From fbfe4b812de119ec8e233627d88422727c823c35 Mon Sep 17 00:00:00 2001
From: ccurme <chester.curme@gmail.com>
Date: Sun, 8 Mar 2026 08:53:13 -0400
Subject: [PATCH] feat(openai): support tool search (#35582)

---
 .../messages/block_translators/openai.py      |  50 ++++
 .../langchain_core/utils/function_calling.py  |   2 +
 .../langchain_openai/chat_models/_compat.py   |  53 +++-
 .../langchain_openai/chat_models/base.py      |  20 +-
 .../tests/cassettes/test_agent_loop.yaml.gz   | Bin 0 -> 2572 bytes
 .../test_agent_loop_streaming.yaml.gz         | Bin 0 -> 5822 bytes
 .../test_client_executed_tool_search.yaml.gz  | Bin 0 -> 4765 bytes
 .../tests/cassettes/test_tool_search.yaml.gz  | Bin 0 -> 3675 bytes
 .../test_tool_search_streaming.yaml.gz        | Bin 0 -> 6814 bytes
 libs/partners/openai/tests/conftest.py        |  22 ++
 .../chat_models/test_responses_api.py         | 258 ++++++++++++++++++
 .../tests/unit_tests/chat_models/test_base.py | 114 +++++++-
 libs/partners/openai/uv.lock                  |   8 +-
 13 files changed, 514 insertions(+), 13 deletions(-)
 create mode 100644 libs/partners/openai/tests/cassettes/test_agent_loop.yaml.gz
 create mode 100644 libs/partners/openai/tests/cassettes/test_agent_loop_streaming.yaml.gz
 create mode 100644 libs/partners/openai/tests/cassettes/test_client_executed_tool_search.yaml.gz
 create mode 100644 libs/partners/openai/tests/cassettes/test_tool_search.yaml.gz
 create mode 100644 libs/partners/openai/tests/cassettes/test_tool_search_streaming.yaml.gz

diff --git a/libs/core/langchain_core/messages/block_translators/openai.py b/libs/core/langchain_core/messages/block_translators/openai.py
index 5bcb3a6bfd7..61d4e3c3d0a 100644
--- a/libs/core/langchain_core/messages/block_translators/openai.py
+++ b/libs/core/langchain_core/messages/block_translators/openai.py
@@ -731,6 +731,11 @@ def _convert_to_v1_from_responses(message: AIMessage) -> list[types.ContentBlock
                         tool_call_block["extras"]["item_id"] = block["id"]
                     if "index" in block:
                         tool_call_block["index"] = f"lc_tc_{block['index']}"
+                    for extra_key in ("status", "namespace"):
+                        if extra_key in block:
+                            if "extras" not in tool_call_block:
+                                tool_call_block["extras"] = {}
+                            tool_call_block["extras"][extra_key] = block[extra_key]
                     yield tool_call_block
 
             elif block_type == "web_search_call":
@@ -979,6 +984,51 @@ def _convert_to_v1_from_responses(message: AIMessage) -> list[types.ContentBlock
                     mcp_list_tools_result["index"] = f"lc_mltr_{block['index'] + 1}"
                 yield cast("types.ServerToolResult", mcp_list_tools_result)
 
+            elif (
+                block_type == "tool_search_call" and block.get("execution") == "server"
+            ):
+                tool_search_call: dict[str, Any] = {
+                    "type": "server_tool_call",
+                    "name": "tool_search",
+                    "id": block["id"],
+                    "args": block.get("arguments", {}),
+                }
+                if "index" in block:
+                    tool_search_call["index"] = f"lc_tsc_{block['index']}"
+                extras: dict[str, Any] = {}
+                known = {"type", "id", "arguments", "index"}
+                for key in block:
+                    if key not in known:
+                        extras[key] = block[key]
+                if extras:
+                    tool_search_call["extras"] = extras
+                yield cast("types.ServerToolCall", tool_search_call)
+
+            elif (
+                block_type == "tool_search_output"
+                and block.get("execution") == "server"
+            ):
+                tool_search_output: dict[str, Any] = {
+                    "type": "server_tool_result",
+                    "tool_call_id": block["id"],
+                    "output": {"tools": block.get("tools", [])},
+                }
+                status = block.get("status")
+                if status == "failed":
+                    tool_search_output["status"] = "error"
+                elif status == "completed":
+                    tool_search_output["status"] = "success"
+                if "index" in block and isinstance(block["index"], int):
+                    tool_search_output["index"] = f"lc_tso_{block['index']}"
+                extras_out: dict[str, Any] = {"name": "tool_search"}
+                known_out = {"type", "id", "status", "tools", "index"}
+                for key in block:
+                    if key not in known_out:
+                        extras_out[key] = block[key]
+                if extras_out:
+                    tool_search_output["extras"] = extras_out
+                yield cast("types.ServerToolResult", tool_search_output)
+
             elif block_type in types.KNOWN_BLOCK_TYPES:
                 yield cast("types.ContentBlock", block)
             else:
diff --git a/libs/core/langchain_core/utils/function_calling.py b/libs/core/langchain_core/utils/function_calling.py
index cda5569f795..7c91b84ee8a 100644
--- a/libs/core/langchain_core/utils/function_calling.py
+++ b/libs/core/langchain_core/utils/function_calling.py
@@ -508,6 +508,8 @@ _WellKnownOpenAITools = (
     "image_generation",
     "web_search_preview",
     "web_search",
+    "tool_search",
+    "namespace",
 )
 
 
diff --git a/libs/partners/openai/langchain_openai/chat_models/_compat.py b/libs/partners/openai/langchain_openai/chat_models/_compat.py
index 642cafe6e1c..35f0aac554a 100644
--- a/libs/partners/openai/langchain_openai/chat_models/_compat.py
+++ b/libs/partners/openai/langchain_openai/chat_models/_compat.py
@@ -103,6 +103,8 @@ def _convert_to_v03_ai_message(
                     "mcp_list_tools",
                     "mcp_approval_request",
                     "image_generation_call",
+                    "tool_search_call",
+                    "tool_search_output",
                 ):
                     # Store built-in tool calls in additional_kwargs
                     if "tool_outputs" not in message.additional_kwargs:
@@ -420,17 +422,58 @@ def _convert_from_v1_to_responses(
                 new_block["name"] = block["name"]
             if "extras" in block and "arguments" in block["extras"]:
                 new_block["arguments"] = block["extras"]["arguments"]
-            if any(key not in block for key in ("name", "arguments")):
+            if any(key not in new_block for key in ("name", "arguments")):
                 matching_tool_calls = [
                     call for call in tool_calls if call["id"] == block["id"]
                 ]
                 if matching_tool_calls:
                     tool_call = matching_tool_calls[0]
-                    if "name" not in block:
+                    if "name" not in new_block:
                         new_block["name"] = tool_call["name"]
-                    if "arguments" not in block:
-                        new_block["arguments"] = json.dumps(tool_call["args"])
+                    if "arguments" not in new_block:
+                        new_block["arguments"] = json.dumps(
+                            tool_call["args"], separators=(",", ":")
+                        )
+            if "extras" in block:
+                for extra_key in ("status", "namespace"):
+                    if extra_key in block["extras"]:
+                        new_block[extra_key] = block["extras"][extra_key]
             new_content.append(new_block)
+
+        elif block["type"] == "server_tool_call" and block.get("name") == "tool_search":
+            extras = block.get("extras", {})
+            new_block = {"id": block["id"]}
+            status = extras.get("status")
+            if status:
+                new_block["status"] = status
+            new_block["type"] = "tool_search_call"
+            if "args" in block:
+                new_block["arguments"] = block["args"]
+            execution = extras.get("execution")
+            if execution:
+                new_block["execution"] = execution
+            new_content.append(new_block)
+
+        elif (
+            block["type"] == "server_tool_result"
+            and block.get("extras", {}).get("name") == "tool_search"
+        ):
+            extras = block.get("extras", {})
+            new_block = {"id": block.get("tool_call_id", "")}
+            status = block.get("status")
+            if status == "success":
+                new_block["status"] = "completed"
+            elif status == "error":
+                new_block["status"] = "failed"
+            elif status:
+                new_block["status"] = status
+            new_block["type"] = "tool_search_output"
+            new_block["execution"] = "server"
+            output: dict = block.get("output", {})
+            if isinstance(output, dict) and "tools" in output:
+                new_block["tools"] = output["tools"]
+            new_content.append(new_block)
+
         elif (
             is_data_content_block(cast(dict, block))
             and block["type"] == "image"
@@ -441,7 +484,7 @@ def _convert_from_v1_to_responses(
             new_block = {"type": "image_generation_call", "result": block["base64"]}
             for extra_key in ("id", "status"):
                 if extra_key in block:
-                    new_block[extra_key] = block[extra_key]  # type: ignore[typeddict-item]
+                    new_block[extra_key] = block[extra_key]  # type: ignore[literal-required]
                 elif extra_key in block.get("extras", {}):
                     new_block[extra_key] = block["extras"][extra_key]
             new_content.append(new_block)
diff --git a/libs/partners/openai/langchain_openai/chat_models/base.py b/libs/partners/openai/langchain_openai/chat_models/base.py
index 4351bd529b7..beb62c65578 100644
--- a/libs/partners/openai/langchain_openai/chat_models/base.py
+++ b/libs/partners/openai/langchain_openai/chat_models/base.py
@@ -166,6 +166,7 @@ WellKnownTools = (
     "code_interpreter",
     "mcp",
     "image_generation",
+    "tool_search",
 )
 
 
@@ -1984,6 +1985,14 @@ class BaseChatOpenAI(BaseChatModel):
         formatted_tools = [
             convert_to_openai_tool(tool, strict=strict) for tool in tools
         ]
+        for original, formatted in zip(tools, formatted_tools, strict=False):
+            if (
+                isinstance(original, BaseTool)
+                and hasattr(original, "extras")
+                and isinstance(original.extras, dict)
+                and "defer_loading" in original.extras
+            ):
+                formatted["defer_loading"] = original.extras["defer_loading"]
         tool_names = []
         for tool in formatted_tools:
             if "function" in tool:
@@ -3981,7 +3990,8 @@ def _construct_responses_api_payload(
             # chat api: {"type": "function", "function": {"name": "...", "description": "...", "parameters": {...}, "strict": ...}}  # noqa: E501
             # responses api: {"type": "function", "name": "...", "description": "...", "parameters": {...}, "strict": ...}  # noqa: E501
             if tool["type"] == "function" and "function" in tool:
-                new_tools.append({"type": "function", **tool["function"]})
+                extra = {k: v for k, v in tool.items() if k not in ("type", "function")}
+                new_tools.append({"type": "function", **tool["function"], **extra})
             else:
                 if tool["type"] == "image_generation":
                     # Handle partial images (not yet supported)
@@ -4308,6 +4318,8 @@ def _construct_responses_api_input(messages: Sequence[BaseMessage]) -> list:
                             "mcp_call",
                             "mcp_list_tools",
                             "mcp_approval_request",
+                            "tool_search_call",
+                            "tool_search_output",
                         ):
                             input_.append(_pop_index_and_sub_index(block))
                         elif block_type == "image_generation_call":
@@ -4353,7 +4365,7 @@ def _construct_responses_api_input(messages: Sequence[BaseMessage]) -> list:
         elif msg["role"] in ("user", "system", "developer"):
             if isinstance(msg["content"], list):
                 new_blocks = []
-                non_message_item_types = ("mcp_approval_response",)
+                non_message_item_types = ("mcp_approval_response", "tool_search_output")
                 for block in msg["content"]:
                     if block["type"] in ("text", "image_url", "file"):
                         new_blocks.append(
@@ -4510,6 +4522,8 @@ def _construct_lc_result_from_responses_api(
             "mcp_list_tools",
             "mcp_approval_request",
             "image_generation_call",
+            "tool_search_call",
+            "tool_search_output",
         ):
             content_blocks.append(output.model_dump(exclude_none=True, mode="json"))
 
@@ -4719,6 +4733,8 @@ def _convert_responses_chunk_to_generation_chunk(
         "mcp_list_tools",
         "mcp_approval_request",
         "image_generation_call",
+        "tool_search_call",
+        "tool_search_output",
     ):
         _advance(chunk.output_index)
         tool_output = chunk.item.model_dump(exclude_none=True, mode="json")
diff --git a/libs/partners/openai/tests/cassettes/test_agent_loop.yaml.gz b/libs/partners/openai/tests/cassettes/test_agent_loop.yaml.gz
new file mode 100644
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diff --git a/libs/partners/openai/tests/cassettes/test_agent_loop_streaming.yaml.gz b/libs/partners/openai/tests/cassettes/test_agent_loop_streaming.yaml.gz
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diff --git a/libs/partners/openai/tests/cassettes/test_client_executed_tool_search.yaml.gz b/libs/partners/openai/tests/cassettes/test_client_executed_tool_search.yaml.gz
new file mode 100644
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HcmV?d00001

diff --git a/libs/partners/openai/tests/conftest.py b/libs/partners/openai/tests/conftest.py
index af85f90c10a..748df9beea0 100644
--- a/libs/partners/openai/tests/conftest.py
+++ b/libs/partners/openai/tests/conftest.py
@@ -1,3 +1,4 @@
+import json
 from typing import Any
 
 import pytest
@@ -30,6 +31,9 @@ def remove_response_headers(response: dict) -> dict:
 def vcr_config() -> dict:
     """Extend the default configuration coming from langchain_tests."""
     config = base_vcr_config()
+    config["match_on"] = [
+        m if m != "body" else "json_body" for m in config.get("match_on", [])
+    ]
     config.setdefault("filter_headers", []).extend(_EXTRA_HEADERS)
     config["before_record_request"] = remove_request_headers
     config["before_record_response"] = remove_response_headers
@@ -38,6 +42,24 @@ def vcr_config() -> dict:
     return config
 
 
+def _json_body_matcher(r1: Any, r2: Any) -> None:
+    """Match request bodies as parsed JSON, ignoring key order."""
+    b1 = r1.body or b""
+    b2 = r2.body or b""
+    if isinstance(b1, bytes):
+        b1 = b1.decode("utf-8")
+    if isinstance(b2, bytes):
+        b2 = b2.decode("utf-8")
+    try:
+        j1 = json.loads(b1)
+        j2 = json.loads(b2)
+    except (json.JSONDecodeError, ValueError):
+        assert b1 == b2, f"body mismatch (non-JSON):\n{b1}\n!=\n{b2}"
+        return
+    assert j1 == j2, f"body mismatch:\n{j1}\n!=\n{j2}"
+
+
 def pytest_recording_configure(config: dict, vcr: VCR) -> None:
     vcr.register_persister(CustomPersister())
     vcr.register_serializer("yaml.gz", CustomSerializer())
+    vcr.register_matcher("json_body", _json_body_matcher)
diff --git a/libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py b/libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py
index 56c9e4595f7..98bea67c81a 100644
--- a/libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py
+++ b/libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py
@@ -7,6 +7,13 @@ from typing import Annotated, Any, Literal, cast
 
 import openai
 import pytest
+from langchain.agents import create_agent
+from langchain.agents.middleware.types import (
+    AgentMiddleware,
+    AgentState,
+    ToolCallRequest,
+    hook_config,
+)
 from langchain_core.messages import (
     AIMessage,
     AIMessageChunk,
@@ -14,7 +21,10 @@ from langchain_core.messages import (
     BaseMessageChunk,
     HumanMessage,
     MessageLikeRepresentation,
+    ToolMessage,
 )
+from langchain_core.tools import tool
+from langchain_core.utils.function_calling import convert_to_openai_tool
 from pydantic import BaseModel
 from typing_extensions import TypedDict
 
@@ -193,6 +203,74 @@ def test_function_calling(output_version: Literal["v0", "responses/v1", "v1"]) -
     _check_response(response)
 
 
+@pytest.mark.default_cassette("test_agent_loop.yaml.gz")
+@pytest.mark.vcr
+@pytest.mark.parametrize("output_version", ["responses/v1", "v1"])
+def test_agent_loop(output_version: Literal["responses/v1", "v1"]) -> None:
+    @tool
+    def get_weather(location: str) -> str:
+        """Get the weather for a location."""
+        return "It's sunny."
+
+    llm = ChatOpenAI(
+        model="gpt-5.4",
+        use_responses_api=True,
+        output_version=output_version,
+    )
+    llm_with_tools = llm.bind_tools([get_weather])
+    input_message = HumanMessage("What is the weather in San Francisco, CA?")
+    tool_call_message = llm_with_tools.invoke([input_message])
+    assert isinstance(tool_call_message, AIMessage)
+    tool_calls = tool_call_message.tool_calls
+    assert len(tool_calls) == 1
+    tool_call = tool_calls[0]
+    tool_message = get_weather.invoke(tool_call)
+    assert isinstance(tool_message, ToolMessage)
+    response = llm_with_tools.invoke(
+        [
+            input_message,
+            tool_call_message,
+            tool_message,
+        ]
+    )
+    assert isinstance(response, AIMessage)
+
+
+@pytest.mark.default_cassette("test_agent_loop_streaming.yaml.gz")
+@pytest.mark.vcr
+@pytest.mark.parametrize("output_version", ["responses/v1", "v1"])
+def test_agent_loop_streaming(output_version: Literal["responses/v1", "v1"]) -> None:
+    @tool
+    def get_weather(location: str) -> str:
+        """Get the weather for a location."""
+        return "It's sunny."
+
+    llm = ChatOpenAI(
+        model="gpt-5.2",
+        use_responses_api=True,
+        reasoning={"effort": "medium", "summary": "auto"},
+        streaming=True,
+        output_version=output_version,
+    )
+    llm_with_tools = llm.bind_tools([get_weather])
+    input_message = HumanMessage("What is the weather in San Francisco, CA?")
+    tool_call_message = llm_with_tools.invoke([input_message])
+    assert isinstance(tool_call_message, AIMessage)
+    tool_calls = tool_call_message.tool_calls
+    assert len(tool_calls) == 1
+    tool_call = tool_calls[0]
+    tool_message = get_weather.invoke(tool_call)
+    assert isinstance(tool_message, ToolMessage)
+    response = llm_with_tools.invoke(
+        [
+            input_message,
+            tool_call_message,
+            tool_message,
+        ]
+    )
+    assert isinstance(response, AIMessage)
+
+
 class Foo(BaseModel):
     response: str
 
@@ -1267,3 +1345,183 @@ def test_csv_input() -> None:
         "3" in str(response2.content).lower()
         or "three" in str(response2.content).lower()
     )
+
+
+@pytest.mark.default_cassette("test_tool_search.yaml.gz")
+@pytest.mark.vcr
+@pytest.mark.parametrize("output_version", ["responses/v1", "v1"])
+def test_tool_search(output_version: str) -> None:
+    @tool(extras={"defer_loading": True})
+    def get_weather(location: str) -> str:
+        """Get the current weather for a location."""
+        return f"The weather in {location} is sunny and 72°F"
+
+    @tool(extras={"defer_loading": True})
+    def get_recipe(query: str) -> None:
+        """Get a recipe for chicken soup."""
+
+    model = ChatOpenAI(
+        model="gpt-5.4",
+        use_responses_api=True,
+        output_version=output_version,
+    )
+
+    agent = create_agent(
+        model=model,
+        tools=[get_weather, get_recipe, {"type": "tool_search"}],
+    )
+    input_message = {"role": "user", "content": "What's the weather in San Francisco?"}
+    result = agent.invoke({"messages": [input_message]})
+    assert len(result["messages"]) == 4
+    tool_call_message = result["messages"][1]
+    assert isinstance(tool_call_message, AIMessage)
+    assert tool_call_message.tool_calls
+    if output_version == "v1":
+        assert [block["type"] for block in tool_call_message.content] == [  # type: ignore[index]
+            "server_tool_call",
+            "server_tool_result",
+            "tool_call",
+        ]
+    else:
+        assert [block["type"] for block in tool_call_message.content] == [  # type: ignore[index]
+            "tool_search_call",
+            "tool_search_output",
+            "function_call",
+        ]
+
+    assert isinstance(result["messages"][2], ToolMessage)
+
+    assert result["messages"][3].text
+
+
+@pytest.mark.default_cassette("test_tool_search_streaming.yaml.gz")
+@pytest.mark.vcr
+@pytest.mark.parametrize("output_version", ["responses/v1", "v1"])
+def test_tool_search_streaming(output_version: str) -> None:
+    @tool(extras={"defer_loading": True})
+    def get_weather(location: str) -> str:
+        """Get the current weather for a location."""
+        return f"The weather in {location} is sunny and 72°F"
+
+    @tool(extras={"defer_loading": True})
+    def get_recipe(query: str) -> None:
+        """Get a recipe for chicken soup."""
+
+    model = ChatOpenAI(
+        model="gpt-5.4",
+        use_responses_api=True,
+        streaming=True,
+        output_version=output_version,
+    )
+
+    agent = create_agent(
+        model=model,
+        tools=[get_weather, get_recipe, {"type": "tool_search"}],
+    )
+    input_message = {"role": "user", "content": "What's the weather in San Francisco?"}
+    result = agent.invoke({"messages": [input_message]})
+    assert len(result["messages"]) == 4
+    tool_call_message = result["messages"][1]
+    assert isinstance(tool_call_message, AIMessage)
+    assert tool_call_message.tool_calls
+    if output_version == "v1":
+        assert [block["type"] for block in tool_call_message.content] == [  # type: ignore[index]
+            "server_tool_call",
+            "server_tool_result",
+            "tool_call",
+        ]
+    else:
+        assert [block["type"] for block in tool_call_message.content] == [  # type: ignore[index]
+            "tool_search_call",
+            "tool_search_output",
+            "function_call",
+        ]
+
+    assert isinstance(result["messages"][2], ToolMessage)
+
+    assert result["messages"][3].text
+
+
+@pytest.mark.vcr
+def test_client_executed_tool_search() -> None:
+    @tool
+    def get_weather(location: str) -> str:
+        """Get the current weather for a location."""
+        return f"The weather in {location} is sunny and 72°F"
+
+    def search_tools(goal: str) -> list[dict]:
+        """Search for available tools to help answer the question."""
+        return [
+            {
+                "type": "function",
+                "defer_loading": True,
+                **convert_to_openai_tool(get_weather)["function"],
+            }
+        ]
+
+    tool_search_schema = convert_to_openai_tool(search_tools, strict=True)
+    tool_search_config: dict = {
+        "type": "tool_search",
+        "execution": "client",
+        "description": tool_search_schema["function"]["description"],
+        "parameters": tool_search_schema["function"]["parameters"],
+    }
+
+    class ClientToolSearchMiddleware(AgentMiddleware):
+        @hook_config(can_jump_to=["model"])
+        def after_model(self, state: AgentState, runtime: Any) -> dict[str, Any] | None:
+            last_message = state["messages"][-1]
+            if not isinstance(last_message, AIMessage):
+                return None
+            for block in last_message.content:
+                if isinstance(block, dict) and block.get("type") == "tool_search_call":
+                    call_id = block.get("call_id")
+                    args = block.get("arguments", {})
+                    goal = args.get("goal", "") if isinstance(args, dict) else ""
+                    loaded_tools = search_tools(goal)
+                    tool_search_output = {
+                        "type": "tool_search_output",
+                        "execution": "client",
+                        "call_id": call_id,
+                        "status": "completed",
+                        "tools": loaded_tools,
+                    }
+                    return {
+                        "messages": [HumanMessage(content=[tool_search_output])],
+                        "jump_to": "model",
+                    }
+            return None
+
+        def wrap_tool_call(
+            self,
+            request: ToolCallRequest,
+            handler: Any,
+        ) -> Any:
+            if request.tool_call["name"] == "get_weather":
+                return handler(request.override(tool=get_weather))
+            return handler(request)
+
+    llm = ChatOpenAI(model="gpt-5.4", use_responses_api=True)
+
+    agent = create_agent(
+        model=llm,
+        tools=[tool_search_config],
+        middleware=[ClientToolSearchMiddleware()],
+    )
+
+    result = agent.invoke(
+        {"messages": [HumanMessage("What's the weather in San Francisco?")]}
+    )
+    messages = result["messages"]
+    search_tool_call = messages[1]
+    assert search_tool_call.content[0]["type"] == "tool_search_call"
+
+    search_tool_output = messages[2]
+    assert search_tool_output.content[0]["type"] == "tool_search_output"
+
+    tool_call = messages[3]
+    assert tool_call.tool_calls
+
+    assert isinstance(messages[4], ToolMessage)
+
+    assert messages[5].text
diff --git a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py
index 0f2e6ec7129..a7df5fce6ad 100644
--- a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py
+++ b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py
@@ -2787,13 +2787,13 @@ def test_convert_from_v1_to_chat_completions(
                     "type": "function_call",
                     "call_id": "call_123",
                     "name": "get_weather",
-                    "arguments": '{"location": "San Francisco"}',
+                    "arguments": '{"location":"San Francisco"}',
                 },
                 {
                     "type": "function_call",
                     "call_id": "call_234",
                     "name": "get_weather_2",
-                    "arguments": '{"location": "New York"}',
+                    "arguments": '{"location":"New York"}',
                     "id": "fc_123",
                 },
                 {"type": "text", "text": "Hello "},
@@ -3474,3 +3474,113 @@ def test_context_overflow_error_backwards_compatibility() -> None:
     # Verify it's both types (multiple inheritance)
     assert isinstance(exc_info.value, openai.BadRequestError)
     assert isinstance(exc_info.value, ContextOverflowError)
+
+
+def test_tool_search_passthrough() -> None:
+    """Test that tool_search dict is passed through as a built-in tool."""
+    llm = ChatOpenAI(model="gpt-4o")
+    tool_search = {"type": "tool_search"}
+    bound = llm.bind_tools([tool_search])
+    payload = bound._get_request_payload(  # type: ignore[attr-defined]
+        "test",
+        **bound.kwargs,  # type: ignore[attr-defined]
+    )
+    assert {"type": "tool_search"} in payload["tools"]
+    assert "input" in payload
+
+
+def test_tool_search_with_defer_loading_extras() -> None:
+    """Test that defer_loading from BaseTool extras is merged into tool defs."""
+    from langchain_core.tools import tool
+
+    @tool(extras={"defer_loading": True})
+    def get_weather(location: str) -> str:
+        """Get weather for a location."""
+        return f"Weather in {location}"
+
+    llm = ChatOpenAI(model="gpt-4o")
+    bound = llm.bind_tools([get_weather, {"type": "tool_search"}])
+    payload = bound._get_request_payload(  # type: ignore[attr-defined]
+        "test",
+        **bound.kwargs,  # type: ignore[attr-defined]
+    )
+    weather_tool = None
+    for t in payload["tools"]:
+        if t.get("type") == "function" and t.get("name") == "get_weather":
+            weather_tool = t
+            break
+    assert weather_tool is not None
+    assert weather_tool["defer_loading"] is True
+    assert {"type": "tool_search"} in payload["tools"]
+
+
+def test_namespace_passthrough() -> None:
+    """Test that namespace tool dicts are passed through unchanged."""
+    llm = ChatOpenAI(model="gpt-4o")
+    namespace_tool = {
+        "type": "namespace",
+        "name": "crm",
+        "description": "CRM tools.",
+        "tools": [
+            {
+                "type": "function",
+                "name": "list_orders",
+                "description": "List orders.",
+                "defer_loading": True,
+                "parameters": {
+                    "type": "object",
+                    "properties": {"customer_id": {"type": "string"}},
+                    "required": ["customer_id"],
+                },
+            }
+        ],
+    }
+    bound = llm.bind_tools([namespace_tool, {"type": "tool_search"}])
+    payload = bound._get_request_payload(  # type: ignore[attr-defined]
+        "test",
+        **bound.kwargs,  # type: ignore[attr-defined]
+    )
+    ns = None
+    for t in payload["tools"]:
+        if t.get("type") == "namespace":
+            ns = t
+            break
+    assert ns is not None
+    assert ns["name"] == "crm"
+    assert ns["tools"][0]["defer_loading"] is True
+    assert {"type": "tool_search"} in payload["tools"]
+
+
+def test_defer_loading_in_responses_api_payload() -> None:
+    """Test that defer_loading is preserved in Responses API tool format."""
+    from langchain_openai.chat_models.base import _construct_responses_api_payload
+
+    messages: list = []
+    payload = {
+        "model": "gpt-4o",
+        "tools": [
+            {
+                "type": "function",
+                "function": {
+                    "name": "get_weather",
+                    "description": "Get weather.",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {"location": {"type": "string"}},
+                    },
+                },
+                "defer_loading": True,
+            },
+            {"type": "tool_search"},
+        ],
+    }
+    result = _construct_responses_api_payload(messages, payload)
+    weather_tool = None
+    for t in result["tools"]:
+        if t.get("name") == "get_weather":
+            weather_tool = t
+            break
+    assert weather_tool is not None
+    assert weather_tool["defer_loading"] is True
+    assert weather_tool["type"] == "function"
+    assert {"type": "tool_search"} in result["tools"]
diff --git a/libs/partners/openai/uv.lock b/libs/partners/openai/uv.lock
index d203c59d3d8..f71847bbbe7 100644
--- a/libs/partners/openai/uv.lock
+++ b/libs/partners/openai/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10.0, <4.0.0"
 resolution-markers = [
     "python_full_version >= '3.13' and platform_python_implementation == 'PyPy'",
@@ -1105,7 +1105,7 @@ wheels = [
 
 [[package]]
 name = "openai"
-version = "2.21.0"
+version = "2.26.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "anyio" },
@@ -1117,9 +1117,9 @@ dependencies = [
     { name = "tqdm" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/92/e5/3d197a0947a166649f566706d7a4c8f7fe38f1fa7b24c9bcffe4c7591d44/openai-2.21.0.tar.gz", hash = "sha256:81b48ce4b8bbb2cc3af02047ceb19561f7b1dc0d4e52d1de7f02abfd15aa59b7", size = 644374, upload-time = "2026-02-14T00:12:01.577Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/d7/91/2a06c4e9597c338cac1e5e5a8dd6f29e1836fc229c4c523529dca387fda8/openai-2.26.0.tar.gz", hash = "sha256:b41f37c140ae0034a6e92b0c509376d907f3a66109935fba2c1b471a7c05a8fb", size = 666702, upload-time = "2026-03-05T23:17:35.874Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/cc/56/0a89092a453bb2c676d66abee44f863e742b2110d4dbb1dbcca3f7e5fc33/openai-2.21.0-py3-none-any.whl", hash = "sha256:0bc1c775e5b1536c294eded39ee08f8407656537ccc71b1004104fe1602e267c", size = 1103065, upload-time = "2026-02-14T00:11:59.603Z" },
+    { url = "https://files.pythonhosted.org/packages/c6/2e/3f73e8ca53718952222cacd0cf7eecc9db439d020f0c1fe7ae717e4e199a/openai-2.26.0-py3-none-any.whl", hash = "sha256:6151bf8f83802f036117f06cc8a57b3a4da60da9926826cc96747888b57f394f", size = 1136409, upload-time = "2026-03-05T23:17:34.072Z" },
 ]
 
 [[package]]