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ruff: more rules across the board & fixes (#31898)

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* standardizes ruff dep version across all `pyproject.toml` files
* cli: ruff rules and corrections
* langchain: rules and corrections
This commit is contained in:
Mason Daugherty 2025-07-07 17:48:01 -04:00 committed by GitHub
parent 706a66eccd
commit e7eac27241
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408 changed files with 2783 additions and 1671 deletions
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1
Makefile
View File

@ -71,7 +71,6 @@ spell_fix:
lint lint_package lint_tests:
uv run --group lint ruff check docs cookbook
uv run --group lint ruff format docs cookbook cookbook --diff
uv run --group lint ruff check docs cookbook
git --no-pager grep 'from langchain import' docs cookbook | grep -vE 'from langchain import (hub)' && echo "Error: no importing langchain from root in docs, except for hub" && exit 1 || exit 0
git --no-pager grep 'api.python.langchain.com' -- docs/docs ':!docs/docs/additional_resources/arxiv_references.mdx' ':!docs/docs/integrations/document_loaders/sitemap.ipynb' || exit 0 && \

16
libs/cli/langchain_cli/cli.py
View File

@ -11,7 +11,9 @@ from langchain_cli.utils.packages import get_langserve_export, get_package_root
app = typer.Typer(no_args_is_help=True, add_completion=False)
app.add_typer(
template_namespace.package_cli, name="template", help=template_namespace.__doc__
template_namespace.package_cli,
name="template",
help=template_namespace.__doc__,
)
app.add_typer(app_namespace.app_cli, name="app", help=app_namespace.__doc__)
app.add_typer(
@ -32,7 +34,7 @@ app.command(
)
def version_callback(show_version: bool) -> None:
def version_callback(show_version: bool) -> None: # noqa: FBT001
if show_version:
typer.echo(f"langchain-cli {__version__}")
raise typer.Exit
@ -40,8 +42,8 @@ def version_callback(show_version: bool) -> None:
@app.callback()
def main(
version: bool = typer.Option(
False,
version: bool = typer.Option( # noqa: FBT001
False, # noqa: FBT003
"--version",
"-v",
help="Print the current CLI version.",
@ -56,10 +58,12 @@ def main(
def serve(
*,
port: Annotated[
Optional[int], typer.Option(help="The port to run the server on")
Optional[int],
typer.Option(help="The port to run the server on"),
] = None,
host: Annotated[
Optional[str], typer.Option(help="The host to run the server on")
Optional[str],
typer.Option(help="The host to run the server on"),
] = None,
) -> None:
"""Start the LangServe app, whether it's a template or an app."""

6
libs/cli/langchain_cli/dev_scripts.py
View File

@ -1,7 +1,7 @@
# type: ignore
"""Development Scripts for template packages."""
from collections.abc import Sequence
from typing import Literal
from fastapi import FastAPI
from langserve import add_routes
@ -12,9 +12,9 @@ from langchain_cli.utils.packages import get_langserve_export, get_package_root
def create_demo_server(
*,
config_keys: Sequence[str] = (),
playground_type: str = "default",
playground_type: Literal["default", "chat"] = "default",
):
"""Creates a demo server for the current template."""
"""Create a demo server for the current template."""
app = FastAPI()
package_root = get_package_root()
pyproject = package_root / "pyproject.toml"

2
libs/cli/langchain_cli/integration_template/Makefile
View File

@ -39,7 +39,7 @@ lint lint_diff lint_package lint_tests:
format format_diff:
[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES)
[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES)
[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --fix $(PYTHON_FILES)
spell_check:
poetry run codespell --toml pyproject.toml

45
libs/cli/langchain_cli/namespaces/app.py
View File

@ -79,7 +79,9 @@ def new(
package_prompt = "What package would you like to add? (leave blank to skip)"
while True:
package_str = typer.prompt(
package_prompt, default="", show_default=False
package_prompt,
default="",
show_default=False,
)
if not package_str:
break
@ -121,26 +123,29 @@ def new(
typer.echo("Then add templates with commands like:\n")
typer.echo(" langchain app add extraction-openai-functions")
typer.echo(
" langchain app add git+ssh://git@github.com/efriis/simple-pirate.git\n\n"
" langchain app add git+ssh://git@github.com/efriis/simple-pirate.git\n\n",
)
@app_cli.command()
def add(
dependencies: Annotated[
Optional[list[str]], typer.Argument(help="The dependency to add")
Optional[list[str]],
typer.Argument(help="The dependency to add"),
] = None,
*,
api_path: Annotated[list[str], typer.Option(help="API paths to add")] = [],
project_dir: Annotated[
Optional[Path], typer.Option(help="The project directory")
Optional[Path],
typer.Option(help="The project directory"),
] = None,
repo: Annotated[
list[str],
typer.Option(help="Install templates from a specific github repo instead"),
] = [],
branch: Annotated[
list[str], typer.Option(help="Install templates from a specific branch")
list[str],
typer.Option(help="Install templates from a specific branch"),
] = [],
pip: Annotated[
bool,
@ -152,13 +157,12 @@ def add(
),
],
) -> None:
"""Adds the specified template to the current LangServe app.
"""Add the specified template to the current LangServe app.
e.g.:
langchain app add extraction-openai-functions
langchain app add git+ssh://git@github.com/efriis/simple-pirate.git
"""
if not branch and not repo:
warnings.warn(
"Adding templates from the default branch and repo is deprecated."
@ -173,7 +177,7 @@ def add(
package_dir = project_root / "packages"
create_events(
[{"event": "serve add", "properties": {"parsed_dep": d}} for d in parsed_deps]
[{"event": "serve add", "properties": {"parsed_dep": d}} for d in parsed_deps],
)
# group by repo/ref
@ -248,7 +252,7 @@ def add(
cmd = ["pip", "install", "-e", *installed_destination_strs]
cmd_str = " \\\n ".join(installed_destination_strs)
typer.echo(f"Running: pip install -e \\\n {cmd_str}")
subprocess.run(cmd, cwd=cwd)
subprocess.run(cmd, cwd=cwd) # noqa: S603
chain_names = []
for e in installed_exports:
@ -296,10 +300,11 @@ def remove(
api_paths: Annotated[list[str], typer.Argument(help="The API paths to remove")],
*,
project_dir: Annotated[
Optional[Path], typer.Option(help="The project directory")
Optional[Path],
typer.Option(help="The project directory"),
] = None,
) -> None:
"""Removes the specified package from the current LangServe app."""
"""Remove the specified package from the current LangServe app."""
project_root = get_package_root(project_dir)
project_pyproject = project_root / "pyproject.toml"
@ -320,7 +325,7 @@ def remove(
shutil.rmtree(package_dir)
remove_deps.append(api_path)
except Exception:
except Exception: # noqa: S110
pass
try:
@ -334,16 +339,19 @@ def remove(
def serve(
*,
port: Annotated[
Optional[int], typer.Option(help="The port to run the server on")
Optional[int],
typer.Option(help="The port to run the server on"),
] = None,
host: Annotated[
Optional[str], typer.Option(help="The host to run the server on")
Optional[str],
typer.Option(help="The host to run the server on"),
] = None,
app: Annotated[
Optional[str], typer.Option(help="The app to run, e.g. `app.server:app`")
Optional[str],
typer.Option(help="The app to run, e.g. `app.server:app`"),
] = None,
) -> None:
"""Starts the LangServe app."""
"""Start the LangServe app."""
# add current dir as first entry of path
sys.path.append(str(Path.cwd()))
@ -353,5 +361,8 @@ def serve(
import uvicorn
uvicorn.run(
app_str, host=host_str, port=port if port is not None else 8000, reload=True
app_str,
host=host_str,
port=port if port is not None else 8000,
reload=True,
)

17
libs/cli/langchain_cli/namespaces/integration.py
View File

@ -66,7 +66,7 @@ def new(
Optional[str],
typer.Option(
help="The name of the integration in PascalCase. e.g. `MyIntegration`."
" This is used to name classes like `MyIntegrationVectorStore`"
" This is used to name classes like `MyIntegrationVectorStore`",
),
] = None,
src: Annotated[
@ -85,7 +85,7 @@ def new(
),
] = None,
) -> None:
"""Creates a new integration package."""
"""Create a new integration package."""
try:
replacements = _process_name(name)
except ValueError as e:
@ -96,13 +96,14 @@ def new(
if not re.match(r"^[A-Z][a-zA-Z0-9]*$", name_class):
typer.echo(
"Name should only contain letters (a-z, A-Z), numbers, and underscores"
", and start with a capital letter."
", and start with a capital letter.",
)
raise typer.Exit(code=1)
replacements["__ModuleName__"] = name_class
else:
replacements["__ModuleName__"] = typer.prompt(
"Name of integration in PascalCase", default=replacements["__ModuleName__"]
"Name of integration in PascalCase",
default=replacements["__ModuleName__"],
)
project_template_dir = Path(__file__).parents[1] / "integration_template"
@ -124,7 +125,7 @@ def new(
# poetry install
subprocess.run(
["poetry", "install", "--with", "lint,test,typing,test_integration"],
["poetry", "install", "--with", "lint,test,typing,test_integration"], # noqa: S607
cwd=destination_dir,
)
else:
@ -152,7 +153,7 @@ def new(
if len(dst_paths) != len(set(dst_paths)):
typer.echo(
"Duplicate destination paths provided or computed - please "
"specify them explicitly with --dst."
"specify them explicitly with --dst.",
)
raise typer.Exit(code=1)
@ -224,10 +225,10 @@ def create_doc(
),
] = "docs/docs/integrations/chat/",
) -> None:
"""Creates a new integration doc."""
"""Create a new integration doc."""
if component_type not in TEMPLATE_MAP:
typer.echo(
f"Unrecognized {component_type=}. Expected one of {_component_types_str}."
f"Unrecognized {component_type=}. Expected one of {_component_types_str}.",
)
raise typer.Exit(code=1)

58
libs/cli/langchain_cli/namespaces/migrate/generate/generic.py
View File

@ -6,14 +6,17 @@ import pkgutil
def generate_raw_migrations(
from_package: str, to_package: str, filter_by_all: bool = False
from_package: str,
to_package: str,
filter_by_all: bool = False, # noqa: FBT001, FBT002
) -> list[tuple[str, str]]:
"""Scan the `langchain` package and generate migrations for all modules."""
package = importlib.import_module(from_package)
items = []
for _importer, modname, _ispkg in pkgutil.walk_packages(
package.__path__, package.__name__ + "."
package.__path__,
package.__name__ + ".",
):
try:
module = importlib.import_module(modname)
@ -34,33 +37,35 @@ def generate_raw_migrations(
obj = getattr(module, name, None)
except ImportError:
continue
if obj and (inspect.isclass(obj) or inspect.isfunction(obj)):
if obj.__module__.startswith(to_package):
items.append(
(f"{modname}.{name}", f"{obj.__module__}.{obj.__name__}")
)
if (
obj
and (inspect.isclass(obj) or inspect.isfunction(obj))
and obj.__module__.startswith(to_package)
):
items.append(
(f"{modname}.{name}", f"{obj.__module__}.{obj.__name__}"),
)
if not filter_by_all:
# Iterate over all members of the module
for name, obj in inspect.getmembers(module):
# Check if it's a class or function
if inspect.isclass(obj) or inspect.isfunction(obj):
# Check if the module name of the obj starts with
# 'langchain_community'
if obj.__module__.startswith(to_package):
items.append(
(f"{modname}.{name}", f"{obj.__module__}.{obj.__name__}")
)
# Check if the module name of the obj starts with
# 'langchain_community'
if inspect.isclass(obj) or (
inspect.isfunction(obj) and obj.__module__.startswith(to_package)
):
items.append(
(f"{modname}.{name}", f"{obj.__module__}.{obj.__name__}"),
)
return items
def generate_top_level_imports(pkg: str) -> list[tuple[str, str]]:
"""This code will look at all the top level modules in langchain_community.
"""Look at all the top level modules in langchain_community.
It'll attempt to import everything from each __init__ file
for example,
Attempt to import everything from each ``__init__`` file. For example,
langchain_community/
chat_models/
@ -74,10 +79,10 @@ def generate_top_level_imports(pkg: str) -> list[tuple[str, str]]:
Each tuple will contain the fully qualified path of the class / function to where
its logic is defined
(e.g., langchain_community.chat_models.xyz_implementation.ver2.XYZ)
(e.g., ``langchain_community.chat_models.xyz_implementation.ver2.XYZ``)
and the second tuple will contain the path
to importing it from the top level namespaces
(e.g., langchain_community.chat_models.XYZ)
(e.g., ``langchain_community.chat_models.XYZ``)
"""
package = importlib.import_module(pkg)
@ -98,7 +103,7 @@ def generate_top_level_imports(pkg: str) -> list[tuple[str, str]]:
top_level_import = f"{module_name}.{name}"
# Append the tuple with original and top-level paths
items.append(
(f"{original_module}.{original_name}", top_level_import)
(f"{original_module}.{original_name}", top_level_import),
)
# Handle the package itself (root level)
@ -106,7 +111,8 @@ def generate_top_level_imports(pkg: str) -> list[tuple[str, str]]:
# Only iterate through top-level modules/packages
for _finder, modname, ispkg in pkgutil.iter_modules(
package.__path__, package.__name__ + "."
package.__path__,
package.__name__ + ".",
):
if ispkg:
try:
@ -119,11 +125,15 @@ def generate_top_level_imports(pkg: str) -> list[tuple[str, str]]:
def generate_simplified_migrations(
from_package: str, to_package: str, filter_by_all: bool = True
from_package: str,
to_package: str,
filter_by_all: bool = True, # noqa: FBT001, FBT002
) -> list[tuple[str, str]]:
"""Get all the raw migrations, then simplify them if possible."""
raw_migrations = generate_raw_migrations(
from_package, to_package, filter_by_all=filter_by_all
from_package,
to_package,
filter_by_all=filter_by_all,
)
top_level_simplifications = generate_top_level_imports(to_package)
top_level_dict = dict(top_level_simplifications)

2
libs/cli/langchain_cli/namespaces/migrate/generate/grit.py
View File

@ -17,7 +17,7 @@ def dump_migrations_as_grit(name: str, migration_pairs: list[tuple[str, str]]) -
]
"""
for from_module, to_module in migration_pairs
]
],
)
pattern_name = f"langchain_migrate_{name}"
return f"""

1
libs/cli/langchain_cli/namespaces/migrate/generate/partner.py
View File

@ -28,6 +28,7 @@ def get_migrations_for_partner_package(pkg_name: str) -> list[tuple[str, str]]:
Returns:
List of 2-tuples containing old and new import paths.
"""
package = importlib.import_module(pkg_name)
classes_ = find_subclasses_in_module(

17
libs/cli/langchain_cli/namespaces/migrate/generate/utils.py
View File

@ -20,7 +20,7 @@ class ImportExtractor(ast.NodeVisitor):
self.imports: list = []
self.package = from_package
def visit_ImportFrom(self, node) -> None:
def visit_ImportFrom(self, node) -> None: # noqa: N802
if node.module and (
self.package is None or str(node.module).startswith(self.package)
):
@ -39,7 +39,7 @@ def _get_class_names(code: str) -> list[str]:
# Define a node visitor class to collect class names
class ClassVisitor(ast.NodeVisitor):
def visit_ClassDef(self, node) -> None:
def visit_ClassDef(self, node) -> None: # noqa: N802
class_names.append(node.name)
self.generic_visit(node)
@ -79,7 +79,9 @@ def _get_all_classnames_from_file(file: Path, pkg: str) -> list[tuple[str, str]]
def identify_all_imports_in_file(
file: str, *, from_package: Optional[str] = None
file: str,
*,
from_package: Optional[str] = None,
) -> list[tuple[str, str]]:
"""Let's also identify all the imports in the given file."""
with open(file, encoding="utf-8") as f:
@ -96,10 +98,13 @@ def identify_pkg_source(pkg_root: str) -> pathlib.Path:
Returns:
Returns the path to the source code for the package.
"""
dirs = [d for d in Path(pkg_root).iterdir() if d.is_dir()]
matching_dirs = [d for d in dirs if d.name.startswith("langchain_")]
assert len(matching_dirs) == 1, "There should be only one langchain package."
if len(matching_dirs) != 1:
msg = "There should be only one langchain package."
raise ValueError(msg)
return matching_dirs[0]
@ -134,7 +139,9 @@ def list_init_imports_by_package(pkg_root: str) -> list[tuple[str, str]]:
def find_imports_from_package(
code: str, *, from_package: Optional[str] = None
code: str,
*,
from_package: Optional[str] = None,
) -> list[tuple[str, str]]:
# Parse the code into an AST
tree = ast.parse(code)

12
libs/cli/langchain_cli/namespaces/migrate/main.py
View File

@ -4,7 +4,7 @@ from pathlib import Path
import rich
import typer
from gritql import run # type: ignore
from gritql import run # type: ignore[import]
from typer import Option
@ -17,13 +17,13 @@ def get_gritdir_path() -> Path:
def migrate(
ctx: typer.Context,
# Using diff instead of dry-run for backwards compatibility with the old CLI
diff: bool = Option(
False,
diff: bool = Option( # noqa: FBT001
False, # noqa: FBT003
"--diff",
help="Show the changes that would be made without applying them.",
),
interactive: bool = Option(
False,
interactive: bool = Option( # noqa: FBT001
False, # noqa: FBT003
"--interactive",
help="Prompt for confirmation before making each change",
),
@ -54,7 +54,7 @@ def migrate(
'⚠️ This script is a "best-effort", and is likely to make some '
"mistakes.\n\n"
"🛡️ Backup your code prior to running the migration script -- it will "
"modify your files!\n\n"
"modify your files!\n\n",
)
rich.print("-" * 10)
rich.print()

26
libs/cli/langchain_cli/namespaces/template.py
View File

@ -16,12 +16,12 @@ package_cli = typer.Typer(no_args_is_help=True, add_completion=False)
@package_cli.command()
def new(
name: Annotated[str, typer.Argument(help="The name of the folder to create")],
with_poetry: Annotated[
with_poetry: Annotated[ # noqa: FBT002
bool,
typer.Option("--with-poetry/--no-poetry", help="Don't run poetry install"),
] = False,
) -> None:
"""Creates a new template package."""
"""Create a new template package."""
computed_name = name if name != "." else Path.cwd().name
destination_dir = Path.cwd() / name if name != "." else Path.cwd()
@ -53,8 +53,9 @@ def new(
pyproject_contents = pyproject.read_text()
pyproject.write_text(
pyproject_contents.replace("__package_name__", package_name).replace(
"__module_name__", module_name
)
"__module_name__",
module_name,
),
)
# move module folder
@ -71,23 +72,26 @@ def new(
readme_contents = readme.read_text()
readme.write_text(
readme_contents.replace("__package_name__", package_name).replace(
"__app_route_code__", app_route_code
)
"__app_route_code__",
app_route_code,
),
)
# poetry install
if with_poetry:
subprocess.run(["poetry", "install"], cwd=destination_dir)
subprocess.run(["poetry", "install"], cwd=destination_dir) # noqa: S607
@package_cli.command()
def serve(
*,
port: Annotated[
Optional[int], typer.Option(help="The port to run the server on")
Optional[int],
typer.Option(help="The port to run the server on"),
] = None,
host: Annotated[
Optional[str], typer.Option(help="The host to run the server on")
Optional[str],
typer.Option(help="The host to run the server on"),
] = None,
configurable: Annotated[
Optional[bool],
@ -104,7 +108,7 @@ def serve(
),
] = False,
) -> None:
"""Starts a demo app for this template."""
"""Start a demo app for this template."""
# load pyproject.toml
project_dir = get_package_root()
pyproject = project_dir / "pyproject.toml"
@ -136,7 +140,7 @@ def serve(
@package_cli.command()
def list(contains: Annotated[Optional[str], typer.Argument()] = None) -> None:
def list(contains: Annotated[Optional[str], typer.Argument()] = None) -> None: # noqa: A001
"""List all or search for available templates."""
from langchain_cli.utils.github import list_packages

2
libs/cli/langchain_cli/utils/events.py
View File

@ -20,7 +20,7 @@ def create_events(events: list[EventDict]) -> Optional[Any]:
"properties": event.get("properties"),
}
for event in events
]
],
}
conn = http.client.HTTPSConnection("app.firstpartyhq.com")

11
libs/cli/langchain_cli/utils/git.py
View File

@ -122,7 +122,9 @@ def parse_dependencies(
api_path: list[str],
) -> list[DependencySource]:
num_deps = max(
len(dependencies) if dependencies is not None else 0, len(repo), len(branch)
len(dependencies) if dependencies is not None else 0,
len(repo),
len(branch),
)
if (
(dependencies and len(dependencies) != num_deps)
@ -143,7 +145,10 @@ def parse_dependencies(
return [
parse_dependency_string(iter_dep, iter_repo, iter_branch, iter_api_path)
for iter_dep, iter_repo, iter_branch, iter_api_path in zip(
inner_deps, inner_repos, inner_branches, inner_api_paths
inner_deps,
inner_repos,
inner_branches,
inner_api_paths,
)
]
@ -186,7 +191,7 @@ def copy_repo(
source: Path,
destination: Path,
) -> None:
"""Copies a repo, ignoring git folders.
"""Copiy a repo, ignoring git folders.
Raises FileNotFound error if it can't find source
"""

4
libs/cli/langchain_cli/utils/github.py
View File

@ -13,7 +13,9 @@ def list_packages(*, contains: Optional[str] = None):
}
conn.request(
"GET", "/repos/langchain-ai/langchain/contents/templates", headers=headers
"GET",
"/repos/langchain-ai/langchain/contents/templates",
headers=headers,
)
res = conn.getresponse()

1
libs/cli/langchain_cli/utils/packages.py
View File

@ -26,6 +26,7 @@ class LangServeExport(TypedDict):
module: The module to import from, tool.langserve.export_module
attr: The attribute to import from the module, tool.langserve.export_attr
package_name: The name of the package, tool.poetry.name
"""
module: str

8
libs/cli/langchain_cli/utils/pyproject.py
View File

@ -14,7 +14,8 @@ def _get_dep_inline_table(path: Path) -> InlineTable:
def add_dependencies_to_pyproject_toml(
pyproject_toml: Path, local_editable_dependencies: Iterable[tuple[str, Path]]
pyproject_toml: Path,
local_editable_dependencies: Iterable[tuple[str, Path]],
) -> None:
"""Add dependencies to pyproject.toml."""
with open(pyproject_toml, encoding="utf-8") as f:
@ -24,14 +25,15 @@ def add_dependencies_to_pyproject_toml(
{
name: _get_dep_inline_table(loc.relative_to(pyproject_toml.parent))
for name, loc in local_editable_dependencies
}
},
)
with open(pyproject_toml, "w", encoding="utf-8") as f:
dump(pyproject, f)
def remove_dependencies_from_pyproject_toml(
pyproject_toml: Path, local_editable_dependencies: Iterable[str]
pyproject_toml: Path,
local_editable_dependencies: Iterable[str],
) -> None:
"""Remove dependencies from pyproject.toml."""
with open(pyproject_toml, encoding="utf-8") as f:

43
libs/cli/pyproject.toml
View File

@ -49,12 +49,45 @@ exclude = [
[tool.ruff.lint]
select = [
"E", # pycodestyle
"F", # pyflakes
"I", # isort
"T201", # print
"UP", # pyupgrade
"A", # flake8-builtins
"ARG", # flake8-unused-arguments
"ASYNC", # flake8-async
"C4", # flake8-comprehensions
"COM", # flake8-commas
"D", # pydocstyle
"DOC", # pydoclint
"E", # pycodestyle error
"EM", # flake8-errmsg
"F", # pyflakes
"FA", # flake8-future-annotations
"FBT", # flake8-boolean-trap
"FLY", # flake8-flynt
"I", # isort
"ICN", # flake8-import-conventions
"INT", # flake8-gettext
"ISC", # isort-comprehensions
"N", # pep8-naming
"PT", # flake8-pytest-style
"PGH", # pygrep-hooks
"PIE", # flake8-pie
"PERF", # flake8-perf
"PYI", # flake8-pyi
"Q", # flake8-quotes
"RET", # flake8-return
"RSE", # flake8-rst-docstrings
"RUF", # ruff
"S", # flake8-bandit
"SLF", # flake8-self
"SLOT", # flake8-slots
"SIM", # flake8-simplify
"T10", # flake8-debugger
"T20", # flake8-print
"TID", # flake8-tidy-imports
"UP", # pyupgrade
"W", # pycodestyle warning
"YTT", # flake8-2020
]
ignore = ["D100", "D101", "D102", "D103", "D104", "D105", "D107"]
pyupgrade.keep-runtime-typing = true
[tool.mypy]

12
libs/cli/scripts/generate_migrations.py
View File

@ -1,4 +1,3 @@
# type: ignore
"""Script to generate migrations for the migration script."""
import json
@ -45,12 +44,17 @@ def cli() -> None:
)
@click.option(
"--format",
"format_",
type=click.Choice(["json", "grit"], case_sensitive=False),
default="json",
help="The output format for the migration script (json or grit).",
)
def generic(
pkg1: str, pkg2: str, output: str, filter_by_all: bool, format: str
pkg1: str,
pkg2: str,
output: str,
filter_by_all: bool, # noqa: FBT001
format_: str,
) -> None:
"""Generate a migration script."""
click.echo("Migration script generated.")
@ -62,9 +66,9 @@ def generic(
name = f"{pkg1}_to_{pkg2}"
if output is None:
output = f"{name}.json" if format == "json" else f"{name}.grit"
output = f"{name}.json" if format_ == "json" else f"{name}.grit"
if format == "json":
if format_ == "json":
dumped = json.dumps(migrations, indent=2, sort_keys=True)
else:
dumped = dump_migrations_as_grit(name, migrations)

2
libs/cli/tests/unit_tests/migrate/cli_runner/file.py
View File

@ -6,7 +6,7 @@ class File:
self.name = name
self.content = "\n".join(content or [])
def __eq__(self, __value: object) -> bool:
def __eq__(self, __value: object, /) -> bool:
if not isinstance(__value, File):
return NotImplemented

4
libs/cli/tests/unit_tests/migrate/cli_runner/folder.py
View File

@ -34,12 +34,12 @@ class Folder:
files.append(cls.from_structure(path))
else:
files.append(
File(path.name, path.read_text(encoding="utf-8").splitlines())
File(path.name, path.read_text(encoding="utf-8").splitlines()),
)
return Folder(name, *files)
def __eq__(self, __value: object) -> bool:
def __eq__(self, __value: object, /) -> bool:
if isinstance(__value, File):
return False

8
libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py
View File

@ -34,7 +34,7 @@ def find_issue(current: Folder, expected: Folder) -> str:
expected_file.content.splitlines(),
fromfile=current_file.name,
tofile=expected_file.name,
)
),
)
return "Unknown"
@ -47,8 +47,10 @@ def test_command_line(tmp_path: Path) -> None:
before.create_structure(root=Path(td))
# The input is used to force through the confirmation.
result = runner.invoke(app, ["migrate", before.name, "--force"])
assert result.exit_code == 0, result.output
if result.exit_code != 0:
raise RuntimeError(result.output)
after = Folder.from_structure(Path(td) / before.name)
assert after == expected, find_issue(after, expected)
if after != expected:
raise ValueError(find_issue(after, expected))

21
libs/cli/tests/unit_tests/migrate/generate/test_langchain_migration.py
View File

@ -12,14 +12,15 @@ def test_create_json_agent_migration() -> None:
"""Test the migration of create_json_agent from langchain to langchain_community."""
with sup1(), sup2():
raw_migrations = generate_simplified_migrations(
from_package="langchain", to_package="langchain_community"
from_package="langchain",
to_package="langchain_community",
)
json_agent_migrations = [
migration
for migration in raw_migrations
if "create_json_agent" in migration[0]
]
assert json_agent_migrations == [
if json_agent_migrations != [
(
"langchain.agents.create_json_agent",
"langchain_community.agent_toolkits.create_json_agent",
@ -32,7 +33,9 @@ def test_create_json_agent_migration() -> None:
"langchain.agents.agent_toolkits.json.base.create_json_agent",
"langchain_community.agent_toolkits.create_json_agent",
),
]
]:
msg = "json_agent_migrations did not match the expected value"
raise ValueError(msg)
@pytest.mark.xfail(reason="Unknown reason")
@ -40,15 +43,21 @@ def test_create_single_store_retriever_db() -> None:
"""Test migration from langchain to langchain_core."""
with sup1(), sup2():
raw_migrations = generate_simplified_migrations(
from_package="langchain", to_package="langchain_core"
from_package="langchain",
to_package="langchain_core",
)
# SingleStore was an old name for VectorStoreRetriever
single_store_migration = [
migration for migration in raw_migrations if "SingleStore" in migration[0]
]
assert single_store_migration == [
if single_store_migration != [
(
"langchain.vectorstores.singlestoredb.SingleStoreDBRetriever",
"langchain_core.vectorstores.VectorStoreRetriever",
),
]
]:
msg = (
"Unexpected migration: single_store_migration does not match expected "
"value"
)
raise ValueError(msg)

6
libs/cli/tests/unit_tests/migrate/generate/test_partner_migrations.py
View File

@ -9,7 +9,7 @@ pytest.importorskip(modname="langchain_openai")
def test_generate_migrations() -> None:
migrations = get_migrations_for_partner_package("langchain_openai")
assert migrations == [
if migrations != [
("langchain_community.llms.openai.OpenAI", "langchain_openai.OpenAI"),
("langchain_community.llms.openai.AzureOpenAI", "langchain_openai.AzureOpenAI"),
(
@ -43,4 +43,6 @@ def test_generate_migrations() -> None:
"langchain_openai.AzureChatOpenAI",
),
("langchain_community.chat_models.ChatOpenAI", "langchain_openai.ChatOpenAI"),
]
]:
msg = "Migrations do not match expected result"
raise ValueError(msg)

4
libs/cli/tests/unit_tests/migrate/generate/test_utils.py
View File

@ -2,4 +2,6 @@ from langchain_cli.namespaces.migrate.generate.utils import PKGS_ROOT
def test_root() -> None:
assert PKGS_ROOT.name == "libs"
if PKGS_ROOT.name != "libs":
msg = "Expected PKGS_ROOT.name to be 'libs'."
raise ValueError(msg)

7
libs/cli/tests/unit_tests/test_events.py
View File

@ -5,6 +5,7 @@ from langchain_cli.utils.events import EventDict, create_events
@pytest.mark.xfail(reason="Unknown reason")
def test_create_events() -> None:
assert create_events(
[EventDict(event="Test Event", properties={"test": "test"})]
) == {"status": "success"}
result = create_events([EventDict(event="Test Event", properties={"test": "test"})])
if result != {"status": "success"}:
msg = "Expected {'status': 'success'}, got " + repr(result)
raise ValueError(msg)

50
libs/cli/tests/unit_tests/test_utils.py
View File

@ -18,17 +18,37 @@ def _assert_dependency_equals(
subdirectory: Optional[str] = None,
event_metadata: Optional[dict] = None,
) -> None:
assert dep["git"] == git
assert dep["ref"] == ref
assert dep["subdirectory"] == subdirectory
if event_metadata is not None:
assert dep["event_metadata"] == event_metadata
if dep["git"] != git:
msg = f"Expected git to be {git} but got {dep['git']}"
raise ValueError(msg)
if dep["ref"] != ref:
msg = f"Expected ref to be {ref} but got {dep['ref']}"
raise ValueError(msg)
if dep["subdirectory"] != subdirectory:
msg = (
f"Expected subdirectory to be {subdirectory} but got {dep['subdirectory']}"
)
raise ValueError(msg)
if dep["subdirectory"] != subdirectory:
msg = (
f"Expected subdirectory to be {subdirectory} but got {dep['subdirectory']}"
)
raise ValueError(msg)
if event_metadata is not None and dep["event_metadata"] != event_metadata:
msg = (
f"Expected event_metadata to be {event_metadata} "
f"but got {dep['event_metadata']}"
)
raise ValueError(msg)
def test_dependency_string() -> None:
_assert_dependency_equals(
parse_dependency_string(
"git+ssh://git@github.com/efriis/myrepo.git", None, None, None
"git+ssh://git@github.com/efriis/myrepo.git",
None,
None,
None,
),
git="ssh://git@github.com/efriis/myrepo.git",
ref=None,
@ -49,7 +69,10 @@ def test_dependency_string() -> None:
_assert_dependency_equals(
parse_dependency_string(
"git+ssh://git@github.com:efriis/myrepo.git#develop", None, None, None
"git+ssh://git@github.com:efriis/myrepo.git#develop",
None,
None,
None,
),
git="ssh://git@github.com:efriis/myrepo.git",
ref="develop",
@ -59,7 +82,10 @@ def test_dependency_string() -> None:
# also support a slash in ssh
_assert_dependency_equals(
parse_dependency_string(
"git+ssh://git@github.com/efriis/myrepo.git#develop", None, None, None
"git+ssh://git@github.com/efriis/myrepo.git#develop",
None,
None,
None,
),
git="ssh://git@github.com/efriis/myrepo.git",
ref="develop",
@ -69,7 +95,10 @@ def test_dependency_string() -> None:
# looks like poetry supports both an @ and a #
_assert_dependency_equals(
parse_dependency_string(
"git+ssh://git@github.com:efriis/myrepo.git@develop", None, None, None
"git+ssh://git@github.com:efriis/myrepo.git@develop",
None,
None,
None,
),
git="ssh://git@github.com:efriis/myrepo.git",
ref="develop",
@ -100,7 +129,8 @@ def test_dependency_string_both() -> None:
def test_dependency_string_invalids() -> None:
# expect error for wrong order
with pytest.raises(ValueError):
# Bypassing validation since the ValueError message is dynamic
with pytest.raises(ValueError): # noqa: PT011
parse_dependency_string(
"git+https://github.com/efriis/myrepo.git#subdirectory=src@branch",
None,

4
libs/core/pyproject.toml
View File

@ -26,9 +26,7 @@ readme = "README.md"
repository = "https://github.com/langchain-ai/langchain"
[dependency-groups]
lint = [
"ruff<0.13.0,>=0.12.2",
]
lint = ["ruff<0.13,>=0.12.2"]
typing = [
"mypy<1.16,>=1.15",
"types-pyyaml<7.0.0.0,>=6.0.12.2",

40
libs/langchain/langchain/__init__.py
View File

@ -28,11 +28,11 @@ def _warn_on_import(name: str, replacement: Optional[str] = None) -> None:
if replacement:
warnings.warn(
f"Importing {name} from langchain root module is no longer supported. "
f"Please use {replacement} instead."
f"Please use {replacement} instead.",
)
else:
warnings.warn(
f"Importing {name} from langchain root module is no longer supported."
f"Importing {name} from langchain root module is no longer supported.",
)
@ -170,7 +170,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.llms import HuggingFaceTextGenInference
_warn_on_import(
name, replacement="langchain_community.llms.HuggingFaceTextGenInference"
name,
replacement="langchain_community.llms.HuggingFaceTextGenInference",
)
return HuggingFaceTextGenInference
@ -235,7 +236,8 @@ def __getattr__(name: str) -> Any:
from langchain_core.prompts import FewShotPromptTemplate
_warn_on_import(
name, replacement="langchain_core.prompts.FewShotPromptTemplate"
name,
replacement="langchain_core.prompts.FewShotPromptTemplate",
)
return FewShotPromptTemplate
@ -263,7 +265,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import ArxivAPIWrapper
_warn_on_import(
name, replacement="langchain_community.utilities.ArxivAPIWrapper"
name,
replacement="langchain_community.utilities.ArxivAPIWrapper",
)
return ArxivAPIWrapper
@ -271,7 +274,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import GoldenQueryAPIWrapper
_warn_on_import(
name, replacement="langchain_community.utilities.GoldenQueryAPIWrapper"
name,
replacement="langchain_community.utilities.GoldenQueryAPIWrapper",
)
return GoldenQueryAPIWrapper
@ -279,7 +283,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import GoogleSearchAPIWrapper
_warn_on_import(
name, replacement="langchain_community.utilities.GoogleSearchAPIWrapper"
name,
replacement="langchain_community.utilities.GoogleSearchAPIWrapper",
)
return GoogleSearchAPIWrapper
@ -287,7 +292,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import GoogleSerperAPIWrapper
_warn_on_import(
name, replacement="langchain_community.utilities.GoogleSerperAPIWrapper"
name,
replacement="langchain_community.utilities.GoogleSerperAPIWrapper",
)
return GoogleSerperAPIWrapper
@ -295,7 +301,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import PowerBIDataset
_warn_on_import(
name, replacement="langchain_community.utilities.PowerBIDataset"
name,
replacement="langchain_community.utilities.PowerBIDataset",
)
return PowerBIDataset
@ -303,7 +310,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import SearxSearchWrapper
_warn_on_import(
name, replacement="langchain_community.utilities.SearxSearchWrapper"
name,
replacement="langchain_community.utilities.SearxSearchWrapper",
)
return SearxSearchWrapper
@ -311,7 +319,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import WikipediaAPIWrapper
_warn_on_import(
name, replacement="langchain_community.utilities.WikipediaAPIWrapper"
name,
replacement="langchain_community.utilities.WikipediaAPIWrapper",
)
return WikipediaAPIWrapper
@ -319,7 +328,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import WolframAlphaAPIWrapper
_warn_on_import(
name, replacement="langchain_community.utilities.WolframAlphaAPIWrapper"
name,
replacement="langchain_community.utilities.WolframAlphaAPIWrapper",
)
return WolframAlphaAPIWrapper
@ -339,7 +349,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.vectorstores import ElasticVectorSearch
_warn_on_import(
name, replacement="langchain_community.vectorstores.ElasticVectorSearch"
name,
replacement="langchain_community.vectorstores.ElasticVectorSearch",
)
return ElasticVectorSearch
@ -348,7 +359,8 @@ def __getattr__(name: str) -> Any:
from langchain_community.utilities import SerpAPIWrapper
_warn_on_import(
name, replacement="langchain_community.utilities.SerpAPIWrapper"
name,
replacement="langchain_community.utilities.SerpAPIWrapper",
)
return SerpAPIWrapper

4
libs/langchain/langchain/agents/__init__.py
View File

@ -122,7 +122,9 @@ def __getattr__(name: str) -> Any:
# Get directory of langchain package
HERE = Path(__file__).parents[1]
relative_path = as_import_path(
Path(__file__).parent, suffix=name, relative_to=HERE
Path(__file__).parent,
suffix=name,
relative_to=HERE,
)
old_path = "langchain." + relative_path
new_path = "langchain_experimental." + relative_path

109
libs/langchain/langchain/agents/agent.py
View File

@ -135,7 +135,8 @@ class BaseSingleActionAgent(BaseModel):
if early_stopping_method == "force":
# `force` just returns a constant string
return AgentFinish(
{"output": "Agent stopped due to iteration limit or time limit."}, ""
{"output": "Agent stopped due to iteration limit or time limit."},
"",
)
msg = f"Got unsupported early_stopping_method `{early_stopping_method}`"
raise ValueError(msg)
@ -375,7 +376,7 @@ class AgentOutputParser(BaseOutputParser[Union[AgentAction, AgentFinish]]):
class MultiActionAgentOutputParser(
BaseOutputParser[Union[list[AgentAction], AgentFinish]]
BaseOutputParser[Union[list[AgentAction], AgentFinish]],
):
"""Base class for parsing agent output into agent actions/finish.
@ -491,7 +492,8 @@ class RunnableAgent(BaseSingleActionAgent):
# Because the response from the plan is not a generator, we need to
# accumulate the output into final output and return that.
async for chunk in self.runnable.astream(
inputs, config={"callbacks": callbacks}
inputs,
config={"callbacks": callbacks},
):
if final_output is None:
final_output = chunk
@ -499,7 +501,8 @@ class RunnableAgent(BaseSingleActionAgent):
final_output += chunk
else:
final_output = await self.runnable.ainvoke(
inputs, config={"callbacks": callbacks}
inputs,
config={"callbacks": callbacks},
)
return final_output
@ -607,7 +610,8 @@ class RunnableMultiActionAgent(BaseMultiActionAgent):
# Because the response from the plan is not a generator, we need to
# accumulate the output into final output and return that.
async for chunk in self.runnable.astream(
inputs, config={"callbacks": callbacks}
inputs,
config={"callbacks": callbacks},
):
if final_output is None:
final_output = chunk
@ -615,7 +619,8 @@ class RunnableMultiActionAgent(BaseMultiActionAgent):
final_output += chunk
else:
final_output = await self.runnable.ainvoke(
inputs, config={"callbacks": callbacks}
inputs,
config={"callbacks": callbacks},
)
return final_output
@ -764,7 +769,8 @@ class Agent(BaseSingleActionAgent):
]
def _construct_scratchpad(
self, intermediate_steps: list[tuple[AgentAction, str]]
self,
intermediate_steps: list[tuple[AgentAction, str]],
) -> Union[str, list[BaseMessage]]:
"""Construct the scratchpad that lets the agent continue its thought process."""
thoughts = ""
@ -816,7 +822,9 @@ class Agent(BaseSingleActionAgent):
return await self.output_parser.aparse(full_output)
def get_full_inputs(
self, intermediate_steps: list[tuple[AgentAction, str]], **kwargs: Any
self,
intermediate_steps: list[tuple[AgentAction, str]],
**kwargs: Any,
) -> builtins.dict[str, Any]:
"""Create the full inputs for the LLMChain from intermediate steps.
@ -858,7 +866,7 @@ class Agent(BaseSingleActionAgent):
if "agent_scratchpad" not in prompt.input_variables:
logger.warning(
"`agent_scratchpad` should be a variable in prompt.input_variables."
" Did not find it, so adding it at the end."
" Did not find it, so adding it at the end.",
)
prompt.input_variables.append("agent_scratchpad")
if isinstance(prompt, PromptTemplate):
@ -964,7 +972,8 @@ class Agent(BaseSingleActionAgent):
if early_stopping_method == "force":
# `force` just returns a constant string
return AgentFinish(
{"output": "Agent stopped due to iteration limit or time limit."}, ""
{"output": "Agent stopped due to iteration limit or time limit."},
"",
)
if early_stopping_method == "generate":
# Generate does one final forward pass
@ -1072,7 +1081,8 @@ class AgentExecutor(Chain):
as an observation.
"""
trim_intermediate_steps: Union[
int, Callable[[list[tuple[AgentAction, str]]], list[tuple[AgentAction, str]]]
int,
Callable[[list[tuple[AgentAction, str]]], list[tuple[AgentAction, str]]],
] = -1
"""How to trim the intermediate steps before returning them.
Defaults to -1, which means no trimming.
@ -1153,11 +1163,13 @@ class AgentExecutor(Chain):
stream_runnable = values.pop("stream_runnable", True)
if multi_action:
values["agent"] = RunnableMultiActionAgent(
runnable=agent, stream_runnable=stream_runnable
runnable=agent,
stream_runnable=stream_runnable,
)
else:
values["agent"] = RunnableAgent(
runnable=agent, stream_runnable=stream_runnable
runnable=agent,
stream_runnable=stream_runnable,
)
return values
@ -1281,7 +1293,9 @@ class AgentExecutor(Chain):
) -> dict[str, Any]:
if run_manager:
await run_manager.on_agent_finish(
output, color="green", verbose=self.verbose
output,
color="green",
verbose=self.verbose,
)
final_output = output.return_values
if self.return_intermediate_steps:
@ -1289,7 +1303,8 @@ class AgentExecutor(Chain):
return final_output
def _consume_next_step(
self, values: NextStepOutput
self,
values: NextStepOutput,
) -> Union[AgentFinish, list[tuple[AgentAction, str]]]:
if isinstance(values[-1], AgentFinish):
if len(values) != 1:
@ -1314,8 +1329,8 @@ class AgentExecutor(Chain):
inputs,
intermediate_steps,
run_manager,
)
)
),
),
)
def _iter_next_step(
@ -1391,7 +1406,10 @@ class AgentExecutor(Chain):
yield agent_action
for agent_action in actions:
yield self._perform_agent_action(
name_to_tool_map, color_mapping, agent_action, run_manager
name_to_tool_map,
color_mapping,
agent_action,
run_manager,
)
def _perform_agent_action(
@ -1451,7 +1469,7 @@ class AgentExecutor(Chain):
intermediate_steps,
run_manager,
)
]
],
)
async def _aiter_next_step(
@ -1528,7 +1546,10 @@ class AgentExecutor(Chain):
result = await asyncio.gather(
*[
self._aperform_agent_action(
name_to_tool_map, color_mapping, agent_action, run_manager
name_to_tool_map,
color_mapping,
agent_action,
run_manager,
)
for agent_action in actions
],
@ -1547,7 +1568,9 @@ class AgentExecutor(Chain):
) -> AgentStep:
if run_manager:
await run_manager.on_agent_action(
agent_action, verbose=self.verbose, color="green"
agent_action,
verbose=self.verbose,
color="green",
)
# Otherwise we lookup the tool
if agent_action.tool in name_to_tool_map:
@ -1589,7 +1612,8 @@ class AgentExecutor(Chain):
name_to_tool_map = {tool.name: tool for tool in self.tools}
# We construct a mapping from each tool to a color, used for logging.
color_mapping = get_color_mapping(
[tool.name for tool in self.tools], excluded_colors=["green", "red"]
[tool.name for tool in self.tools],
excluded_colors=["green", "red"],
)
intermediate_steps: list[tuple[AgentAction, str]] = []
# Let's start tracking the number of iterations and time elapsed
@ -1607,7 +1631,9 @@ class AgentExecutor(Chain):
)
if isinstance(next_step_output, AgentFinish):
return self._return(
next_step_output, intermediate_steps, run_manager=run_manager
next_step_output,
intermediate_steps,
run_manager=run_manager,
)
intermediate_steps.extend(next_step_output)
@ -1617,12 +1643,16 @@ class AgentExecutor(Chain):
tool_return = self._get_tool_return(next_step_action)
if tool_return is not None:
return self._return(
tool_return, intermediate_steps, run_manager=run_manager
tool_return,
intermediate_steps,
run_manager=run_manager,
)
iterations += 1
time_elapsed = time.time() - start_time
output = self._action_agent.return_stopped_response(
self.early_stopping_method, intermediate_steps, **inputs
self.early_stopping_method,
intermediate_steps,
**inputs,
)
return self._return(output, intermediate_steps, run_manager=run_manager)
@ -1636,7 +1666,8 @@ class AgentExecutor(Chain):
name_to_tool_map = {tool.name: tool for tool in self.tools}
# We construct a mapping from each tool to a color, used for logging.
color_mapping = get_color_mapping(
[tool.name for tool in self.tools], excluded_colors=["green"]
[tool.name for tool in self.tools],
excluded_colors=["green"],
)
intermediate_steps: list[tuple[AgentAction, str]] = []
# Let's start tracking the number of iterations and time elapsed
@ -1668,28 +1699,39 @@ class AgentExecutor(Chain):
tool_return = self._get_tool_return(next_step_action)
if tool_return is not None:
return await self._areturn(
tool_return, intermediate_steps, run_manager=run_manager
tool_return,
intermediate_steps,
run_manager=run_manager,
)
iterations += 1
time_elapsed = time.time() - start_time
output = self._action_agent.return_stopped_response(
self.early_stopping_method, intermediate_steps, **inputs
self.early_stopping_method,
intermediate_steps,
**inputs,
)
return await self._areturn(
output, intermediate_steps, run_manager=run_manager
output,
intermediate_steps,
run_manager=run_manager,
)
except (TimeoutError, asyncio.TimeoutError):
# stop early when interrupted by the async timeout
output = self._action_agent.return_stopped_response(
self.early_stopping_method, intermediate_steps, **inputs
self.early_stopping_method,
intermediate_steps,
**inputs,
)
return await self._areturn(
output, intermediate_steps, run_manager=run_manager
output,
intermediate_steps,
run_manager=run_manager,
)
def _get_tool_return(
self, next_step_output: tuple[AgentAction, str]
self,
next_step_output: tuple[AgentAction, str],
) -> Optional[AgentFinish]:
"""Check if the tool is a returning tool."""
agent_action, observation = next_step_output
@ -1709,7 +1751,8 @@ class AgentExecutor(Chain):
return None
def _prepare_intermediate_steps(
self, intermediate_steps: list[tuple[AgentAction, str]]
self,
intermediate_steps: list[tuple[AgentAction, str]],
) -> list[tuple[AgentAction, str]]:
if (
isinstance(self.trim_intermediate_steps, int)

43
libs/langchain/langchain/agents/agent_iterator.py
View File

@ -147,7 +147,7 @@ class AgentExecutorIterator:
self.iterations += 1
self.time_elapsed = time.time() - self.start_time
logger.debug(
f"Agent Iterations: {self.iterations} ({self.time_elapsed:.2f}s elapsed)"
f"Agent Iterations: {self.iterations} ({self.time_elapsed:.2f}s elapsed)",
)
def make_final_outputs(
@ -160,8 +160,10 @@ class AgentExecutorIterator:
prepared_outputs = AddableDict(
self.agent_executor.prep_outputs(
self.inputs, outputs, return_only_outputs=True
)
self.inputs,
outputs,
return_only_outputs=True,
),
)
if self.include_run_info:
prepared_outputs[RUN_KEY] = RunInfo(run_id=run_manager.run_id)
@ -187,7 +189,8 @@ class AgentExecutorIterator:
)
try:
while self.agent_executor._should_continue(
self.iterations, self.time_elapsed
self.iterations,
self.time_elapsed,
):
# take the next step: this plans next action, executes it,
# yielding action and observation as they are generated
@ -254,7 +257,8 @@ class AgentExecutorIterator:
try:
async with asyncio_timeout(self.agent_executor.max_execution_time):
while self.agent_executor._should_continue(
self.iterations, self.time_elapsed
self.iterations,
self.time_elapsed,
):
# take the next step: this plans next action, executes it,
# yielding action and observation as they are generated
@ -272,11 +276,13 @@ class AgentExecutorIterator:
if self.yield_actions:
if isinstance(chunk, AgentAction):
yield AddableDict(
actions=[chunk], messages=chunk.messages
actions=[chunk],
messages=chunk.messages,
)
elif isinstance(chunk, AgentStep):
yield AddableDict(
steps=[chunk], messages=chunk.messages
steps=[chunk],
messages=chunk.messages,
)
# convert iterator output to format handled by _process_next_step
@ -285,7 +291,8 @@ class AgentExecutorIterator:
self.update_iterations()
# decide if this is the final output
output = await self._aprocess_next_step_output(
next_step, run_manager
next_step,
run_manager,
)
is_final = "intermediate_step" not in output
# yield the final output always
@ -317,7 +324,7 @@ class AgentExecutorIterator:
logger.debug("Processing output of Agent loop step")
if isinstance(next_step_output, AgentFinish):
logger.debug(
"Hit AgentFinish: _return -> on_chain_end -> run final output logic"
"Hit AgentFinish: _return -> on_chain_end -> run final output logic",
)
return self._return(next_step_output, run_manager=run_manager)
@ -345,7 +352,7 @@ class AgentExecutorIterator:
logger.debug("Processing output of async Agent loop step")
if isinstance(next_step_output, AgentFinish):
logger.debug(
"Hit AgentFinish: _areturn -> on_chain_end -> run final output logic"
"Hit AgentFinish: _areturn -> on_chain_end -> run final output logic",
)
return await self._areturn(next_step_output, run_manager=run_manager)
@ -388,26 +395,34 @@ class AgentExecutorIterator:
return await self._areturn(output, run_manager=run_manager)
def _return(
self, output: AgentFinish, run_manager: CallbackManagerForChainRun
self,
output: AgentFinish,
run_manager: CallbackManagerForChainRun,
) -> AddableDict:
"""
Return the final output of the iterator.
"""
returned_output = self.agent_executor._return(
output, self.intermediate_steps, run_manager=run_manager
output,
self.intermediate_steps,
run_manager=run_manager,
)
returned_output["messages"] = output.messages
run_manager.on_chain_end(returned_output)
return self.make_final_outputs(returned_output, run_manager)
async def _areturn(
self, output: AgentFinish, run_manager: AsyncCallbackManagerForChainRun
self,
output: AgentFinish,
run_manager: AsyncCallbackManagerForChainRun,
) -> AddableDict:
"""
Return the final output of the async iterator.
"""
returned_output = await self.agent_executor._areturn(
output, self.intermediate_steps, run_manager=run_manager
output,
self.intermediate_steps,
run_manager=run_manager,
)
returned_output["messages"] = output.messages
await run_manager.on_chain_end(returned_output)

2
libs/langchain/langchain/agents/agent_toolkits/ainetwork/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"AINetworkToolkit": "langchain_community.agent_toolkits.ainetwork.toolkit"
"AINetworkToolkit": "langchain_community.agent_toolkits.ainetwork.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/amadeus/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"AmadeusToolkit": "langchain_community.agent_toolkits.amadeus.toolkit"
"AmadeusToolkit": "langchain_community.agent_toolkits.amadeus.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/azure_cognitive_services.py
View File

@ -13,7 +13,7 @@ if TYPE_CHECKING:
DEPRECATED_LOOKUP = {
"AzureCognitiveServicesToolkit": (
"langchain_community.agent_toolkits.azure_cognitive_services"
)
),
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/clickup/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"ClickupToolkit": "langchain_community.agent_toolkits.clickup.toolkit"
"ClickupToolkit": "langchain_community.agent_toolkits.clickup.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

6
libs/langchain/langchain/agents/agent_toolkits/conversational_retrieval/openai_functions.py
View File

@ -20,7 +20,7 @@ def _get_default_system_message() -> SystemMessage:
"Do your best to answer the questions. "
"Feel free to use any tools available to look up "
"relevant information, only if necessary"
)
),
)
@ -58,7 +58,9 @@ def create_conversational_retrieval_agent(
if remember_intermediate_steps:
memory: BaseMemory = AgentTokenBufferMemory(
memory_key=memory_key, llm=llm, max_token_limit=max_token_limit
memory_key=memory_key,
llm=llm,
max_token_limit=max_token_limit,
)
else:
memory = ConversationTokenBufferMemory(

2
libs/langchain/langchain/agents/agent_toolkits/file_management/__init__.py
View File

@ -15,7 +15,7 @@ if TYPE_CHECKING:
DEPRECATED_LOOKUP = {
"FileManagementToolkit": (
"langchain_community.agent_toolkits.file_management.toolkit"
)
),
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/file_management/toolkit.py
View File

@ -13,7 +13,7 @@ if TYPE_CHECKING:
DEPRECATED_LOOKUP = {
"FileManagementToolkit": (
"langchain_community.agent_toolkits.file_management.toolkit"
)
),
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/gitlab/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"GitLabToolkit": "langchain_community.agent_toolkits.gitlab.toolkit"
"GitLabToolkit": "langchain_community.agent_toolkits.gitlab.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/json/base.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"create_json_agent": "langchain_community.agent_toolkits.json.base"
"create_json_agent": "langchain_community.agent_toolkits.json.base",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/multion/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"MultionToolkit": "langchain_community.agent_toolkits.multion.toolkit"
"MultionToolkit": "langchain_community.agent_toolkits.multion.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/office365/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"O365Toolkit": "langchain_community.agent_toolkits.office365.toolkit"
"O365Toolkit": "langchain_community.agent_toolkits.office365.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/openapi/base.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"create_openapi_agent": "langchain_community.agent_toolkits.openapi.base"
"create_openapi_agent": "langchain_community.agent_toolkits.openapi.base",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/playwright/__init__.py
View File

@ -13,7 +13,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"PlayWrightBrowserToolkit": "langchain_community.agent_toolkits.playwright.toolkit"
"PlayWrightBrowserToolkit": "langchain_community.agent_toolkits.playwright.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/playwright/toolkit.py
View File

@ -11,7 +11,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"PlayWrightBrowserToolkit": "langchain_community.agent_toolkits.playwright.toolkit"
"PlayWrightBrowserToolkit": "langchain_community.agent_toolkits.playwright.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/powerbi/base.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"create_pbi_agent": "langchain_community.agent_toolkits.powerbi.base"
"create_pbi_agent": "langchain_community.agent_toolkits.powerbi.base",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/powerbi/chat_base.py
View File

@ -11,7 +11,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"create_pbi_chat_agent": "langchain_community.agent_toolkits.powerbi.chat_base"
"create_pbi_chat_agent": "langchain_community.agent_toolkits.powerbi.chat_base",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/powerbi/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"PowerBIToolkit": "langchain_community.agent_toolkits.powerbi.toolkit"
"PowerBIToolkit": "langchain_community.agent_toolkits.powerbi.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/spark_sql/base.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"create_spark_sql_agent": "langchain_community.agent_toolkits.spark_sql.base"
"create_spark_sql_agent": "langchain_community.agent_toolkits.spark_sql.base",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/spark_sql/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"SparkSQLToolkit": "langchain_community.agent_toolkits.spark_sql.toolkit"
"SparkSQLToolkit": "langchain_community.agent_toolkits.spark_sql.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/agents/agent_toolkits/sql/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"SQLDatabaseToolkit": "langchain_community.agent_toolkits.sql.toolkit"
"SQLDatabaseToolkit": "langchain_community.agent_toolkits.sql.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

6
libs/langchain/langchain/agents/agent_toolkits/vectorstore/prompt.py
View File

@ -1,13 +1,11 @@
# flake8: noqa
PREFIX = """You are an agent designed to answer questions about sets of documents.
You have access to tools for interacting with the documents, and the inputs to the tools are questions.
Sometimes, you will be asked to provide sources for your questions, in which case you should use the appropriate tool to do so.
If the question does not seem relevant to any of the tools provided, just return "I don't know" as the answer.
"""
""" # noqa: E501
ROUTER_PREFIX = """You are an agent designed to answer questions.
You have access to tools for interacting with different sources, and the inputs to the tools are questions.
Your main task is to decide which of the tools is relevant for answering question at hand.
For complex questions, you can break the question down into sub questions and use tools to answers the sub questions.
"""
""" # noqa: E501

9
libs/langchain/langchain/agents/agent_toolkits/vectorstore/toolkit.py
View File

@ -40,7 +40,8 @@ class VectorStoreToolkit(BaseToolkit):
msg = "You need to install langchain-community to use this toolkit."
raise ImportError(msg)
description = VectorStoreQATool.get_description(
self.vectorstore_info.name, self.vectorstore_info.description
self.vectorstore_info.name,
self.vectorstore_info.description,
)
qa_tool = VectorStoreQATool(
name=self.vectorstore_info.name,
@ -49,7 +50,8 @@ class VectorStoreToolkit(BaseToolkit):
llm=self.llm,
)
description = VectorStoreQAWithSourcesTool.get_description(
self.vectorstore_info.name, self.vectorstore_info.description
self.vectorstore_info.name,
self.vectorstore_info.description,
)
qa_with_sources_tool = VectorStoreQAWithSourcesTool(
name=f"{self.vectorstore_info.name}_with_sources",
@ -82,7 +84,8 @@ class VectorStoreRouterToolkit(BaseToolkit):
raise ImportError(msg)
for vectorstore_info in self.vectorstores:
description = VectorStoreQATool.get_description(
vectorstore_info.name, vectorstore_info.description
vectorstore_info.name,
vectorstore_info.description,
)
qa_tool = VectorStoreQATool(
name=vectorstore_info.name,

2
libs/langchain/langchain/agents/agent_toolkits/zapier/toolkit.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"ZapierToolkit": "langchain_community.agent_toolkits.zapier.toolkit"
"ZapierToolkit": "langchain_community.agent_toolkits.zapier.toolkit",
}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)

12
libs/langchain/langchain/agents/chat/base.py
View File

@ -49,7 +49,8 @@ class ChatAgent(Agent):
return "Thought:"
def _construct_scratchpad(
self, intermediate_steps: list[tuple[AgentAction, str]]
self,
intermediate_steps: list[tuple[AgentAction, str]],
) -> str:
agent_scratchpad = super()._construct_scratchpad(intermediate_steps)
if not isinstance(agent_scratchpad, str):
@ -106,14 +107,7 @@ class ChatAgent(Agent):
tool_strings = "\n".join([f"{tool.name}: {tool.description}" for tool in tools])
tool_names = ", ".join([tool.name for tool in tools])
format_instructions = format_instructions.format(tool_names=tool_names)
template = "\n\n".join(
[
system_message_prefix,
tool_strings,
format_instructions,
system_message_suffix,
]
)
template = f"{system_message_prefix}\n\n{tool_strings}\n\n{format_instructions}\n\n{system_message_suffix}" # noqa: E501
messages = [
SystemMessagePromptTemplate.from_template(template),
HumanMessagePromptTemplate.from_template(human_message),

4
libs/langchain/langchain/agents/chat/output_parser.py
View File

@ -57,7 +57,9 @@ class ChatOutputParser(AgentOutputParser):
)
raise OutputParserException(msg)
return AgentAction(
response["action"], response.get("action_input", {}), text
response["action"],
response.get("action_input", {}),
text,
)
except Exception as exc:

7
libs/langchain/langchain/agents/chat/prompt.py
View File

@ -1,5 +1,4 @@
# flake8: noqa
SYSTEM_MESSAGE_PREFIX = """Answer the following questions as best you can. You have access to the following tools:"""
SYSTEM_MESSAGE_PREFIX = """Answer the following questions as best you can. You have access to the following tools:""" # noqa: E501
FORMAT_INSTRUCTIONS = """The way you use the tools is by specifying a json blob.
Specifically, this json should have a `action` key (with the name of the tool to use) and a `action_input` key (with the input to the tool going here).
@ -25,6 +24,6 @@ $JSON_BLOB
Observation: the result of the action
... (this Thought/Action/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question"""
SYSTEM_MESSAGE_SUFFIX = """Begin! Reminder to always use the exact characters `Final Answer` when responding."""
Final Answer: the final answer to the original input question""" # noqa: E501
SYSTEM_MESSAGE_SUFFIX = """Begin! Reminder to always use the exact characters `Final Answer` when responding.""" # noqa: E501
HUMAN_MESSAGE = "{input}\n\n{agent_scratchpad}"

14
libs/langchain/langchain/agents/conversational/base.py
View File

@ -36,7 +36,9 @@ class ConversationalAgent(Agent):
@classmethod
def _get_default_output_parser(
cls, ai_prefix: str = "AI", **kwargs: Any
cls,
ai_prefix: str = "AI",
**kwargs: Any,
) -> AgentOutputParser:
return ConvoOutputParser(ai_prefix=ai_prefix)
@ -93,13 +95,15 @@ class ConversationalAgent(Agent):
A PromptTemplate with the template assembled from the pieces here.
"""
tool_strings = "\n".join(
[f"> {tool.name}: {tool.description}" for tool in tools]
[f"> {tool.name}: {tool.description}" for tool in tools],
)
tool_names = ", ".join([tool.name for tool in tools])
format_instructions = format_instructions.format(
tool_names=tool_names, ai_prefix=ai_prefix, human_prefix=human_prefix
tool_names=tool_names,
ai_prefix=ai_prefix,
human_prefix=human_prefix,
)
template = "\n\n".join([prefix, tool_strings, format_instructions, suffix])
template = f"{prefix}\n\n{tool_strings}\n\n{format_instructions}\n\n{suffix}"
if input_variables is None:
input_variables = ["input", "chat_history", "agent_scratchpad"]
return PromptTemplate(template=template, input_variables=input_variables)
@ -161,7 +165,7 @@ class ConversationalAgent(Agent):
)
tool_names = [tool.name for tool in tools]
_output_parser = output_parser or cls._get_default_output_parser(
ai_prefix=ai_prefix
ai_prefix=ai_prefix,
)
return cls(
llm_chain=llm_chain,

3
libs/langchain/langchain/agents/conversational/output_parser.py
View File

@ -34,7 +34,8 @@ class ConvoOutputParser(AgentOutputParser):
if f"{self.ai_prefix}:" in text:
return AgentFinish(
{"output": text.split(f"{self.ai_prefix}:")[-1].strip()}, text
{"output": text.split(f"{self.ai_prefix}:")[-1].strip()},
text,
)
regex = r"Action: (.*?)[\n]*Action Input: ([\s\S]*)"
match = re.search(regex, text, re.DOTALL)

5
libs/langchain/langchain/agents/conversational/prompt.py
View File

@ -1,4 +1,3 @@
# flake8: noqa
PREFIX = """Assistant is a large language model trained by OpenAI.
Assistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.
@ -10,7 +9,7 @@ Overall, Assistant is a powerful tool that can help with a wide range of tasks a
TOOLS:
------
Assistant has access to the following tools:"""
Assistant has access to the following tools:""" # noqa: E501
FORMAT_INSTRUCTIONS = """To use a tool, please use the following format:
```
@ -25,7 +24,7 @@ When you have a response to say to the Human, or if you do not need to use a too
```
Thought: Do I need to use a tool? No
{ai_prefix}: [your response here]
```"""
```""" # noqa: E501
SUFFIX = """Begin!

12
libs/langchain/langchain/agents/conversational_chat/base.py
View File

@ -96,15 +96,16 @@ class ConversationalChatAgent(Agent):
A PromptTemplate.
"""
tool_strings = "\n".join(
[f"> {tool.name}: {tool.description}" for tool in tools]
[f"> {tool.name}: {tool.description}" for tool in tools],
)
tool_names = ", ".join([tool.name for tool in tools])
_output_parser = output_parser or cls._get_default_output_parser()
format_instructions = human_message.format(
format_instructions=_output_parser.get_format_instructions()
format_instructions=_output_parser.get_format_instructions(),
)
final_prompt = format_instructions.format(
tool_names=tool_names, tools=tool_strings
tool_names=tool_names,
tools=tool_strings,
)
if input_variables is None:
input_variables = ["input", "chat_history", "agent_scratchpad"]
@ -117,14 +118,15 @@ class ConversationalChatAgent(Agent):
return ChatPromptTemplate(input_variables=input_variables, messages=messages)
def _construct_scratchpad(
self, intermediate_steps: list[tuple[AgentAction, str]]
self,
intermediate_steps: list[tuple[AgentAction, str]],
) -> list[BaseMessage]:
"""Construct the scratchpad that lets the agent continue its thought process."""
thoughts: list[BaseMessage] = []
for action, observation in intermediate_steps:
thoughts.append(AIMessage(content=action.log))
human_message = HumanMessage(
content=self.template_tool_response.format(observation=observation)
content=self.template_tool_response.format(observation=observation),
)
thoughts.append(human_message)
return thoughts

11
libs/langchain/langchain/agents/conversational_chat/prompt.py
View File

@ -1,11 +1,10 @@
# flake8: noqa
PREFIX = """Assistant is a large language model trained by OpenAI.
Assistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.
Assistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based on the input it receives, allowing it to engage in discussions and provide explanations and descriptions on a wide range of topics.
Overall, Assistant is a powerful system that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist."""
Overall, Assistant is a powerful system that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist.""" # noqa: E501
FORMAT_INSTRUCTIONS = """RESPONSE FORMAT INSTRUCTIONS
----------------------------
@ -31,7 +30,7 @@ Use this if you want to respond directly to the human. Markdown code snippet for
"action": "Final Answer",
"action_input": string \\\\ You should put what you want to return to use here
}}}}
```"""
```""" # noqa: E501
SUFFIX = """TOOLS
------
@ -45,13 +44,13 @@ USER'S INPUT
--------------------
Here is the user's input (remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else):
{{{{input}}}}"""
{{{{input}}}}""" # noqa: E501
TEMPLATE_TOOL_RESPONSE = """TOOL RESPONSE:
TEMPLATE_TOOL_RESPONSE = """TOOL RESPONSE:
---------------------
{observation}
USER'S INPUT
--------------------
Okay, so what is the response to my last comment? If using information obtained from the tools you must mention it explicitly without mentioning the tool names - I have forgotten all TOOL RESPONSES! Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else."""
Okay, so what is the response to my last comment? If using information obtained from the tools you must mention it explicitly without mentioning the tool names - I have forgotten all TOOL RESPONSES! Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else.""" # noqa: E501

2
libs/langchain/langchain/agents/format_scratchpad/log_to_messages.py
View File

@ -20,7 +20,7 @@ def format_log_to_messages(
for action, observation in intermediate_steps:
thoughts.append(AIMessage(content=action.log))
human_message = HumanMessage(
content=template_tool_response.format(observation=observation)
content=template_tool_response.format(observation=observation),
)
thoughts.append(human_message)
return thoughts

6
libs/langchain/langchain/agents/format_scratchpad/openai_functions.py
View File

@ -6,7 +6,8 @@ from langchain_core.messages import AIMessage, BaseMessage, FunctionMessage
def _convert_agent_action_to_messages(
agent_action: AgentAction, observation: str
agent_action: AgentAction,
observation: str,
) -> list[BaseMessage]:
"""Convert an agent action to a message.
@ -28,7 +29,8 @@ def _convert_agent_action_to_messages(
def _create_function_message(
agent_action: AgentAction, observation: str
agent_action: AgentAction,
observation: str,
) -> FunctionMessage:
"""Convert agent action and observation into a function message.
Args:

3
libs/langchain/langchain/agents/format_scratchpad/tools.py
View File

@ -12,7 +12,8 @@ from langchain.agents.output_parsers.tools import ToolAgentAction
def _create_tool_message(
agent_action: ToolAgentAction, observation: str
agent_action: ToolAgentAction,
observation: str,
) -> ToolMessage:
"""Convert agent action and observation into a tool message.

10
libs/langchain/langchain/agents/initialize.py
View File

@ -76,11 +76,17 @@ def initialize_agent(
agent_cls = AGENT_TO_CLASS[agent]
agent_kwargs = agent_kwargs or {}
agent_obj = agent_cls.from_llm_and_tools(
llm, tools, callback_manager=callback_manager, **agent_kwargs
llm,
tools,
callback_manager=callback_manager,
**agent_kwargs,
)
elif agent_path is not None:
agent_obj = load_agent(
agent_path, llm=llm, tools=tools, callback_manager=callback_manager
agent_path,
llm=llm,
tools=tools,
callback_manager=callback_manager,
)
with contextlib.suppress(NotImplementedError):
# TODO: Add tags from the serialized object directly.

7
libs/langchain/langchain/agents/json_chat/base.py
View File

@ -162,7 +162,7 @@ def create_json_chat_agent(
)
""" # noqa: E501
missing_vars = {"tools", "tool_names", "agent_scratchpad"}.difference(
prompt.input_variables + list(prompt.partial_variables)
prompt.input_variables + list(prompt.partial_variables),
)
if missing_vars:
msg = f"Prompt missing required variables: {missing_vars}"
@ -185,8 +185,9 @@ def create_json_chat_agent(
return (
RunnablePassthrough.assign(
agent_scratchpad=lambda x: format_log_to_messages(
x["intermediate_steps"], template_tool_response=template_tool_response
)
x["intermediate_steps"],
template_tool_response=template_tool_response,
),
)
| prompt
| llm_to_use

5
libs/langchain/langchain/agents/json_chat/prompt.py
View File

@ -1,9 +1,8 @@
# flake8: noqa
TEMPLATE_TOOL_RESPONSE = """TOOL RESPONSE:
TEMPLATE_TOOL_RESPONSE = """TOOL RESPONSE:
---------------------
{observation}
USER'S INPUT
--------------------
Okay, so what is the response to my last comment? If using information obtained from the tools you must mention it explicitly without mentioning the tool names - I have forgotten all TOOL RESPONSES! Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else - even if you just want to respond to the user. Do NOT respond with anything except a JSON snippet no matter what!"""
Okay, so what is the response to my last comment? If using information obtained from the tools you must mention it explicitly without mentioning the tool names - I have forgotten all TOOL RESPONSES! Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else - even if you just want to respond to the user. Do NOT respond with anything except a JSON snippet no matter what!""" # noqa: E501

3
libs/langchain/langchain/agents/load_tools.py
View File

@ -3,7 +3,8 @@ from typing import Any
from langchain._api import create_importer
_importer = create_importer(
__package__, fallback_module="langchain_community.agent_toolkits.load_tools"
__package__,
fallback_module="langchain_community.agent_toolkits.load_tools",
)

13
libs/langchain/langchain/agents/loading.py
View File

@ -20,7 +20,10 @@ URL_BASE = "https://raw.githubusercontent.com/hwchase17/langchain-hub/master/age
def _load_agent_from_tools(
config: dict, llm: BaseLanguageModel, tools: list[Tool], **kwargs: Any
config: dict,
llm: BaseLanguageModel,
tools: list[Tool],
**kwargs: Any,
) -> Union[BaseSingleActionAgent, BaseMultiActionAgent]:
config_type = config.pop("_type")
if config_type not in AGENT_TO_CLASS:
@ -87,7 +90,7 @@ def load_agent_from_config(
if "output_parser" in config:
logger.warning(
"Currently loading output parsers on agent is not supported, "
"will just use the default one."
"will just use the default one.",
)
del config["output_parser"]
@ -97,7 +100,8 @@ def load_agent_from_config(
@deprecated("0.1.0", removal="1.0")
def load_agent(
path: Union[str, Path], **kwargs: Any
path: Union[str, Path],
**kwargs: Any,
) -> Union[BaseSingleActionAgent, BaseMultiActionAgent]:
"""Unified method for loading an agent from LangChainHub or local fs.
@ -123,7 +127,8 @@ def load_agent(
def _load_agent_from_file(
file: Union[str, Path], **kwargs: Any
file: Union[str, Path],
**kwargs: Any,
) -> Union[BaseSingleActionAgent, BaseMultiActionAgent]:
"""Load agent from file."""
valid_suffixes = {"json", "yaml"}

7
libs/langchain/langchain/agents/mrkl/base.py
View File

@ -104,7 +104,7 @@ class ZeroShotAgent(Agent):
tool_strings = render_text_description(list(tools))
tool_names = ", ".join([tool.name for tool in tools])
format_instructions = format_instructions.format(tool_names=tool_names)
template = "\n\n".join([prefix, tool_strings, format_instructions, suffix])
template = f"{prefix}\n\n{tool_strings}\n\n{format_instructions}\n\n{suffix}"
if input_variables:
return PromptTemplate(template=template, input_variables=input_variables)
return PromptTemplate.from_template(template)
@ -186,7 +186,10 @@ class MRKLChain(AgentExecutor):
@classmethod
def from_chains(
cls, llm: BaseLanguageModel, chains: list[ChainConfig], **kwargs: Any
cls,
llm: BaseLanguageModel,
chains: list[ChainConfig],
**kwargs: Any,
) -> AgentExecutor:
"""User-friendly way to initialize the MRKL chain.

10
libs/langchain/langchain/agents/mrkl/output_parser.py
View File

@ -53,7 +53,8 @@ class MRKLOutputParser(AgentOutputParser):
start_index = text.find(FINAL_ANSWER_ACTION) + len(FINAL_ANSWER_ACTION)
end_index = text.find("\n\n", start_index)
return AgentFinish(
{"output": text[start_index:end_index].strip()}, text[:end_index]
{"output": text[start_index:end_index].strip()},
text[:end_index],
)
msg = f"{FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE}: {text}"
raise OutputParserException(msg)
@ -70,7 +71,8 @@ class MRKLOutputParser(AgentOutputParser):
if includes_answer:
return AgentFinish(
{"output": text.split(FINAL_ANSWER_ACTION)[-1].strip()}, text
{"output": text.split(FINAL_ANSWER_ACTION)[-1].strip()},
text,
)
if not re.search(r"Action\s*\d*\s*:[\s]*(.*?)", text, re.DOTALL):
@ -82,7 +84,9 @@ class MRKLOutputParser(AgentOutputParser):
send_to_llm=True,
)
if not re.search(
r"[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)", text, re.DOTALL
r"[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)",
text,
re.DOTALL,
):
msg = f"Could not parse LLM output: `{text}`"
raise OutputParserException(

3
libs/langchain/langchain/agents/mrkl/prompt.py
View File

@ -1,5 +1,4 @@
# flake8: noqa
PREFIX = """Answer the following questions as best you can. You have access to the following tools:"""
PREFIX = """Answer the following questions as best you can. You have access to the following tools:""" # noqa: E501
FORMAT_INSTRUCTIONS = """Use the following format:
Question: the input question you must answer

49
libs/langchain/langchain/agents/openai_assistant/base.py
View File

@ -273,7 +273,10 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
@override
def invoke(
self, input: dict, config: Optional[RunnableConfig] = None, **kwargs: Any
self,
input: dict,
config: Optional[RunnableConfig] = None,
**kwargs: Any,
) -> OutputType:
"""Invoke assistant.
@ -314,13 +317,15 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
inheritable_metadata=config.get("metadata"),
)
run_manager = callback_manager.on_chain_start(
dumpd(self), input, name=config.get("run_name") or self.get_name()
dumpd(self),
input,
name=config.get("run_name") or self.get_name(),
)
try:
# Being run within AgentExecutor and there are tool outputs to submit.
if self.as_agent and input.get("intermediate_steps"):
tool_outputs = self._parse_intermediate_steps(
input["intermediate_steps"]
input["intermediate_steps"],
)
run = self.client.beta.threads.runs.submit_tool_outputs(**tool_outputs)
# Starting a new thread and a new run.
@ -332,7 +337,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
"content": input["content"],
"metadata": input.get("message_metadata"),
"attachments": input.get("attachments"),
}
},
],
"metadata": input.get("thread_metadata"),
}
@ -401,7 +406,10 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
@override
async def ainvoke(
self, input: dict, config: Optional[RunnableConfig] = None, **kwargs: Any
self,
input: dict,
config: Optional[RunnableConfig] = None,
**kwargs: Any,
) -> OutputType:
"""Async invoke assistant.
@ -442,16 +450,18 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
inheritable_metadata=config.get("metadata"),
)
run_manager = callback_manager.on_chain_start(
dumpd(self), input, name=config.get("run_name") or self.get_name()
dumpd(self),
input,
name=config.get("run_name") or self.get_name(),
)
try:
# Being run within AgentExecutor and there are tool outputs to submit.
if self.as_agent and input.get("intermediate_steps"):
tool_outputs = await self._aparse_intermediate_steps(
input["intermediate_steps"]
input["intermediate_steps"],
)
run = await self.async_client.beta.threads.runs.submit_tool_outputs(
**tool_outputs
**tool_outputs,
)
# Starting a new thread and a new run.
elif "thread_id" not in input:
@ -461,7 +471,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
"role": "user",
"content": input["content"],
"metadata": input.get("message_metadata"),
}
},
],
"metadata": input.get("thread_metadata"),
}
@ -479,7 +489,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
# framework.
else:
run = await self.async_client.beta.threads.runs.submit_tool_outputs(
**input
**input,
)
run = await self._await_for_run(run.id, run.thread_id)
except BaseException as e:
@ -495,7 +505,8 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
return response
def _parse_intermediate_steps(
self, intermediate_steps: list[tuple[OpenAIAssistantAction, str]]
self,
intermediate_steps: list[tuple[OpenAIAssistantAction, str]],
) -> dict:
last_action, last_output = intermediate_steps[-1]
run = self._wait_for_run(last_action.run_id, last_action.thread_id)
@ -575,7 +586,8 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
)
messages = self.client.beta.threads.messages.list(
run.thread_id, order="asc"
run.thread_id,
order="asc",
)
new_messages = [msg for msg in messages if msg.run_id == run.id]
if not self.as_agent:
@ -633,7 +645,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
log="",
run_id=run.id,
thread_id=run.thread_id,
)
),
)
return actions
run_info = json.dumps(run.dict(), indent=2)
@ -650,7 +662,8 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
return run
async def _aparse_intermediate_steps(
self, intermediate_steps: list[tuple[OpenAIAssistantAction, str]]
self,
intermediate_steps: list[tuple[OpenAIAssistantAction, str]],
) -> dict:
last_action, last_output = intermediate_steps[-1]
run = self._wait_for_run(last_action.run_id, last_action.thread_id)
@ -730,7 +743,8 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
)
messages = await self.async_client.beta.threads.messages.list(
run.thread_id, order="asc"
run.thread_id,
order="asc",
)
new_messages = [msg for msg in messages if msg.run_id == run.id]
if not self.as_agent:
@ -784,7 +798,7 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
log="",
run_id=run.id,
thread_id=run.thread_id,
)
),
)
return actions
run_info = json.dumps(run.dict(), indent=2)
@ -795,7 +809,8 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
in_progress = True
while in_progress:
run = await self.async_client.beta.threads.runs.retrieve(
run_id, thread_id=thread_id
run_id,
thread_id=thread_id,
)
in_progress = run.status in ("in_progress", "queued")
if in_progress:

25
libs/langchain/langchain/agents/openai_functions_agent/base.py
View File

@ -161,7 +161,9 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
prompt = self.prompt.format_prompt(**full_inputs)
messages = prompt.to_messages()
predicted_message = await self.llm.apredict_messages(
messages, functions=self.functions, callbacks=callbacks
messages,
functions=self.functions,
callbacks=callbacks,
)
return self.output_parser._parse_ai_message(predicted_message)
@ -188,12 +190,15 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
if early_stopping_method == "force":
# `force` just returns a constant string
return AgentFinish(
{"output": "Agent stopped due to iteration limit or time limit."}, ""
{"output": "Agent stopped due to iteration limit or time limit."},
"",
)
if early_stopping_method == "generate":
# Generate does one final forward pass
agent_decision = self.plan(
intermediate_steps, with_functions=False, **kwargs
intermediate_steps,
with_functions=False,
**kwargs,
)
if isinstance(agent_decision, AgentFinish):
return agent_decision
@ -209,7 +214,7 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
def create_prompt(
cls,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
content="You are a helpful AI assistant.",
),
extra_prompt_messages: Optional[list[BaseMessagePromptTemplate]] = None,
) -> ChatPromptTemplate:
@ -233,7 +238,7 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
*_prompts,
HumanMessagePromptTemplate.from_template("{input}"),
MessagesPlaceholder(variable_name="agent_scratchpad"),
]
],
)
return ChatPromptTemplate(messages=messages)
@ -245,7 +250,7 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
callback_manager: Optional[BaseCallbackManager] = None,
extra_prompt_messages: Optional[list[BaseMessagePromptTemplate]] = None,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
content="You are a helpful AI assistant.",
),
**kwargs: Any,
) -> BaseSingleActionAgent:
@ -274,7 +279,9 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
def create_openai_functions_agent(
llm: BaseLanguageModel, tools: Sequence[BaseTool], prompt: ChatPromptTemplate
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
prompt: ChatPromptTemplate,
) -> Runnable:
"""Create an agent that uses OpenAI function calling.
@ -357,8 +364,8 @@ def create_openai_functions_agent(
return (
RunnablePassthrough.assign(
agent_scratchpad=lambda x: format_to_openai_function_messages(
x["intermediate_steps"]
)
x["intermediate_steps"],
),
)
| prompt
| llm_with_tools

19
libs/langchain/langchain/agents/openai_functions_multi_agent/base.py
View File

@ -95,7 +95,8 @@ def _parse_ai_message(message: BaseMessage) -> Union[list[AgentAction], AgentFin
return final_tools
return AgentFinish(
return_values={"output": message.content}, log=str(message.content)
return_values={"output": message.content},
log=str(message.content),
)
@ -190,7 +191,7 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
},
"required": ["action_name", "action"],
},
}
},
},
"required": ["actions"],
},
@ -222,7 +223,9 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
prompt = self.prompt.format_prompt(**full_inputs)
messages = prompt.to_messages()
predicted_message = self.llm.predict_messages(
messages, functions=self.functions, callbacks=callbacks
messages,
functions=self.functions,
callbacks=callbacks,
)
return _parse_ai_message(predicted_message)
@ -251,7 +254,9 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
prompt = self.prompt.format_prompt(**full_inputs)
messages = prompt.to_messages()
predicted_message = await self.llm.apredict_messages(
messages, functions=self.functions, callbacks=callbacks
messages,
functions=self.functions,
callbacks=callbacks,
)
return _parse_ai_message(predicted_message)
@ -259,7 +264,7 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
def create_prompt(
cls,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
content="You are a helpful AI assistant.",
),
extra_prompt_messages: Optional[list[BaseMessagePromptTemplate]] = None,
) -> BasePromptTemplate:
@ -283,7 +288,7 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
*_prompts,
HumanMessagePromptTemplate.from_template("{input}"),
MessagesPlaceholder(variable_name="agent_scratchpad"),
]
],
)
return ChatPromptTemplate(messages=messages)
@ -295,7 +300,7 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
callback_manager: Optional[BaseCallbackManager] = None,
extra_prompt_messages: Optional[list[BaseMessagePromptTemplate]] = None,
system_message: Optional[SystemMessage] = SystemMessage(
content="You are a helpful AI assistant."
content="You are a helpful AI assistant.",
),
**kwargs: Any,
) -> BaseMultiActionAgent:

8
libs/langchain/langchain/agents/openai_tools/base.py
View File

@ -86,21 +86,21 @@ def create_openai_tools_agent(
)
"""
missing_vars = {"agent_scratchpad"}.difference(
prompt.input_variables + list(prompt.partial_variables)
prompt.input_variables + list(prompt.partial_variables),
)
if missing_vars:
msg = f"Prompt missing required variables: {missing_vars}"
raise ValueError(msg)
llm_with_tools = llm.bind(
tools=[convert_to_openai_tool(tool, strict=strict) for tool in tools]
tools=[convert_to_openai_tool(tool, strict=strict) for tool in tools],
)
return (
RunnablePassthrough.assign(
agent_scratchpad=lambda x: format_to_openai_tool_messages(
x["intermediate_steps"]
)
x["intermediate_steps"],
),
)
| prompt
| llm_with_tools

8
libs/langchain/langchain/agents/output_parsers/openai_functions.py
View File

@ -75,11 +75,15 @@ class OpenAIFunctionsAgentOutputParser(AgentOutputParser):
)
return AgentFinish(
return_values={"output": message.content}, log=str(message.content)
return_values={"output": message.content},
log=str(message.content),
)
def parse_result(
self, result: list[Generation], *, partial: bool = False
self,
result: list[Generation],
*,
partial: bool = False,
) -> Union[AgentAction, AgentFinish]:
if not isinstance(result[0], ChatGeneration):
msg = "This output parser only works on ChatGeneration output"

7
libs/langchain/langchain/agents/output_parsers/openai_tools.py
View File

@ -30,7 +30,7 @@ def parse_ai_message_to_openai_tool_action(
log=action.log,
message_log=action.message_log,
tool_call_id=action.tool_call_id,
)
),
)
else:
final_actions.append(action)
@ -54,7 +54,10 @@ class OpenAIToolsAgentOutputParser(MultiActionAgentOutputParser):
return "openai-tools-agent-output-parser"
def parse_result(
self, result: list[Generation], *, partial: bool = False
self,
result: list[Generation],
*,
partial: bool = False,
) -> Union[list[AgentAction], AgentFinish]:
if not isinstance(result[0], ChatGeneration):
msg = "This output parser only works on ChatGeneration output"

4
libs/langchain/langchain/agents/output_parsers/react_json_single_input.py
View File

@ -67,7 +67,9 @@ class ReActJsonSingleInputOutputParser(AgentOutputParser):
)
raise OutputParserException(msg)
return AgentAction(
response["action"], response.get("action_input", {}), text
response["action"],
response.get("action_input", {}),
text,
)
except Exception:

7
libs/langchain/langchain/agents/output_parsers/react_single_input.py
View File

@ -67,7 +67,8 @@ class ReActSingleInputOutputParser(AgentOutputParser):
if includes_answer:
return AgentFinish(
{"output": text.split(FINAL_ANSWER_ACTION)[-1].strip()}, text
{"output": text.split(FINAL_ANSWER_ACTION)[-1].strip()},
text,
)
if not re.search(r"Action\s*\d*\s*:[\s]*(.*?)", text, re.DOTALL):
@ -79,7 +80,9 @@ class ReActSingleInputOutputParser(AgentOutputParser):
send_to_llm=True,
)
if not re.search(
r"[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)", text, re.DOTALL
r"[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)",
text,
re.DOTALL,
):
msg = f"Could not parse LLM output: `{text}`"
raise OutputParserException(

12
libs/langchain/langchain/agents/output_parsers/tools.py
View File

@ -33,7 +33,8 @@ def parse_ai_message_to_tool_action(
else:
if not message.additional_kwargs.get("tool_calls"):
return AgentFinish(
return_values={"output": message.content}, log=str(message.content)
return_values={"output": message.content},
log=str(message.content),
)
# Best-effort parsing
tool_calls = []
@ -43,7 +44,7 @@ def parse_ai_message_to_tool_action(
try:
args = json.loads(function["arguments"] or "{}")
tool_calls.append(
ToolCall(name=function_name, args=args, id=tool_call["id"])
ToolCall(name=function_name, args=args, id=tool_call["id"]),
)
except JSONDecodeError:
msg = (
@ -71,7 +72,7 @@ def parse_ai_message_to_tool_action(
log=log,
message_log=[message],
tool_call_id=tool_call["id"],
)
),
)
return actions
@ -90,7 +91,10 @@ class ToolsAgentOutputParser(MultiActionAgentOutputParser):
return "tools-agent-output-parser"
def parse_result(
self, result: list[Generation], *, partial: bool = False
self,
result: list[Generation],
*,
partial: bool = False,
) -> Union[list[AgentAction], AgentFinish]:
if not isinstance(result[0], ChatGeneration):
msg = "This output parser only works on ChatGeneration output"

2
libs/langchain/langchain/agents/react/agent.py
View File

@ -118,7 +118,7 @@ def create_react_agent(
prompt = PromptTemplate.from_template(template)
""" # noqa: E501
missing_vars = {"tools", "tool_names", "agent_scratchpad"}.difference(
prompt.input_variables + list(prompt.partial_variables)
prompt.input_variables + list(prompt.partial_variables),
)
if missing_vars:
msg = f"Prompt missing required variables: {missing_vars}"

1
libs/langchain/langchain/agents/react/textworld_prompt.py
View File

@ -1,4 +1,3 @@
# flake8: noqa
from langchain_core.prompts.prompt import PromptTemplate
EXAMPLES = [

29
libs/langchain/langchain/agents/react/wiki_prompt.py
View File

@ -1,4 +1,3 @@
# flake8: noqa
from langchain_core.prompts.prompt import PromptTemplate
EXAMPLES = [
@ -16,7 +15,7 @@ Thought: I need to instead search High Plains (United States).
Action: Search[High Plains (United States)]
Observation: The High Plains are a subregion of the Great Plains. From east to west, the High Plains rise in elevation from around 1,800 to 7,000 ft (550 to 2,130 m).[3]
Thought: High Plains rise in elevation from around 1,800 to 7,000 ft, so the answer is 1,800 to 7,000 ft.
Action: Finish[1,800 to 7,000 ft]""",
Action: Finish[1,800 to 7,000 ft]""", # noqa: E501
"""Question: Musician and satirist Allie Goertz wrote a song about the "The Simpsons" character Milhouse, who Matt Groening named after who?
Thought: The question simplifies to "The Simpsons" character Milhouse is named after who. I only need to search Milhouse and find who it is named after.
Action: Search[Milhouse]
@ -25,16 +24,16 @@ Thought: The paragraph does not tell who Milhouse is named after, maybe I can lo
Action: Lookup[named after]
Observation: (Result 1 / 1) Milhouse was named after U.S. president Richard Nixon, whose middle name was Milhous.
Thought: Milhouse was named after U.S. president Richard Nixon, so the answer is Richard Nixon.
Action: Finish[Richard Nixon]""",
Action: Finish[Richard Nixon]""", # noqa: E501
"""Question: Which documentary is about Finnish rock groups, Adam Clayton Powell or The Saimaa Gesture?
Thought: I need to search Adam Clayton Powell and The Saimaa Gesture, and find which documentary is about Finnish rock groups.
Action: Search[Adam Clayton Powell]
Observation: Could not find [Adam Clayton Powell]. Similar: [’Adam Clayton Powell III’, ’Seventh Avenue (Manhattan)’, ’Adam Clayton Powell Jr. State Office Building’, ’Isabel Washington Powell’, ’Adam Powell’, ’Adam Clayton Powell (film)’, ’Giancarlo Esposito’].
Observation: Could not find [Adam Clayton Powell]. Similar: ['Adam Clayton Powell III', 'Seventh Avenue (Manhattan)', 'Adam Clayton Powell Jr. State Office Building', 'Isabel Washington Powell', 'Adam Powell', 'Adam Clayton Powell (film)', 'Giancarlo Esposito'].
Thought: To find the documentary, I can search Adam Clayton Powell (film).
Action: Search[Adam Clayton Powell (film)]
Observation: Adam Clayton Powell is a 1989 American documentary film directed by Richard Kilberg. The film is about the rise and fall of influential African-American politician Adam Clayton Powell Jr.[3][4] It was later aired as part of the PBS series The American Experience.
Thought: Adam Clayton Powell (film) is a documentary about an African-American politician, not Finnish rock groups. So the documentary about Finnish rock groups must instead be The Saimaa Gesture.
Action: Finish[The Saimaa Gesture]""",
Action: Finish[The Saimaa Gesture]""", # noqa: E501
"""Question: What profession does Nicholas Ray and Elia Kazan have in common?
Thought: I need to search Nicholas Ray and Elia Kazan, find their professions, then find the profession they have in common.
Action: Search[Nicholas Ray]
@ -43,16 +42,16 @@ Thought: Professions of Nicholas Ray are director, screenwriter, and actor. I ne
Action: Search[Elia Kazan]
Observation: Elia Kazan was an American film and theatre director, producer, screenwriter and actor.
Thought: Professions of Elia Kazan are director, producer, screenwriter, and actor. So profession Nicholas Ray and Elia Kazan have in common is director, screenwriter, and actor.
Action: Finish[director, screenwriter, actor]""",
"""Question: Which magazine was started first Arthur’s Magazine or First for Women?
Thought: I need to search Arthur’s Magazine and First for Women, and find which was started first.
Action: Search[Arthur’s Magazine]
Observation: Arthur’s Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.
Thought: Arthur’s Magazine was started in 1844. I need to search First for Women next.
Action: Finish[director, screenwriter, actor]""", # noqa: E501
"""Question: Which magazine was started first Arthur's Magazine or First for Women?
Thought: I need to search Arthur's Magazine and First for Women, and find which was started first.
Action: Search[Arthur's Magazine]
Observation: Arthur's Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.
Thought: Arthur's Magazine was started in 1844. I need to search First for Women next.
Action: Search[First for Women]
Observation: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.
Thought: First for Women was started in 1989. 1844 (Arthur’s Magazine) < 1989 (First for Women), so Arthur’s Magazine was started first.
Action: Finish[Arthur’s Magazine]""",
Observation: First for Women is a woman's magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.
Thought: First for Women was started in 1989. 1844 (Arthur's Magazine) < 1989 (First for Women), so Arthur's Magazine was started first.
Action: Finish[Arthur's Magazine]""", # noqa: E501
"""Question: Were Pavel Urysohn and Leonid Levin known for the same type of work?
Thought: I need to search Pavel Urysohn and Leonid Levin, find their types of work, then find if they are the same.
Action: Search[Pavel Urysohn]
@ -61,7 +60,7 @@ Thought: Pavel Urysohn is a mathematician. I need to search Leonid Levin next an
Action: Search[Leonid Levin]
Observation: Leonid Anatolievich Levin is a Soviet-American mathematician and computer scientist.
Thought: Leonid Levin is a mathematician and computer scientist. So Pavel Urysohn and Leonid Levin have the same type of work.
Action: Finish[yes]""",
Action: Finish[yes]""", # noqa: E501
]
SUFFIX = """\nQuestion: {input}
{agent_scratchpad}"""

5
libs/langchain/langchain/agents/schema.py
View File

@ -12,7 +12,8 @@ class AgentScratchPadChatPromptTemplate(ChatPromptTemplate):
return False
def _construct_agent_scratchpad(
self, intermediate_steps: list[tuple[AgentAction, str]]
self,
intermediate_steps: list[tuple[AgentAction, str]],
) -> str:
if len(intermediate_steps) == 0:
return ""
@ -29,6 +30,6 @@ class AgentScratchPadChatPromptTemplate(ChatPromptTemplate):
def _merge_partial_and_user_variables(self, **kwargs: Any) -> dict[str, Any]:
intermediate_steps = kwargs.pop("intermediate_steps")
kwargs["agent_scratchpad"] = self._construct_agent_scratchpad(
intermediate_steps
intermediate_steps,
)
return kwargs

10
libs/langchain/langchain/agents/self_ask_with_search/base.py
View File

@ -76,7 +76,9 @@ class SelfAskWithSearchChain(AgentExecutor):
self,
llm: BaseLanguageModel,
search_chain: Union[
GoogleSerperAPIWrapper, SearchApiAPIWrapper, SerpAPIWrapper
GoogleSerperAPIWrapper,
SearchApiAPIWrapper,
SerpAPIWrapper,
],
**kwargs: Any,
):
@ -92,7 +94,9 @@ class SelfAskWithSearchChain(AgentExecutor):
def create_self_ask_with_search_agent(
llm: BaseLanguageModel, tools: Sequence[BaseTool], prompt: BasePromptTemplate
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
prompt: BasePromptTemplate,
) -> Runnable:
"""Create an agent that uses self-ask with search prompting.
@ -180,7 +184,7 @@ def create_self_ask_with_search_agent(
prompt = PromptTemplate.from_template(template)
""" # noqa: E501
missing_vars = {"agent_scratchpad"}.difference(
prompt.input_variables + list(prompt.partial_variables)
prompt.input_variables + list(prompt.partial_variables),
)
if missing_vars:
msg = f"Prompt missing required variables: {missing_vars}"

1
libs/langchain/langchain/agents/self_ask_with_search/prompt.py
View File

@ -1,4 +1,3 @@
# flake8: noqa
from langchain_core.prompts.prompt import PromptTemplate
_DEFAULT_TEMPLATE = """Question: Who lived longer, Muhammad Ali or Alan Turing?

13
libs/langchain/langchain/agents/structured_chat/base.py
View File

@ -35,7 +35,7 @@ class StructuredChatAgent(Agent):
"""Structured Chat Agent."""
output_parser: AgentOutputParser = Field(
default_factory=StructuredChatOutputParserWithRetries
default_factory=StructuredChatOutputParserWithRetries,
)
"""Output parser for the agent."""
@ -50,7 +50,8 @@ class StructuredChatAgent(Agent):
return "Thought:"
def _construct_scratchpad(
self, intermediate_steps: list[tuple[AgentAction, str]]
self,
intermediate_steps: list[tuple[AgentAction, str]],
) -> str:
agent_scratchpad = super()._construct_scratchpad(intermediate_steps)
if not isinstance(agent_scratchpad, str):
@ -70,7 +71,9 @@ class StructuredChatAgent(Agent):
@classmethod
def _get_default_output_parser(
cls, llm: Optional[BaseLanguageModel] = None, **kwargs: Any
cls,
llm: Optional[BaseLanguageModel] = None,
**kwargs: Any,
) -> AgentOutputParser:
return StructuredChatOutputParserWithRetries.from_llm(llm=llm)
@ -96,7 +99,7 @@ class StructuredChatAgent(Agent):
formatted_tools = "\n".join(tool_strings)
tool_names = ", ".join([tool.name for tool in tools])
format_instructions = format_instructions.format(tool_names=tool_names)
template = "\n\n".join([prefix, formatted_tools, format_instructions, suffix])
template = f"{prefix}\n\n{formatted_tools}\n\n{format_instructions}\n\n{suffix}"
if input_variables is None:
input_variables = ["input", "agent_scratchpad"]
_memory_prompts = memory_prompts or []
@ -275,7 +278,7 @@ def create_structured_chat_agent(
)
""" # noqa: E501
missing_vars = {"tools", "tool_names", "agent_scratchpad"}.difference(
prompt.input_variables + list(prompt.partial_variables)
prompt.input_variables + list(prompt.partial_variables),
)
if missing_vars:
msg = f"Prompt missing required variables: {missing_vars}"

7
libs/langchain/langchain/agents/structured_chat/output_parser.py
View File

@ -43,7 +43,9 @@ class StructuredChatOutputParser(AgentOutputParser):
if response["action"] == "Final Answer":
return AgentFinish({"output": response["action_input"]}, text)
return AgentAction(
response["action"], response.get("action_input", {}), text
response["action"],
response.get("action_input", {}),
text,
)
return AgentFinish({"output": text}, text)
except Exception as e:
@ -88,7 +90,8 @@ class StructuredChatOutputParserWithRetries(AgentOutputParser):
if llm is not None:
base_parser = base_parser or StructuredChatOutputParser()
output_fixing_parser: OutputFixingParser = OutputFixingParser.from_llm(
llm=llm, parser=base_parser
llm=llm,
parser=base_parser,
)
return cls(output_fixing_parser=output_fixing_parser)
if base_parser is not None:

7
libs/langchain/langchain/agents/structured_chat/prompt.py
View File

@ -1,5 +1,4 @@
# flake8: noqa
PREFIX = """Respond to the human as helpfully and accurately as possible. You have access to the following tools:"""
PREFIX = """Respond to the human as helpfully and accurately as possible. You have access to the following tools:""" # noqa: E501
FORMAT_INSTRUCTIONS = """Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
Valid "action" values: "Final Answer" or {tool_names}
@ -30,6 +29,6 @@ Action:
"action": "Final Answer",
"action_input": "Final response to human"
}}}}
```"""
```""" # noqa: E501
SUFFIX = """Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation:.
Thought:"""
Thought:""" # noqa: E501

4
libs/langchain/langchain/agents/tool_calling_agent/base.py
View File

@ -87,7 +87,7 @@ def create_tool_calling_agent(
messages will be passed in here.
"""
missing_vars = {"agent_scratchpad"}.difference(
prompt.input_variables + list(prompt.partial_variables)
prompt.input_variables + list(prompt.partial_variables),
)
if missing_vars:
msg = f"Prompt missing required variables: {missing_vars}"
@ -102,7 +102,7 @@ def create_tool_calling_agent(
return (
RunnablePassthrough.assign(
agent_scratchpad=lambda x: message_formatter(x["intermediate_steps"])
agent_scratchpad=lambda x: message_formatter(x["intermediate_steps"]),
)
| prompt
| llm_with_tools

4
libs/langchain/langchain/agents/xml/base.py
View File

@ -52,7 +52,7 @@ class XMLAgent(BaseSingleActionAgent):
def get_default_prompt() -> ChatPromptTemplate:
base_prompt = ChatPromptTemplate.from_template(agent_instructions)
return base_prompt + AIMessagePromptTemplate.from_template(
"{intermediate_steps}"
"{intermediate_steps}",
)
@staticmethod
@ -205,7 +205,7 @@ def create_xml_agent(
prompt = PromptTemplate.from_template(template)
""" # noqa: E501
missing_vars = {"tools", "agent_scratchpad"}.difference(
prompt.input_variables + list(prompt.partial_variables)
prompt.input_variables + list(prompt.partial_variables),
)
if missing_vars:
msg = f"Prompt missing required variables: {missing_vars}"

3
libs/langchain/langchain/agents/xml/prompt.py
View File

@ -1,4 +1,3 @@
# flake8: noqa
# TODO: deprecate
agent_instructions = """You are a helpful assistant. Help the user answer any questions.
@ -19,4 +18,4 @@ When you are done, respond with a final answer between <final_answer></final_ans
Begin!
Question: {question}"""
Question: {question}""" # noqa: E501

2
libs/langchain/langchain/callbacks/argilla_callback.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"ArgillaCallbackHandler": "langchain_community.callbacks.argilla_callback"
"ArgillaCallbackHandler": "langchain_community.callbacks.argilla_callback",
}
_import_attribute = create_importer(__file__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/callbacks/arize_callback.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"ArizeCallbackHandler": "langchain_community.callbacks.arize_callback"
"ArizeCallbackHandler": "langchain_community.callbacks.arize_callback",
}
_import_attribute = create_importer(__file__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/callbacks/arthur_callback.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"ArthurCallbackHandler": "langchain_community.callbacks.arthur_callback"
"ArthurCallbackHandler": "langchain_community.callbacks.arthur_callback",
}
_import_attribute = create_importer(__file__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/callbacks/clearml_callback.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"ClearMLCallbackHandler": "langchain_community.callbacks.clearml_callback"
"ClearMLCallbackHandler": "langchain_community.callbacks.clearml_callback",
}
_import_attribute = create_importer(__file__, deprecated_lookups=DEPRECATED_LOOKUP)

2
libs/langchain/langchain/callbacks/comet_ml_callback.py
View File

@ -9,7 +9,7 @@ if TYPE_CHECKING:
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {
"CometCallbackHandler": "langchain_community.callbacks.comet_ml_callback"
"CometCallbackHandler": "langchain_community.callbacks.comet_ml_callback",
}
_import_attribute = create_importer(__file__, deprecated_lookups=DEPRECATED_LOOKUP)

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