_agent_mcp_tools.py
@@ -91,7 +91,7 @@ async def test_tool_execution_structured_output(self) -> None:
             assert tool_message, "No tool message found in response"
             assert tool_message.name == "temperature", "Invalid tool name"
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "31.5" in response, "Invalid LLM response"
 
     @patch(
@@ -188,7 +188,7 @@ async def test_multiple_and_concurrent_tool_calls(self) -> None:
                 ]
             )
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "31.5" in response, "Invalid LLM response"
             assert "30.0" in response, "Invalid LLM response"
             assert "25.5" in response, "Invalid LLM response"
@@ -205,7 +205,7 @@ async def test_multiple_and_concurrent_tool_calls(self) -> None:
                     )
                 ]
             )
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "28.5" in response, "Invalid LLM response"
 
             # Make sure MCP was alive during entire Agent lifetime.
@@ -377,7 +377,7 @@ async def dispatch(
                 assert tool_message, "No tool message found in response"
                 assert tool_message.name == "temperature", "Invalid tool name"
 
-                response = result.final_message.content
+                response = self.parse_content(result.final_message)
                 assert "31.5" in response, "Invalid LLM response"
 
                 assert trace_id == agent.trace_id
@@ -417,7 +417,12 @@ async def test_remote_tools_mcp_app_unavailable(self) -> None:
                     [HumanMessage(content="What is your name? Answer in one word")]
                 )
 
-                response = result.final_message.content.strip().lower().replace(".", "")
+                response = (
+                    self.parse_content(result.final_message)
+                    .strip()
+                    .lower()
+                    .replace(".", "")
+                )
                 assert "stefan" in response
 
     @patch(
@@ -492,7 +497,7 @@ async def lifespan(app: Starlette) -> AsyncGenerator[None, Any]:
                 assert type(tool_messages[0].result) is ToolFailureResult
                 assert type(tool_messages[1].result) is ToolResult
 
-                response = result.final_message.content
+                response = self.parse_content(result.final_message)
                 assert "31.5" in response, "Invalid LLM response"
 
     @patch(
@@ -595,7 +600,7 @@ async def lifespan(app: Starlette) -> AsyncGenerator[None, Any]:
                         )
                 assert found_tool_message, "missing ToolMessage in agent response"
 
-                response = result.final_message.content
+                response = self.parse_content(result.final_message)
                 assert "31.5" in response, "Invalid LLM response"
 
     @patch(
@@ -656,7 +661,7 @@ async def middleware(
             assert tool_message, "No tool message found in response"
             assert tool_message.name == "temperature", "Invalid tool name"
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "22" in response, "Invalid LLM response"
 
 
diff --git a/tests/integration/ai/test_anthropic_agent.py b/tests/integration/ai/test_anthropic_agent.py
index eeed9349..3f88c58f 100644
--- a/tests/integration/ai/test_anthropic_agent.py
+++ b/tests/integration/ai/test_anthropic_agent.py
@@ -47,6 +47,11 @@ async def test_agent_with_anthropic_round_trip(self):
                 [HumanMessage(content="What is your name? Answer in one word")]
             )
 
-            response = result.final_message.content.strip().lower().replace(".", "")
+            response = (
+                self.parse_content(result.final_message)
+                .strip()
+                .lower()
+                .replace(".", "")
+            )
             assert result.structured_output is None
             assert "stefan" in response
diff --git a/tests/integration/ai/test_conversation_store.py b/tests/integration/ai/test_conversation_store.py
index a5c10b34..b3d28038 100644
--- a/tests/integration/ai/test_conversation_store.py
+++ b/tests/integration/ai/test_conversation_store.py
@@ -12,8 +12,8 @@
 # License for the specific language governing permissions and limitations
 # under the License.
 
-from pydantic import BaseModel, Field
 import pytest
+from pydantic import BaseModel, Field
 
 from splunklib.ai import Agent
 from splunklib.ai.conversation_store import InMemoryStore
@@ -44,7 +44,7 @@ async def test_agent_does_not_remember_state_without_store(self) -> None:
 
             result = await agent.invoke([HumanMessage(content="What is my name?")])
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
 
             assert "Chris" not in response, "Agent remembered the name"
 
@@ -101,7 +101,7 @@ async def _agent_middleware(
 
             result = await agent.invoke([HumanMessage(content="What is my name?")])
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
 
             assert "Chris" in response, "Agent did not remember the name"
 
@@ -146,7 +146,7 @@ async def _agent_middleware(
 
             result = await agent.invoke([HumanMessage(content="What is my name?")])
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
 
             assert "Mike" in response, "Agent did not remember the name"
 
@@ -185,7 +185,7 @@ async def _model_middleware(
                 [HumanMessage(content="What is my name?")],
                 thread_id="2",
             )
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Mike" not in response, (
                 "Agent remembered the name from a different thread_id"
             )
@@ -219,14 +219,14 @@ async def test_thread_id_in_constructor(self) -> None:
                 [HumanMessage(content="What is my name?")],
                 thread_id="2",
             )
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Mike" in response, "Agent did not remember the name"
 
             # When thread_id not specified the one from the agent constructor is used.
             result = await agent.invoke(
                 [HumanMessage(content="What is my name?")],
             )
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Mike" in response, "Agent did not remember the name"
 
         # Now use the same conversation_store in a different agent with same thread_ids.
@@ -242,21 +242,21 @@ async def test_thread_id_in_constructor(self) -> None:
                 [HumanMessage(content="What is my name?")],
                 thread_id="1",
             )
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Chris" in response, "Agent did not remember the name"
 
             result = await agent.invoke(
                 [HumanMessage(content="What is my name?")],
                 thread_id="2",
             )
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Mike" in response, "Agent did not remember the name"
 
             # When thread_id not specified the one from the agent constructor is used.
             result = await agent.invoke(
                 [HumanMessage(content="What is my name?")],
             )
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Mike" in response, "Agent did not remember the name"
 
 
@@ -328,7 +328,7 @@ async def _model_middleware(
                 assert isinstance(third_ai_msg.calls[0], SubagentCall)
                 assert thread_id == third_ai_msg.calls[0].thread_id, "missing thread_id"
 
-                assert "chris" in resp.final_message.content.lower()
+                assert "chris" in self.parse_content(resp.final_message).lower()
 
     # TODO: unskip the test once we switch to a better model
     @pytest.mark.asyncio
@@ -403,4 +403,4 @@ class MemoryAgentInput(BaseModel):
                 assert isinstance(third_ai_msg.calls[0], SubagentCall)
                 assert thread_id == third_ai_msg.calls[0].thread_id, "invalid thread_id"
 
-                assert "chris" in resp.final_message.content.lower()
+                assert "chris" in self.parse_content(resp.final_message).lower()
diff --git a/tests/integration/ai/test_hooks.py b/tests/integration/ai/test_hooks.py
index ad22a75b..45c34894 100644
--- a/tests/integration/ai/test_hooks.py
+++ b/tests/integration/ai/test_hooks.py
@@ -29,8 +29,14 @@
     before_agent,
     before_model,
 )
-from splunklib.ai.messages import AIMessage, AgentResponse, HumanMessage
-from splunklib.ai.middleware import AgentRequest, ModelMiddlewareHandler, ModelRequest, ModelResponse, model_middleware
+from splunklib.ai.messages import AgentResponse, AIMessage, HumanMessage
+from splunklib.ai.middleware import (
+    AgentRequest,
+    ModelMiddlewareHandler,
+    ModelRequest,
+    ModelResponse,
+    model_middleware,
+)
 from tests.ai_testlib import AITestCase
 
 
@@ -62,7 +68,7 @@ def test_hook_after(resp: ModelResponse) -> None:
             nonlocal hook_calls
             hook_calls += 1
 
-            response = resp.message.content.strip().lower().replace(".", "")
+            response = self.parse_content(resp.message).strip().lower().replace(".", "")
             assert "stefan" == response
 
         @after_model
@@ -70,7 +76,7 @@ async def test_async_hook_after(resp: ModelResponse) -> None:
             nonlocal hook_calls
             hook_calls += 1
 
-            response = resp.message.content.strip().lower().replace(".", "")
+            response = self.parse_content(resp.message).strip().lower().replace(".", "")
             assert "stefan" == response
 
         async with Agent(
@@ -92,7 +98,12 @@ async def test_async_hook_after(resp: ModelResponse) -> None:
                 ]
             )
 
-            response = result.final_message.content.strip().lower().replace(".", "")
+            response = (
+                self.parse_content(result.final_message)
+                .strip()
+                .lower()
+                .replace(".", "")
+            )
             assert "stefan" == response
             assert hook_calls == 4
 
@@ -159,7 +170,12 @@ async def after_async_agent_hook(resp: AgentResponse) -> None:
                 ]
             )
 
-            response = result.final_message.content.strip().lower().replace(".", "")
+            response = (
+                self.parse_content(result.final_message)
+                .strip()
+                .lower()
+                .replace(".", "")
+            )
             assert '{"name":"stefan"}' == response
             assert hook_calls == 4
 
@@ -197,10 +213,12 @@ async def test_agent_loop_stop_conditions_conversation_limit(self) -> None:
             with pytest.raises(
                 StepsLimitExceededException, match="Steps limit of 2 exceeded"
             ):
-                _ = await agent.invoke([
-                    HumanMessage(content="hi, my name is Chris"),
-                    HumanMessage(content="What is my name?"),
-                ])
+                _ = await agent.invoke(
+                    [
+                        HumanMessage(content="hi, my name is Chris"),
+                        HumanMessage(content="What is my name?"),
+                    ]
+                )
 
     @pytest.mark.asyncio
     async def test_agent_loop_stop_conditions_conversation_limit_with_checkpointer(
@@ -220,13 +238,17 @@ async def test_agent_loop_stop_conditions_conversation_limit_with_checkpointer(
             with pytest.raises(
                 StepsLimitExceededException, match="Steps limit of 2 exceeded"
             ):
-                _ = await agent.invoke([
-                    HumanMessage(content="What is my name?"),
-                    HumanMessage(content="Are you sure?"),
-                ])
+                _ = await agent.invoke(
+                    [
+                        HumanMessage(content="What is my name?"),
+                        HumanMessage(content="Are you sure?"),
+                    ]
+                )
 
     @pytest.mark.asyncio
-    async def test_agent_loop_stop_conditions_steps_accumulate_across_invokes(self) -> None:
+    async def test_agent_loop_stop_conditions_steps_accumulate_across_invokes(
+        self,
+    ) -> None:
         pytest.importorskip("langchain_openai")
 
         step_limit = StepLimitMiddleware(2)
diff --git a/tests/integration/ai/test_middleware.py b/tests/integration/ai/test_middleware.py
index d699bb5b..1278de33 100644
--- a/tests/integration/ai/test_middleware.py
+++ b/tests/integration/ai/test_middleware.py
@@ -95,7 +95,7 @@ async def test_middleware(
                 [HumanMessage(content="What is the weather like today in Krakow?")]
             )
 
-            response = res.final_message.content
+            response = self.parse_content(res.final_message)
             assert "31.5" in response
             assert middleware_called, "Middleware was not called"
 
@@ -162,7 +162,7 @@ async def test_middleware(
                 [HumanMessage(content="What is the weather like today in Krakow?")]
             )
 
-            response = res.final_message.content
+            response = self.parse_content(res.final_message)
             assert "31.5" in response
             assert middleware_called, "Middleware was not called"
 
@@ -200,7 +200,7 @@ async def test_middleware(
                 [HumanMessage(content="What is the weather like today in Kraków?")]
             )
 
-            response = res.final_message.content
+            response = self.parse_content(res.final_message)
             assert "0.5" in response, "Invalid response from LLM"
 
             tool_message = next(
@@ -253,7 +253,7 @@ async def second_middleware(
             res = await agent.invoke(
                 [HumanMessage(content="What is the weather like today in Krakow?")]
             )
-            assert "31.5" in res.final_message.content
+            assert "31.5" in self.parse_content(res.final_message)
             assert first_called, "First middleware was called after the second"
             assert second_called, "Second middleware was called before the first"
 
@@ -295,7 +295,7 @@ async def model_test_middleware(
             res = await agent.invoke(
                 [HumanMessage(content="What is the weather like today in Krakow?")]
             )
-            assert "31.5" in res.final_message.content
+            assert "31.5" in self.parse_content(res.final_message)
             assert tool_called
             assert model_called
 
@@ -349,7 +349,7 @@ async def subagent_middleware(
             tool_result = await agent.invoke(
                 [HumanMessage(content="What is the weather like today in Krakow?")]
             )
-            assert "31.5" in tool_result.final_message.content
+            assert "31.5" in self.parse_content(tool_result.final_message)
 
         class NicknameGeneratorInput(BaseModel):
             name: str = Field(description="The person's full name", min_length=1)
@@ -377,7 +377,7 @@ class NicknameGeneratorInput(BaseModel):
             subagent_result = await supervisor.invoke(
                 [HumanMessage(content="Generate a nickname for Chris")]
             )
-            assert "Chris-zilla" in subagent_result.final_message.content
+            assert "Chris-zilla" in self.parse_content(subagent_result.final_message)
 
         assert model_called
         assert tool_called
@@ -442,7 +442,7 @@ async def test_middleware(
             )
             assert subagent_message, "No subagent message found in response"
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Chris-zilla" in response, "Agent did generate valid nickname"
 
             assert middleware_called, "Middleware was not called"
@@ -492,7 +492,7 @@ async def test_middleware(
                 [HumanMessage(content="Generate a nickname for Chris")]
             )
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Chris-superstar" in response, "Invalid response from LLM"
 
             subagent_message = next(
@@ -500,7 +500,7 @@ async def test_middleware(
             )
             assert subagent_message, "SubagentMessage not found in messages"
             assert isinstance(subagent_message.result, SubagentTextResult)
-            assert subagent_message.result.content == "Chris-superstar", (
+            assert self.parse_content(subagent_message.result) == "Chris-superstar", (
                 "Invalid response from subagent"
             )
             assert middleware_called, "Middleware was not called"
@@ -621,7 +621,7 @@ async def test_middleware(
                 [HumanMessage(content="Generate a nickname for Chris")]
             )
 
-            response = result.final_message.content
+            response = self.parse_content(result.final_message)
             assert "Chris-zilla" in response, "Agent did generate valid nickname"
             assert middleware_called, "Middleware was not called"
 
@@ -657,7 +657,7 @@ async def test_middleware(
                 ]
             )
 
-            response = res.final_message.content
+            response = self.parse_content(res.final_message)
             assert "My response is made up" == response
             assert middleware_called, "Middleware was not called"
 
@@ -715,7 +715,7 @@ async def mutating_middleware(
             res = await agent.invoke(
                 [HumanMessage(content="What is the capital of Germany?")]
             )
-            assert "Paris" in res.final_message.content
+            assert "Paris" in self.parse_content(res.final_message)
 
     @patch(
         "splunklib.ai.agent._testing_local_tools_path",
@@ -752,7 +752,7 @@ async def mutating_middleware(
                 [HumanMessage(content="What is the weather like today in Berlin?")]
             )
             # Berlin returns 22.1C; Krakow returns 31.5C
-            assert "31.5" in res.final_message.content
+            assert "31.5" in self.parse_content(res.final_message)
 
     @pytest.mark.asyncio
     async def test_subagent_middleware_arg_mutation_reaches_subagent(self) -> None:
@@ -796,7 +796,7 @@ async def mutating_middleware(
             result = await supervisor.invoke(
                 [HumanMessage(content="Generate a nickname for Bob")]
             )
-            assert "Alice-zilla" in result.final_message.content
+            assert "Alice-zilla" in self.parse_content(result.final_message)
 
     @pytest.mark.asyncio
     async def test_model_middleware_structured_output(self) -> None:
diff --git a/tests/integration/ai/test_structured_output.py b/tests/integration/ai/test_structured_output.py
index 9f793f95..67f4c572 100644
--- a/tests/integration/ai/test_structured_output.py
+++ b/tests/integration/ai/test_structured_output.py
@@ -302,7 +302,7 @@ async def _model_middleware(
                 )
 
                 try:
-                    Person.model_validate_json(e.message.content)
+                    Person.model_validate_json(self.parse_content(e.message))
                     raise AssertionError(
                         "args are valid, but got an StructuredOutputGenerationException"
                     )
@@ -314,7 +314,7 @@ async def _model_middleware(
             assert after_first_model_call, "generation error did not happen"
             assert resp.structured_output is not None, "missing structured_output"
             assert (
-                Person.model_validate_json(resp.message.content)
+                Person.model_validate_json(self.parse_content(resp.message))
                 == resp.structured_output
             ), "invalid structured output"
 
@@ -345,7 +345,7 @@ async def _model_middleware(
 
             assert len(result.final_message.structured_output_calls) == 0
             assert (
-                Person.model_validate_json(result.final_message.content)
+                Person.model_validate_json(self.parse_content(result.final_message))
                 == result.structured_output
             )
 
@@ -827,7 +827,9 @@ async def _model_middleware(
                 assert "ALL letters must be capitalized" in e.error.validation_error
                 assert len(e.message.structured_output_calls) == 0
 
-                args = PersonNotRestricted.model_validate_json(e.message.content)
+                args = PersonNotRestricted.model_validate_json(
+                    self.parse_content(e.message)
+                )
                 args.name = args.name.upper()
 
                 return ModelResponse(
diff --git a/tests/system/test_apps/ai_agentic_test_app/bin/agentic_endpoint.py b/tests/system/test_apps/ai_agentic_test_app/bin/agentic_endpoint.py
index 2b02b387..a81f1ff0 100644
--- a/tests/system/test_apps/ai_agentic_test_app/bin/agentic_endpoint.py
+++ b/tests/system/test_apps/ai_agentic_test_app/bin/agentic_endpoint.py
@@ -21,7 +21,13 @@
 from typing import override
 
 from splunklib.ai.agent import Agent
-from splunklib.ai.messages import HumanMessage
+from splunklib.ai.messages import (
+    AIMessage,
+    ContentBlock,
+    HumanMessage,
+    SubagentTextResult,
+    TextBlock,
+)
 from splunklib.ai.tool_settings import ToolSettings
 from tests.cre_testlib import CRETestHandler
 
@@ -58,5 +64,30 @@ async def run(self) -> None:
                 [HumanMessage(content="What is your name? Answer in one word")]
             )
 
-            response = result.final_message.content.strip().lower().replace(".", "")
+            response = (
+                self.parse_content(result.final_message)
+                .strip()
+                .lower()
+                .replace(".", "")
+            )
             self.response.write(response)
+
+    def _parse_content_block(self, block: str | ContentBlock) -> str | None:
+        match block:
+            case TextBlock():
+                return block.text
+            case str():
+                return block
+            case _:
+                return None
+
+    def parse_content(self, message: AIMessage | SubagentTextResult) -> str:
+        """Parses the content from AIMessage and builds a single string our of it"""
+        if isinstance(message.content, str):
+            return message.content
+
+        return " ".join(
+            parsed_block
+            for block in message.content
+            if (parsed_block := self._parse_content_block(block))
+        )
diff --git a/tests/system/test_apps/ai_agentic_test_local_tools_app/bin/agentic_app_tools_endpoint.py b/tests/system/test_apps/ai_agentic_test_local_tools_app/bin/agentic_app_tools_endpoint.py
index 044233e6..80928dc8 100644
--- a/tests/system/test_apps/ai_agentic_test_local_tools_app/bin/agentic_app_tools_endpoint.py
+++ b/tests/system/test_apps/ai_agentic_test_local_tools_app/bin/agentic_app_tools_endpoint.py
@@ -22,7 +22,13 @@
 from typing import override
 
 from splunklib.ai.agent import Agent
-from splunklib.ai.messages import HumanMessage
+from splunklib.ai.messages import (
+    AIMessage,
+    ContentBlock,
+    HumanMessage,
+    SubagentTextResult,
+    TextBlock,
+)
 from splunklib.ai.tool_settings import ToolSettings
 from tests.cre_testlib import CRETestHandler
 
@@ -75,5 +81,30 @@ async def run(self) -> None:
                 [HumanMessage(content="What is your name? Answer in one word")]
             )
 
-            response = result.final_message.content.strip().lower().replace(".", "")
+            response = (
+                self.parse_content(result.final_message)
+                .strip()
+                .lower()
+                .replace(".", "")
+            )
             self.response.write(response)
+
+    def _parse_content_block(self, block: str | ContentBlock) -> str | None:
+        match block:
+            case TextBlock():
+                return block.text
+            case str():
+                return block
+            case _:
+                return None
+
+    def parse_content(self, message: AIMessage | SubagentTextResult) -> str:
+        """Parses the content from AIMessage and builds a single string our of it"""
+        if isinstance(message.content, str):
+            return message.content
+
+        return " ".join(
+            parsed_block
+            for block in message.content
+            if (parsed_block := self._parse_content_block(block))
+        )
diff --git a/tests/unit/ai/engine/test_langchain_backend.py b/tests/unit/ai/engine/test_langchain_backend.py
index c02426bd..d4319896 100644
--- a/tests/unit/ai/engine/test_langchain_backend.py
+++ b/tests/unit/ai/engine/test_langchain_backend.py
@@ -30,10 +30,12 @@
 from splunklib.ai.messages import (
     AIMessage,
     HumanMessage,
+    OpaqueBlock,
     SubagentCall,
     SubagentFailureResult,
     SubagentMessage,
     SystemMessage,
+    TextBlock,
     ToolCall,
     ToolFailureResult,
     ToolMessage,
@@ -56,6 +58,95 @@ def test_map_message_from_langchain_ai_with_tool_calls(self) -> None:
             ToolCall(name="lookup", args={"q": "test"}, id="tc-1", type=ToolType.REMOTE)
         ]
 
+    def test_map_message_from_langchain_ai_with_text_content_block(self) -> None:
+        text_block = {
+            "type": "text",
+            "text": "test-content-block",
+            "extras": {
+                # simulate gemini model returning thought signature in extra field of text content block
+                "signature": "EjQKMgEMOdbHDmsQ+BTM6duYJ43i5npxkpn28Ir0VjD1p6w4fUqIdYszIcWx+XcqAW1a8E+Q"
+            },
+        }
+        message = LC_AIMessage(content=[text_block], tool_calls=[])
+
+        mapped = lc._map_message_from_langchain(message)
+
+        assert isinstance(mapped, AIMessage)
+        assert isinstance(mapped.content[0], TextBlock)
+        assert mapped.content[0].text == "test-content-block"
+
+    def test_map_message_from_langchain_ai_with_list_of_str(self) -> None:
+        message = LC_AIMessage(content=["one", "two"], tool_calls=[])
+
+        mapped = lc._map_message_from_langchain(message)
+
+        assert isinstance(mapped, AIMessage)
+        assert mapped.content == ["one", "two"]
+
+    def test_map_message_from_langchain_ai_with_other_content_block(self) -> None:
+        content_block = {
+            "type": "image",
+        }
+        message = LC_AIMessage(content=[content_block], tool_calls=[])
+
+        mapped = lc._map_message_from_langchain(message)
+
+        assert isinstance(mapped, AIMessage)
+        assert isinstance(mapped.content[0], OpaqueBlock)
+        assert mapped.content[0].data == content_block
+
+    def test_map_message_from_langchain_ai_with_mixed_content(self) -> None:
+        content_block = {
+            "type": "image",
+        }
+        text_block = {
+            "type": "text",
+            "text": "test",
+        }
+        message = LC_AIMessage(
+            content=[content_block, text_block, "test"], tool_calls=[]
+        )
+
+        mapped = lc._map_message_from_langchain(message)
+
+        assert isinstance(mapped, AIMessage)
+        assert isinstance(mapped.content[0], OpaqueBlock)
+        assert mapped.content[0].data == content_block
+        assert isinstance(mapped.content[1], TextBlock)
+        assert mapped.content[1].text == "test"
+        assert mapped.content[2] == "test"
+
+    def test_map_message_from_langchain_ai_tool_call_with_additional_kwargs(
+        self,
+    ) -> None:
+        tool_call = LC_ToolCall(
+            name=f"__local-startup_time",
+            args={"q": "test"},
+            id="tc-2",
+        )
+        # simulate gemini models returning thought signature in additional kwargs
+        # when calling tools.
+        additional_kwargs = {
+            "function_call": {"name": "__local-startup_time", "arguments": "{}"},
+            "__gemini_function_call_thought_signatures__": {
+                "28e28045-9846-4c9c-ab46-97f33bff5a9c": "EjQKMgEMOdbHH9gTl8BkX2uMM52753GCboanCcnUp9XB896IdThnG42GB8lRSkqGGxVbv5JY"
+            },
+        }
+        message = LC_AIMessage(
+            content="done", tool_calls=[tool_call], additional_kwargs=additional_kwargs
+        )
+        mapped = lc._map_message_from_langchain(message)
+        assert isinstance(mapped, AIMessage)
+        assert mapped.calls == [
+            ToolCall(
+                name="startup_time",
+                args={"q": "test"},
+                id="tc-2",
+                type=ToolType.LOCAL,
+            )
+        ]
+        assert mapped.extras == additional_kwargs
+
     def test_map_message_from_langchain_ai_with_agent_call(self) -> None:
         tool_call = LC_ToolCall(
             name=f"{lc.AGENT_PREFIX}assistant",
@@ -159,6 +250,69 @@ def test_map_message_to_langchain_ai(self) -> None:
         assert mapped.content == "hi"
         assert mapped.tool_calls == [LC_ToolCall(name="lookup", args={}, id="tc-1")]
 
+    def test_map_message_to_langchain_ai_with_text_content_block(self) -> None:
+        extras = {
+            "signature": "EjQKMgEMOdbHDmsQ+BTM6duYJ43i5npxkpn28Ir0VjD1p6w4fUqIdYszIcWx+XcqAW1a8E+Q"
+        }
+        message = AIMessage(
+            content=[
+                TextBlock(
+                    text="test-content-block",
+                    extras=extras,
+                )
+            ],
+            calls=[],
+        )
+        mapped = lc._map_message_to_langchain(message)
+
+        assert isinstance(mapped, LC_AIMessage)
+        assert isinstance(mapped.content[0], dict)
+        assert mapped.content[0]["type"] == "text"
+        assert mapped.content[0]["text"] == "test-content-block"
+        assert mapped.content[0]["extras"] == extras
+
+    def test_map_message_to_langchain_ai_with_list_of_str(self) -> None:
+        message = AIMessage(
+            content=["one", "two"],
+            calls=[],
+        )
+        mapped = lc._map_message_to_langchain(message)
+
+        assert isinstance(mapped, LC_AIMessage)
+        assert mapped.content == ["one", "two"]
+
+    def test_map_message_to_langchain_ai_with_opaque_content_block(self) -> None:
+        some_data = {"type": "unsupported"}
+        message = AIMessage(
+            content=[OpaqueBlock(data=some_data)],
+            calls=[],
+        )
+        mapped = lc._map_message_to_langchain(message)
+
+        assert isinstance(mapped, LC_AIMessage)
+        assert isinstance(mapped.content[0], dict)
+        assert mapped.content[0]["type"] == "unsupported"
+
+    def test_map_message_to_langchain_ai_with_mixed_content_block(self) -> None:
+        some_data = {"type": "unsupported"}
+        message = AIMessage(
+            content=[
+                OpaqueBlock(data=some_data),
+                TextBlock(text="test-content-block"),
+                "test",
+            ],
+            calls=[],
+        )
+        mapped = lc._map_message_to_langchain(message)
+
+        assert isinstance(mapped, LC_AIMessage)
+        assert isinstance(mapped.content[0], dict)
+        assert mapped.content[0]["type"] == "unsupported"
+        assert isinstance(mapped.content[1], dict)
+        assert mapped.content[1]["type"] == "text"
+        assert mapped.content[1]["text"] == "test-content-block"
+        assert mapped.content[2] == "test"
+
     def test_map_message_to_langchain_ai_with_agent_call(self) -> None:
         message = AIMessage(
             content="hi",
@@ -182,6 +336,42 @@ def test_map_message_to_langchain_ai_with_agent_call(self) -> None:
             )
         ]
 
+    def test_map_message_to_langchain_ai_with_tool_call_with_thought_signature(
+        self,
+    ) -> None:
+        extras = {
+            "function_call": {
+                "name": "__local-startup_time",
+                "arguments": '{"q": "test"}',
+            },
+            "__gemini_function_call_thought_signatures__": {
+                "28e28045-9846-4c9c-ab46-97f33bff5a9c": "EjQKMgEMOdbHH9gTl8BkX2uMM52753GCboanCcnUp9XB896IdThnG42GB8lRSkqGGxVbv5JY"
+            },
+        }
+        message = AIMessage(
+            content="hi",
+            calls=[
+                ToolCall(
+                    name="startup_time",
+                    args={"q": "test"},
+                    id="tc-2",
+                    type=ToolType.LOCAL,
+                )
+            ],
+            extras=extras,
+        )
+        mapped = lc._map_message_to_langchain(message)
+
+        assert isinstance(mapped, LC_AIMessage)
+        assert mapped.tool_calls == [
+            LC_ToolCall(
+                name=f"__local-startup_time",
+                args={"q": "test"},
+                id="tc-2",
+            )
+        ]
+        assert mapped.additional_kwargs == extras
+
     def test_map_message_to_langchain_human(self) -> None:
         message = HumanMessage(content="hello")
         mapped = lc._map_message_to_langchain(message)