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Merge branch 'master' into bagatur/tool_description_optional

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Bagatur 2024-10-30 17:02:52 -07:00 committed by GitHub
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16 changed files with 213 additions and 191 deletions
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2
.github/workflows/_release.yml vendored
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@ -338,6 +338,8 @@ jobs:
packages-dir: ${{ inputs.working-directory }}/dist/
verbose: true
print-hash: true
# Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
attestations: false
mark-release:
needs:

2
.github/workflows/_test_release.yml vendored
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@ -98,3 +98,5 @@ jobs:
# This is *only for CI use* and is *extremely dangerous* otherwise!
# https://github.com/pypa/gh-action-pypi-publish#tolerating-release-package-file-duplicates
skip-existing: true
# Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
attestations: false

1
libs/community/extended_testing_deps.txt
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@ -58,6 +58,7 @@ oracledb>=2.2.0,<3
pandas>=2.0.1,<3
pdfminer-six>=20221105,<20240706
pgvector>=0.1.6,<0.2
playwright>=1.48.0,<2
praw>=7.7.1,<8
premai>=0.3.25,<0.4
psychicapi>=0.8.0,<0.9

6
libs/community/langchain_community/tools/playwright/current_page.py
View File

@ -15,12 +15,16 @@ from langchain_community.tools.playwright.utils import (
)
class CurrentWebPageToolInput(BaseModel):
"""Explicit no-args input for CurrentWebPageTool."""
class CurrentWebPageTool(BaseBrowserTool): # type: ignore[override, override]
"""Tool for getting the URL of the current webpage."""
name: str = "current_webpage"
description: str = "Returns the URL of the current page"
args_schema: Type[BaseModel] = BaseModel
args_schema: Type[BaseModel] = CurrentWebPageToolInput
def _run(
self,

6
libs/community/langchain_community/tools/playwright/extract_text.py
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@ -15,12 +15,16 @@ from langchain_community.tools.playwright.utils import (
)
class ExtractTextToolInput(BaseModel):
"""Explicit no-args input for ExtractTextTool."""
class ExtractTextTool(BaseBrowserTool): # type: ignore[override, override]
"""Tool for extracting all the text on the current webpage."""
name: str = "extract_text"
description: str = "Extract all the text on the current webpage"
args_schema: Type[BaseModel] = BaseModel
args_schema: Type[BaseModel] = ExtractTextToolInput
@model_validator(mode="before")
@classmethod

6
libs/community/langchain_community/tools/playwright/navigate_back.py
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@ -15,12 +15,16 @@ from langchain_community.tools.playwright.utils import (
)
class NavigateBackToolInput(BaseModel):
"""Explicit no-args input for NavigateBackTool."""
class NavigateBackTool(BaseBrowserTool): # type: ignore[override, override]
"""Navigate back to the previous page in the browser history."""
name: str = "previous_webpage"
description: str = "Navigate back to the previous page in the browser history"
args_schema: Type[BaseModel] = BaseModel
args_schema: Type[BaseModel] = NavigateBackToolInput
def _run(self, run_manager: Optional[CallbackManagerForToolRun] = None) -> str:
"""Use the tool."""

0
libs/community/tests/unit_tests/tools/playwright/__init__.py Normal file
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26
libs/community/tests/unit_tests/tools/playwright/test_all.py Normal file
View File

@ -0,0 +1,26 @@
"""Test Playwright's Tools."""
from unittest.mock import Mock
import pytest
from langchain_community.agent_toolkits import PlayWrightBrowserToolkit
@pytest.mark.requires("playwright")
@pytest.mark.requires("bs4")
def test_playwright_tools_schemas() -> None:
"""Test calling 'tool_call_schema' for every tool to check to init issues."""
from playwright.sync_api import Browser
sync_browser = Mock(spec=Browser)
tools = PlayWrightBrowserToolkit.from_browser(sync_browser=sync_browser).get_tools()
for tool in tools:
try:
tool.tool_call_schema
except Exception as e:
raise AssertionError(
f"Error for '{tool.name}' tool: {type(e).__name__}: {e}"
) from e

8
libs/core/langchain_core/tools/base.py
View File

@ -449,7 +449,7 @@ class ChildTool(BaseTool):
def tool_call_schema(self) -> type[BaseModel]:
full_schema = self.get_input_schema()
fields = []
for name, type_ in _get_all_basemodel_annotations(full_schema).items():
for name, type_ in get_all_basemodel_annotations(full_schema).items():
if not _is_injected_arg_type(type_):
fields.append(name)
return _create_subset_model(
@ -962,7 +962,7 @@ def _is_injected_arg_type(type_: type) -> bool:
)
def _get_all_basemodel_annotations(
def get_all_basemodel_annotations(
cls: Union[TypeBaseModel, Any], *, default_to_bound: bool = True
) -> dict[str, type]:
# cls has no subscript: cls = FooBar
@ -980,7 +980,7 @@ def _get_all_basemodel_annotations(
orig_bases: tuple = getattr(cls, "__orig_bases__", ())
# cls has subscript: cls = FooBar[int]
else:
annotations = _get_all_basemodel_annotations(
annotations = get_all_basemodel_annotations(
get_origin(cls), default_to_bound=False
)
orig_bases = (cls,)
@ -994,7 +994,7 @@ def _get_all_basemodel_annotations(
# if class = FooBar inherits from Baz, parent = Baz
if isinstance(parent, type) and is_pydantic_v1_subclass(parent):
annotations.update(
_get_all_basemodel_annotations(parent, default_to_bound=False)
get_all_basemodel_annotations(parent, default_to_bound=False)
)
continue

8
libs/core/pyproject.toml
View File

@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
[tool.poetry]
name = "langchain-core"
version = "0.3.13"
version = "0.3.14"
description = "Building applications with LLMs through composability"
authors = []
license = "MIT"
@ -84,20 +84,17 @@ classmethod-decorators = [ "classmethod", "langchain_core.utils.pydantic.pre_ini
[tool.poetry.group.lint.dependencies]
ruff = "^0.5"
[tool.poetry.group.typing.dependencies]
mypy = ">=1.10,<1.11"
types-pyyaml = "^6.0.12.2"
types-requests = "^2.28.11.5"
types-jinja2 = "^2.11.9"
[tool.poetry.group.dev.dependencies]
jupyter = "^1.0.0"
setuptools = "^67.6.1"
grandalf = "^0.8"
[tool.poetry.group.test.dependencies]
pytest = "^8"
freezegun = "^1.2.2"
@ -116,15 +113,12 @@ python = "<3.12"
version = "^1.26.0"
python = ">=3.12"
[tool.poetry.group.test_integration.dependencies]
[tool.poetry.group.typing.dependencies.langchain-text-splitters]
path = "../text-splitters"
develop = true
[tool.poetry.group.test.dependencies.langchain-standard-tests]
path = "../standard-tests"
develop = true

7
libs/core/tests/unit_tests/runnables/test_runnable.py
View File

@ -1891,6 +1891,13 @@ async def test_prompt_with_chat_model_async(
)
@pytest.mark.skipif(
condition=sys.version_info[1] == 13,
reason=(
"temporary, py3.13 exposes some invalid assumptions about order of batch async "
"executions."
),
)
@freeze_time("2023-01-01")
async def test_prompt_with_llm(
mocker: MockerFixture, snapshot: SnapshotAssertion

26
libs/core/tests/unit_tests/test_tools.py
View File

@ -47,9 +47,9 @@ from langchain_core.tools import (
from langchain_core.tools.base import (
InjectedToolArg,
SchemaAnnotationError,
_get_all_basemodel_annotations,
_is_message_content_block,
_is_message_content_type,
get_all_basemodel_annotations,
)
from langchain_core.utils.function_calling import convert_to_openai_function
from langchain_core.utils.pydantic import PYDANTIC_MAJOR_VERSION, _create_subset_model
@ -1912,19 +1912,19 @@ def test__get_all_basemodel_annotations_v2(use_v1_namespace: bool) -> None:
c: dict
expected = {"a": str, "b": Annotated[ModelA[dict[str, Any]], "foo"], "c": dict}
actual = _get_all_basemodel_annotations(ModelC)
actual = get_all_basemodel_annotations(ModelC)
assert actual == expected
expected = {"a": str, "b": Annotated[ModelA[dict[str, Any]], "foo"]}
actual = _get_all_basemodel_annotations(ModelB)
actual = get_all_basemodel_annotations(ModelB)
assert actual == expected
expected = {"a": Any}
actual = _get_all_basemodel_annotations(ModelA)
actual = get_all_basemodel_annotations(ModelA)
assert actual == expected
expected = {"a": int}
actual = _get_all_basemodel_annotations(ModelA[int])
actual = get_all_basemodel_annotations(ModelA[int])
assert actual == expected
D = TypeVar("D", bound=Union[str, int])
@ -1938,7 +1938,7 @@ def test__get_all_basemodel_annotations_v2(use_v1_namespace: bool) -> None:
"c": dict,
"d": Union[str, int, None],
}
actual = _get_all_basemodel_annotations(ModelD)
actual = get_all_basemodel_annotations(ModelD)
assert actual == expected
expected = {
@ -1947,7 +1947,7 @@ def test__get_all_basemodel_annotations_v2(use_v1_namespace: bool) -> None:
"c": dict,
"d": Union[int, None],
}
actual = _get_all_basemodel_annotations(ModelD[int])
actual = get_all_basemodel_annotations(ModelD[int])
assert actual == expected
@ -1969,19 +1969,19 @@ def test__get_all_basemodel_annotations_v1() -> None:
c: dict
expected = {"a": str, "b": Annotated[ModelA[dict[str, Any]], "foo"], "c": dict}
actual = _get_all_basemodel_annotations(ModelC)
actual = get_all_basemodel_annotations(ModelC)
assert actual == expected
expected = {"a": str, "b": Annotated[ModelA[dict[str, Any]], "foo"]}
actual = _get_all_basemodel_annotations(ModelB)
actual = get_all_basemodel_annotations(ModelB)
assert actual == expected
expected = {"a": Any}
actual = _get_all_basemodel_annotations(ModelA)
actual = get_all_basemodel_annotations(ModelA)
assert actual == expected
expected = {"a": int}
actual = _get_all_basemodel_annotations(ModelA[int])
actual = get_all_basemodel_annotations(ModelA[int])
assert actual == expected
D = TypeVar("D", bound=Union[str, int])
@ -1995,7 +1995,7 @@ def test__get_all_basemodel_annotations_v1() -> None:
"c": dict,
"d": Union[str, int, None],
}
actual = _get_all_basemodel_annotations(ModelD)
actual = get_all_basemodel_annotations(ModelD)
assert actual == expected
expected = {
@ -2004,7 +2004,7 @@ def test__get_all_basemodel_annotations_v1() -> None:
"c": dict,
"d": Union[int, None],
}
actual = _get_all_basemodel_annotations(ModelD[int])
actual = get_all_basemodel_annotations(ModelD[int])
assert actual == expected

265
libs/langchain/poetry.lock generated
View File

@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
[[package]]
name = "aiohappyeyeballs"
@ -1905,13 +1905,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
[[package]]
name = "jupyterlab"
version = "4.2.5"
version = "4.3.0"
description = "JupyterLab computational environment"
optional = false
python-versions = ">=3.8"
files = [
{file = "jupyterlab-4.2.5-py3-none-any.whl", hash = "sha256:73b6e0775d41a9fee7ee756c80f58a6bed4040869ccc21411dc559818874d321"},
{file = "jupyterlab-4.2.5.tar.gz", hash = "sha256:ae7f3a1b8cb88b4f55009ce79fa7c06f99d70cd63601ee4aa91815d054f46f75"},
{file = "jupyterlab-4.3.0-py3-none-any.whl", hash = "sha256:f67e1095ad61ae04349024f0b40345062ab108a0c6998d9810fec6a3c1a70cd5"},
{file = "jupyterlab-4.3.0.tar.gz", hash = "sha256:7c6835cbf8df0af0ec8a39332e85ff11693fb9a468205343b4fc0bfbc74817e5"},
]
[package.dependencies]
@ -1932,9 +1932,9 @@ tornado = ">=6.2.0"
traitlets = "*"
[package.extras]
dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.3.5)"]
docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"]
docs-screenshots = ["altair (==5.3.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.2)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.1.post2)", "matplotlib (==3.8.3)", "nbconvert (>=7.0.0)", "pandas (==2.2.1)", "scipy (==1.12.0)", "vega-datasets (==0.9.0)"]
dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.6.9)"]
docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<8.1.0)", "sphinx-copybutton"]
docs-screenshots = ["altair (==5.4.1)", "ipython (==8.16.1)", "ipywidgets (==8.1.5)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.2.post3)", "matplotlib (==3.9.2)", "nbconvert (>=7.0.0)", "pandas (==2.2.3)", "scipy (==1.14.1)", "vega-datasets (==0.9.0)"]
test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
upgrade-extension = ["copier (>=9,<10)", "jinja2-time (<0.3)", "pydantic (<3.0)", "pyyaml-include (<3.0)", "tomli-w (<2.0)"]
@ -1988,7 +1988,7 @@ files = [
[[package]]
name = "langchain-core"
version = "0.3.13"
version = "0.3.14"
description = "Building applications with LLMs through composability"
optional = false
python-versions = ">=3.9,<4.0"
@ -2050,7 +2050,7 @@ url = "../standard-tests"
[[package]]
name = "langchain-text-splitters"
version = "0.3.0"
version = "0.3.1"
description = "LangChain text splitting utilities"
optional = false
python-versions = ">=3.9,<4.0"
@ -2058,7 +2058,7 @@ files = []
develop = true
[package.dependencies]
langchain-core = "^0.3.0"
langchain-core = "^0.3.13"
[package.source]
type = "directory"
@ -2082,13 +2082,13 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
[[package]]
name = "langsmith"
version = "0.1.137"
version = "0.1.138"
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
optional = false
python-versions = "<4.0,>=3.8.1"
files = [
{file = "langsmith-0.1.137-py3-none-any.whl", hash = "sha256:4256d5c61133749890f7b5c88321dbb133ce0f440c621ea28e76513285859b81"},
{file = "langsmith-0.1.137.tar.gz", hash = "sha256:56cdfcc6c74cb20a3f437d5bd144feb5bf93f54c5a2918d1e568cbd084a372d4"},
{file = "langsmith-0.1.138-py3-none-any.whl", hash = "sha256:5c2bd5c11c75f7b3d06a0f06b115186e7326ca969fd26d66ffc65a0669012aee"},
{file = "langsmith-0.1.138.tar.gz", hash = "sha256:1ecf613bb52f6bf17f1510e24ad8b70d4b0259bc9d3dbfd69b648c66d4644f0b"},
]
[package.dependencies]
@ -2490,26 +2490,26 @@ files = [
[[package]]
name = "notebook"
version = "7.2.2"
version = "7.0.7"
description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
optional = false
python-versions = ">=3.8"
files = [
{file = "notebook-7.2.2-py3-none-any.whl", hash = "sha256:c89264081f671bc02eec0ed470a627ed791b9156cad9285226b31611d3e9fe1c"},
{file = "notebook-7.2.2.tar.gz", hash = "sha256:2ef07d4220421623ad3fe88118d687bc0450055570cdd160814a59cf3a1c516e"},
{file = "notebook-7.0.7-py3-none-any.whl", hash = "sha256:289b606d7e173f75a18beb1406ef411b43f97f7a9c55ba03efa3622905a62346"},
{file = "notebook-7.0.7.tar.gz", hash = "sha256:3bcff00c17b3ac142ef5f436d50637d936b274cfa0b41f6ac0175363de9b4e09"},
]
[package.dependencies]
jupyter-server = ">=2.4.0,<3"
jupyterlab = ">=4.2.0,<4.3"
jupyterlab-server = ">=2.27.1,<3"
jupyterlab = ">=4.0.2,<5"
jupyterlab-server = ">=2.22.1,<3"
notebook-shim = ">=0.2,<0.3"
tornado = ">=6.2.0"
[package.extras]
dev = ["hatch", "pre-commit"]
docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.27.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.22.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
[[package]]
name = "notebook-shim"
@ -2575,13 +2575,13 @@ files = [
[[package]]
name = "openai"
version = "1.52.2"
version = "1.53.0"
description = "The official Python library for the openai API"
optional = true
python-versions = ">=3.7.1"
files = [
{file = "openai-1.52.2-py3-none-any.whl", hash = "sha256:57e9e37bc407f39bb6ec3a27d7e8fb9728b2779936daa1fcf95df17d3edfaccc"},
{file = "openai-1.52.2.tar.gz", hash = "sha256:87b7d0f69d85f5641678d414b7ee3082363647a5c66a462ed7f3ccb59582da0d"},
{file = "openai-1.53.0-py3-none-any.whl", hash = "sha256:20f408c32fc5cb66e60c6882c994cdca580a5648e10045cd840734194f033418"},
{file = "openai-1.53.0.tar.gz", hash = "sha256:be2c4e77721b166cce8130e544178b7d579f751b4b074ffbaade3854b6f85ec5"},
]
[package.dependencies]
@ -4073,61 +4073,14 @@ description = "Database Abstraction Library"
optional = false
python-versions = ">=3.7"
files = [
{file = "SQLAlchemy-2.0.36-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:59b8f3adb3971929a3e660337f5dacc5942c2cdb760afcabb2614ffbda9f9f72"},
{file = "SQLAlchemy-2.0.36-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:37350015056a553e442ff672c2d20e6f4b6d0b2495691fa239d8aa18bb3bc908"},
{file = "SQLAlchemy-2.0.36-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8318f4776c85abc3f40ab185e388bee7a6ea99e7fa3a30686580b209eaa35c08"},
{file = "SQLAlchemy-2.0.36-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c245b1fbade9c35e5bd3b64270ab49ce990369018289ecfde3f9c318411aaa07"},
{file = "SQLAlchemy-2.0.36-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:69f93723edbca7342624d09f6704e7126b152eaed3cdbb634cb657a54332a3c5"},
{file = "SQLAlchemy-2.0.36-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f9511d8dd4a6e9271d07d150fb2f81874a3c8c95e11ff9af3a2dfc35fe42ee44"},
{file = "SQLAlchemy-2.0.36-cp310-cp310-win32.whl", hash = "sha256:c3f3631693003d8e585d4200730616b78fafd5a01ef8b698f6967da5c605b3fa"},
{file = "SQLAlchemy-2.0.36-cp310-cp310-win_amd64.whl", hash = "sha256:a86bfab2ef46d63300c0f06936bd6e6c0105faa11d509083ba8f2f9d237fb5b5"},
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{file = "SQLAlchemy-2.0.36-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d0ddd9db6e59c44875211bc4c7953a9f6638b937b0a88ae6d09eb46cced54eff"},
{file = "SQLAlchemy-2.0.36-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2519f3a5d0517fc159afab1015e54bb81b4406c278749779be57a569d8d1bb0d"},
{file = "SQLAlchemy-2.0.36-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:59b1ee96617135f6e1d6f275bbe988f419c5178016f3d41d3c0abb0c819f75bb"},
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[package.dependencies]
@ -4927,4 +4880,4 @@ type = ["pytest-mypy"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.9,<4.0"
content-hash = "52b6e8f0985fd682a9d475a66d374b4588fddee44dc622efcc8cbb0ceccc6532"
content-hash = "f426834916aac5361268adcaa2eee8ee310c3b1eb46b60b54a97334ef2c2a1da"

4
libs/langchain/pyproject.toml
View File

@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
[tool.poetry]
name = "langchain"
version = "0.3.5"
version = "0.3.6"
description = "Building applications with LLMs through composability"
authors = []
license = "MIT"
@ -33,7 +33,7 @@ langchain-server = "langchain.server:main"
[tool.poetry.dependencies]
python = ">=3.9,<4.0"
langchain-core = "^0.3.13"
langchain-core = "^0.3.14"
langchain-text-splitters = "^0.3.0"
langsmith = "^0.1.17"
pydantic = "^2.7.4"

15
libs/partners/anthropic/langchain_anthropic/chat_models.py
View File

@ -139,7 +139,10 @@ def _merge_messages(
]
)
last = merged[-1] if merged else None
if isinstance(last, HumanMessage) and isinstance(curr, HumanMessage):
if any(
all(isinstance(m, c) for m in (curr, last))
for c in (SystemMessage, HumanMessage)
):
if isinstance(last.content, str):
new_content: List = [{"type": "text", "text": last.content}]
else:
@ -148,7 +151,7 @@ def _merge_messages(
new_content.append({"type": "text", "text": curr.content})
else:
new_content.extend(curr.content)
merged[-1] = curr.model_copy(update={"content": new_content}, deep=False)
merged[-1] = curr.model_copy(update={"content": new_content})
else:
merged.append(curr)
return merged
@ -174,14 +177,14 @@ def _format_messages(
merged_messages = _merge_messages(messages)
for i, message in enumerate(merged_messages):
if message.type == "system":
if i != 0:
raise ValueError("System message must be at beginning of message list.")
if isinstance(message.content, list):
if system is not None:
raise ValueError("Received multiple non-consecutive system messages.")
elif isinstance(message.content, list):
system = [
(
block
if isinstance(block, dict)
else {"type": "text", "text": "block"}
else {"type": "text", "text": block}
)
for block in message.content
]

22
libs/partners/anthropic/tests/unit_tests/test_chat_models.py
View File

@ -695,6 +695,28 @@ def test__format_messages_with_cache_control() -> None:
assert expected_messages == actual_messages
def test__format_messages_with_multiple_system() -> None:
messages = [
HumanMessage("baz"),
SystemMessage("bar"),
SystemMessage("baz"),
SystemMessage(
[
{"type": "text", "text": "foo", "cache_control": {"type": "ephemeral"}},
]
),
]
expected_system = [
{"type": "text", "text": "bar"},
{"type": "text", "text": "baz"},
{"type": "text", "text": "foo", "cache_control": {"type": "ephemeral"}},
]
expected_messages = [{"role": "user", "content": "baz"}]
actual_system, actual_messages = _format_messages(messages)
assert expected_system == actual_system
assert expected_messages == actual_messages
def test_anthropic_api_key_is_secret_string() -> None:
"""Test that the API key is stored as a SecretStr."""
chat_model = ChatAnthropic( # type: ignore[call-arg, call-arg]