carry over changes

libs/core/langchain_core/language_models/chat_models.py

@@ -311,6 +311,18 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
     does not properly support streaming.
     """
 
+    output_version: str = "v0"
+    """Version of AIMessage output format to use.
+
+    This field is used to roll-out new output formats for chat model AIMessages
+    in a backwards-compatible way.
+
+    All chat models currently support the default of ``"v0"``. Chat model subclasses
+    can override with (customizable) supported values.
+
+    .. versionadded:: 0.3.68
+    """
+
     @model_validator(mode="before")
     @classmethod
     def raise_deprecation(cls, values: dict) -> Any:

libs/core/langchain_core/messages/__init__.py

@@ -33,6 +33,15 @@ if TYPE_CHECKING:
     )
     from langchain_core.messages.chat import ChatMessage, ChatMessageChunk
     from langchain_core.messages.content_blocks import (
+        Base64ContentBlock,
+        ContentBlock,
+        DocumentCitation,
+        NonStandardAnnotation,
+        NonStandardContentBlock,
+        ReasoningContentBlock,
+        TextContentBlock,
+        ToolCallContentBlock,
+        UrlCitation,
         convert_to_openai_data_block,
         convert_to_openai_image_block,
         is_data_content_block,
@@ -66,23 +75,32 @@ __all__ = (
     "AIMessage",
     "AIMessageChunk",
     "AnyMessage",
+    "Base64ContentBlock",
     "BaseMessage",
     "BaseMessageChunk",
     "ChatMessage",
     "ChatMessageChunk",
+    "ContentBlock",
+    "DocumentCitation",
     "FunctionMessage",
     "FunctionMessageChunk",
     "HumanMessage",
     "HumanMessageChunk",
     "InvalidToolCall",
     "MessageLikeRepresentation",
+    "NonStandardAnnotation",
+    "NonStandardContentBlock",
+    "ReasoningContentBlock",
     "RemoveMessage",
     "SystemMessage",
     "SystemMessageChunk",
+    "TextContentBlock",
     "ToolCall",
     "ToolCallChunk",
+    "ToolCallContentBlock",
     "ToolMessage",
     "ToolMessageChunk",
+    "UrlCitation",
     "_message_from_dict",
     "convert_to_messages",
     "convert_to_openai_data_block",
@@ -103,25 +121,34 @@ __all__ = (
 _dynamic_imports = {
     "AIMessage": "ai",
     "AIMessageChunk": "ai",
+    "Base64ContentBlock": "content_blocks",
     "BaseMessage": "base",
     "BaseMessageChunk": "base",
     "merge_content": "base",
     "message_to_dict": "base",
     "messages_to_dict": "base",
+    "ContentBlock": "content_blocks",
     "ChatMessage": "chat",
     "ChatMessageChunk": "chat",
+    "DocumentCitation": "content_blocks",
     "FunctionMessage": "function",
     "FunctionMessageChunk": "function",
     "HumanMessage": "human",
     "HumanMessageChunk": "human",
+    "NonStandardAnnotation": "content_blocks",
+    "NonStandardContentBlock": "content_blocks",
+    "ReasoningContentBlock": "content_blocks",
     "RemoveMessage": "modifier",
     "SystemMessage": "system",
     "SystemMessageChunk": "system",
     "InvalidToolCall": "tool",
+    "TextContentBlock": "content_blocks",
     "ToolCall": "tool",
     "ToolCallChunk": "tool",
+    "ToolCallContentBlock": "content_blocks",
     "ToolMessage": "tool",
     "ToolMessageChunk": "tool",
+    "UrlCitation": "content_blocks",
     "AnyMessage": "utils",
     "MessageLikeRepresentation": "utils",
     "_message_from_dict": "utils",

libs/core/langchain_core/messages/base.py

@@ -7,6 +7,7 @@ from typing import TYPE_CHECKING, Any, Optional, Union, cast
 from pydantic import ConfigDict, Field
 
 from langchain_core.load.serializable import Serializable
+from langchain_core.messages import ContentBlock
 from langchain_core.utils import get_bolded_text
 from langchain_core.utils._merge import merge_dicts, merge_lists
 from langchain_core.utils.interactive_env import is_interactive_env
@@ -23,7 +24,7 @@ class BaseMessage(Serializable):
     Messages are the inputs and outputs of ChatModels.
     """
 
-    content: Union[str, list[Union[str, dict]]]
+    content: Union[str, list[Union[str, ContentBlock, dict]]]
     """The string contents of the message."""
 
     additional_kwargs: dict = Field(default_factory=dict)

libs/core/langchain_core/messages/content_blocks.py

@@ -7,6 +7,93 @@ from pydantic import TypeAdapter, ValidationError
 from typing_extensions import NotRequired, TypedDict
 
 
+# Text and annotations
+class UrlCitation(TypedDict, total=False):
+    """Citation from a URL."""
+
+    type: Literal["url_citation"]
+
+    url: str
+    """Source URL."""
+
+    title: NotRequired[str]
+    """Source title."""
+
+    cited_text: NotRequired[str]
+    """Text from the source that is being cited."""
+
+    start_index: NotRequired[int]
+    """Start index of the response text for which the annotation applies."""
+
+    end_index: NotRequired[int]
+    """End index of the response text for which the annotation applies."""
+
+
+class DocumentCitation(TypedDict, total=False):
+    """Annotation for data from a document."""
+
+    type: Literal["document_citation"]
+
+    title: NotRequired[str]
+    """Source title."""
+
+    cited_text: NotRequired[str]
+    """Text from the source that is being cited."""
+
+    start_index: NotRequired[int]
+    """Start index of the response text for which the annotation applies."""
+
+    end_index: NotRequired[int]
+    """End index of the response text for which the annotation applies."""
+
+
+class NonStandardAnnotation(TypedDict, total=False):
+    """Provider-specific annotation format."""
+
+    type: Literal["non_standard_annotation"]
+    """Type of the content block."""
+    value: dict[str, Any]
+    """Provider-specific annotation data."""
+
+
+class TextContentBlock(TypedDict, total=False):
+    """Content block for text output."""
+
+    type: Literal["text"]
+    """Type of the content block."""
+    text: str
+    """Block text."""
+    annotations: NotRequired[
+        list[Union[UrlCitation, DocumentCitation, NonStandardAnnotation]]
+    ]
+    """Citations and other annotations."""
+
+
+# Tool calls
+class ToolCallContentBlock(TypedDict, total=False):
+    """Content block for tool calls.
+
+    These are references to a :class:`~langchain_core.messages.tool.ToolCall` in the
+    message's ``tool_calls`` attribute.
+    """
+
+    type: Literal["tool_call"]
+    """Type of the content block."""
+    id: str
+    """Tool call ID."""
+
+
+# Reasoning
+class ReasoningContentBlock(TypedDict, total=False):
+    """Content block for reasoning output."""
+
+    type: Literal["reasoning"]
+    """Type of the content block."""
+    reasoning: NotRequired[str]
+    """Reasoning text."""
+
+
+# Multi-modal
 class BaseDataContentBlock(TypedDict, total=False):
     """Base class for data content blocks."""
 
@@ -68,6 +155,28 @@ DataContentBlock = Union[
 _DataContentBlockAdapter: TypeAdapter[DataContentBlock] = TypeAdapter(DataContentBlock)
 
 
+# Non-standard
+class NonStandardContentBlock(TypedDict, total=False):
+    """Content block provider-specific data.
+
+    This block contains data for which there is not yet a standard type.
+    """
+
+    type: Literal["non_standard"]
+    """Type of the content block."""
+    value: dict[str, Any]
+    """Provider-specific data."""
+
+
+ContentBlock = Union[
+    TextContentBlock,
+    ToolCallContentBlock,
+    ReasoningContentBlock,
+    DataContentBlock,
+    NonStandardContentBlock,
+]
+
+
 def is_data_content_block(
     content_block: dict,
 ) -> bool:

libs/core/tests/unit_tests/language_models/chat_models/test_cache.py

@@ -300,8 +300,9 @@ def test_llm_representation_for_serializable() -> None:
     assert chat._get_llm_string() == (
         '{"id": ["tests", "unit_tests", "language_models", "chat_models", '
         '"test_cache", "CustomChat"], "kwargs": {"messages": {"id": '
-        '["builtins", "list_iterator"], "lc": 1, "type": "not_implemented"}}, "lc": '
+        '["builtins", "list_iterator"], "lc": 1, "type": "not_implemented"}, '
-        '1, "name": "CustomChat", "type": "constructor"}---[(\'stop\', None)]'
+        '"output_version": "v0"}, "lc": 1, "name": "CustomChat", "type": '
+        "\"constructor\"}---[('stop', None)]"
     )
 
 

libs/partners/openai/langchain_openai/chat_models/_compat.py

@@ -1,7 +1,10 @@
 """
-This module converts between AIMessage output formats for the Responses API.
+This module converts between AIMessage output formats, which are governed by the
+``output_version`` attribute on ChatOpenAI. Supported values are ``"v0"``,
+``"responses/v1"``, and ``"v1"``.
 
-ChatOpenAI v0.3 stores reasoning and tool outputs in AIMessage.additional_kwargs:
+``"v0"`` corresponds to the format as of ChatOpenAI v0.3. For the Responses API, it
+stores reasoning and tool outputs in AIMessage.additional_kwargs:
 
 .. code-block:: python
 
@@ -24,8 +27,9 @@ ChatOpenAI v0.3 stores reasoning and tool outputs in AIMessage.additional_kwargs
         id="msg_123",
     )
 
-To retain information about response item sequencing (and to accommodate multiple
+``"responses/v1"`` is only applicable to the Responses API. It retains information
-reasoning items), ChatOpenAI now stores these items in the content sequence:
+about response item sequencing and accommodates multiple reasoning items by
+representing these items in the content sequence:
 
 .. code-block:: python
 
@@ -52,18 +56,39 @@ reasoning items), ChatOpenAI now stores these items in the content sequence:
 There are other, small improvements as well-- e.g., we store message IDs on text
 content blocks, rather than on the AIMessage.id, which now stores the response ID.
 
+``"v1"`` represents LangChain's cross-provider standard format.
+
 For backwards compatibility, this module provides functions to convert between the
-old and new formats. The functions are used internally by ChatOpenAI.
+formats. The functions are used internally by ChatOpenAI.
 """  # noqa: E501
 
 import json
-from typing import Union
+from collections.abc import Iterable
+from typing import TYPE_CHECKING, Any, Union, cast
 
-from langchain_core.messages import AIMessage
+from langchain_core.messages import (
+    AIMessage,
+    AIMessageChunk,
+    DocumentCitation,
+    NonStandardAnnotation,
+    ReasoningContentBlock,
+    UrlCitation,
+    is_data_content_block,
+)
+
+if TYPE_CHECKING:
+    from langchain_core.messages import (
+        Base64ContentBlock,
+        NonStandardContentBlock,
+        ReasoningContentBlock,
+        TextContentBlock,
+        ToolCallContentBlock,
+    )
 
 _FUNCTION_CALL_IDS_MAP_KEY = "__openai_function_call_ids__"
 
 
+# v0.3 / Responses
 def _convert_to_v03_ai_message(
     message: AIMessage, has_reasoning: bool = False
 ) -> AIMessage:
@@ -248,3 +273,279 @@ def _convert_from_v03_ai_message(message: AIMessage) -> AIMessage:
         },
         deep=False,
     )
+
+
+# v1 / Chat Completions
+def _convert_to_v1_from_chat_completions(message: AIMessage) -> AIMessage:
+    """Mutate a Chat Completions message to v1 format."""
+    if isinstance(message.content, str):
+        if message.content:
+            block: TextContentBlock = {"type": "text", "text": message.content}
+            message.content = [block]
+        else:
+            message.content = []
+
+    for tool_call in message.tool_calls:
+        if id_ := tool_call.get("id"):
+            tool_callblock: ToolCallContentBlock = {"type": "tool_call", "id": id_}
+            message.content.append(tool_callblock)
+
+    if "tool_calls" in message.additional_kwargs:
+        _ = message.additional_kwargs.pop("tool_calls")
+
+    if "token_usage" in message.response_metadata:
+        _ = message.response_metadata.pop("token_usage")
+
+    return message
+
+
+def _convert_to_v1_from_chat_completions_chunk(chunk: AIMessageChunk) -> AIMessageChunk:
+    result = _convert_to_v1_from_chat_completions(cast(AIMessage, chunk))
+    return cast(AIMessageChunk, result)
+
+
+def _convert_from_v1_to_chat_completions(message: AIMessage) -> AIMessage:
+    """Convert a v1 message to the Chat Completions format."""
+    if isinstance(message.content, list):
+        new_content: list = []
+        for block in message.content:
+            if isinstance(block, dict):
+                block_type = block.get("type")
+                if block_type == "text":
+                    # Strip annotations
+                    new_content.append({"type": "text", "text": block["text"]})
+                elif block_type in ("reasoning", "tool_call"):
+                    pass
+                else:
+                    new_content.append(block)
+            else:
+                new_content.append(block)
+        return message.model_copy(update={"content": new_content})
+
+    return message
+
+
+# v1 / Responses
+def _convert_annotation_to_v1(
+    annotation: dict[str, Any],
+) -> Union[UrlCitation, DocumentCitation, NonStandardAnnotation]:
+    annotation_type = annotation.get("type")
+
+    if annotation_type == "url_citation":
+        new_annotation: UrlCitation = {"type": "url_citation", "url": annotation["url"]}
+        for field in ("title", "start_index", "end_index"):
+            if field in annotation:
+                new_annotation[field] = annotation[field]
+        return new_annotation
+
+    elif annotation_type == "file_citation":
+        new_annotation: DocumentCitation = {"type": "document_citation"}
+        if "filename" in annotation:
+            new_annotation["title"] = annotation["filename"]
+        for field in ("file_id", "index"):  # OpenAI-specific
+            if field in annotation:
+                new_annotation[field] = annotation[field]
+        return new_annotation
+
+    # TODO: standardise container_file_citation?
+    else:
+        new_annotation: NonStandardAnnotation = {
+            "type": "non_standard_annotation",
+            "value": annotation,
+        }
+    return new_annotation
+
+
+def _explode_reasoning(block: dict[str, Any]) -> Iterable[ReasoningContentBlock]:
+    if block.get("type") != "reasoning" or "summary" not in block:
+        yield block
+        return
+
+    if not block["summary"]:
+        _ = block.pop("summary", None)
+        yield block
+        return
+
+    # Common part for every exploded line, except 'summary'
+    common = {k: v for k, v in block.items() if k != "summary"}
+
+    # Optional keys that must appear only in the first exploded item
+    first_only = {
+        k: common.pop(k) for k in ("encrypted_content", "status") if k in common
+    }
+
+    for idx, part in enumerate(block["summary"]):
+        new_block = dict(common)
+        new_block["reasoning"] = part.get("text", "")
+        if idx == 0:
+            new_block.update(first_only)
+        yield cast(ReasoningContentBlock, new_block)
+
+
+def _convert_to_v1_from_responses(message: AIMessage) -> AIMessage:
+    """Mutate a Responses message to v1 format."""
+    if not isinstance(message.content, list):
+        return message
+
+    def _iter_blocks() -> Iterable[dict[str, Any]]:
+        for block in message.content:
+            block_type = block.get("type")
+
+            if block_type == "text":
+                if "annotations" in block:
+                    block["annotations"] = [
+                        _convert_annotation_to_v1(a) for a in block["annotations"]
+                    ]
+                yield block
+
+            elif block_type == "reasoning":
+                yield from _explode_reasoning(block)
+
+            elif block_type == "image_generation_call" and (
+                result := block.get("result")
+            ):
+                new_block: Base64ContentBlock = {
+                    "type": "image",
+                    "source_type": "base64",
+                    "data": result,
+                }
+                for extra_key in ("id", "status"):
+                    if extra_key in block:
+                        new_block[extra_key] = block[extra_key]
+                yield new_block
+
+            elif block_type == "function_call":
+                new_block: ToolCallContentBlock = {
+                    "type": "tool_call",
+                    "id": block["call_id"],
+                }
+                if "id" in block:
+                    new_block["item_id"] = block["id"]
+                for extra_key in ("arguments", "name"):
+                    if extra_key in block:
+                        new_block[extra_key] = block[extra_key]
+                yield new_block
+
+            else:
+                new_block: NonStandardContentBlock = {
+                    "type": "non_standard",
+                    "value": block,
+                }
+                if "index" in new_block["value"]:
+                    new_block["index"] = new_block["value"].pop("index")
+                yield new_block
+
+    # Replace the list with the fully converted one
+    message.content = list(_iter_blocks())
+
+    return message
+
+
+def _convert_annotation_from_v1(annotation: dict[str, Any]) -> dict[str, Any]:
+    annotation_type = annotation.get("type")
+
+    if annotation_type == "document_citation":
+        new_ann: dict[str, Any] = {"type": "file_citation"}
+
+        if "title" in annotation:
+            new_ann["filename"] = annotation["title"]
+
+        for fld in ("file_id", "index"):
+            if fld in annotation:
+                new_ann[fld] = annotation[fld]
+
+        return new_ann
+
+    elif annotation_type == "non_standard_annotation":
+        return annotation["value"]
+
+    else:
+        return dict(annotation)
+
+
+def _implode_reasoning_blocks(blocks: list[dict[str, Any]]) -> Iterable[dict[str, Any]]:
+    i = 0
+    n = len(blocks)
+
+    while i < n:
+        block = blocks[i]
+
+        # Ordinary block – just yield a shallow copy
+        if block.get("type") != "reasoning" or "reasoning" not in block:
+            yield dict(block)
+            i += 1
+            continue
+
+        summary: list[dict[str, str]] = [
+            {"type": "summary_text", "text": block.get("reasoning", "")}
+        ]
+        # 'common' is every field except the exploded 'reasoning'
+        common = {k: v for k, v in block.items() if k != "reasoning"}
+
+        i += 1
+        while i < n:
+            next_ = blocks[i]
+            if next_.get("type") == "reasoning" and "reasoning" in next_:
+                summary.append(
+                    {"type": "summary_text", "text": next_.get("reasoning", "")}
+                )
+                i += 1
+            else:
+                break
+
+        merged = dict(common)
+        merged["summary"] = summary
+        yield merged
+
+
+def _convert_from_v1_to_responses(message: AIMessage) -> AIMessage:
+    if not isinstance(message.content, list):
+        return message
+
+    new_content: list = []
+    for block in message.content:
+        if isinstance(block, dict):
+            block_type = block.get("type")
+            if block_type == "text" and "annotations" in block:
+                # Need a copy because we’re changing the annotations list
+                new_block = dict(block)
+                new_block["annotations"] = [
+                    _convert_annotation_from_v1(a) for a in block["annotations"]
+                ]
+                new_content.append(new_block)
+            elif block_type == "tool_call":
+                new_block = {"type": "function_call", "call_id": block["id"]}
+                if "item_id" in block:
+                    new_block["id"] = block["item_id"]
+                if "name" in block and "arguments" in block:
+                    new_block["name"] = block["name"]
+                    new_block["arguments"] = block["arguments"]
+                else:
+                    tool_call = next(
+                        call for call in message.tool_calls if call["id"] == block["id"]
+                    )
+                    if "name" not in block:
+                        new_block["name"] = tool_call["name"]
+                    if "arguments" not in block:
+                        new_block["arguments"] = json.dumps(tool_call["args"])
+                new_content.append(new_block)
+            elif (
+                is_data_content_block(block)
+                and block["type"] == "image"
+                and block["source_type"] == "base64"
+            ):
+                new_block = {"type": "image_generation_call", "result": block["data"]}
+                for extra_key in ("id", "status"):
+                    if extra_key in block:
+                        new_block[extra_key] = block[extra_key]
+                new_content.append(new_block)
+            elif block_type == "non_standard" and "value" in block:
+                new_content.append(block["value"])
+            else:
+                new_content.append(block)
+        else:
+            new_content.append(block)
+
+    new_content = list(_implode_reasoning_blocks(new_content))
+
+    return message.model_copy(update={"content": new_content})

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -108,7 +108,12 @@ from langchain_openai.chat_models._client_utils import (
 )
 from langchain_openai.chat_models._compat import (
     _convert_from_v03_ai_message,
+    _convert_from_v1_to_chat_completions,
+    _convert_from_v1_to_responses,
     _convert_to_v03_ai_message,
+    _convert_to_v1_from_chat_completions,
+    _convert_to_v1_from_chat_completions_chunk,
+    _convert_to_v1_from_responses,
 )
 
 if TYPE_CHECKING:
@@ -649,7 +654,7 @@ class BaseChatOpenAI(BaseChatModel):
     .. versionadded:: 0.3.9
     """
 
-    output_version: Literal["v0", "responses/v1"] = "v0"
+    output_version: str = "v0"
     """Version of AIMessage output format to use.
 
     This field is used to roll-out new output formats for chat model AIMessages
@@ -660,9 +665,9 @@ class BaseChatOpenAI(BaseChatModel):
     - ``"v0"``: AIMessage format as of langchain-openai 0.3.x.
     - ``"responses/v1"``: Formats Responses API output
       items into AIMessage content blocks.
+    - ``"v1"``: v1 of LangChain cross-provider standard.
 
-    Currently only impacts the Responses API. ``output_version="responses/v1"`` is
+    ``output_version="v1"`` is recommended.
-    recommended.
 
     .. versionadded:: 0.3.25
 
@@ -849,6 +854,10 @@ class BaseChatOpenAI(BaseChatModel):
                 message=default_chunk_class(content="", usage_metadata=usage_metadata),
                 generation_info=base_generation_info,
             )
+            if self.output_version == "v1":
+                generation_chunk.message = _convert_to_v1_from_chat_completions_chunk(
+                    cast(AIMessageChunk, generation_chunk.message)
+                )
             return generation_chunk
 
         choice = choices[0]
@@ -876,6 +885,20 @@ class BaseChatOpenAI(BaseChatModel):
         if usage_metadata and isinstance(message_chunk, AIMessageChunk):
             message_chunk.usage_metadata = usage_metadata
 
+        if self.output_version == "v1":
+            message_chunk = cast(AIMessageChunk, message_chunk)
+            # Convert to v1 format
+            if isinstance(message_chunk.content, str):
+                message_chunk = _convert_to_v1_from_chat_completions_chunk(
+                    message_chunk
+                )
+                if message_chunk.content:
+                    message_chunk.content[0]["index"] = 0  # type: ignore[index]
+            else:
+                message_chunk = _convert_to_v1_from_chat_completions_chunk(
+                    message_chunk
+                )
+
         generation_chunk = ChatGenerationChunk(
             message=message_chunk, generation_info=generation_info or None
         )
@@ -1168,7 +1191,12 @@ class BaseChatOpenAI(BaseChatModel):
             else:
                 payload = _construct_responses_api_payload(messages, payload)
         else:
-            payload["messages"] = [_convert_message_to_dict(m) for m in messages]
+            payload["messages"] = [
+                _convert_message_to_dict(_convert_from_v1_to_chat_completions(m))
+                if isinstance(m, AIMessage)
+                else _convert_message_to_dict(m)
+                for m in messages
+            ]
         return payload
 
     def _create_chat_result(
@@ -1234,6 +1262,11 @@ class BaseChatOpenAI(BaseChatModel):
             if hasattr(message, "refusal"):
                 generations[0].message.additional_kwargs["refusal"] = message.refusal
 
+        if self.output_version == "v1":
+            _ = llm_output.pop("token_usage", None)
+            generations[0].message = _convert_to_v1_from_chat_completions(
+                cast(AIMessage, generations[0].message)
+            )
         return ChatResult(generations=generations, llm_output=llm_output)
 
     async def _astream(
@@ -3464,6 +3497,7 @@ def _construct_responses_api_input(messages: Sequence[BaseMessage]) -> list:
     for lc_msg in messages:
         if isinstance(lc_msg, AIMessage):
             lc_msg = _convert_from_v03_ai_message(lc_msg)
+            lc_msg = _convert_from_v1_to_responses(lc_msg)
         msg = _convert_message_to_dict(lc_msg)
         # "name" parameter unsupported
         if "name" in msg:
@@ -3607,7 +3641,7 @@ def _construct_lc_result_from_responses_api(
     response: Response,
     schema: Optional[type[_BM]] = None,
     metadata: Optional[dict] = None,
-    output_version: Literal["v0", "responses/v1"] = "v0",
+    output_version: str = "v0",
 ) -> ChatResult:
     """Construct ChatResponse from OpenAI Response API response."""
     if response.error:
@@ -3746,6 +3780,8 @@ def _construct_lc_result_from_responses_api(
     )
     if output_version == "v0":
         message = _convert_to_v03_ai_message(message)
+    elif output_version == "v1":
+        message = _convert_to_v1_from_responses(message)
     else:
         pass
     return ChatResult(generations=[ChatGeneration(message=message)])
@@ -3759,7 +3795,7 @@ def _convert_responses_chunk_to_generation_chunk(
     schema: Optional[type[_BM]] = None,
     metadata: Optional[dict] = None,
     has_reasoning: bool = False,
-    output_version: Literal["v0", "responses/v1"] = "v0",
+    output_version: str = "v0",
 ) -> tuple[int, int, int, Optional[ChatGenerationChunk]]:
     def _advance(output_idx: int, sub_idx: Optional[int] = None) -> None:
         """Advance indexes tracked during streaming.
@@ -3826,6 +3862,16 @@ def _convert_responses_chunk_to_generation_chunk(
             annotation = chunk.annotation.model_dump(exclude_none=True, mode="json")
         content.append({"annotations": [annotation], "index": current_index})
     elif chunk.type == "response.output_text.done":
+        if output_version == "v1":
+            content.append(
+                {
+                    "type": "text",
+                    "text": "",
+                    "id": chunk.item_id,
+                    "index": current_index,
+                }
+            )
+        else:
             content.append({"id": chunk.item_id, "index": current_index})
     elif chunk.type == "response.created":
         id = chunk.response.id
@@ -3902,21 +3948,34 @@ def _convert_responses_chunk_to_generation_chunk(
         content.append({"type": "refusal", "refusal": chunk.refusal})
     elif chunk.type == "response.output_item.added" and chunk.item.type == "reasoning":
         _advance(chunk.output_index)
+        current_sub_index = 0
         reasoning = chunk.item.model_dump(exclude_none=True, mode="json")
         reasoning["index"] = current_index
         content.append(reasoning)
     elif chunk.type == "response.reasoning_summary_part.added":
+        if output_version in ("v0", "responses/v1"):
             _advance(chunk.output_index)
             content.append(
                 {
                     # langchain-core uses the `index` key to aggregate text blocks.
                     "summary": [
-                    {"index": chunk.summary_index, "type": "summary_text", "text": ""}
+                        {
+                            "index": chunk.summary_index,
+                            "type": "summary_text",
+                            "text": "",
+                        }
                     ],
                     "index": current_index,
                     "type": "reasoning",
                 }
             )
+        else:
+            block = {"type": "reasoning", "reasoning": ""}
+            if chunk.summary_index > 0:
+                _advance(chunk.output_index, chunk.summary_index)
+                block["id"] = chunk.item_id
+            block["index"] = current_index
+            content.append(block)
     elif chunk.type == "response.image_generation_call.partial_image":
         # Partial images are not supported yet.
         pass
@@ -3951,6 +4010,8 @@ def _convert_responses_chunk_to_generation_chunk(
             AIMessageChunk,
             _convert_to_v03_ai_message(message, has_reasoning=has_reasoning),
         )
+    elif output_version == "v1":
+        message = _convert_to_v1_from_responses(message)
     else:
         pass
     return (

libs/partners/openai/tests/integration_tests/chat_models/test_responses_api.py

@@ -52,9 +52,11 @@ def _check_response(response: Optional[BaseMessage]) -> None:
     assert response.response_metadata["service_tier"]
 
 
+@pytest.mark.default_cassette("test_web_search.yaml.gz")
 @pytest.mark.vcr
-def test_web_search() -> None:
+@pytest.mark.parametrize("output_version", ["responses/v1", "v1"])
-    llm = ChatOpenAI(model=MODEL_NAME, output_version="responses/v1")
+def test_web_search(output_version: Literal["v0", "responses/v1", "v1"]) -> None:
+    llm = ChatOpenAI(model=MODEL_NAME, output_version=output_version)
     first_response = llm.invoke(
         "What was a positive news story from today?",
         tools=[{"type": "web_search_preview"}],
@@ -141,13 +143,15 @@ async def test_web_search_async() -> None:
         assert tool_output["type"] == "web_search_call"
 
 
-@pytest.mark.flaky(retries=3, delay=1)
+@pytest.mark.default_cassette("test_function_calling.yaml.gz")
-def test_function_calling() -> None:
+@pytest.mark.vcr
+@pytest.mark.parametrize("output_version", ["v0", "responses/v1", "v1"])
+def test_function_calling(output_version: Literal["v0", "responses/v1", "v1"]) -> None:
     def multiply(x: int, y: int) -> int:
         """return x * y"""
         return x * y
 
-    llm = ChatOpenAI(model=MODEL_NAME)
+    llm = ChatOpenAI(model=MODEL_NAME, output_version=output_version)
     bound_llm = llm.bind_tools([multiply, {"type": "web_search_preview"}])
     ai_msg = cast(AIMessage, bound_llm.invoke("whats 5 * 4"))
     assert len(ai_msg.tool_calls) == 1
@@ -297,8 +301,8 @@ def test_function_calling_and_structured_output() -> None:
 
 @pytest.mark.default_cassette("test_reasoning.yaml.gz")
 @pytest.mark.vcr
-@pytest.mark.parametrize("output_version", ["v0", "responses/v1"])
+@pytest.mark.parametrize("output_version", ["v0", "responses/v1", "v1"])
-def test_reasoning(output_version: Literal["v0", "responses/v1"]) -> None:
+def test_reasoning(output_version: Literal["v0", "responses/v1", "v1"]) -> None:
     llm = ChatOpenAI(
         model="o4-mini", use_responses_api=True, output_version=output_version
     )
@@ -376,9 +380,9 @@ def test_file_search() -> None:
 
 @pytest.mark.default_cassette("test_stream_reasoning_summary.yaml.gz")
 @pytest.mark.vcr
-@pytest.mark.parametrize("output_version", ["v0", "responses/v1"])
+@pytest.mark.parametrize("output_version", ["v0", "responses/v1", "v1"])
 def test_stream_reasoning_summary(
-    output_version: Literal["v0", "responses/v1"],
+    output_version: Literal["v0", "responses/v1", "v1"],
 ) -> None:
     llm = ChatOpenAI(
         model="o4-mini",
@@ -398,7 +402,14 @@ def test_stream_reasoning_summary(
     if output_version == "v0":
         reasoning = response_1.additional_kwargs["reasoning"]
         assert set(reasoning.keys()) == {"id", "type", "summary"}
-    else:
+        summary = reasoning["summary"]
+        assert isinstance(summary, list)
+        for block in summary:
+            assert isinstance(block, dict)
+            assert isinstance(block["type"], str)
+            assert isinstance(block["text"], str)
+            assert block["text"]
+    elif output_version == "responses/v1":
         reasoning = next(
             block
             for block in response_1.content
@@ -412,6 +423,18 @@ def test_stream_reasoning_summary(
             assert isinstance(block["type"], str)
             assert isinstance(block["text"], str)
             assert block["text"]
+    else:
+        # v1
+        total_reasoning_blocks = 0
+        for block in response_1.content:
+            if block["type"] == "reasoning":
+                total_reasoning_blocks += 1
+                assert isinstance(block["id"], str) and block["id"].startswith("rs_")
+                assert isinstance(block["reasoning"], str)
+                assert isinstance(block["index"], int)
+        assert (
+            total_reasoning_blocks > 1
+        )  # This query typically generates multiple reasoning blocks
 
     # Check we can pass back summaries
     message_2 = {"role": "user", "content": "Thank you."}

libs/partners/openai/tests/unit_tests/chat_models/test_base.py

@@ -51,7 +51,11 @@ from langchain_openai import ChatOpenAI
 from langchain_openai.chat_models._compat import (
     _FUNCTION_CALL_IDS_MAP_KEY,
     _convert_from_v03_ai_message,
+    _convert_from_v1_to_chat_completions,
+    _convert_from_v1_to_responses,
     _convert_to_v03_ai_message,
+    _convert_to_v1_from_chat_completions,
+    _convert_to_v1_from_responses,
 )
 from langchain_openai.chat_models.base import (
     _construct_lc_result_from_responses_api,
@@ -2296,7 +2300,7 @@ def test_mcp_tracing() -> None:
     assert payload["tools"][0]["headers"]["Authorization"] == "Bearer PLACEHOLDER"
 
 
-def test_compat() -> None:
+def test_compat_responses_v1() -> None:
     # Check compatibility with v0.3 message format
     message_v03 = AIMessage(
         content=[
@@ -2357,6 +2361,421 @@ def test_compat() -> None:
     assert message_v03_output is not message_v03
 
 
+@pytest.mark.parametrize(
+    "message_v1, expected",
+    [
+        (
+            AIMessage(
+                [
+                    {"type": "reasoning", "reasoning": "Reasoning text"},
+                    {"type": "tool_call", "id": "call_123"},
+                    {
+                        "type": "text",
+                        "text": "Hello, world!",
+                        "annotations": [
+                            {"type": "url_citation", "url": "https://example.com"}
+                        ],
+                    },
+                ],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    }
+                ],
+                id="chatcmpl-123",
+                response_metadata={"foo": "bar"},
+            ),
+            AIMessage(
+                [{"type": "text", "text": "Hello, world!"}],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    }
+                ],
+                id="chatcmpl-123",
+                response_metadata={"foo": "bar"},
+            ),
+        )
+    ],
+)
+def test_convert_from_v1_to_chat_completions(
+    message_v1: AIMessage, expected: AIMessage
+) -> None:
+    result = _convert_from_v1_to_chat_completions(message_v1)
+    assert result == expected
+
+    # Check no mutation
+    assert message_v1 != result
+
+
+@pytest.mark.parametrize(
+    "message_chat_completions, expected",
+    [
+        (
+            AIMessage(
+                "Hello, world!", id="chatcmpl-123", response_metadata={"foo": "bar"}
+            ),
+            AIMessage(
+                [{"type": "text", "text": "Hello, world!"}],
+                id="chatcmpl-123",
+                response_metadata={"foo": "bar"},
+            ),
+        ),
+        (
+            AIMessage(
+                [{"type": "text", "text": "Hello, world!"}],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    }
+                ],
+                id="chatcmpl-123",
+                response_metadata={"foo": "bar"},
+            ),
+            AIMessage(
+                [
+                    {"type": "text", "text": "Hello, world!"},
+                    {"type": "tool_call", "id": "call_123"},
+                ],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    }
+                ],
+                id="chatcmpl-123",
+                response_metadata={"foo": "bar"},
+            ),
+        ),
+        (
+            AIMessage(
+                "",
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    }
+                ],
+                id="chatcmpl-123",
+                response_metadata={"foo": "bar"},
+                additional_kwargs={"tool_calls": [{"foo": "bar"}]},
+            ),
+            AIMessage(
+                [{"type": "tool_call", "id": "call_123"}],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    }
+                ],
+                id="chatcmpl-123",
+                response_metadata={"foo": "bar"},
+            ),
+        ),
+    ],
+)
+def test_convert_to_v1_from_chat_completions(
+    message_chat_completions: AIMessage, expected: AIMessage
+) -> None:
+    result = _convert_to_v1_from_chat_completions(message_chat_completions)
+    assert result == expected
+
+
+@pytest.mark.parametrize(
+    "message_v1, expected",
+    [
+        (
+            AIMessage(
+                [
+                    {"type": "reasoning", "id": "abc123"},
+                    {"type": "reasoning", "id": "abc234", "reasoning": "foo "},
+                    {"type": "reasoning", "id": "abc234", "reasoning": "bar"},
+                    {"type": "tool_call", "id": "call_123"},
+                    {
+                        "type": "tool_call",
+                        "id": "call_234",
+                        "name": "get_weather_2",
+                        "arguments": '{"location": "New York"}',
+                        "item_id": "fc_123",
+                    },
+                    {"type": "text", "text": "Hello "},
+                    {
+                        "type": "text",
+                        "text": "world",
+                        "annotations": [
+                            {"type": "url_citation", "url": "https://example.com"},
+                            {
+                                "type": "document_citation",
+                                "title": "my doc",
+                                "index": 1,
+                                "file_id": "file_123",
+                            },
+                            {
+                                "type": "non_standard_annotation",
+                                "value": {"bar": "baz"},
+                            },
+                        ],
+                    },
+                    {
+                        "type": "image",
+                        "source_type": "base64",
+                        "data": "...",
+                        "id": "img_123",
+                    },
+                    {
+                        "type": "non_standard",
+                        "value": {"type": "something_else", "foo": "bar"},
+                    },
+                ],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    },
+                    {
+                        # Make values different to check we pull from content when
+                        # available
+                        "type": "tool_call",
+                        "id": "call_234",
+                        "name": "get_weather_3",
+                        "args": {"location": "Boston"},
+                    },
+                ],
+                id="resp123",
+                response_metadata={"foo": "bar"},
+            ),
+            AIMessage(
+                [
+                    {"type": "reasoning", "id": "abc123"},
+                    {
+                        "type": "reasoning",
+                        "id": "abc234",
+                        "summary": [
+                            {"type": "summary_text", "text": "foo "},
+                            {"type": "summary_text", "text": "bar"},
+                        ],
+                    },
+                    {
+                        "type": "function_call",
+                        "call_id": "call_123",
+                        "name": "get_weather",
+                        "arguments": '{"location": "San Francisco"}',
+                    },
+                    {
+                        "type": "function_call",
+                        "call_id": "call_234",
+                        "name": "get_weather_2",
+                        "arguments": '{"location": "New York"}',
+                        "id": "fc_123",
+                    },
+                    {"type": "text", "text": "Hello "},
+                    {
+                        "type": "text",
+                        "text": "world",
+                        "annotations": [
+                            {"type": "url_citation", "url": "https://example.com"},
+                            {
+                                "type": "file_citation",
+                                "filename": "my doc",
+                                "index": 1,
+                                "file_id": "file_123",
+                            },
+                            {"bar": "baz"},
+                        ],
+                    },
+                    {"type": "image_generation_call", "id": "img_123", "result": "..."},
+                    {"type": "something_else", "foo": "bar"},
+                ],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    },
+                    {
+                        # Make values different to check we pull from content when
+                        # available
+                        "type": "tool_call",
+                        "id": "call_234",
+                        "name": "get_weather_3",
+                        "args": {"location": "Boston"},
+                    },
+                ],
+                id="resp123",
+                response_metadata={"foo": "bar"},
+            ),
+        )
+    ],
+)
+def test_convert_from_v1_to_responses(
+    message_v1: AIMessage, expected: AIMessage
+) -> None:
+    result = _convert_from_v1_to_responses(message_v1)
+    assert result == expected
+
+    # Check no mutation
+    assert message_v1 != result
+
+
+@pytest.mark.parametrize(
+    "message_responses, expected",
+    [
+        (
+            AIMessage(
+                [
+                    {"type": "reasoning", "id": "abc123"},
+                    {
+                        "type": "reasoning",
+                        "id": "abc234",
+                        "summary": [
+                            {"type": "summary_text", "text": "foo "},
+                            {"type": "summary_text", "text": "bar"},
+                        ],
+                    },
+                    {
+                        "type": "function_call",
+                        "call_id": "call_123",
+                        "name": "get_weather",
+                        "arguments": '{"location": "San Francisco"}',
+                    },
+                    {
+                        "type": "function_call",
+                        "call_id": "call_234",
+                        "name": "get_weather_2",
+                        "arguments": '{"location": "New York"}',
+                        "id": "fc_123",
+                    },
+                    {"type": "text", "text": "Hello "},
+                    {
+                        "type": "text",
+                        "text": "world",
+                        "annotations": [
+                            {"type": "url_citation", "url": "https://example.com"},
+                            {
+                                "type": "file_citation",
+                                "filename": "my doc",
+                                "index": 1,
+                                "file_id": "file_123",
+                            },
+                            {"bar": "baz"},
+                        ],
+                    },
+                    {"type": "image_generation_call", "id": "img_123", "result": "..."},
+                    {"type": "something_else", "foo": "bar"},
+                ],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    },
+                    {
+                        # Make values different to check we pull from content when
+                        # available
+                        "type": "tool_call",
+                        "id": "call_234",
+                        "name": "get_weather_3",
+                        "args": {"location": "Boston"},
+                    },
+                ],
+                id="resp123",
+                response_metadata={"foo": "bar"},
+            ),
+            AIMessage(
+                [
+                    {"type": "reasoning", "id": "abc123"},
+                    {"type": "reasoning", "id": "abc234", "reasoning": "foo "},
+                    {"type": "reasoning", "id": "abc234", "reasoning": "bar"},
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "arguments": '{"location": "San Francisco"}',
+                    },
+                    {
+                        "type": "tool_call",
+                        "id": "call_234",
+                        "name": "get_weather_2",
+                        "arguments": '{"location": "New York"}',
+                        "item_id": "fc_123",
+                    },
+                    {"type": "text", "text": "Hello "},
+                    {
+                        "type": "text",
+                        "text": "world",
+                        "annotations": [
+                            {"type": "url_citation", "url": "https://example.com"},
+                            {
+                                "type": "document_citation",
+                                "title": "my doc",
+                                "index": 1,
+                                "file_id": "file_123",
+                            },
+                            {
+                                "type": "non_standard_annotation",
+                                "value": {"bar": "baz"},
+                            },
+                        ],
+                    },
+                    {
+                        "type": "image",
+                        "source_type": "base64",
+                        "data": "...",
+                        "id": "img_123",
+                    },
+                    {
+                        "type": "non_standard",
+                        "value": {"type": "something_else", "foo": "bar"},
+                    },
+                ],
+                tool_calls=[
+                    {
+                        "type": "tool_call",
+                        "id": "call_123",
+                        "name": "get_weather",
+                        "args": {"location": "San Francisco"},
+                    },
+                    {
+                        # Make values different to check we pull from content when
+                        # available
+                        "type": "tool_call",
+                        "id": "call_234",
+                        "name": "get_weather_3",
+                        "args": {"location": "Boston"},
+                    },
+                ],
+                id="resp123",
+                response_metadata={"foo": "bar"},
+            ),
+        )
+    ],
+)
+def test_convert_to_v1_from_responses(
+    message_responses: AIMessage, expected: AIMessage
+) -> None:
+    result = _convert_to_v1_from_responses(message_responses)
+    assert result == expected
+
+
 def test_get_last_messages() -> None:
     messages: list[BaseMessage] = [HumanMessage("Hello")]
     last_messages, previous_response_id = _get_last_messages(messages)

libs/partners/openai/tests/unit_tests/chat_models/test_responses_stream.py

@@ -1,6 +1,7 @@
 from typing import Any, Optional
 from unittest.mock import MagicMock, patch
 
+import pytest
 from langchain_core.messages import AIMessageChunk, BaseMessageChunk
 from openai.types.responses import (
     ResponseCompletedEvent,
@@ -610,8 +611,97 @@ def _strip_none(obj: Any) -> Any:
         return obj
 
 
-def test_responses_stream() -> None:
+@pytest.mark.parametrize(
-    llm = ChatOpenAI(model="o4-mini", output_version="responses/v1")
+    "output_version, expected_content",
+    [
+        (
+            "responses/v1",
+            [
+                {
+                    "id": "rs_123",
+                    "summary": [
+                        {
+                            "index": 0,
+                            "type": "summary_text",
+                            "text": "reasoning block one",
+                        },
+                        {
+                            "index": 1,
+                            "type": "summary_text",
+                            "text": "another reasoning block",
+                        },
+                    ],
+                    "type": "reasoning",
+                    "index": 0,
+                },
+                {"type": "text", "text": "text block one", "index": 1, "id": "msg_123"},
+                {
+                    "type": "text",
+                    "text": "another text block",
+                    "index": 2,
+                    "id": "msg_123",
+                },
+                {
+                    "id": "rs_234",
+                    "summary": [
+                        {"index": 0, "type": "summary_text", "text": "more reasoning"},
+                        {
+                            "index": 1,
+                            "type": "summary_text",
+                            "text": "still more reasoning",
+                        },
+                    ],
+                    "type": "reasoning",
+                    "index": 3,
+                },
+                {"type": "text", "text": "more", "index": 4, "id": "msg_234"},
+                {"type": "text", "text": "text", "index": 5, "id": "msg_234"},
+            ],
+        ),
+        (
+            "v1",
+            [
+                {
+                    "type": "reasoning",
+                    "reasoning": "reasoning block one",
+                    "id": "rs_123",
+                    "index": 0,
+                },
+                {
+                    "type": "reasoning",
+                    "reasoning": "another reasoning block",
+                    "id": "rs_123",
+                    "index": 1,
+                },
+                {"type": "text", "text": "text block one", "index": 2, "id": "msg_123"},
+                {
+                    "type": "text",
+                    "text": "another text block",
+                    "index": 3,
+                    "id": "msg_123",
+                },
+                {
+                    "type": "reasoning",
+                    "reasoning": "more reasoning",
+                    "id": "rs_234",
+                    "index": 4,
+                },
+                {
+                    "type": "reasoning",
+                    "reasoning": "still more reasoning",
+                    "id": "rs_234",
+                    "index": 5,
+                },
+                {"type": "text", "text": "more", "index": 6, "id": "msg_234"},
+                {"type": "text", "text": "text", "index": 7, "id": "msg_234"},
+            ],
+        ),
+    ],
+)
+def test_responses_stream(output_version: str, expected_content: list[dict]) -> None:
+    llm = ChatOpenAI(
+        model="o4-mini", use_responses_api=True, output_version=output_version
+    )
     mock_client = MagicMock()
 
     def mock_create(*args: Any, **kwargs: Any) -> MockSyncContextManager:
@@ -620,36 +710,14 @@ def test_responses_stream() -> None:
     mock_client.responses.create = mock_create
 
     full: Optional[BaseMessageChunk] = None
+    chunks = []
     with patch.object(llm, "root_client", mock_client):
         for chunk in llm.stream("test"):
             assert isinstance(chunk, AIMessageChunk)
             full = chunk if full is None else full + chunk
-    assert isinstance(full, AIMessageChunk)
+            chunks.append(chunk)
 
-    expected_content = [
+    assert isinstance(full, AIMessageChunk)
-        {
-            "id": "rs_123",
-            "summary": [
-                {"index": 0, "type": "summary_text", "text": "reasoning block one"},
-                {"index": 1, "type": "summary_text", "text": "another reasoning block"},
-            ],
-            "type": "reasoning",
-            "index": 0,
-        },
-        {"type": "text", "text": "text block one", "index": 1, "id": "msg_123"},
-        {"type": "text", "text": "another text block", "index": 2, "id": "msg_123"},
-        {
-            "id": "rs_234",
-            "summary": [
-                {"index": 0, "type": "summary_text", "text": "more reasoning"},
-                {"index": 1, "type": "summary_text", "text": "still more reasoning"},
-            ],
-            "type": "reasoning",
-            "index": 3,
-        },
-        {"type": "text", "text": "more", "index": 4, "id": "msg_234"},
-        {"type": "text", "text": "text", "index": 5, "id": "msg_234"},
-    ]
     assert full.content == expected_content
     assert full.additional_kwargs == {}
     assert full.id == "resp_123"