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fix: docs and formatting (#32448)

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Mason Daugherty 2025-08-07 15:17:25 -04:00 committed by GitHub
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9 changed files with 602 additions and 581 deletions
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4
docs/api_reference/create_api_rst.py
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@ -217,8 +217,8 @@ def _load_package_modules(
# Get the full namespace of the module
namespace = str(relative_module_name).replace(".py", "").replace("/", ".")
# Keep only the top level namespace
# (but make special exception for content_blocks and messages.v1)
if namespace == "messages.content_blocks" or namespace == "messages.v1":
# (but make special exception for content_blocks and v1.messages)
if namespace == "messages.content_blocks" or namespace == "v1.messages":
top_namespace = namespace # Keep full namespace for content_blocks
else:
top_namespace = namespace.split(".")[0]

4
docs/docs/how_to/graph_constructing.ipynb
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@ -122,13 +122,13 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"from langchain_experimental.graph_transformers import LLMGraphTransformer\n",
"# from langchain_experimental.graph_transformers import LLMGraphTransformer\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"llm = ChatOpenAI(temperature=0, model_name=\"gpt-4-turbo\")\n",

4
docs/docs/how_to/semantic-chunker.ipynb
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@ -74,12 +74,12 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "a88ff70c",
"metadata": {},
"outputs": [],
"source": [
"from langchain_experimental.text_splitter import SemanticChunker\n",
"# from langchain_experimental.text_splitter import SemanticChunker\n",
"from langchain_openai.embeddings import OpenAIEmbeddings\n",
"\n",
"text_splitter = SemanticChunker(OpenAIEmbeddings())"

53
docs/docs/how_to/sql_csv.ipynb
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@ -612,56 +612,11 @@
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": null,
"id": "35ea904e-795f-411b-bef8-6484dbb6e35c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3m\n",
"Invoking: `python_repl_ast` with `{'query': \"df[['Age', 'Fare']].corr().iloc[0,1]\"}`\n",
"\n",
"\n",
"\u001b[0m\u001b[36;1m\u001b[1;3m0.11232863699941621\u001b[0m\u001b[32;1m\u001b[1;3m\n",
"Invoking: `python_repl_ast` with `{'query': \"df[['Fare', 'Survived']].corr().iloc[0,1]\"}`\n",
"\n",
"\n",
"\u001b[0m\u001b[36;1m\u001b[1;3m0.2561785496289603\u001b[0m\u001b[32;1m\u001b[1;3mThe correlation between Age and Fare is approximately 0.112, and the correlation between Fare and Survival is approximately 0.256.\n",
"\n",
"Therefore, the correlation between Fare and Survival (0.256) is greater than the correlation between Age and Fare (0.112).\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"{'input': \"What's the correlation between age and fare? is that greater than the correlation between fare and survival?\",\n",
" 'output': 'The correlation between Age and Fare is approximately 0.112, and the correlation between Fare and Survival is approximately 0.256.\\n\\nTherefore, the correlation between Fare and Survival (0.256) is greater than the correlation between Age and Fare (0.112).'}"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain_experimental.agents import create_pandas_dataframe_agent\n",
"\n",
"agent = create_pandas_dataframe_agent(\n",
" llm, df, agent_type=\"openai-tools\", verbose=True, allow_dangerous_code=True\n",
")\n",
"agent.invoke(\n",
" {\n",
" \"input\": \"What's the correlation between age and fare? is that greater than the correlation between fare and survival?\"\n",
" }\n",
")"
]
"outputs": [],
"source": "from langchain_experimental.agents import create_pandas_dataframe_agent\n\nagent = create_pandas_dataframe_agent(\n llm, df, agent_type=\"openai-tools\", verbose=True, allow_dangerous_code=True\n)\nagent.invoke(\n {\n \"input\": \"What's the correlation between age and fare? is that greater than the correlation between fare and survival?\"\n }\n)"
},
{
"cell_type": "markdown",
@ -786,4 +741,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
}
}

5
docs/docs/integrations/graphs/kuzu_db.ipynb
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@ -132,12 +132,13 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from langchain_core.documents import Document\n",
"from langchain_experimental.graph_transformers import LLMGraphTransformer\n",
"\n",
"# from langchain_experimental.graph_transformers import LLMGraphTransformer\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"# Define the LLMGraphTransformer\n",

4
docs/docs/integrations/graphs/memgraph.ipynb
View File

@ -548,12 +548,12 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from langchain_core.documents import Document\n",
"from langchain_experimental.graph_transformers import LLMGraphTransformer"
"# from langchain_experimental.graph_transformers import LLMGraphTransformer"
]
},
{

932
libs/core/langchain_core/runnables/base.py
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File diff suppressed because it is too large Load Diff

2
libs/core/langchain_core/v1/__init__.py
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@ -1 +1 @@
"""LangChain v1.0 types."""
"""LangChain v1.0.0 types."""

175
libs/core/langchain_core/v1/chat_models.py
View File

@ -105,13 +105,14 @@ def _format_for_tracing(messages: Sequence[MessageV1]) -> list[MessageV1]:
- Update image content blocks to OpenAI Chat Completions format (backward
compatibility).
- Add "type" key to content blocks that have a single key.
- Add ``'type'`` key to content blocks that have a single key.
Args:
messages: List of messages to format.
Returns:
List of messages formatted for tracing.
"""
messages_to_trace = []
for message in messages:
@ -142,10 +143,11 @@ def generate_from_stream(stream: Iterator[AIMessageChunkV1]) -> AIMessageV1:
"""Generate from a stream.
Args:
stream: Iterator of AIMessageChunkV1.
stream: Iterator of ``AIMessageChunkV1``.
Returns:
AIMessageV1: aggregated message.
"""
generation = next(stream, None)
if generation:
@ -162,10 +164,11 @@ async def agenerate_from_stream(
"""Async generate from a stream.
Args:
stream: Iterator of AIMessageChunkV1.
stream: Iterator of ``AIMessageChunkV1``.
Returns:
AIMessageV1: aggregated message.
"""
chunks = [chunk async for chunk in stream]
return await run_in_executor(None, generate_from_stream, iter(chunks))
@ -196,48 +199,48 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
Key imperative methods:
Methods that actually call the underlying model.
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| Method | Input | Output | Description |
+===========================+================================================================+=====================================================================+==================================================================================================+
| `invoke` | str | list[dict | tuple | BaseMessage] | PromptValue | BaseMessage | A single chat model call. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| `ainvoke` | ''' | BaseMessage | Defaults to running invoke in an async executor. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| `stream` | ''' | Iterator[BaseMessageChunk] | Defaults to yielding output of invoke. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| `astream` | ''' | AsyncIterator[BaseMessageChunk] | Defaults to yielding output of ainvoke. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| `astream_events` | ''' | AsyncIterator[StreamEvent] | Event types: 'on_chat_model_start', 'on_chat_model_stream', 'on_chat_model_end'. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| `batch` | list['''] | list[BaseMessage] | Defaults to running invoke in concurrent threads. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| `abatch` | list['''] | list[BaseMessage] | Defaults to running ainvoke in concurrent threads. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| `batch_as_completed` | list['''] | Iterator[tuple[int, Union[BaseMessage, Exception]]] | Defaults to running invoke in concurrent threads. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| `abatch_as_completed` | list['''] | AsyncIterator[tuple[int, Union[BaseMessage, Exception]]] | Defaults to running ainvoke in concurrent threads. |
+---------------------------+----------------------------------------------------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| Method | Input | Output | Description |
+=============================+================================================================+=========================================================================+==================================================================================================+
| ``invoke`` | str | list[dict | tuple | BaseMessage] | PromptValue | ``BaseMessage`` | A single chat model call. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| ``ainvoke`` | ''' | ``BaseMessage`` | Defaults to running ``invoke`` in an async executor. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| ``stream`` | ''' | ``Iterator[BaseMessageChunk]`` | Defaults to yielding output of ``invoke``. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| ``astream`` | ''' | ``AsyncIterator[BaseMessageChunk]`` | Defaults to yielding output of ``ainvoke``. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| ``astream_events`` | ''' | ``AsyncIterator[StreamEvent]`` | Event types: ``'on_chat_model_start'``, ``'on_chat_model_stream'``, ``'on_chat_model_end'``. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| ``batch`` | list['''] | ``list[BaseMessage]`` | Defaults to running ``invoke`` in concurrent threads. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| ``abatch`` | list['''] | ``list[BaseMessage]`` | Defaults to running ``ainvoke`` in concurrent threads. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| ``batch_as_completed`` | list['''] | ``Iterator[tuple[int, Union[BaseMessage, Exception]]]`` | Defaults to running ``invoke`` in concurrent threads. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| ``abatch_as_completed`` | list['''] | ``AsyncIterator[tuple[int, Union[BaseMessage, Exception]]]`` | Defaults to running ``ainvoke`` in concurrent threads. |
+-----------------------------+----------------------------------------------------------------+-------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
This table provides a brief overview of the main imperative methods. Please see the base Runnable reference for full documentation.
This table provides a brief overview of the main imperative methods. Please see the base ``Runnable`` reference for full documentation.
Key declarative methods:
Methods for creating another Runnable using the ChatModel.
Methods for creating another ``Runnable`` using the ``ChatModel``.
+----------------------------------+-----------------------------------------------------------------------------------------------------------+
| Method | Description |
+==================================+===========================================================================================================+
| `bind_tools` | Create ChatModel that can call tools. |
+----------------------------------+-----------------------------------------------------------------------------------------------------------+
| `with_structured_output` | Create wrapper that structures model output using schema. |
+----------------------------------+-----------------------------------------------------------------------------------------------------------+
| `with_retry` | Create wrapper that retries model calls on failure. |
+----------------------------------+-----------------------------------------------------------------------------------------------------------+
| `with_fallbacks` | Create wrapper that falls back to other models on failure. |
+----------------------------------+-----------------------------------------------------------------------------------------------------------+
| `configurable_fields` | Specify init args of the model that can be configured at runtime via the RunnableConfig. |
+----------------------------------+-----------------------------------------------------------------------------------------------------------+
| `configurable_alternatives` | Specify alternative models which can be swapped in at runtime via the RunnableConfig. |
+----------------------------------+-----------------------------------------------------------------------------------------------------------+
+------------------------------------+-----------------------------------------------------------------------------------------------------------+
| Method | Description |
+====================================+===========================================================================================================+
| ``bind_tools`` | Create ``ChatModel`` that can call tools. |
+------------------------------------+-----------------------------------------------------------------------------------------------------------+
| ``with_structured_output`` | Create wrapper that structures model output using schema. |
+------------------------------------+-----------------------------------------------------------------------------------------------------------+
| ``with_retry`` | Create wrapper that retries model calls on failure. |
+------------------------------------+-----------------------------------------------------------------------------------------------------------+
| ``with_fallbacks`` | Create wrapper that falls back to other models on failure. |
+------------------------------------+-----------------------------------------------------------------------------------------------------------+
| ``configurable_fields`` | Specify init args of the model that can be configured at runtime via the ``RunnableConfig``. |
+------------------------------------+-----------------------------------------------------------------------------------------------------------+
| ``configurable_alternatives`` | Specify alternative models which can be swapped in at runtime via the ``RunnableConfig``. |
+------------------------------------+-----------------------------------------------------------------------------------------------------------+
This table provides a brief overview of the main declarative methods. Please see the reference for each method for full documentation.
@ -246,24 +249,23 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
Please reference the table below for information about which
methods and properties are required or optional for implementations.
+----------------------------------+--------------------------------------------------------------------+-------------------+
| Method/Property | Description | Required/Optional |
+==================================+====================================================================+===================+
| `_generate` | Use to generate a chat result from a prompt | Required |
+----------------------------------+--------------------------------------------------------------------+-------------------+
| `_llm_type` (property) | Used to uniquely identify the type of the model. Used for logging. | Required |
+----------------------------------+--------------------------------------------------------------------+-------------------+
| `_identifying_params` (property) | Represent model parameterization for tracing purposes. | Optional |
+----------------------------------+--------------------------------------------------------------------+-------------------+
| `_stream` | Use to implement streaming | Optional |
+----------------------------------+--------------------------------------------------------------------+-------------------+
| `_agenerate` | Use to implement a native async method | Optional |
+----------------------------------+--------------------------------------------------------------------+-------------------+
| `_astream` | Use to implement async version of `_stream` | Optional |
+----------------------------------+--------------------------------------------------------------------+-------------------+
+------------------------------------+--------------------------------------------------------------------+-------------------+
| Method/Property | Description | Required/Optional |
+====================================+====================================================================+===================+
| ``_generate`` | Use to generate a chat result from a prompt | Required |
+------------------------------------+--------------------------------------------------------------------+-------------------+
| ``_llm_type`` (property) | Used to uniquely identify the type of the model. Used for logging. | Required |
+------------------------------------+--------------------------------------------------------------------+-------------------+
| ``_identifying_params`` (property) | Represent model parameterization for tracing purposes. | Optional |
+------------------------------------+--------------------------------------------------------------------+-------------------+
| ``_stream`` | Use to implement streaming | Optional |
+------------------------------------+--------------------------------------------------------------------+-------------------+
| ``_agenerate`` | Use to implement a native ``async`` method | Optional |
+------------------------------------+--------------------------------------------------------------------+-------------------+
| ``_astream`` | Use to implement async version of ``_stream`` | Optional |
+------------------------------------+--------------------------------------------------------------------+-------------------+
Follow the guide for more information on how to implement a custom Chat Model:
[Guide](https://python.langchain.com/docs/how_to/custom_chat_model/).
`Follow the guide for more information on how to implement a custom Chat Model. <https://python.langchain.com/docs/how_to/custom_chat_model/>`__
""" # noqa: E501
@ -283,9 +285,10 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
provided. This offers the best of both worlds.
- If False (default), will always use streaming case if available.
The main reason for this flag is that code might be written using ``.stream()`` and
The main reason for this flag is that code might be written using ``stream()`` and
a user may want to swap out a given model for another model whose the implementation
does not properly support streaming.
"""
cache: Union[BaseCache, bool, None] = Field(default=None, exclude=True)
@ -294,9 +297,10 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
* If true, will use the global cache.
* If false, will not use a cache
* If None, will use the global cache if it's set, otherwise no cache.
* If instance of BaseCache, will use the provided cache.
* If instance of ``BaseCache``, will use the provided cache.
Caching is not currently supported for streaming methods of models.
"""
verbose: bool = Field(default_factory=_get_verbosity, exclude=True, repr=False)
"""Whether to print out response text."""
@ -332,6 +336,7 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
Returns:
The verbosity setting to use.
"""
if verbose is None:
return _get_verbosity()
@ -340,7 +345,7 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
@property
@override
def InputType(self) -> Any:
"""Get the input type for this runnable."""
"""Get the input type for this ``Runnable``."""
from langchain_core.prompt_values import (
ChatPromptValueConcrete,
StringPromptValue,
@ -358,7 +363,7 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
@property
@override
def OutputType(self) -> Any:
"""Get the output type for this runnable."""
"""Get the output type for this ``Runnable``."""
return AIMessageV1
def _convert_input(self, model_input: LanguageModelInput) -> list[MessageV1]:
@ -825,10 +830,11 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
Args:
tools: Sequence of tools to bind to the model.
tool_choice: The tool to use. If "any" then any tool can be used.
tool_choice: The tool to use. If ``'any'`` then any tool can be used.
Returns:
A Runnable that returns a message.
A ``Runnable`` that returns a message.
"""
raise NotImplementedError
@ -853,30 +859,30 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
validated by the Pydantic class. Otherwise the model output will be a
dict and will not be validated. See :meth:`langchain_core.utils.function_calling.convert_to_openai_tool`
for more on how to properly specify types and descriptions of
schema fields when specifying a Pydantic or TypedDict class.
schema fields when specifying a Pydantic or ``TypedDict`` class.
include_raw:
If False then only the parsed structured output is returned. If
an error occurs during model output parsing it will be raised. If True
then both the raw model response (a BaseMessage) and the parsed model
then both the raw model response (a ``BaseMessage``) and the parsed model
response will be returned. If an error occurs during output parsing it
will be caught and returned as well. The final output is always a dict
with keys "raw", "parsed", and "parsing_error".
with keys ``'raw'``, ``'parsed'``, and ``'parsing_error'``.
Returns:
A Runnable that takes same inputs as a :class:`langchain_core.language_models.chat.BaseChatModel`.
A ``Runnable`` that takes same inputs as a :class:`langchain_core.language_models.chat.BaseChatModel`.
If ``include_raw`` is False and ``schema`` is a Pydantic class, Runnable outputs
If ``include_raw`` is False and ``schema`` is a Pydantic class, ``Runnable`` outputs
an instance of ``schema`` (i.e., a Pydantic object).
Otherwise, if ``include_raw`` is False then Runnable outputs a dict.
Otherwise, if ``include_raw`` is False then ``Runnable`` outputs a dict.
If ``include_raw`` is True, then Runnable outputs a dict with keys:
- ``"raw"``: BaseMessage
If ``include_raw`` is True, then ``Runnable`` outputs a dict with keys:
- ``"raw"``: ``BaseMessage``
- ``"parsed"``: None if there was a parsing error, otherwise the type depends on the ``schema`` as described above.
- ``"parsing_error"``: Optional[BaseException]
- ``"parsing_error"``: ``Optional[BaseException]``
Example: Pydantic schema (include_raw=False):
Example: Pydantic schema ``(include_raw=False)``:
.. code-block:: python
from pydantic import BaseModel
@ -896,7 +902,7 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
# justification='Both a pound of bricks and a pound of feathers weigh one pound. The weight is the same, but the volume or density of the objects may differ.'
# )
Example: Pydantic schema (include_raw=True):
Example: Pydantic schema ``(include_raw=True)``:
.. code-block:: python
from pydantic import BaseModel
@ -916,7 +922,7 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
# 'parsing_error': None
# }
Example: Dict schema (include_raw=False):
Example: Dict schema ``(include_raw=False)``:
.. code-block:: python
from pydantic import BaseModel
@ -939,7 +945,8 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
.. versionchanged:: 0.2.26
Added support for TypedDict class.
Added support for ``TypedDict`` class.
""" # noqa: E501
_ = kwargs.pop("method", None)
_ = kwargs.pop("strict", None)
@ -997,7 +1004,8 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
Returns:
A list of ids corresponding to the tokens in the text, in order they occur
in the text.
in the text.
"""
if self.custom_get_token_ids is not None:
return self.custom_get_token_ids(text)
@ -1013,6 +1021,7 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
Returns:
The integer number of tokens in the text.
"""
return len(self.get_token_ids(text))
@ -1025,16 +1034,18 @@ class BaseChatModel(RunnableSerializable[LanguageModelInput, AIMessageV1], ABC):
Useful for checking if an input fits in a model's context window.
**Note**: the base implementation of get_num_tokens_from_messages ignores
tool schemas.
.. note::
The base implementation of ``get_num_tokens_from_messages`` ignores tool
schemas.
Args:
messages: The message inputs to tokenize.
tools: If provided, sequence of dict, BaseModel, function, or BaseTools
to be converted to tool schemas.
tools: If provided, sequence of ``dict``, ``BaseModel``, function, or
``BaseTools`` to be converted to tool schemas.
Returns:
The sum of the number of tokens across the messages.
"""
messages_v0 = [convert_from_v1_message(message) for message in messages]
if tools is not None: