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feat(openai): support apply_patch built-in tool (#37157)

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[Docs](https://github.com/langchain-ai/docs/pull/4370)

Fixes #37031

Adds support for OpenAI Responses API `apply_patch` built-in tool.

This PR:
- Adds `apply_patch` to the OpenAI well-known tools list so
`bind_tools([{"type": "apply_patch"}])` works.
- Preserves `apply_patch_call` and `apply_patch_call_output` items when
converting OpenAI Responses API outputs into LangChain
`AIMessage.content`.
- Preserves the same item types in streaming `AIMessageChunk`
conversion.
- Supports round-trip input conversion for `apply_patch_call` and
`apply_patch_call_output`.
- Adds unit tests for core tool passthrough, non-streaming conversion,
streaming conversion, and round-trip input conversion.

## Testing

- `cd libs/core && uv run --group test pytest
tests/unit_tests/utils/test_function_calling.py -k "apply_patch" -vv`
- `cd libs/partners/openai && uv run --group test pytest
tests/unit_tests/chat_models/test_base.py -k "apply_patch" -vv`
- `cd libs/core && uv run --all-groups ruff check
langchain_core/utils/function_calling.py
tests/unit_tests/utils/test_function_calling.py`
- `cd libs/partners/openai && uv run --all-groups ruff check
langchain_openai/chat_models/base.py
tests/unit_tests/chat_models/test_base.py`

---------

Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
This commit is contained in:
Nidhi Rajani
2026-06-09 16:13:37 -04:00
committed by GitHub
parent 7e9c916c7e
commit 0f45b2c285
9 changed files with 401 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
libs/core/langchain_core/utils/function_calling.py
View File

@@ -508,6 +508,7 @@ _WellKnownOpenAITools = (
"web_search_preview",
"web_search",
"tool_search",
"apply_patch",
"namespace",
)
@@ -546,7 +547,7 @@ def convert_to_openai_tool(
Return OpenAI Responses API-style tools unchanged. This includes
any dict with `"type"` in `"file_search"`, `"function"`,
`"computer_use_preview"`, `"web_search_preview"`.
`"computer_use_preview"`, `"web_search_preview"`, `"apply_patch"`.
!!! warning "Behavior changed in `langchain-core` 0.3.63"

9
libs/core/tests/unit_tests/utils/test_function_calling.py
View File

@@ -1245,6 +1245,15 @@ def test_convert_to_openai_function_json_schema_missing_title_includes_schema()
convert_to_openai_function(schema_without_title)
def test_convert_to_openai_tool_apply_patch_passthrough() -> None:
"""Test apply_patch is passed through as an OpenAI built-in tool."""
tool = {"type": "apply_patch"}
result = convert_to_openai_tool(tool)
assert result == tool
def test_convert_to_openai_tool_computer_passthrough() -> None:
"""Test that the 'computer' tool type is passed through unchanged."""
computer_tool = {

2
libs/langchain_v1/uv.lock generated
View File

@@ -2225,7 +2225,7 @@ wheels = [
[[package]]
name = "langchain-core"
version = "1.4.1"
version = "1.4.2"
source = { editable = "../core" }
dependencies = [
{ name = "jsonpatch" },

6
libs/partners/openai/langchain_openai/chat_models/_compat.py
View File

@@ -105,6 +105,8 @@ def _convert_to_v03_ai_message(
"image_generation_call",
"tool_search_call",
"tool_search_output",
"apply_patch_call",
"apply_patch_call_output",
):
# Store built-in tool calls in additional_kwargs
if "tool_outputs" not in message.additional_kwargs:
@@ -285,11 +287,11 @@ def _consolidate_calls(items: Iterable[dict[str, Any]]) -> Iterator[dict[str, An
try:
nxt = next(items) # look-ahead one element
except StopIteration: # no “result” - just yield the call back
except StopIteration: # no "result" - just yield the call back
yield current
break
# If this really is the matching “result” - collapse
# If this really is the matching "result" - collapse
if nxt.get("type") == "server_tool_result" and nxt.get(
"tool_call_id"
) == current.get("id"):

13
libs/partners/openai/langchain_openai/chat_models/base.py
View File

@@ -192,6 +192,7 @@ WellKnownTools = (
"mcp",
"image_generation",
"tool_search",
"apply_patch",
)
@@ -4490,6 +4491,8 @@ def _construct_responses_api_input(messages: Sequence[BaseMessage]) -> list:
"mcp_approval_request",
"tool_search_call",
"tool_search_output",
"apply_patch_call",
"apply_patch_call_output",
):
input_.append(_pop_index_and_sub_index(block))
elif block_type == "image_generation_call":
@@ -4535,7 +4538,11 @@ 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", "tool_search_output")
non_message_item_types = (
"mcp_approval_response",
"tool_search_output",
"apply_patch_call_output",
)
for block in msg["content"]:
if block["type"] in ("text", "image_url", "file"):
new_blocks.append(
@@ -4704,6 +4711,8 @@ def _construct_lc_result_from_responses_api(
"image_generation_call",
"tool_search_call",
"tool_search_output",
"apply_patch_call",
"apply_patch_call_output",
):
content_blocks.append(output.model_dump(exclude_none=True, mode="json"))
@@ -4958,6 +4967,8 @@ def _convert_responses_chunk_to_generation_chunk(
"image_generation_call",
"tool_search_call",
"tool_search_output",
"apply_patch_call",
"apply_patch_call_output",
):
_advance(chunk.output_index)
tool_output = chunk.item.model_dump(exclude_none=True, mode="json")

BIN
libs/partners/openai/tests/cassettes/test_apply_patch.yaml.gz Normal file
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56
libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py
View File

@@ -200,6 +200,62 @@ async def test_web_search_async() -> None:
assert tool_output["type"] == "web_search_call"
@pytest.mark.default_cassette("test_apply_patch.yaml.gz")
@pytest.mark.vcr
def test_apply_patch() -> None:
"""Test the apply_patch built-in tool end-to-end.
apply_patch is a client-executed tool: the model proposes a file operation
via an `apply_patch_call` block, the client applies it, and the result is
returned as an ``apply_patch_call_output`` block. Requires a model that
supports the tool.
"""
prompt = "Create a new file named hello.txt containing the line: hello world"
llm = ChatOpenAI(model="gpt-5.1", output_version="responses/v1")
tool = {"type": "apply_patch"}
# Non-streaming: the model should emit an apply_patch_call block.
response = llm.invoke(prompt, tools=[tool])
assert isinstance(response, AIMessage)
calls = [
block
for block in response.content
if isinstance(block, dict) and block["type"] == "apply_patch_call"
]
assert len(calls) == 1
call = calls[0]
assert call["call_id"]
assert call["operation"]["type"] in ("create_file", "update_file", "delete_file")
# Streaming: the apply_patch_call block survives chunk aggregation.
aggregated: BaseMessageChunk | None = None
for chunk in llm.stream(prompt, tools=[tool]):
assert isinstance(chunk, AIMessageChunk)
aggregated = chunk if aggregated is None else aggregated + chunk
assert isinstance(aggregated, AIMessageChunk)
assert any(
isinstance(block, dict) and block["type"] == "apply_patch_call"
for block in aggregated.content
)
# Round-trip: return an apply_patch_call_output and continue the conversation.
output_message = HumanMessage(
content=[
{
"type": "apply_patch_call_output",
"call_id": call["call_id"],
"status": "completed",
"output": f"Created {call['operation']['path']}",
}
]
)
follow_up = llm.invoke(
[HumanMessage(prompt), response, output_message],
tools=[tool],
)
assert isinstance(follow_up, AIMessage)
@pytest.mark.default_cassette("test_function_calling.yaml.gz")
@pytest.mark.vcr
@pytest.mark.parametrize("output_version", ["v0", "responses/v1", "v1"])

244
libs/partners/openai/tests/unit_tests/chat_models/test_base.py
View File

@@ -35,8 +35,14 @@ from langchain_core.runnables import RunnableLambda
from langchain_core.runnables.base import RunnableBinding, RunnableSequence
from langchain_core.tracers.base import BaseTracer
from langchain_core.tracers.schemas import Run
from openai.types.responses import ResponseOutputMessage, ResponseReasoningItem
from openai.types.responses import (
ResponseApplyPatchToolCall,
ResponseApplyPatchToolCallOutput,
ResponseOutputMessage,
ResponseReasoningItem,
)
from openai.types.responses.response import IncompleteDetails, Response
from openai.types.responses.response_apply_patch_tool_call import OperationCreateFile
from openai.types.responses.response_error import ResponseError
from openai.types.responses.response_file_search_tool_call import (
ResponseFileSearchToolCall,
@@ -71,6 +77,7 @@ from langchain_openai.chat_models.base import (
_construct_responses_api_input,
_convert_dict_to_message,
_convert_message_to_dict,
_convert_responses_chunk_to_generation_chunk,
_convert_to_openai_response_format,
_create_usage_metadata,
_create_usage_metadata_responses,
@@ -1924,6 +1931,178 @@ def test__construct_lc_result_from_responses_api_no_usage_metadata() -> None:
assert cast(AIMessage, result.generations[0].message).usage_metadata is None
def test__construct_lc_result_from_responses_api_apply_patch_response() -> None:
"""Test a response with apply_patch output."""
response = Response(
id="resp_123",
created_at=1234567890,
model="gpt-4o",
object="response",
parallel_tool_calls=True,
tools=[],
tool_choice="auto",
output=[
ResponseApplyPatchToolCall(
id="apply_patch_123",
type="apply_patch_call",
call_id="call_123",
operation=OperationCreateFile(
type="create_file",
path="hello.txt",
diff="+hello\n",
),
status="completed",
)
],
)
result = _construct_lc_result_from_responses_api(response)
message = cast(AIMessage, result.generations[0].message)
assert message.content == [
{
"type": "apply_patch_call",
"id": "apply_patch_123",
"call_id": "call_123",
"operation": {
"type": "create_file",
"path": "hello.txt",
"diff": "+hello\n",
},
"status": "completed",
}
]
assert message.tool_calls == []
assert message.invalid_tool_calls == []
def test__construct_lc_result_from_responses_api_apply_patch_call_output() -> None:
"""Test a response with apply_patch_call_output output."""
response = Response(
id="resp_123",
created_at=1234567890,
model="gpt-4o",
object="response",
parallel_tool_calls=True,
tools=[],
tool_choice="auto",
output=[
ResponseApplyPatchToolCallOutput(
id="apply_patch_output_123",
type="apply_patch_call_output",
call_id="call_123",
status="completed",
output="Created hello.txt",
)
],
)
result = _construct_lc_result_from_responses_api(response)
message = result.generations[0].message
assert message.content == [
{
"type": "apply_patch_call_output",
"id": "apply_patch_output_123",
"call_id": "call_123",
"status": "completed",
"output": "Created hello.txt",
}
]
def test__construct_responses_api_input_apply_patch_round_trip() -> None:
"""Test apply_patch content blocks are preserved when sent back as input."""
messages = [
AIMessage(
content=[
{
"type": "apply_patch_call",
"call_id": "call_123",
"operation": {
"type": "create_file",
"path": "hello.txt",
"diff": "+hello\\n",
},
"status": "completed",
}
]
),
HumanMessage(
content=[
{
"type": "apply_patch_call_output",
"call_id": "call_123",
"status": "completed",
"output": "Created hello.txt",
}
]
),
]
result = _construct_responses_api_input(messages)
assert result == [
{
"type": "apply_patch_call",
"call_id": "call_123",
"operation": {
"type": "create_file",
"path": "hello.txt",
"diff": "+hello\\n",
},
"status": "completed",
},
{
"type": "apply_patch_call_output",
"call_id": "call_123",
"status": "completed",
"output": "Created hello.txt",
},
]
def test__convert_responses_chunk_to_generation_chunk_apply_patch_response() -> None:
"""Test streamed apply_patch output item is preserved in message chunks."""
chunk = MagicMock()
chunk.type = "response.output_item.done"
chunk.output_index = 0
chunk.item = ResponseApplyPatchToolCall(
id="apply_patch_123",
type="apply_patch_call",
call_id="call_123",
operation=OperationCreateFile(
type="create_file",
path="hello.txt",
diff="+hello\n",
),
status="completed",
)
_, _, _, generation_chunk = _convert_responses_chunk_to_generation_chunk(
chunk,
current_index=-1,
current_output_index=-1,
current_sub_index=-1,
)
assert generation_chunk is not None
assert generation_chunk.message.content == [
{
"type": "apply_patch_call",
"id": "apply_patch_123",
"call_id": "call_123",
"operation": {
"type": "create_file",
"path": "hello.txt",
"diff": "+hello\n",
},
"status": "completed",
"index": 0,
}
]
def test__construct_lc_result_from_responses_api_web_search_response() -> None:
"""Test a response with web search output."""
from openai.types.responses.response_function_web_search import (
@@ -2747,6 +2926,57 @@ def test_compat_responses_v03() -> None:
assert message_v03_output is not message_v03
def test_compat_responses_v03_apply_patch_tool_outputs() -> None:
message = AIMessage(
content=[
{"type": "text", "text": "Done.", "id": "msg_123"},
{
"type": "apply_patch_call",
"id": "apply_patch_123",
"call_id": "call_123",
"operation": {
"type": "create_file",
"path": "hello.txt",
"diff": "+hello\n",
},
"status": "completed",
},
{
"type": "apply_patch_call_output",
"id": "apply_patch_output_123",
"call_id": "call_123",
"status": "completed",
"output": "Created hello.txt",
},
],
id="resp_123",
)
message_v03_output = _convert_to_v03_ai_message(message)
assert message_v03_output.content == [{"type": "text", "text": "Done."}]
assert message_v03_output.additional_kwargs["tool_outputs"] == [
{
"type": "apply_patch_call",
"id": "apply_patch_123",
"call_id": "call_123",
"operation": {
"type": "create_file",
"path": "hello.txt",
"diff": "+hello\n",
},
"status": "completed",
},
{
"type": "apply_patch_call_output",
"id": "apply_patch_output_123",
"call_id": "call_123",
"status": "completed",
"output": "Created hello.txt",
},
]
@pytest.mark.parametrize(
("message_v1", "expected"),
[
@@ -3695,6 +3925,18 @@ def test_get_request_payload_responses_api_input_file_blocks_passthrough() -> No
]
def test_apply_patch_passthrough() -> None:
"""Test that apply_patch dict is passed through as a built-in tool."""
llm = ChatOpenAI(model="gpt-4o", api_key=SecretStr("test-api-key"))
bound = llm.bind_tools([{"type": "apply_patch"}])
payload = bound._get_request_payload( # type: ignore[attr-defined]
"test",
**bound.kwargs, # type: ignore[attr-defined]
)
assert {"type": "apply_patch"} in payload["tools"]
assert "input" in payload
def test_tool_search_passthrough() -> None:
"""Test that tool_search dict is passed through as a built-in tool."""
llm = ChatOpenAI(model="gpt-4o")

86
libs/partners/openai/uv.lock generated
View File

@@ -559,7 +559,7 @@ wheels = [
[[package]]
name = "langchain"
version = "1.3.1"
version = "1.3.4"
source = { editable = "../../langchain_v1" }
dependencies = [
{ name = "langchain-core" },
@@ -587,7 +587,7 @@ requires-dist = [
{ name = "langchain-perplexity", marker = "extra == 'perplexity'" },
{ name = "langchain-together", marker = "extra == 'together'" },
{ name = "langchain-xai", marker = "extra == 'xai'" },
{ name = "langgraph", specifier = ">=1.2.0,<1.3.0" },
{ name = "langgraph", specifier = ">=1.2.4,<1.3.0" },
{ name = "pydantic", specifier = ">=2.7.4,<3.0.0" },
]
provides-extras = ["community", "anthropic", "openai", "azure-ai", "google-vertexai", "google-genai", "fireworks", "ollama", "together", "mistralai", "huggingface", "groq", "aws", "baseten", "deepseek", "xai", "perplexity"]
@@ -624,7 +624,7 @@ typing = [
[[package]]
name = "langchain-core"
version = "1.4.0"
version = "1.4.2"
source = { editable = "../../core" }
dependencies = [
{ name = "jsonpatch" },
@@ -773,14 +773,14 @@ typing = [
[[package]]
name = "langchain-protocol"
version = "0.0.14"
version = "0.0.16"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "typing-extensions" },
]
sdist = { url = "https://files.pythonhosted.org/packages/05/bf/efb5e2ed832e4d6d45590e25a9e5191986b291b543bc6a807b48bee070b0/langchain_protocol-0.0.14.tar.gz", hash = "sha256:bc1e8553122e6ede310280462d5813023a172ff2785ccbbdec54d43f3a15e5f2", size = 5862, upload-time = "2026-04-29T16:40:18.657Z" }
sdist = { url = "https://files.pythonhosted.org/packages/36/e7/8300ba22d968653051fd06e3117d783872dddf3dcebdd6b1d386836eb43c/langchain_protocol-0.0.16.tar.gz", hash = "sha256:806c7cdd951b1c4f692fa40fce60821ff0f221d4360e27673ddf2c2b99c2b7ff", size = 5969, upload-time = "2026-05-28T23:05:11.121Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/c2/e9/06c47ecb2aff08f83dfa30058da3bf86be64862c19569043ed5331bbeecd/langchain_protocol-0.0.14-py3-none-any.whl", hash = "sha256:ffc35089779bd8ca217015180cef5e660fc3b074efdaa0f2e95df73583f1a047", size = 6984, upload-time = "2026-04-29T16:40:17.841Z" },
{ url = "https://files.pythonhosted.org/packages/1f/9c/06dfcc88d02a6364e8d864c421ddd3736305cb0a6c853f75c302c80fe17c/langchain_protocol-0.0.16-py3-none-any.whl", hash = "sha256:3658c142c5d0fb3a023a4be442ce4c15c6d626aab6135eb79a76dc64ad19c3c3", size = 7037, upload-time = "2026-05-28T23:05:10.163Z" },
]
[[package]]
@@ -830,7 +830,7 @@ typing = [
[[package]]
name = "langgraph"
version = "1.2.0"
version = "1.2.4"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "langchain-core" },
@@ -840,9 +840,9 @@ dependencies = [
{ name = "pydantic" },
{ name = "xxhash" },
]
sdist = { url = "https://files.pythonhosted.org/packages/58/61/d5d25e783035aa307d289b37e082258a6061c0fb4caa4a284f3bf1e87169/langgraph-1.2.0.tar.gz", hash = "sha256:4a9baaf62afc5d5f63144a50095140a34b9aa9b7cea695d25326d564775348e7", size = 690248, upload-time = "2026-05-12T03:46:39.164Z" }
sdist = { url = "https://files.pythonhosted.org/packages/1c/43/dac5a2621c1e57f8eb7f0703f6f6fe34a5caf62f8f0fb4d2bb395bb454ea/langgraph-1.2.4.tar.gz", hash = "sha256:5df076973a2d23efb13eceb279d1e5b46feebcbbeded0a86a2ef669abd9e4399", size = 720374, upload-time = "2026-06-02T17:07:37.347Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/f6/e8/e3304ac0015c2bdb04ad9785e4ed65c788855ce7857ce6104dd2f5d322db/langgraph-1.2.0-py3-none-any.whl", hash = "sha256:03fd5895a8d4b70db1ff63ebc3bacead29dd20cd794a8b1a483e7ec9018f7a65", size = 234262, upload-time = "2026-05-12T03:46:37.971Z" },
{ url = "https://files.pythonhosted.org/packages/48/9e/31ca236104966d7bb14ea9e93cfd73350aea8c41008ddf057b65794ed10d/langgraph-1.2.4-py3-none-any.whl", hash = "sha256:ffe3e1e31dce28907640f82525858470f293506d2b272d07ea3b3ce97974b067", size = 245402, upload-time = "2026-06-02T17:07:35.977Z" },
]
[[package]]
@@ -873,15 +873,18 @@ wheels = [
[[package]]
name = "langgraph-sdk"
version = "0.3.3"
version = "0.4.2"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "httpx" },
{ name = "langchain-core" },
{ name = "langchain-protocol" },
{ name = "orjson" },
{ name = "websockets" },
]
sdist = { url = "https://files.pythonhosted.org/packages/c3/0f/ed0634c222eed48a31ba48eab6881f94ad690d65e44fe7ca838240a260c1/langgraph_sdk-0.3.3.tar.gz", hash = "sha256:c34c3dce3b6848755eb61f0c94369d1ba04aceeb1b76015db1ea7362c544fb26", size = 130589, upload-time = "2026-01-13T00:30:43.894Z" }
sdist = { url = "https://files.pythonhosted.org/packages/b4/2b/bd8ac26d4e97f6df88ef05ce5b6a38945a3903e1025d926f4752aa88aa97/langgraph_sdk-0.4.2.tar.gz", hash = "sha256:b88f0f5f6328ac0680d6790614a905b2bcfa257f2276dba4e38f0e86db0aa738", size = 348327, upload-time = "2026-06-01T17:51:19.856Z" }
wheels = [
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{ url = "https://files.pythonhosted.org/packages/a0/05/aac507337cceae773c2cc9ab91eb6301963af7aeeb55b4217a00e15aff17/langgraph_sdk-0.4.2-py3-none-any.whl", hash = "sha256:75fa5096c1177ce39c847096a8fe3745ffd480ddb412995f836e9f5f884c43dd", size = 160521, upload-time = "2026-06-01T17:51:18.849Z" },
]
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