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Merge branch 'master' into pprados/pdf-router

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Philippe PRADOS 2025-04-16 09:07:21 +02:00 committed by GitHub
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27 changed files with 677 additions and 182 deletions
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7
.github/workflows/_release.yml vendored
View File

@ -395,8 +395,11 @@ jobs:
# Checkout the latest package files
rm -rf $GITHUB_WORKSPACE/libs/partners/${{ matrix.partner }}/*
cd $GITHUB_WORKSPACE/libs/partners/${{ matrix.partner }}
git checkout "$LATEST_PACKAGE_TAG" -- .
rm -rf $GITHUB_WORKSPACE/libs/standard-tests/*
cd $GITHUB_WORKSPACE/libs/
git checkout "$LATEST_PACKAGE_TAG" -- standard-tests/
git checkout "$LATEST_PACKAGE_TAG" -- partners/${{ matrix.partner }}/
cd partners/${{ matrix.partner }}
# Print as a sanity check
echo "Version number from pyproject.toml: "

8
libs/core/langchain_core/indexing/api.py
View File

@ -37,14 +37,18 @@ T = TypeVar("T")
def _hash_string_to_uuid(input_string: str) -> uuid.UUID:
"""Hashes a string and returns the corresponding UUID."""
hash_value = hashlib.sha1(input_string.encode("utf-8")).hexdigest() # noqa: S324
hash_value = hashlib.sha1(
input_string.encode("utf-8"), usedforsecurity=False
).hexdigest()
return uuid.uuid5(NAMESPACE_UUID, hash_value)
def _hash_nested_dict_to_uuid(data: dict[Any, Any]) -> uuid.UUID:
"""Hashes a nested dictionary and returns the corresponding UUID."""
serialized_data = json.dumps(data, sort_keys=True)
hash_value = hashlib.sha1(serialized_data.encode("utf-8")).hexdigest() # noqa: S324
hash_value = hashlib.sha1(
serialized_data.encode("utf-8"), usedforsecurity=False
).hexdigest()
return uuid.uuid5(NAMESPACE_UUID, hash_value)

9
libs/core/langchain_core/load/__init__.py
View File

@ -5,15 +5,20 @@ from typing import TYPE_CHECKING
if TYPE_CHECKING:
from langchain_core.load.dump import dumpd, dumps
from langchain_core.load.load import load, loads
from langchain_core.load.load import loads
from langchain_core.load.serializable import Serializable
# Unfortunately, we have to eagerly import load from langchain_core/load/load.py
# eagerly to avoid a namespace conflict. We want users to still be able to use
# `from langchain_core.load import load` to get the load function, but
# the `from langchain_core.load.load import load` absolute import should also work.
from langchain_core.load.load import load
__all__ = ["dumpd", "dumps", "load", "loads", "Serializable"]
_dynamic_imports = {
"dumpd": "dump",
"dumps": "dump",
"load": "load",
"loads": "load",
"Serializable": "serializable",
}

2
libs/core/langchain_core/output_parsers/__init__.py
View File

@ -99,4 +99,4 @@ def __getattr__(attr_name: str) -> object:
def __dir__() -> list[str]:
return list(__all__)
return __all__

146
libs/core/langchain_core/prompts/chat.py
View File

@ -25,7 +25,6 @@ from pydantic import (
from typing_extensions import Self, override
from langchain_core._api import deprecated
from langchain_core.load import Serializable
from langchain_core.messages import (
AIMessage,
AnyMessage,
@ -39,6 +38,10 @@ from langchain_core.messages.base import get_msg_title_repr
from langchain_core.prompt_values import ChatPromptValue, ImageURL, PromptValue
from langchain_core.prompts.base import BasePromptTemplate
from langchain_core.prompts.image import ImagePromptTemplate
from langchain_core.prompts.message import (
BaseMessagePromptTemplate,
_DictMessagePromptTemplate,
)
from langchain_core.prompts.prompt import PromptTemplate
from langchain_core.prompts.string import (
PromptTemplateFormat,
@ -52,87 +55,6 @@ if TYPE_CHECKING:
from collections.abc import Sequence
class BaseMessagePromptTemplate(Serializable, ABC):
"""Base class for message prompt templates."""
@classmethod
def is_lc_serializable(cls) -> bool:
"""Return whether or not the class is serializable.
Returns: True.
"""
return True
@classmethod
def get_lc_namespace(cls) -> list[str]:
"""Get the namespace of the langchain object.
Default namespace is ["langchain", "prompts", "chat"].
"""
return ["langchain", "prompts", "chat"]
@abstractmethod
def format_messages(self, **kwargs: Any) -> list[BaseMessage]:
"""Format messages from kwargs. Should return a list of BaseMessages.
Args:
**kwargs: Keyword arguments to use for formatting.
Returns:
List of BaseMessages.
"""
async def aformat_messages(self, **kwargs: Any) -> list[BaseMessage]:
"""Async format messages from kwargs.
Args:
**kwargs: Keyword arguments to use for formatting.
Returns:
List of BaseMessages.
"""
return self.format_messages(**kwargs)
@property
@abstractmethod
def input_variables(self) -> list[str]:
"""Input variables for this prompt template.
Returns:
List of input variables.
"""
def pretty_repr(
self,
html: bool = False, # noqa: FBT001,FBT002
) -> str:
"""Human-readable representation.
Args:
html: Whether to format as HTML. Defaults to False.
Returns:
Human-readable representation.
"""
raise NotImplementedError
def pretty_print(self) -> None:
"""Print a human-readable representation."""
print(self.pretty_repr(html=is_interactive_env())) # noqa: T201
def __add__(self, other: Any) -> ChatPromptTemplate:
"""Combine two prompt templates.
Args:
other: Another prompt template.
Returns:
Combined prompt template.
"""
prompt = ChatPromptTemplate(messages=[self])
return prompt + other
class MessagesPlaceholder(BaseMessagePromptTemplate):
"""Prompt template that assumes variable is already list of messages.
@ -473,7 +395,10 @@ class _StringImageMessagePromptTemplate(BaseMessagePromptTemplate):
"""Human message prompt template. This is a message sent from the user."""
prompt: Union[
StringPromptTemplate, list[Union[StringPromptTemplate, ImagePromptTemplate]]
StringPromptTemplate,
list[
Union[StringPromptTemplate, ImagePromptTemplate, _DictMessagePromptTemplate]
],
]
"""Prompt template."""
additional_kwargs: dict = Field(default_factory=dict)
@ -484,7 +409,10 @@ class _StringImageMessagePromptTemplate(BaseMessagePromptTemplate):
@classmethod
def from_template(
cls: type[Self],
template: Union[str, list[Union[str, _TextTemplateParam, _ImageTemplateParam]]],
template: Union[
str,
list[Union[str, _TextTemplateParam, _ImageTemplateParam, dict[str, Any]]],
],
template_format: PromptTemplateFormat = "f-string",
*,
partial_variables: Optional[dict[str, Any]] = None,
@ -567,6 +495,19 @@ class _StringImageMessagePromptTemplate(BaseMessagePromptTemplate):
msg = f"Invalid image template: {tmpl}"
raise ValueError(msg)
prompt.append(img_template_obj)
elif isinstance(tmpl, dict):
if template_format == "jinja2":
msg = (
"jinja2 is unsafe and is not supported for templates "
"expressed as dicts. Please use 'f-string' or 'mustache' "
"format."
)
raise ValueError(msg)
data_template_obj = _DictMessagePromptTemplate(
template=cast("dict[str, Any]", tmpl),
template_format=template_format,
)
prompt.append(data_template_obj)
else:
msg = f"Invalid template: {tmpl}"
raise ValueError(msg)
@ -644,11 +585,16 @@ class _StringImageMessagePromptTemplate(BaseMessagePromptTemplate):
for prompt in self.prompt:
inputs = {var: kwargs[var] for var in prompt.input_variables}
if isinstance(prompt, StringPromptTemplate):
formatted: Union[str, ImageURL] = prompt.format(**inputs)
formatted: Union[str, ImageURL, dict[str, Any]] = prompt.format(
**inputs
)
content.append({"type": "text", "text": formatted})
elif isinstance(prompt, ImagePromptTemplate):
formatted = prompt.format(**inputs)
content.append({"type": "image_url", "image_url": formatted})
elif isinstance(prompt, _DictMessagePromptTemplate):
formatted = prompt.format(**inputs)
content.append(formatted)
return self._msg_class(
content=content, additional_kwargs=self.additional_kwargs
)
@ -671,11 +617,16 @@ class _StringImageMessagePromptTemplate(BaseMessagePromptTemplate):
for prompt in self.prompt:
inputs = {var: kwargs[var] for var in prompt.input_variables}
if isinstance(prompt, StringPromptTemplate):
formatted: Union[str, ImageURL] = await prompt.aformat(**inputs)
formatted: Union[str, ImageURL, dict[str, Any]] = await prompt.aformat(
**inputs
)
content.append({"type": "text", "text": formatted})
elif isinstance(prompt, ImagePromptTemplate):
formatted = await prompt.aformat(**inputs)
content.append({"type": "image_url", "image_url": formatted})
elif isinstance(prompt, _DictMessagePromptTemplate):
formatted = prompt.format(**inputs)
content.append(formatted)
return self._msg_class(
content=content, additional_kwargs=self.additional_kwargs
)
@ -811,7 +762,7 @@ MessageLikeRepresentation = Union[
Union[str, list[dict], list[object]],
],
str,
dict,
dict[str, Any],
]
@ -984,7 +935,8 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
"""
_messages = [
_convert_to_message(message, template_format) for message in messages
_convert_to_message_template(message, template_format)
for message in messages
]
# Automatically infer input variables from messages
@ -1071,7 +1023,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
ValueError: If input variables do not match.
"""
messages = values["messages"]
input_vars = set()
input_vars: set = set()
optional_variables = set()
input_types: dict[str, Any] = values.get("input_types", {})
for message in messages:
@ -1126,7 +1078,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
return cls.from_messages([message])
@classmethod
@deprecated("0.0.1", alternative="from_messages classmethod", pending=True)
@deprecated("0.0.1", alternative="from_messages", pending=True)
def from_role_strings(
cls, string_messages: list[tuple[str, str]]
) -> ChatPromptTemplate:
@ -1146,7 +1098,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
)
@classmethod
@deprecated("0.0.1", alternative="from_messages classmethod", pending=True)
@deprecated("0.0.1", alternative="from_messages", pending=True)
def from_strings(
cls, string_messages: list[tuple[type[BaseMessagePromptTemplate], str]]
) -> ChatPromptTemplate:
@ -1297,7 +1249,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
Args:
message: representation of a message to append.
"""
self.messages.append(_convert_to_message(message))
self.messages.append(_convert_to_message_template(message))
def extend(self, messages: Sequence[MessageLikeRepresentation]) -> None:
"""Extend the chat template with a sequence of messages.
@ -1305,7 +1257,9 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
Args:
messages: sequence of message representations to append.
"""
self.messages.extend([_convert_to_message(message) for message in messages])
self.messages.extend(
[_convert_to_message_template(message) for message in messages]
)
@overload
def __getitem__(self, index: int) -> MessageLike: ...
@ -1425,7 +1379,7 @@ def _create_template_from_message_type(
return message
def _convert_to_message(
def _convert_to_message_template(
message: MessageLikeRepresentation,
template_format: PromptTemplateFormat = "f-string",
) -> Union[BaseMessage, BaseMessagePromptTemplate, BaseChatPromptTemplate]:
@ -1488,3 +1442,7 @@ def _convert_to_message(
raise NotImplementedError(msg)
return _message
# For backwards compat:
_convert_to_message = _convert_to_message_template

6
libs/core/langchain_core/prompts/few_shot.py
View File

@ -14,10 +14,8 @@ from typing_extensions import override
from langchain_core.example_selectors import BaseExampleSelector
from langchain_core.messages import BaseMessage, get_buffer_string
from langchain_core.prompts.chat import (
BaseChatPromptTemplate,
BaseMessagePromptTemplate,
)
from langchain_core.prompts.chat import BaseChatPromptTemplate
from langchain_core.prompts.message import BaseMessagePromptTemplate
from langchain_core.prompts.prompt import PromptTemplate
from langchain_core.prompts.string import (
DEFAULT_FORMATTER_MAPPING,

186
libs/core/langchain_core/prompts/message.py Normal file
View File

@ -0,0 +1,186 @@
"""Message prompt templates."""
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import TYPE_CHECKING, Any, Literal
from langchain_core.load import Serializable
from langchain_core.messages import BaseMessage, convert_to_messages
from langchain_core.prompts.string import (
DEFAULT_FORMATTER_MAPPING,
get_template_variables,
)
from langchain_core.utils.interactive_env import is_interactive_env
if TYPE_CHECKING:
from langchain_core.prompts.chat import ChatPromptTemplate
class BaseMessagePromptTemplate(Serializable, ABC):
"""Base class for message prompt templates."""
@classmethod
def is_lc_serializable(cls) -> bool:
"""Return whether or not the class is serializable.
Returns: True.
"""
return True
@classmethod
def get_lc_namespace(cls) -> list[str]:
"""Get the namespace of the langchain object.
Default namespace is ["langchain", "prompts", "chat"].
"""
return ["langchain", "prompts", "chat"]
@abstractmethod
def format_messages(self, **kwargs: Any) -> list[BaseMessage]:
"""Format messages from kwargs. Should return a list of BaseMessages.
Args:
**kwargs: Keyword arguments to use for formatting.
Returns:
List of BaseMessages.
"""
async def aformat_messages(self, **kwargs: Any) -> list[BaseMessage]:
"""Async format messages from kwargs.
Args:
**kwargs: Keyword arguments to use for formatting.
Returns:
List of BaseMessages.
"""
return self.format_messages(**kwargs)
@property
@abstractmethod
def input_variables(self) -> list[str]:
"""Input variables for this prompt template.
Returns:
List of input variables.
"""
def pretty_repr(
self,
html: bool = False, # noqa: FBT001,FBT002
) -> str:
"""Human-readable representation.
Args:
html: Whether to format as HTML. Defaults to False.
Returns:
Human-readable representation.
"""
raise NotImplementedError
def pretty_print(self) -> None:
"""Print a human-readable representation."""
print(self.pretty_repr(html=is_interactive_env())) # noqa: T201
def __add__(self, other: Any) -> ChatPromptTemplate:
"""Combine two prompt templates.
Args:
other: Another prompt template.
Returns:
Combined prompt template.
"""
from langchain_core.prompts.chat import ChatPromptTemplate
prompt = ChatPromptTemplate(messages=[self])
return prompt + other
class _DictMessagePromptTemplate(BaseMessagePromptTemplate):
"""Template represented by a dict that recursively fills input vars in string vals.
Special handling of image_url dicts to load local paths. These look like:
``{"type": "image_url", "image_url": {"path": "..."}}``
"""
template: dict[str, Any]
template_format: Literal["f-string", "mustache"]
def format_messages(self, **kwargs: Any) -> list[BaseMessage]:
msg_dict = _insert_input_variables(self.template, kwargs, self.template_format)
return convert_to_messages([msg_dict])
@property
def input_variables(self) -> list[str]:
return _get_input_variables(self.template, self.template_format)
@property
def _prompt_type(self) -> str:
return "message-dict-prompt"
@classmethod
def get_lc_namespace(cls) -> list[str]:
return ["langchain_core", "prompts", "message"]
def format(
self,
**kwargs: Any,
) -> dict[str, Any]:
"""Format the prompt with the inputs."""
return _insert_input_variables(self.template, kwargs, self.template_format)
def _get_input_variables(
template: dict, template_format: Literal["f-string", "mustache"]
) -> list[str]:
input_variables = []
for v in template.values():
if isinstance(v, str):
input_variables += get_template_variables(v, template_format)
elif isinstance(v, dict):
input_variables += _get_input_variables(v, template_format)
elif isinstance(v, (list, tuple)):
for x in v:
if isinstance(x, str):
input_variables += get_template_variables(x, template_format)
elif isinstance(x, dict):
input_variables += _get_input_variables(x, template_format)
return list(set(input_variables))
def _insert_input_variables(
template: dict[str, Any],
inputs: dict[str, Any],
template_format: Literal["f-string", "mustache"],
) -> dict[str, Any]:
formatted = {}
formatter = DEFAULT_FORMATTER_MAPPING[template_format]
for k, v in template.items():
if isinstance(v, str):
formatted[k] = formatter(v, **inputs)
elif isinstance(v, dict):
# No longer support loading local images.
if k == "image_url" and "path" in v:
msg = (
"Specifying image inputs via file path in environments with "
"user-input paths is a security vulnerability. Out of an abundance "
"of caution, the utility has been removed to prevent possible "
"misuse."
)
raise ValueError(msg)
formatted[k] = _insert_input_variables(v, inputs, template_format)
elif isinstance(v, (list, tuple)):
formatted_v = []
for x in v:
if isinstance(x, str):
formatted_v.append(formatter(x, **inputs))
elif isinstance(x, dict):
formatted_v.append(
_insert_input_variables(x, inputs, template_format)
)
formatted[k] = type(v)(formatted_v)
return formatted

2
libs/core/langchain_core/version.py
View File

@ -1,3 +1,3 @@
"""langchain-core version information and utilities."""
VERSION = "0.3.51"
VERSION = "0.3.52"

2
libs/core/pyproject.toml
View File

@ -17,7 +17,7 @@ dependencies = [
"pydantic<3.0.0,>=2.7.4; python_full_version >= \"3.12.4\"",
]
name = "langchain-core"
version = "0.3.51"
version = "0.3.52"
description = "Building applications with LLMs through composability"
readme = "README.md"

5
libs/core/tests/unit_tests/messages/test_utils.py
View File

@ -1,7 +1,6 @@
import base64
import json
import re
import typing
from collections.abc import Sequence
from typing import Any, Callable, Optional, Union
@ -666,9 +665,7 @@ class FakeTokenCountingModel(FakeChatModel):
self,
messages: list[BaseMessage],
tools: Optional[
Sequence[
Union[typing.Dict[str, Any], type, Callable, BaseTool] # noqa: UP006
]
Sequence[Union[dict[str, Any], type, Callable, BaseTool]]
] = None,
) -> int:
return dummy_token_counter(messages)

1
libs/core/tests/unit_tests/output_parsers/test_pydantic_parser.py
View File

@ -146,7 +146,6 @@ def test_pydantic_output_parser() -> None:
)
result = pydantic_parser.parse(DEF_RESULT)
print("parse_result:", result) # noqa: T201
assert result == DEF_EXPECTED_RESULT
assert pydantic_parser.OutputType is TestModel

180
libs/core/tests/unit_tests/prompts/test_chat.py
View File

@ -18,26 +18,29 @@ from langchain_core.messages import (
ChatMessage,
HumanMessage,
SystemMessage,
ToolMessage,
get_buffer_string,
)
from langchain_core.prompt_values import ChatPromptValue
from langchain_core.prompts import PromptTemplate
from langchain_core.prompts.chat import (
AIMessagePromptTemplate,
BaseMessagePromptTemplate,
ChatMessagePromptTemplate,
ChatPromptTemplate,
HumanMessagePromptTemplate,
MessagesPlaceholder,
SystemMessagePromptTemplate,
_convert_to_message,
_convert_to_message_template,
)
from langchain_core.prompts.message import BaseMessagePromptTemplate
from langchain_core.prompts.string import PromptTemplateFormat
from langchain_core.utils.pydantic import (
PYDANTIC_VERSION,
)
from tests.unit_tests.pydantic_utils import _normalize_schema
CUR_DIR = Path(__file__).parent.absolute().resolve()
@pytest.fixture
def messages() -> list[BaseMessagePromptTemplate]:
@ -521,7 +524,7 @@ def test_convert_to_message(
args: Any, expected: Union[BaseMessage, BaseMessagePromptTemplate]
) -> None:
"""Test convert to message."""
assert _convert_to_message(args) == expected
assert _convert_to_message_template(args) == expected
def test_chat_prompt_template_indexing() -> None:
@ -566,7 +569,7 @@ def test_convert_to_message_is_strict() -> None:
# meow does not correspond to a valid message type.
# this test is here to ensure that functionality to interpret `meow`
# as a role is NOT added.
_convert_to_message(("meow", "question"))
_convert_to_message_template(("meow", "question"))
def test_chat_message_partial() -> None:
@ -955,7 +958,7 @@ def test_chat_prompt_w_msgs_placeholder_ser_des(snapshot: SnapshotAssertion) ->
assert load(dumpd(prompt)) == prompt
async def test_chat_tmpl_serdes(snapshot: SnapshotAssertion) -> None:
def test_chat_tmpl_serdes(snapshot: SnapshotAssertion) -> None:
"""Test chat prompt template ser/des."""
template = ChatPromptTemplate(
[
@ -1006,6 +1009,89 @@ async def test_chat_tmpl_serdes(snapshot: SnapshotAssertion) -> None:
assert load(dumpd(template)) == template
@pytest.mark.xfail(
reason=(
"In a breaking release, we can update `_convert_to_message_template` to use "
"_DictMessagePromptTemplate for all `dict` inputs, allowing for templatization "
"of message attributes outside content blocks. That would enable the below "
"test to pass."
)
)
def test_chat_tmpl_dict_msg() -> None:
template = ChatPromptTemplate(
[
{
"role": "assistant",
"content": [
{
"type": "text",
"text": "{text1}",
"cache_control": {"type": "ephemeral"},
},
],
"name": "{name1}",
"tool_calls": [
{
"name": "{tool_name1}",
"args": {"arg1": "{tool_arg1}"},
"id": "1",
"type": "tool_call",
}
],
},
{
"role": "tool",
"content": "{tool_content2}",
"tool_call_id": "1",
"name": "{tool_name1}",
},
]
)
expected = [
AIMessage(
[
{
"type": "text",
"text": "important message",
"cache_control": {"type": "ephemeral"},
},
],
name="foo",
tool_calls=[
{
"name": "do_stuff",
"args": {"arg1": "important arg1"},
"id": "1",
"type": "tool_call",
}
],
),
ToolMessage("foo", name="do_stuff", tool_call_id="1"),
]
actual = template.invoke(
{
"text1": "important message",
"name1": "foo",
"tool_arg1": "important arg1",
"tool_name1": "do_stuff",
"tool_content2": "foo",
}
).to_messages()
assert actual == expected
partial_ = template.partial(text1="important message")
actual = partial_.invoke(
{
"name1": "foo",
"tool_arg1": "important arg1",
"tool_name1": "do_stuff",
"tool_content2": "foo",
}
).to_messages()
assert actual == expected
def test_chat_prompt_template_variable_names() -> None:
"""This test was written for an edge case that triggers a warning from Pydantic.
@ -1049,3 +1135,87 @@ def test_chat_prompt_template_variable_names() -> None:
"title": "PromptInput",
"type": "object",
}
def test_data_prompt_template_deserializable() -> None:
"""Test that the image prompt template is serializable."""
load(
dumpd(
ChatPromptTemplate.from_messages(
[
(
"system",
[{"type": "image", "source_type": "url", "url": "{url}"}],
)
]
)
)
)
@pytest.mark.requires("jinja2")
@pytest.mark.parametrize(
("template_format", "cache_control_placeholder", "source_data_placeholder"),
[
("f-string", "{cache_type}", "{source_data}"),
("mustache", "{{cache_type}}", "{{source_data}}"),
],
)
def test_chat_prompt_template_data_prompt_from_message(
template_format: PromptTemplateFormat,
cache_control_placeholder: str,
source_data_placeholder: str,
) -> None:
prompt: dict = {
"type": "image",
"source_type": "base64",
"data": f"{source_data_placeholder}",
}
template = ChatPromptTemplate.from_messages(
[("human", [prompt])], template_format=template_format
)
assert template.format_messages(source_data="base64data") == [
HumanMessage(
content=[
{
"type": "image",
"source_type": "base64",
"data": "base64data",
}
]
)
]
# metadata
prompt["metadata"] = {"cache_control": {"type": f"{cache_control_placeholder}"}}
template = ChatPromptTemplate.from_messages(
[("human", [prompt])], template_format=template_format
)
assert template.format_messages(
cache_type="ephemeral", source_data="base64data"
) == [
HumanMessage(
content=[
{
"type": "image",
"source_type": "base64",
"data": "base64data",
"metadata": {"cache_control": {"type": "ephemeral"}},
}
]
)
]
def test_dict_message_prompt_template_errors_on_jinja2() -> None:
prompt = {
"type": "image",
"source_type": "base64",
"data": "{source_data}",
}
with pytest.raises(ValueError, match="jinja2"):
_ = ChatPromptTemplate.from_messages(
[("human", [prompt])], template_format="jinja2"
)

61
libs/core/tests/unit_tests/prompts/test_message.py Normal file
View File

@ -0,0 +1,61 @@
from pathlib import Path
from langchain_core.messages import AIMessage, BaseMessage, ToolMessage
from langchain_core.prompts.message import _DictMessagePromptTemplate
CUR_DIR = Path(__file__).parent.absolute().resolve()
def test__dict_message_prompt_template_fstring() -> None:
template = {
"role": "assistant",
"content": [
{"type": "text", "text": "{text1}", "cache_control": {"type": "ephemeral"}},
],
"name": "{name1}",
"tool_calls": [
{
"name": "{tool_name1}",
"args": {"arg1": "{tool_arg1}"},
"id": "1",
"type": "tool_call",
}
],
}
prompt = _DictMessagePromptTemplate(template=template, template_format="f-string")
expected: BaseMessage = AIMessage(
[
{
"type": "text",
"text": "important message",
"cache_control": {"type": "ephemeral"},
},
],
name="foo",
tool_calls=[
{
"name": "do_stuff",
"args": {"arg1": "important arg1"},
"id": "1",
"type": "tool_call",
}
],
)
actual = prompt.format_messages(
text1="important message",
name1="foo",
tool_arg1="important arg1",
tool_name1="do_stuff",
)[0]
assert actual == expected
template = {
"role": "tool",
"content": "{content1}",
"tool_call_id": "1",
"name": "{name1}",
}
prompt = _DictMessagePromptTemplate(template=template, template_format="f-string")
expected = ToolMessage("foo", name="bar", tool_call_id="1")
actual = prompt.format_messages(content1="foo", name1="bar")[0]
assert actual == expected

3
libs/core/uv.lock
View File

@ -1,5 +1,4 @@
version = 1
revision = 1
requires-python = ">=3.9, <4.0"
resolution-markers = [
"python_full_version >= '3.13'",
@ -938,7 +937,7 @@ wheels = [
[[package]]
name = "langchain-core"
version = "0.3.51"
version = "0.3.52"
source = { editable = "." }
dependencies = [
{ name = "jsonpatch" },

3
libs/langchain/langchain/chat_models/base.py
View File

@ -133,6 +133,7 @@ def init_chat_model(
- 'mistral...' -> 'mistralai'
- 'deepseek...' -> 'deepseek'
- 'grok...' -> 'xai'
- 'sonar...' -> 'perplexity'
configurable_fields: Which model parameters are
configurable:
@ -504,6 +505,8 @@ def _attempt_infer_model_provider(model_name: str) -> Optional[str]:
return "deepseek"
elif model_name.startswith("grok"):
return "xai"
elif model_name.startswith("sonar"):
return "perplexity"
else:
return None

4
libs/partners/anthropic/pyproject.toml
View File

@ -8,11 +8,11 @@ license = { text = "MIT" }
requires-python = "<4.0,>=3.9"
dependencies = [
"anthropic<1,>=0.49.0",
"langchain-core<1.0.0,>=0.3.45",
"langchain-core<1.0.0,>=0.3.52",
"pydantic<3.0.0,>=2.7.4",
]
name = "langchain-anthropic"
version = "0.3.10"
version = "0.3.11"
description = "An integration package connecting AnthropicMessages and LangChain"
readme = "README.md"

26
libs/partners/anthropic/uv.lock
View File

@ -1,7 +1,8 @@
version = 1
requires-python = ">=3.9, <4.0"
resolution-markers = [
"python_full_version >= '3.12.4'",
"python_full_version >= '3.13'",
"python_full_version >= '3.12.4' and python_full_version < '3.13'",
"python_full_version >= '3.12' and python_full_version < '3.12.4'",
"python_full_version < '3.12'",
]
@ -406,7 +407,7 @@ wheels = [
[[package]]
name = "langchain-anthropic"
version = "0.3.10"
version = "0.3.11"
source = { editable = "." }
dependencies = [
{ name = "anthropic" },
@ -485,7 +486,7 @@ typing = [
[[package]]
name = "langchain-core"
version = "0.3.48"
version = "0.3.52"
source = { editable = "../../core" }
dependencies = [
{ name = "jsonpatch" },
@ -515,16 +516,18 @@ dev = [
{ name = "jupyter", specifier = ">=1.0.0,<2.0.0" },
{ name = "setuptools", specifier = ">=67.6.1,<68.0.0" },
]
lint = [{ name = "ruff", specifier = ">=0.9.2,<1.0.0" }]
lint = [{ name = "ruff", specifier = ">=0.11.2,<0.12.0" }]
test = [
{ name = "blockbuster", specifier = "~=1.5.18" },
{ name = "freezegun", specifier = ">=1.2.2,<2.0.0" },
{ name = "grandalf", specifier = ">=0.8,<1.0" },
{ name = "langchain-tests", directory = "../../standard-tests" },
{ name = "numpy", marker = "python_full_version < '3.12'", specifier = ">=1.24.0,<2.0.0" },
{ name = "numpy", marker = "python_full_version >= '3.12'", specifier = ">=1.26.0,<3" },
{ name = "numpy", marker = "python_full_version < '3.13'", specifier = ">=1.26.4" },
{ name = "numpy", marker = "python_full_version >= '3.13'", specifier = ">=2.1.0" },
{ name = "pytest", specifier = ">=8,<9" },
{ name = "pytest-asyncio", specifier = ">=0.21.1,<1.0.0" },
{ name = "pytest-benchmark" },
{ name = "pytest-codspeed" },
{ name = "pytest-mock", specifier = ">=3.10.0,<4.0.0" },
{ name = "pytest-socket", specifier = ">=0.7.0,<1.0.0" },
{ name = "pytest-watcher", specifier = ">=0.3.4,<1.0.0" },
@ -535,15 +538,14 @@ test = [
test-integration = []
typing = [
{ name = "langchain-text-splitters", directory = "../../text-splitters" },
{ name = "mypy", specifier = ">=1.10,<1.11" },
{ name = "types-jinja2", specifier = ">=2.11.9,<3.0.0" },
{ name = "mypy", specifier = ">=1.15,<1.16" },
{ name = "types-pyyaml", specifier = ">=6.0.12.2,<7.0.0.0" },
{ name = "types-requests", specifier = ">=2.28.11.5,<3.0.0.0" },
]
[[package]]
name = "langchain-tests"
version = "0.3.16"
version = "0.3.18"
source = { editable = "../../standard-tests" }
dependencies = [
{ name = "httpx" },
@ -560,7 +562,8 @@ dependencies = [
requires-dist = [
{ name = "httpx", specifier = ">=0.25.0,<1" },
{ name = "langchain-core", editable = "../../core" },
{ name = "numpy", specifier = ">=1.26.2,<3" },
{ name = "numpy", marker = "python_full_version < '3.13'", specifier = ">=1.26.2" },
{ name = "numpy", marker = "python_full_version >= '3.13'", specifier = ">=2.1.0" },
{ name = "pytest", specifier = ">=7,<9" },
{ name = "pytest-asyncio", specifier = ">=0.20,<1" },
{ name = "pytest-socket", specifier = ">=0.6.0,<1" },
@ -698,7 +701,8 @@ name = "numpy"
version = "2.2.2"
source = { registry = "https://pypi.org/simple" }
resolution-markers = [
"python_full_version >= '3.12.4'",
"python_full_version >= '3.13'",
"python_full_version >= '3.12.4' and python_full_version < '3.13'",
"python_full_version >= '3.12' and python_full_version < '3.12.4'",
]
sdist = { url = "https://files.pythonhosted.org/packages/ec/d0/c12ddfd3a02274be06ffc71f3efc6d0e457b0409c4481596881e748cb264/numpy-2.2.2.tar.gz", hash = "sha256:ed6906f61834d687738d25988ae117683705636936cc605be0bb208b23df4d8f", size = 20233295 }

4
libs/partners/chroma/pyproject.toml
View File

@ -7,13 +7,13 @@ authors = []
license = { text = "MIT" }
requires-python = "<4,>=3.9"
dependencies = [
"langchain-core!=0.3.0,!=0.3.1,!=0.3.10,!=0.3.11,!=0.3.12,!=0.3.13,!=0.3.14,!=0.3.2,!=0.3.3,!=0.3.4,!=0.3.5,!=0.3.6,!=0.3.7,!=0.3.8,!=0.3.9,<0.4.0,>=0.2.43",
"langchain-core>=0.3.52",
"numpy>=1.26.0; python_version < '3.13'",
"numpy>=2.1.0; python_version >= '3.13'",
"chromadb!=0.5.10,!=0.5.11,!=0.5.12,!=0.5.4,!=0.5.5,!=0.5.7,!=0.5.9,<0.7.0,>=0.4.0",
]
name = "langchain-chroma"
version = "0.2.2"
version = "0.2.3"
description = "An integration package connecting Chroma and LangChain"
readme = "README.md"

11
libs/partners/chroma/uv.lock
View File

@ -736,7 +736,7 @@ wheels = [
[[package]]
name = "langchain-chroma"
version = "0.2.2"
version = "0.2.3"
source = { editable = "." }
dependencies = [
{ name = "chromadb" },
@ -814,7 +814,7 @@ typing = [
[[package]]
name = "langchain-core"
version = "0.3.51"
version = "0.3.52"
source = { editable = "../../core" }
dependencies = [
{ name = "jsonpatch" },
@ -854,6 +854,8 @@ test = [
{ name = "numpy", marker = "python_full_version >= '3.13'", specifier = ">=2.1.0" },
{ name = "pytest", specifier = ">=8,<9" },
{ name = "pytest-asyncio", specifier = ">=0.21.1,<1.0.0" },
{ name = "pytest-benchmark" },
{ name = "pytest-codspeed" },
{ name = "pytest-mock", specifier = ">=3.10.0,<4.0.0" },
{ name = "pytest-socket", specifier = ">=0.7.0,<1.0.0" },
{ name = "pytest-watcher", specifier = ">=0.3.4,<1.0.0" },
@ -864,15 +866,14 @@ test = [
test-integration = []
typing = [
{ name = "langchain-text-splitters", directory = "../../text-splitters" },
{ name = "mypy", specifier = ">=1.10,<1.11" },
{ name = "types-jinja2", specifier = ">=2.11.9,<3.0.0" },
{ name = "mypy", specifier = ">=1.15,<1.16" },
{ name = "types-pyyaml", specifier = ">=6.0.12.2,<7.0.0.0" },
{ name = "types-requests", specifier = ">=2.28.11.5,<3.0.0.0" },
]
[[package]]
name = "langchain-tests"
version = "0.3.17"
version = "0.3.18"
source = { editable = "../../standard-tests" }
dependencies = [
{ name = "httpx" },

41
libs/partners/ollama/langchain_ollama/chat_models.py
View File

@ -30,6 +30,7 @@ from langchain_core.messages import (
SystemMessage,
ToolCall,
ToolMessage,
is_data_content_block,
)
from langchain_core.messages.ai import UsageMetadata
from langchain_core.messages.tool import tool_call
@ -173,6 +174,20 @@ def _lc_tool_call_to_openai_tool_call(tool_call: ToolCall) -> dict:
}
def _get_image_from_data_content_block(block: dict) -> str:
"""Format standard data content block to format expected by Ollama."""
if block["type"] == "image":
if block["source_type"] == "base64":
return block["data"]
else:
error_message = "Image data only supported through in-line base64 format."
raise ValueError(error_message)
else:
error_message = f"Blocks of type {block['type']} not supported."
raise ValueError(error_message)
def _is_pydantic_class(obj: Any) -> bool:
return isinstance(obj, type) and is_basemodel_subclass(obj)
@ -553,7 +568,9 @@ class ChatOllama(BaseChatModel):
images.append(image_url_components[1])
else:
images.append(image_url_components[0])
elif is_data_content_block(content_part):
image = _get_image_from_data_content_block(content_part)
images.append(image)
else:
raise ValueError(
"Unsupported message content type. "
@ -719,6 +736,11 @@ class ChatOllama(BaseChatModel):
is_thinking = False
for stream_resp in self._create_chat_stream(messages, stop, **kwargs):
if not isinstance(stream_resp, str):
if stream_resp.get("done") is True:
generation_info = dict(stream_resp)
_ = generation_info.pop("message", None)
else:
generation_info = None
chunk = ChatGenerationChunk(
message=AIMessageChunk(
content=(
@ -732,11 +754,7 @@ class ChatOllama(BaseChatModel):
),
tool_calls=_get_tool_calls_from_response(stream_resp),
),
generation_info=(
dict(stream_resp).pop("message", None)
if stream_resp.get("done") is True
else None
),
generation_info=generation_info,
)
if chunk.generation_info and (
model := chunk.generation_info.get("model")
@ -773,6 +791,11 @@ class ChatOllama(BaseChatModel):
is_thinking = False
async for stream_resp in self._acreate_chat_stream(messages, stop, **kwargs):
if not isinstance(stream_resp, str):
if stream_resp.get("done") is True:
generation_info = dict(stream_resp)
_ = generation_info.pop("message", None)
else:
generation_info = None
chunk = ChatGenerationChunk(
message=AIMessageChunk(
content=(
@ -786,11 +809,7 @@ class ChatOllama(BaseChatModel):
),
tool_calls=_get_tool_calls_from_response(stream_resp),
),
generation_info=(
dict(stream_resp).pop("message", None)
if stream_resp.get("done") is True
else None
),
generation_info=generation_info,
)
if chunk.generation_info and (
model := chunk.generation_info.get("model")

23
libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_standard.py
View File

@ -14,10 +14,6 @@ class TestChatOllama(ChatModelIntegrationTests):
def chat_model_params(self) -> dict:
return {"model": "llama3.1"}
@property
def supports_image_inputs(self) -> bool:
return True
@property
def supports_json_mode(self) -> bool:
return True
@ -25,3 +21,22 @@ class TestChatOllama(ChatModelIntegrationTests):
@property
def has_tool_choice(self) -> bool:
return False
def test_image_model() -> None:
class ImageModelTests(ChatModelIntegrationTests):
@property
def chat_model_class(self) -> type[ChatOllama]:
return ChatOllama
@property
def chat_model_params(self) -> dict:
return {"model": "gemma3:4b"}
@property
def supports_image_inputs(self) -> bool:
return True
test_instance = ImageModelTests()
model = test_instance.chat_model_class(**test_instance.chat_model_params)
ImageModelTests().test_image_inputs(model)

4
libs/partners/openai/pyproject.toml
View File

@ -7,12 +7,12 @@ authors = []
license = { text = "MIT" }
requires-python = "<4.0,>=3.9"
dependencies = [
"langchain-core<1.0.0,>=0.3.49",
"langchain-core<1.0.0,>=0.3.52",
"openai<2.0.0,>=1.68.2",
"tiktoken<1,>=0.7",
]
name = "langchain-openai"
version = "0.3.12"
version = "0.3.13"
description = "An integration package connecting OpenAI and LangChain"
readme = "README.md"

12
libs/partners/openai/uv.lock
View File

@ -1,5 +1,4 @@
version = 1
revision = 1
requires-python = ">=3.9, <4.0"
resolution-markers = [
"python_full_version >= '3.13'",
@ -464,7 +463,7 @@ wheels = [
[[package]]
name = "langchain-core"
version = "0.3.51"
version = "0.3.52"
source = { editable = "../../core" }
dependencies = [
{ name = "jsonpatch" },
@ -504,6 +503,8 @@ test = [
{ name = "numpy", marker = "python_full_version >= '3.13'", specifier = ">=2.1.0" },
{ name = "pytest", specifier = ">=8,<9" },
{ name = "pytest-asyncio", specifier = ">=0.21.1,<1.0.0" },
{ name = "pytest-benchmark" },
{ name = "pytest-codspeed" },
{ name = "pytest-mock", specifier = ">=3.10.0,<4.0.0" },
{ name = "pytest-socket", specifier = ">=0.7.0,<1.0.0" },
{ name = "pytest-watcher", specifier = ">=0.3.4,<1.0.0" },
@ -514,15 +515,14 @@ test = [
test-integration = []
typing = [
{ name = "langchain-text-splitters", directory = "../../text-splitters" },
{ name = "mypy", specifier = ">=1.10,<1.11" },
{ name = "types-jinja2", specifier = ">=2.11.9,<3.0.0" },
{ name = "mypy", specifier = ">=1.15,<1.16" },
{ name = "types-pyyaml", specifier = ">=6.0.12.2,<7.0.0.0" },
{ name = "types-requests", specifier = ">=2.28.11.5,<3.0.0.0" },
]
[[package]]
name = "langchain-openai"
version = "0.3.12"
version = "0.3.13"
source = { editable = "." }
dependencies = [
{ name = "langchain-core" },
@ -609,7 +609,7 @@ typing = [
[[package]]
name = "langchain-tests"
version = "0.3.17"
version = "0.3.18"
source = { editable = "../../standard-tests" }
dependencies = [
{ name = "httpx" },

4
libs/partners/perplexity/pyproject.toml
View File

@ -7,11 +7,11 @@ authors = []
license = { text = "MIT" }
requires-python = "<4.0,>=3.9"
dependencies = [
"langchain-core<1.0.0,>=0.3.50",
"langchain-core<1.0.0,>=0.3.52",
"openai<2.0.0,>=1.68.2",
]
name = "langchain-perplexity"
version = "0.1.0"
version = "0.1.1"
description = "An integration package connecting Perplexity and LangChain"
readme = "README.md"

95
libs/partners/perplexity/uv.lock
View File

@ -1,8 +1,8 @@
version = 1
revision = 1
requires-python = ">=3.9, <4.0"
resolution-markers = [
"python_full_version >= '3.12.4'",
"python_full_version >= '3.13'",
"python_full_version >= '3.12.4' and python_full_version < '3.13'",
"python_full_version >= '3.12' and python_full_version < '3.12.4'",
"python_full_version < '3.12'",
]
@ -464,7 +464,7 @@ wheels = [
[[package]]
name = "langchain-core"
version = "0.3.50"
version = "0.3.52"
source = { editable = "../../core" }
dependencies = [
{ name = "jsonpatch" },
@ -500,10 +500,12 @@ test = [
{ name = "freezegun", specifier = ">=1.2.2,<2.0.0" },
{ name = "grandalf", specifier = ">=0.8,<1.0" },
{ name = "langchain-tests", directory = "../../standard-tests" },
{ name = "numpy", marker = "python_full_version < '3.12'", specifier = ">=1.24.0,<2.0.0" },
{ name = "numpy", marker = "python_full_version >= '3.12'", specifier = ">=1.26.0,<3" },
{ name = "numpy", marker = "python_full_version < '3.13'", specifier = ">=1.26.4" },
{ name = "numpy", marker = "python_full_version >= '3.13'", specifier = ">=2.1.0" },
{ name = "pytest", specifier = ">=8,<9" },
{ name = "pytest-asyncio", specifier = ">=0.21.1,<1.0.0" },
{ name = "pytest-benchmark" },
{ name = "pytest-codspeed" },
{ name = "pytest-mock", specifier = ">=3.10.0,<4.0.0" },
{ name = "pytest-socket", specifier = ">=0.7.0,<1.0.0" },
{ name = "pytest-watcher", specifier = ">=0.3.4,<1.0.0" },
@ -514,15 +516,14 @@ test = [
test-integration = []
typing = [
{ name = "langchain-text-splitters", directory = "../../text-splitters" },
{ name = "mypy", specifier = ">=1.10,<1.11" },
{ name = "types-jinja2", specifier = ">=2.11.9,<3.0.0" },
{ name = "mypy", specifier = ">=1.15,<1.16" },
{ name = "types-pyyaml", specifier = ">=6.0.12.2,<7.0.0.0" },
{ name = "types-requests", specifier = ">=2.28.11.5,<3.0.0.0" },
]
[[package]]
name = "langchain-perplexity"
version = "0.1.0"
version = "0.1.1"
source = { editable = "." }
dependencies = [
{ name = "langchain-core" },
@ -599,12 +600,13 @@ typing = [
[[package]]
name = "langchain-tests"
version = "0.3.17"
version = "0.3.18"
source = { editable = "../../standard-tests" }
dependencies = [
{ name = "httpx" },
{ name = "langchain-core" },
{ name = "numpy" },
{ name = "numpy", version = "1.26.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.13'" },
{ name = "numpy", version = "2.2.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.13'" },
{ name = "pytest" },
{ name = "pytest-asyncio" },
{ name = "pytest-socket" },
@ -615,7 +617,8 @@ dependencies = [
requires-dist = [
{ name = "httpx", specifier = ">=0.25.0,<1" },
{ name = "langchain-core", editable = "../../core" },
{ name = "numpy", specifier = ">=1.26.2,<3" },
{ name = "numpy", marker = "python_full_version < '3.13'", specifier = ">=1.26.2" },
{ name = "numpy", marker = "python_full_version >= '3.13'", specifier = ">=2.1.0" },
{ name = "pytest", specifier = ">=7,<9" },
{ name = "pytest-asyncio", specifier = ">=0.20,<1" },
{ name = "pytest-socket", specifier = ">=0.6.0,<1" },
@ -707,6 +710,11 @@ wheels = [
name = "numpy"
version = "1.26.4"
source = { registry = "https://pypi.org/simple" }
resolution-markers = [
"python_full_version >= '3.12.4' and python_full_version < '3.13'",
"python_full_version >= '3.12' and python_full_version < '3.12.4'",
"python_full_version < '3.12'",
]
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[[package]]
name = "openai"
version = "1.70.0"

4
libs/standard-tests/pyproject.toml
View File

@ -7,7 +7,7 @@ authors = [{ name = "Erick Friis", email = "erick@langchain.dev" }]
license = { text = "MIT" }
requires-python = "<4.0,>=3.9"
dependencies = [
"langchain-core<1.0.0,>=0.3.49",
"langchain-core<1.0.0,>=0.3.52",
"pytest<9,>=7",
"pytest-asyncio<1,>=0.20",
"httpx<1,>=0.25.0",
@ -17,7 +17,7 @@ dependencies = [
"numpy>=2.1.0; python_version>='3.13'",
]
name = "langchain-tests"
version = "0.3.17"
version = "0.3.18"
description = "Standard tests for LangChain implementations"
readme = "README.md"

10
libs/standard-tests/uv.lock
View File

@ -1,5 +1,4 @@
version = 1
revision = 1
requires-python = ">=3.9, <4.0"
resolution-markers = [
"python_full_version >= '3.13'",
@ -290,7 +289,7 @@ wheels = [
[[package]]
name = "langchain-core"
version = "0.3.51"
version = "0.3.52"
source = { editable = "../core" }
dependencies = [
{ name = "jsonpatch" },
@ -330,6 +329,8 @@ test = [
{ name = "numpy", marker = "python_full_version >= '3.13'", specifier = ">=2.1.0" },
{ name = "pytest", specifier = ">=8,<9" },
{ name = "pytest-asyncio", specifier = ">=0.21.1,<1.0.0" },
{ name = "pytest-benchmark" },
{ name = "pytest-codspeed" },
{ name = "pytest-mock", specifier = ">=3.10.0,<4.0.0" },
{ name = "pytest-socket", specifier = ">=0.7.0,<1.0.0" },
{ name = "pytest-watcher", specifier = ">=0.3.4,<1.0.0" },
@ -340,15 +341,14 @@ test = [
test-integration = []
typing = [
{ name = "langchain-text-splitters", directory = "../text-splitters" },
{ name = "mypy", specifier = ">=1.10,<1.11" },
{ name = "types-jinja2", specifier = ">=2.11.9,<3.0.0" },
{ name = "mypy", specifier = ">=1.15,<1.16" },
{ name = "types-pyyaml", specifier = ">=6.0.12.2,<7.0.0.0" },
{ name = "types-requests", specifier = ">=2.28.11.5,<3.0.0.0" },
]
[[package]]
name = "langchain-tests"
version = "0.3.17"
version = "0.3.18"
source = { editable = "." }
dependencies = [
{ name = "httpx" },