diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index f75c16a..ac4b8d1 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -74,9 +74,23 @@ jobs: working-directory: ${{ matrix.working-directory }} secrets: inherit + api-docs: + name: API docs + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + with: + persist-credentials: false + - name: Install uv + uses: astral-sh/setup-uv@v5 + with: + enable-cache: true + python-version: 3.9 + - run: uv run sphinx-build -T -W -b html docs docs/_build/html + ci_success: name: "CI Success" - needs: [build, lint, test, pre-commit] + needs: [build, lint, test, pre-commit, api-docs] if: | always() runs-on: ubuntu-latest diff --git a/.gitignore b/.gitignore index de92250..4ced5ca 100644 --- a/.gitignore +++ b/.gitignore @@ -6,3 +6,6 @@ __pycache__ .env .venv* .local_atlas_uri +docs/langchain_mongodb +docs/langgraph_checkpoint_mongodb +docs/index.md diff --git a/.readthedocs.yaml b/.readthedocs.yaml new file mode 100644 index 0000000..ace1ef1 --- /dev/null +++ b/.readthedocs.yaml @@ -0,0 +1,17 @@ +version: 2 +build: + os: ubuntu-22.04 + tools: + python: "3.11" + jobs: + create_environment: + - asdf plugin add uv + - asdf install uv latest + - asdf global uv latest + install: + - uv sync + build: + html: + - uv run sphinx-build -T -b html docs $READTHEDOCS_OUTPUT/html +sphinx: + configuration: docs/conf.py diff --git a/docs/_extensions/gallery_directive.py b/docs/_extensions/gallery_directive.py new file mode 100644 index 0000000..80642c5 --- /dev/null +++ b/docs/_extensions/gallery_directive.py @@ -0,0 +1,144 @@ +"""A directive to generate a gallery of images from structured data. + +Generating a gallery of images that are all the same size is a common +pattern in documentation, and this can be cumbersome if the gallery is +generated programmatically. This directive wraps this particular use-case +in a helper-directive to generate it with a single YAML configuration file. + +It currently exists for maintainers of the pydata-sphinx-theme, +but might be abstracted into a standalone package if it proves useful. +""" + +from pathlib import Path +from typing import Any, ClassVar, Dict, List + +from docutils import nodes +from docutils.parsers.rst import directives +from sphinx.application import Sphinx +from sphinx.util import logging +from sphinx.util.docutils import SphinxDirective +from yaml import safe_load + +logger = logging.getLogger(__name__) + + +TEMPLATE_GRID = """ +`````{{grid}} {columns} +{options} + +{content} + +````` +""" + +GRID_CARD = """ +````{{grid-item-card}} {title} +{options} + +{content} +```` +""" + + +class GalleryGridDirective(SphinxDirective): + """A directive to show a gallery of images and links in a Bootstrap grid. + + The grid can be generated from a YAML file that contains a list of items, or + from the content of the directive (also formatted in YAML). Use the parameter + "class-card" to add an additional CSS class to all cards. When specifying the grid + items, you can use all parameters from "grid-item-card" directive to customize + individual cards + ["image", "header", "content", "title"]. + + Danger: + This directive can only be used in the context of a Myst documentation page as + the templates use Markdown flavored formatting. + """ + + name = "gallery-grid" + has_content = True + required_arguments = 0 + optional_arguments = 1 + final_argument_whitespace = True + option_spec: ClassVar[dict[str, Any]] = { + # A class to be added to the resulting container + "grid-columns": directives.unchanged, + "class-container": directives.unchanged, + "class-card": directives.unchanged, + } + + def run(self) -> List[nodes.Node]: + """Create the gallery grid.""" + if self.arguments: + # If an argument is given, assume it's a path to a YAML file + # Parse it and load it into the directive content + path_data_rel = Path(self.arguments[0]) + path_doc, _ = self.get_source_info() + path_doc = Path(path_doc).parent + path_data = (path_doc / path_data_rel).resolve() + if not path_data.exists(): + logger.info(f"Could not find grid data at {path_data}.") + nodes.text("No grid data found at {path_data}.") + return + yaml_string = path_data.read_text() + else: + yaml_string = "\n".join(self.content) + + # Use all the element with an img-bottom key as sites to show + # and generate a card item for each of them + grid_items = [] + for item in safe_load(yaml_string): + # remove parameters that are not needed for the card options + title = item.pop("title", "") + + # build the content of the card using some extra parameters + header = f"{item.pop('header')} \n^^^ \n" if "header" in item else "" + image = f"![image]({item.pop('image')}) \n" if "image" in item else "" + content = f"{item.pop('content')} \n" if "content" in item else "" + + # optional parameter that influence all cards + if "class-card" in self.options: + item["class-card"] = self.options["class-card"] + + loc_options_str = "\n".join(f":{k}: {v}" for k, v in item.items()) + " \n" + + card = GRID_CARD.format( + options=loc_options_str, content=header + image + content, title=title + ) + grid_items.append(card) + + # Parse the template with Sphinx Design to create an output container + # Prep the options for the template grid + class_ = "gallery-directive" + f' {self.options.get("class-container", "")}' + options = {"gutter": 2, "class-container": class_} + options_str = "\n".join(f":{k}: {v}" for k, v in options.items()) + + # Create the directive string for the grid + grid_directive = TEMPLATE_GRID.format( + columns=self.options.get("grid-columns", "1 2 3 4"), + options=options_str, + content="\n".join(grid_items), + ) + + # Parse content as a directive so Sphinx Design processes it + container = nodes.container() + self.state.nested_parse([grid_directive], 0, container) + + # Sphinx Design outputs a container too, so just use that + return [container.children[0]] + + +def setup(app: Sphinx) -> Dict[str, Any]: + """Add custom configuration to sphinx app. + + Args: + app: the Sphinx application + + Returns: + the 2 parallel parameters set to ``True``. + """ + app.add_directive("gallery-grid", GalleryGridDirective) + + return { + "parallel_read_safe": True, + "parallel_write_safe": True, + } diff --git a/docs/_static/favicon.png b/docs/_static/favicon.png new file mode 100644 index 0000000..e0335bc Binary files /dev/null and b/docs/_static/favicon.png differ diff --git a/docs/_static/wordmark-api-dark.svg b/docs/_static/wordmark-api-dark.svg new file mode 100644 index 0000000..c33ec92 --- /dev/null +++ b/docs/_static/wordmark-api-dark.svg @@ -0,0 +1,11 @@ + + + + + + + + + + + diff --git a/docs/_static/wordmark-api.svg b/docs/_static/wordmark-api.svg new file mode 100644 index 0000000..a9f8f59 --- /dev/null +++ b/docs/_static/wordmark-api.svg @@ -0,0 +1,11 @@ + + + + + + + + + + + diff --git a/docs/conf.py b/docs/conf.py new file mode 100644 index 0000000..7a53647 --- /dev/null +++ b/docs/conf.py @@ -0,0 +1,236 @@ +"""Configuration file for the Sphinx documentation builder.""" + +# Configuration file for the Sphinx documentation builder. +# +# This file only contains a selection of the most common options. For a full +# list see the documentation: +# https://www.sphinx-doc.org/en/master/usage/configuration.html + +# -- Path setup -------------------------------------------------------------- + +import os +import sys + +from docutils import nodes +from docutils.parsers.rst.directives.admonitions import BaseAdmonition +from docutils.statemachine import StringList + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. + +sys.path.insert(0, os.path.abspath(".")) +sys.path.insert(0, os.path.abspath("../libs")) +from create_api_rst import main + + +class Beta(BaseAdmonition): + required_arguments = 0 + node_class = nodes.admonition + + def run(self): + self.content = self.content or StringList( + [ + ( + "This feature is in beta. It is actively being worked on, so the " + "API may change." + ) + ] + ) + self.arguments = self.arguments or ["Beta"] + return super().run() + + +def setup(app): + main() + app.add_directive("beta", Beta) + app.connect("autodoc-skip-member", skip_private_members) + + +def skip_private_members(app, what, name, obj, skip, options): + if skip: + return True + if hasattr(obj, "__doc__") and obj.__doc__ and ":private:" in obj.__doc__: + return True + if name == "__init__" and getattr(obj, "__objclass__", None) is object: + # dont document default init + return True + return None + + +# -- Project information ----------------------------------------------------- + +project = "🦜🔗 LangChain MongoDB" +copyright = "2024, LangChain Inc" +author = "LangChain, Inc" + +html_favicon = "_static/favicon.png" +html_last_updated_fmt = "%b %d, %Y" + + +# -- General configuration --------------------------------------------------- + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + "sphinx.ext.autodoc", + "sphinx.ext.autodoc.typehints", + "sphinx.ext.mathjax", + "sphinx.ext.autosummary", + "sphinx.ext.napoleon", + "sphinx.ext.viewcode", + "sphinxcontrib.autodoc_pydantic", + "IPython.sphinxext.ipython_console_highlighting", + "myst_parser", + "_extensions.gallery_directive", + "sphinx_design", + "sphinx_copybutton", + "sphinxcontrib.googleanalytics", +] + +source_suffix = [".rst", ".md"] + +# some autodoc pydantic options are repeated in the actual template. +# potentially user error, but there may be bugs in the sphinx extension +# with options not being passed through correctly (from either the location in the code) +autodoc_pydantic_model_show_json = False +autodoc_pydantic_field_list_validators = False +autodoc_pydantic_config_members = False +autodoc_pydantic_model_show_config_summary = False +autodoc_pydantic_model_show_validator_members = False +autodoc_pydantic_model_show_validator_summary = False +autodoc_pydantic_model_signature_prefix = "class" +autodoc_pydantic_field_signature_prefix = "param" +autodoc_member_order = "groupwise" +autoclass_content = "both" +autodoc_typehints_format = "short" +autodoc_typehints = "both" + +# Add any paths that contain templates here, relative to this directory. +templates_path = ["templates"] + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This pattern also affects html_static_path and html_extra_path. +exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"] + + +# -- Options for HTML output ------------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +# The theme to use for HTML and HTML Help pages. +html_theme = "pydata_sphinx_theme" + +# Theme options are theme-specific and customize the look and feel of a theme +# further. For a list of options available for each theme, see the +# documentation. +html_theme_options = { + # # -- General configuration ------------------------------------------------ + "sidebar_includehidden": True, + "use_edit_page_button": False, + # # "analytics": { + # # "plausible_analytics_domain": "scikit-learn.org", + # # "plausible_analytics_url": "https://views.scientific-python.org/js/script.js", + # # }, + # # If "prev-next" is included in article_footer_items, then setting show_prev_next + # # to True would repeat prev and next links. See + # # https://github.com/pydata/pydata-sphinx-theme/blob/b731dc230bc26a3d1d1bb039c56c977a9b3d25d8/src/pydata_sphinx_theme/theme/pydata_sphinx_theme/layout.html#L118-L129 + "show_prev_next": False, + "search_bar_text": "Search", + "navigation_with_keys": True, + "collapse_navigation": True, + "navigation_depth": 3, + "show_nav_level": 1, + "show_toc_level": 3, + "navbar_align": "left", + "header_links_before_dropdown": 5, + "header_dropdown_text": "Integrations", + "logo": { + "image_light": "_static/wordmark-api.svg", + "image_dark": "_static/wordmark-api-dark.svg", + }, + "surface_warnings": True, + # # -- Template placement in theme layouts ---------------------------------- + "navbar_start": ["navbar-logo"], + # # Note that the alignment of navbar_center is controlled by navbar_align + "navbar_center": ["navbar-nav"], + "navbar_end": ["langchain_docs", "theme-switcher", "navbar-icon-links"], + # # navbar_persistent is persistent right (even when on mobiles) + "navbar_persistent": ["search-field"], + "article_header_start": ["breadcrumbs"], + "article_header_end": [], + "article_footer_items": [], + "content_footer_items": [], + # # Use html_sidebars that map page patterns to list of sidebar templates + # "primary_sidebar_end": [], + "footer_start": ["copyright"], + "footer_center": [], + "footer_end": [], + # # When specified as a dictionary, the keys should follow glob-style patterns, as in + # # https://www.sphinx-doc.org/en/master/usage/configuration.html#confval-exclude_patterns + # # In particular, "**" specifies the default for all pages + # # Use :html_theme.sidebar_secondary.remove: for file-wide removal + # "secondary_sidebar_items": {"**": ["page-toc", "sourcelink"]}, + # "show_version_warning_banner": True, + # "announcement": None, + "icon_links": [ + { + # Label for this link + "name": "GitHub", + # URL where the link will redirect + "url": "https://github.com/langchain-ai/langchain-mongodb", # required + # Icon class (if "type": "fontawesome"), or path to local image (if "type": "local") + "icon": "fa-brands fa-square-github", + # The type of image to be used (see below for details) + "type": "fontawesome", + }, + { + "name": "X / Twitter", + "url": "https://twitter.com/langchainai", + "icon": "fab fa-twitter-square", + }, + ], + "icon_links_label": "Quick Links", + "external_links": [], +} + + +html_context = { + "display_github": True, # Integrate GitHub + "github_user": "langchain-ai", # Username + "github_repo": "langchain-mongodb", # Repo name + "github_version": "master", # Version + "conf_py_path": "/docs", # Path in the checkout to the docs root +} + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ["_static"] + +# These paths are either relative to html_static_path +# or fully qualified paths (e.g. https://...) +html_css_files = ["custom.css"] +html_use_index = False + +myst_enable_extensions = ["colon_fence"] + +# generate autosummary even if no references +autosummary_generate = True + +html_copy_source = False +html_show_sourcelink = False + +# Set canonical URL from the Read the Docs Domain +html_baseurl = os.environ.get("READTHEDOCS_CANONICAL_URL", "") + +googleanalytics_id = "G-9B66JQQH2F" + +# Tell Jinja2 templates the build is running on Read the Docs +if os.environ.get("READTHEDOCS", "") == "True": + html_context["READTHEDOCS"] = True + +master_doc = "index" diff --git a/docs/create_api_rst.py b/docs/create_api_rst.py new file mode 100644 index 0000000..1035130 --- /dev/null +++ b/docs/create_api_rst.py @@ -0,0 +1,588 @@ +"""Script for auto-generating api_reference.rst.""" + +import importlib +import inspect +import os +import sys +import typing +import shutil +from enum import Enum +from pathlib import Path +from typing import Dict, List, Literal, Optional, Sequence, TypedDict, Union + +import toml +import typing_extensions +from langchain_core.runnables import Runnable +from pydantic import BaseModel + +ROOT_DIR = Path(__file__).parents[1].absolute() +HERE = Path(__file__).parent + +ClassKind = Literal[ + "TypedDict", + "Regular", + "Pydantic", + "enum", + "RunnablePydantic", + "RunnableNonPydantic", +] + + +class ClassInfo(TypedDict): + """Information about a class.""" + + name: str + """The name of the class.""" + qualified_name: str + """The fully qualified name of the class.""" + kind: ClassKind + """The kind of the class.""" + is_public: bool + """Whether the class is public or not.""" + is_deprecated: bool + """Whether the class is deprecated.""" + + +class FunctionInfo(TypedDict): + """Information about a function.""" + + name: str + """The name of the function.""" + qualified_name: str + """The fully qualified name of the function.""" + is_public: bool + """Whether the function is public or not.""" + is_deprecated: bool + """Whether the function is deprecated.""" + + +class ModuleMembers(TypedDict): + """A dictionary of module members.""" + + classes_: Sequence[ClassInfo] + functions: Sequence[FunctionInfo] + + +def _load_module_members(module_path: str, namespace: str) -> ModuleMembers: + """Load all members of a module. + + Args: + module_path: Path to the module. + namespace: the namespace of the module. + + Returns: + list: A list of loaded module objects. + """ + + classes_: List[ClassInfo] = [] + functions: List[FunctionInfo] = [] + module = importlib.import_module(module_path) + + if ":private:" in (module.__doc__ or ""): + return ModuleMembers(classes_=[], functions=[]) + + for name, type_ in inspect.getmembers(module): + if not hasattr(type_, "__module__"): + continue + if type_.__module__ != module_path: + continue + if ":private:" in (type_.__doc__ or ""): + continue + if hasattr(module, "__all__") and name not in module.__all__: + continue + + if inspect.isclass(type_): + # The type of the class is used to select a template + # for the object when rendering the documentation. + # See `templates` directory for defined templates. + # This is a hacky solution to distinguish between different + # kinds of thing that we want to render. + if type(type_) is typing_extensions._TypedDictMeta: # type: ignore + kind: ClassKind = "TypedDict" + elif type(type_) is typing._TypedDictMeta: # type: ignore + kind: ClassKind = "TypedDict" + elif ( + issubclass(type_, Runnable) + and issubclass(type_, BaseModel) + and type_ is not Runnable + ): + # RunnableSerializable subclasses from Pydantic which + # for which we use autodoc_pydantic for rendering. + # We need to distinguish these from regular Pydantic + # classes so we can hide inherited Runnable methods + # and provide a link to the Runnable interface from + # the template. + kind = "RunnablePydantic" + elif ( + issubclass(type_, Runnable) + and not issubclass(type_, BaseModel) + and type_ is not Runnable + ): + # These are not pydantic classes but are Runnable. + # We'll hide all the inherited methods from Runnable + # but use a regular class template to render. + kind = "RunnableNonPydantic" + elif issubclass(type_, Enum): + kind = "enum" + elif issubclass(type_, BaseModel): + kind = "Pydantic" + else: + kind = "Regular" + + classes_.append( + ClassInfo( + name=name, + qualified_name=f"{namespace}.{name}", + kind=kind, + is_public=not name.startswith("_"), + is_deprecated=".. deprecated::" in (type_.__doc__ or ""), + ) + ) + elif inspect.isfunction(type_): + functions.append( + FunctionInfo( + name=name, + qualified_name=f"{namespace}.{name}", + is_public=not name.startswith("_"), + is_deprecated=".. deprecated::" in (type_.__doc__ or ""), + ) + ) + else: + continue + + return ModuleMembers( + classes_=classes_, + functions=functions, + ) + + +def _merge_module_members( + module_members: Sequence[ModuleMembers], +) -> ModuleMembers: + """Merge module members.""" + classes_: List[ClassInfo] = [] + functions: List[FunctionInfo] = [] + for module in module_members: + classes_.extend(module["classes_"]) + functions.extend(module["functions"]) + + return ModuleMembers( + classes_=classes_, + functions=functions, + ) + + +def _load_package_modules( + package_directory: Union[str, Path], submodule: Optional[str] = None +) -> Dict[str, ModuleMembers]: + """Recursively load modules of a package based on the file system. + + Traversal based on the file system makes it easy to determine which + of the modules/packages are part of the package vs. 3rd party or built-in. + + Parameters: + package_directory (Union[str, Path]): Path to the package directory. + submodule (Optional[str]): Optional name of submodule to load. + + Returns: + Dict[str, ModuleMembers]: A dictionary where keys are module names and values are ModuleMembers objects. + """ + package_path = ( + Path(package_directory) + if isinstance(package_directory, str) + else package_directory + ) + modules_by_namespace = {} + + # Get the high level package name + package_name = package_path.name + + # If we are loading a submodule, add it in + if submodule is not None: + package_path = package_path / submodule + + for file_path in package_path.rglob("*.py"): + if file_path.name.startswith("_"): + continue + + relative_module_name = file_path.relative_to(package_path) + + # Skip if any module part starts with an underscore + if any(part.startswith("_") for part in relative_module_name.parts): + continue + + # Get the full namespace of the module + namespace = str(relative_module_name).replace(".py", "").replace("/", ".") + # Keep only the top level namespace + top_namespace = namespace.split(".")[0] + + try: + # If submodule is present, we need to construct the paths in a slightly + # different way + if submodule is not None: + module_members = _load_module_members( + f"{package_name}.{submodule}.{namespace}", + f"{submodule}.{namespace}", + ) + else: + module_members = _load_module_members( + f"{package_name}.{namespace}", namespace + ) + # Merge module members if the namespace already exists + if top_namespace in modules_by_namespace: + existing_module_members = modules_by_namespace[top_namespace] + _module_members = _merge_module_members( + [existing_module_members, module_members] + ) + else: + _module_members = module_members + + modules_by_namespace[top_namespace] = _module_members + + except ImportError as e: + print(f"Error: Unable to import module '{namespace}' with error: {e}") + + return modules_by_namespace + + +def _construct_doc( + package_namespace: str, + members_by_namespace: Dict[str, ModuleMembers], + package_version: str, +) -> List[typing.Tuple[str, str]]: + """Construct the contents of the reference.rst file for the given package. + + Args: + package_namespace: The package top level namespace + members_by_namespace: The members of the package, dict organized by top level + module contains a list of classes and functions + inside of the top level namespace. + + Returns: + The contents of the reference.rst file. + """ + docs = [] + index_doc = f"""\ +:html_theme.sidebar_secondary.remove: + +.. currentmodule:: {package_namespace} + +.. _{package_namespace}: + +====================================== +{package_namespace.replace('_', '-')}: {package_version} +====================================== + +.. automodule:: {package_namespace} + :no-members: + :no-inherited-members: + +.. toctree:: + :hidden: + :maxdepth: 2 + +""" + index_autosummary = """ +""" + namespaces = sorted(members_by_namespace) + + for module in namespaces: + index_doc += f" {module}\n" + module_doc = f"""\ +.. currentmodule:: {package_namespace} + +.. _{package_namespace}_{module}: +""" + _members = members_by_namespace[module] + classes = [ + el + for el in _members["classes_"] + if el["is_public"] and not el["is_deprecated"] + ] + functions = [ + el + for el in _members["functions"] + if el["is_public"] and not el["is_deprecated"] + ] + deprecated_classes = [ + el for el in _members["classes_"] if el["is_public"] and el["is_deprecated"] + ] + deprecated_functions = [ + el + for el in _members["functions"] + if el["is_public"] and el["is_deprecated"] + ] + if not (classes or functions): + continue + section = f":mod:`{module}`" + underline = "=" * (len(section) + 1) + module_doc += f""" +{section} +{underline} + +.. automodule:: {package_namespace}.{module} + :no-members: + :no-inherited-members: + +""" + + index_autosummary += f""" +:ref:`{package_namespace}_{module}` +{'^' * (len(package_namespace) + len(module) + 8)} +""" + + if classes: + module_doc += f"""\ +**Classes** + +.. currentmodule:: {package_namespace} + +.. autosummary:: + :toctree: {module} +""" + index_autosummary += """ +**Classes** + +.. autosummary:: +""" + + for class_ in sorted(classes, key=lambda c: c["qualified_name"]): + if class_["kind"] == "TypedDict": + template = "typeddict.rst" + elif class_["kind"] == "enum": + template = "enum.rst" + elif class_["kind"] == "Pydantic": + template = "pydantic.rst" + elif class_["kind"] == "RunnablePydantic": + template = "runnable_pydantic.rst" + elif class_["kind"] == "RunnableNonPydantic": + template = "runnable_non_pydantic.rst" + else: + template = "class.rst" + + module_doc += f"""\ + :template: {template} + + {class_["qualified_name"]} + +""" + index_autosummary += f""" + {class_['qualified_name']} +""" + + if functions: + _functions = [f["qualified_name"] for f in functions] + fstring = "\n ".join(sorted(_functions)) + module_doc += f"""\ +**Functions** + +.. currentmodule:: {package_namespace} + +.. autosummary:: + :toctree: {module} + :template: function.rst + + {fstring} + +""" + + index_autosummary += f""" +**Functions** + +.. autosummary:: + + {fstring} +""" + if deprecated_classes: + module_doc += f"""\ +**Deprecated classes** + +.. currentmodule:: {package_namespace} + +.. autosummary:: + :toctree: {module} +""" + + index_autosummary += """ +**Deprecated classes** + +.. autosummary:: +""" + + for class_ in sorted(deprecated_classes, key=lambda c: c["qualified_name"]): + if class_["kind"] == "TypedDict": + template = "typeddict.rst" + elif class_["kind"] == "enum": + template = "enum.rst" + elif class_["kind"] == "Pydantic": + template = "pydantic.rst" + elif class_["kind"] == "RunnablePydantic": + template = "runnable_pydantic.rst" + elif class_["kind"] == "RunnableNonPydantic": + template = "runnable_non_pydantic.rst" + else: + template = "class.rst" + + module_doc += f"""\ + :template: {template} + + {class_["qualified_name"]} + +""" + index_autosummary += f""" + {class_['qualified_name']} +""" + + if deprecated_functions: + _functions = [f["qualified_name"] for f in deprecated_functions] + fstring = "\n ".join(sorted(_functions)) + module_doc += f"""\ +**Deprecated functions** + +.. currentmodule:: {package_namespace} + +.. autosummary:: + :toctree: {module} + :template: function.rst + + {fstring} + +""" + index_autosummary += f""" +**Deprecated functions** + +.. autosummary:: + + {fstring} + +""" + docs.append((f"{module}.rst", module_doc)) + docs.append(("api_docs.rst", index_doc + index_autosummary)) + return docs + + +def _build_rst_file(package_name: str = "langchain") -> None: + """Create a rst file for building of documentation. + + Args: + package_name: Can be either "langchain" or "core" or "experimental". + """ + package_dir = _package_dir(package_name) + package_members = _load_package_modules(package_dir) + package_version = _get_package_version(package_dir) + output_dir = _out_file_path(package_name) + shutil.rmtree(output_dir, ignore_errors=True) + os.mkdir(output_dir) + rsts = _construct_doc( + _package_namespace(package_name), package_members, package_version + ) + for name, rst in rsts: + with open(output_dir / name, "w") as f: + f.write(rst) + + +def _package_namespace(package_name: str) -> str: + """Returns the package name used.""" + if package_name == "langgraph-checkpoint-mongodb": + package_name = "langgraph" + return f"{package_name.replace('-', '_')}" + + +def _package_dir(package_name: str = "langchain") -> Path: + """Return the path to the directory containing the documentation.""" + return ROOT_DIR / "libs" / package_name / _package_namespace(package_name) + + +def _get_package_version(package_dir: Path) -> str: + """Return the version of the package.""" + try: + with open(package_dir.parent / "pyproject.toml", "r") as f: + pyproject = toml.load(f) + except FileNotFoundError: + print( + f"pyproject.toml not found in {package_dir.parent}.\n" + "You are either attempting to build a directory which is not a package or " + "the package is missing a pyproject.toml file which should be added." + "Aborting the build." + ) + exit(1) + return pyproject["project"]["version"] + + +def _out_file_path(package_name: str) -> Path: + """Return the path to the file containing the documentation.""" + return HERE / f"{package_name.replace('-', '_')}" + + +def _build_index(dirs: List[str]) -> None: + integrations = sorted(dirs) + doc = """# LangChain MongoDB Python API Reference + +Welcome to the LangChain MongoDB Python API reference. This is a reference for all +Langchain MongoDB packages. + +For user guides see [https://python.langchain.com](https://python.langchain.com). +""" + if integrations: + integration_headers = [ + " ".join(x.title() for x in dir_.split("-")) for dir_ in integrations + ] + integration_tree = "\n".join( + f"{header_name}<{dir_.replace('-', '_')}/api_docs>" + for header_name, dir_ in zip(integration_headers, integrations) + ) + + integration_grid = "" + integrations_to_show = integrations + for header_name, dir_ in sorted( + zip(integration_headers, integrations), + key=lambda h_d: ( + integrations_to_show.index(h_d[1]) + if h_d[1] in integrations_to_show + else len(integrations_to_show) + ), + )[: len(integrations_to_show)]: + integration_grid += f'\n- header: "**{header_name}**"\n content: {dir_} {_get_package_version(_package_dir(dir_))}\n link: {dir_.replace("-", "_")}/api_docs.html' + doc += f"""## Integrations + +```{{gallery-grid}} +:grid-columns: "1 2 2 3" + +{integration_grid} +``` + +```{{toctree}} +:maxdepth: 2 +:hidden: +:caption: Integrations + +{integration_tree} +``` +""" + with open(HERE / "index.md", "w") as f: + f.write(doc) + + +def main(dirs: Optional[list] = None) -> None: + """Generate the api_reference.rst file for each package.""" + print("Starting to build API reference files.") + if not dirs: + dirs = [dir_ for dir_ in os.listdir(ROOT_DIR / "libs")] + for dir_ in dirs: + # Skip any hidden directories + # Some of these could be present by mistake in the code base + # e.g., .pytest_cache from running tests from the wrong location. + if dir_.startswith("."): + print("Skipping dir:", dir_) + continue + else: + print("Building package:", dir_) + _build_rst_file(package_name=dir_) + + _build_index(dirs) + print("API reference files built.") + + +if __name__ == "__main__": + dirs = sys.argv[1:] or None + main(dirs=dirs) diff --git a/docs/templates/langchain_docs.html b/docs/templates/langchain_docs.html new file mode 100644 index 0000000..774761c --- /dev/null +++ b/docs/templates/langchain_docs.html @@ -0,0 +1,12 @@ + + + + + +Docs + diff --git a/libs/langchain-mongodb/langchain_mongodb/chat_message_histories.py b/libs/langchain-mongodb/langchain_mongodb/chat_message_histories.py index 0022fae..24bb385 100644 --- a/libs/langchain-mongodb/langchain_mongodb/chat_message_histories.py +++ b/libs/langchain-mongodb/langchain_mongodb/chat_message_histories.py @@ -80,7 +80,7 @@ def __init__( provided. session_id: str arbitrary key that is used to store the messages of - a single chat session. + a single chat session. database_name: Optional[str] name of the database to use. collection_name: Optional[str] diff --git a/libs/langchain-mongodb/langchain_mongodb/pipelines.py b/libs/langchain-mongodb/langchain_mongodb/pipelines.py index 5820ce3..85ada4f 100644 --- a/libs/langchain-mongodb/langchain_mongodb/pipelines.py +++ b/libs/langchain-mongodb/langchain_mongodb/pipelines.py @@ -116,7 +116,7 @@ def reciprocal_rank_stage( extra_fields: Any fields other than text_field that one wishes to keep. Returns: - RRF score := \frac{1}{rank + penalty} with rank in [1,2,..,n] + RRF score """ rrf_pipeline = [ diff --git a/libs/langchain-mongodb/langchain_mongodb/utils.py b/libs/langchain-mongodb/langchain_mongodb/utils.py index f228c56..0e33d7d 100644 --- a/libs/langchain-mongodb/langchain_mongodb/utils.py +++ b/libs/langchain-mongodb/langchain_mongodb/utils.py @@ -11,6 +11,7 @@ Functions "maximal_marginal_relevance" and "cosine_similarity" are duplicated in this utility respectively from modules: + - "libs/community/langchain_community/vectorstores/utils.py" - "libs/community/langchain_community/utils/math.py" """ diff --git a/libs/langchain-mongodb/langchain_mongodb/vectorstores.py b/libs/langchain-mongodb/langchain_mongodb/vectorstores.py index 4c7b9ae..5827113 100644 --- a/libs/langchain-mongodb/langchain_mongodb/vectorstores.py +++ b/libs/langchain-mongodb/langchain_mongodb/vectorstores.py @@ -61,12 +61,12 @@ class MongoDBAtlasVectorSearch(VectorStore): Setup: * Set up a MongoDB Atlas cluster. The free tier M0 will allow you to start. - Search Indexes are only available on Atlas, the fully managed cloud service, - not the self-managed MongoDB. - Follow [this guide](https://www.mongodb.com/basics/mongodb-atlas-tutorial) + Search Indexes are only available on Atlas, the fully managed cloud service, + not the self-managed MongoDB. + Follow [this guide](https://www.mongodb.com/basics/mongodb-atlas-tutorial) * Create a Collection and a Vector Search Index.The procedure is described - [here](https://www.mongodb.com/docs/atlas/atlas-vector-search/create-index/#procedure). + [here](https://www.mongodb.com/docs/atlas/atlas-vector-search/create-index/#procedure). * Install ``langchain-mongodb`` @@ -189,6 +189,7 @@ class MongoDBAtlasVectorSearch(VectorStore): * [SIM=0.916096] foo [{'_id': '1', 'baz': 'bar'}] Use as Retriever: + .. code-block:: python retriever = vector_store.as_retriever( diff --git a/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/__init__.py b/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/__init__.py index 9803943..eb7c22d 100644 --- a/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/__init__.py +++ b/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/__init__.py @@ -1,373 +1,4 @@ -from collections.abc import Iterator, Sequence -from contextlib import contextmanager -from typing import ( - Any, - Optional, -) +from .aio import AsyncMongoDBSaver +from .saver import MongoDBSaver -from langchain_core.runnables import RunnableConfig -from pymongo import MongoClient, UpdateOne -from pymongo.database import Database as MongoDatabase - -from langgraph.checkpoint.base import ( - WRITES_IDX_MAP, - BaseCheckpointSaver, - ChannelVersions, - Checkpoint, - CheckpointMetadata, - CheckpointTuple, - get_checkpoint_id, -) - -from .utils import dumps_metadata, loads_metadata - - -class MongoDBSaver(BaseCheckpointSaver): - """A checkpoint saver that stores StateGraph checkpoints in a MongoDB database. - - Args: - client (MongoClient): The MongoDB connection. - db_name (Optional[str]): Database name - checkpoint_collection_name (Optional[str]): Name of Collection of Checkpoints - writes_collection_name (Optional[str]): Name of Collection of intermediate writes. - - Examples: - - >>> from langgraph.checkpoint.mongodb import MongoDBSaver - >>> from langgraph.graph import StateGraph - >>> from pymongo import MongoClient - >>> - >>> builder = StateGraph(int) - >>> builder.add_node("add_one", lambda x: x + 1) - >>> builder.set_entry_point("add_one") - >>> builder.set_finish_point("add_one") - >>> client = MongoClient("mongodb://localhost:27017") - >>> memory = MongoDBSaver(client) - >>> graph = builder.compile(checkpointer=memory) - >>> config = {"configurable": {"thread_id": "1"}} - >>> graph.get_state(config) - >>> result = graph.invoke(3, config) - >>> graph.get_state(config) - StateSnapshot(values=4, next=(), config={'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef8b22d-df71-6ddc-8001-7c821b5c45fd'}}, metadata={'source': 'loop', 'writes': {'add_one': 4}, 'step': 1, 'parents': {}}, created_at='2024-10-15T18:25:34.088329+00:00', parent_config={'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef8b22d-df6f-6eec-8000-20f621dcf3b7'}}, tasks=()) - """ - - client: MongoClient - db: MongoDatabase - - def __init__( - self, - client: MongoClient, - db_name: str = "checkpointing_db", - checkpoint_collection_name: str = "checkpoints", - writes_collection_name: str = "checkpoint_writes", - **kwargs: Any, - ) -> None: - super().__init__() - self.client = client - self.db = self.client[db_name] - self.checkpoint_collection = self.db[checkpoint_collection_name] - self.writes_collection = self.db[writes_collection_name] - - @classmethod - @contextmanager - def from_conn_string( - cls, - conn_string: Optional[str] = None, - db_name: str = "checkpointing_db", - checkpoint_collection_name: str = "checkpoints", - writes_collection_name: str = "checkpoint_writes", - **kwargs: Any, - ) -> Iterator["MongoDBSaver"]: - """Context manager to create a MongoDB checkpoint saver. - Args: - conn_string: MongoDB connection string. See [class:~pymongo.MongoClient]. - db_name: Database name. It will be created if it doesn't exist. - checkpoint_collection_name: Checkpoint Collection name. Created if it doesn't exist. - writes_collection_name: Collection name of intermediate writes. Created if it doesn't exist. - Yields: A new MongoDBSaver. - """ - client: Optional[MongoClient] = None - try: - client = MongoClient(conn_string) - yield MongoDBSaver( - client, - db_name, - checkpoint_collection_name, - writes_collection_name, - **kwargs, - ) - finally: - if client: - client.close() - - def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]: - """Get a checkpoint tuple from the database. - - This method retrieves a checkpoint tuple from the MongoDB database based on the - provided config. If the config contains a "checkpoint_id" key, the checkpoint with - the matching thread ID and checkpoint ID is retrieved. Otherwise, the latest checkpoint - for the given thread ID is retrieved. - - Args: - config (RunnableConfig): The config to use for retrieving the checkpoint. - - Returns: - Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found. - - Examples: - - Basic: - >>> config = {"configurable": {"thread_id": "1"}} - >>> checkpoint_tuple = memory.get_tuple(config) - >>> print(checkpoint_tuple) - CheckpointTuple(...) - - With checkpoint ID: - >>> config = { - ... "configurable": { - ... "thread_id": "1", - ... "checkpoint_ns": "", - ... "checkpoint_id": "1ef4f797-8335-6428-8001-8a1503f9b875", - ... } - ... } - >>> checkpoint_tuple = memory.get_tuple(config) - >>> print(checkpoint_tuple) - CheckpointTuple(...) - """ - thread_id = config["configurable"]["thread_id"] - checkpoint_ns = config["configurable"].get("checkpoint_ns", "") - if checkpoint_id := get_checkpoint_id(config): - query = { - "thread_id": thread_id, - "checkpoint_ns": checkpoint_ns, - "checkpoint_id": checkpoint_id, - } - else: - query = {"thread_id": thread_id, "checkpoint_ns": checkpoint_ns} - - result = self.checkpoint_collection.find( - query, sort=[("checkpoint_id", -1)], limit=1 - ) - for doc in result: - config_values = { - "thread_id": thread_id, - "checkpoint_ns": checkpoint_ns, - "checkpoint_id": doc["checkpoint_id"], - } - checkpoint = self.serde.loads_typed((doc["type"], doc["checkpoint"])) - serialized_writes = self.writes_collection.find(config_values) - pending_writes = [ - ( - doc["task_id"], - doc["channel"], - self.serde.loads_typed((doc["type"], doc["value"])), - ) - for doc in serialized_writes - ] - return CheckpointTuple( - {"configurable": config_values}, - checkpoint, - loads_metadata(doc["metadata"]), - ( - { - "configurable": { - "thread_id": thread_id, - "checkpoint_ns": checkpoint_ns, - "checkpoint_id": doc["parent_checkpoint_id"], - } - } - if doc.get("parent_checkpoint_id") - else None - ), - pending_writes, - ) - - def list( - self, - config: Optional[RunnableConfig], - *, - filter: Optional[dict[str, Any]] = None, - before: Optional[RunnableConfig] = None, - limit: Optional[int] = None, - ) -> Iterator[CheckpointTuple]: - """List checkpoints from the database. - - This method retrieves a list of checkpoint tuples from the MongoDB database based - on the provided config. The checkpoints are ordered by checkpoint ID in descending order (newest first). - - Args: - config (RunnableConfig): The config to use for listing the checkpoints. - filter (Optional[dict[str, Any]]): Additional filtering criteria for metadata. Defaults to None. - before (Optional[RunnableConfig]): If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None. - limit (Optional[int]): The maximum number of checkpoints to return. Defaults to None. - - Yields: - Iterator[CheckpointTuple]: An iterator of checkpoint tuples. - - Examples: - >>> from langgraph.checkpoint.mongodb import MongoDBSaver - >>> with MongoDBSaver.from_conn_string("mongodb://localhost:27017") as memory: - ... # Run a graph, then list the checkpoints - >>> config = {"configurable": {"thread_id": "1"}} - >>> checkpoints = list(memory.list(config, limit=2)) - >>> print(checkpoints) - [CheckpointTuple(...), CheckpointTuple(...)] - """ - query = {} - if config is not None: - if "thread_id" in config["configurable"]: - query["thread_id"] = config["configurable"]["thread_id"] - if "checkpoint_ns" in config["configurable"]: - query["checkpoint_ns"] = config["configurable"]["checkpoint_ns"] - - if filter: - for key, value in filter.items(): - query[f"metadata.{key}"] = dumps_metadata(value) - - if before is not None: - query["checkpoint_id"] = {"$lt": before["configurable"]["checkpoint_id"]} - - result = self.checkpoint_collection.find( - query, limit=0 if limit is None else limit, sort=[("checkpoint_id", -1)] - ) - - for doc in result: - config_values = { - "thread_id": doc["thread_id"], - "checkpoint_ns": doc["checkpoint_ns"], - "checkpoint_id": doc["checkpoint_id"], - } - serialized_writes = self.writes_collection.find(config_values) - pending_writes = [ - ( - wrt["task_id"], - wrt["channel"], - self.serde.loads_typed((wrt["type"], wrt["value"])), - ) - for wrt in serialized_writes - ] - - yield CheckpointTuple( - config={ - "configurable": { - "thread_id": doc["thread_id"], - "checkpoint_ns": doc["checkpoint_ns"], - "checkpoint_id": doc["checkpoint_id"], - } - }, - checkpoint=self.serde.loads_typed((doc["type"], doc["checkpoint"])), - metadata=loads_metadata(doc["metadata"]), - parent_config=( - { - "configurable": { - "thread_id": doc["thread_id"], - "checkpoint_ns": doc["checkpoint_ns"], - "checkpoint_id": doc["parent_checkpoint_id"], - } - } - if doc.get("parent_checkpoint_id") - else None - ), - pending_writes=pending_writes, - ) - - def put( - self, - config: RunnableConfig, - checkpoint: Checkpoint, - metadata: CheckpointMetadata, - new_versions: ChannelVersions, - ) -> RunnableConfig: - """Save a checkpoint to the database. - - This method saves a checkpoint to the MongoDB database. The checkpoint is associated - with the provided config and its parent config (if any). - - Args: - config (RunnableConfig): The config to associate with the checkpoint. - checkpoint (Checkpoint): The checkpoint to save. - metadata (CheckpointMetadata): Additional metadata to save with the checkpoint. - new_versions (ChannelVersions): New channel versions as of this write. - - Returns: - RunnableConfig: Updated configuration after storing the checkpoint. - - Examples: - - >>> from langgraph.checkpoint.mongodb import MongoDBSaver - >>> with MongoDBSaver.from_conn_string("mongodb://localhost:27017") as memory: - >>> config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}} - >>> checkpoint = {"ts": "2024-05-04T06:32:42.235444+00:00", "id": "1ef4f797-8335-6428-8001-8a1503f9b875", "data": {"key": "value"}} - >>> saved_config = memory.put(config, checkpoint, {"source": "input", "step": 1, "writes": {"key": "value"}}, {}) - >>> print(saved_config) - {'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef4f797-8335-6428-8001-8a1503f9b875'}} - """ - thread_id = config["configurable"]["thread_id"] - checkpoint_ns = config["configurable"]["checkpoint_ns"] - checkpoint_id = checkpoint["id"] - type_, serialized_checkpoint = self.serde.dumps_typed(checkpoint) - doc = { - "parent_checkpoint_id": config["configurable"].get("checkpoint_id"), - "type": type_, - "checkpoint": serialized_checkpoint, - "metadata": dumps_metadata(metadata), - } - upsert_query = { - "thread_id": thread_id, - "checkpoint_ns": checkpoint_ns, - "checkpoint_id": checkpoint_id, - } - self.checkpoint_collection.update_one(upsert_query, {"$set": doc}, upsert=True) - return { - "configurable": { - "thread_id": thread_id, - "checkpoint_ns": checkpoint_ns, - "checkpoint_id": checkpoint_id, - } - } - - def put_writes( - self, - config: RunnableConfig, - writes: Sequence[tuple[str, Any]], - task_id: str, - ) -> None: - """Store intermediate writes linked to a checkpoint. - - This method saves intermediate writes associated with a checkpoint to the MongoDB database. - - Args: - config (RunnableConfig): Configuration of the related checkpoint. - writes (Sequence[tuple[str, Any]]): List of writes to store, each as (channel, value) pair. - task_id (str): Identifier for the task creating the writes. - """ - thread_id = config["configurable"]["thread_id"] - checkpoint_ns = config["configurable"]["checkpoint_ns"] - checkpoint_id = config["configurable"]["checkpoint_id"] - set_method = ( # Allow replacement on existing writes only if there were errors. - "$set" if all(w[0] in WRITES_IDX_MAP for w in writes) else "$setOnInsert" - ) - operations = [] - for idx, (channel, value) in enumerate(writes): - upsert_query = { - "thread_id": thread_id, - "checkpoint_ns": checkpoint_ns, - "checkpoint_id": checkpoint_id, - "task_id": task_id, - "idx": WRITES_IDX_MAP.get(channel, idx), - } - type_, serialized_value = self.serde.dumps_typed(value) - operations.append( - UpdateOne( - upsert_query, - { - set_method: { - "channel": channel, - "type": type_, - "value": serialized_value, - } - }, - upsert=True, - ) - ) - self.writes_collection.bulk_write(operations) +__all__ = ["MongoDBSaver", "AsyncMongoDBSaver"] diff --git a/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/aio.py b/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/aio.py index 5ff9c46..22a8a79 100644 --- a/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/aio.py +++ b/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/aio.py @@ -35,6 +35,9 @@ def aiter(cls: Any) -> Any: return cls.__aiter__() +__all__ = ["AsyncMongoDBSaver"] + + class AsyncMongoDBSaver(BaseCheckpointSaver): """A checkpoint saver that stores checkpoints in a MongoDB database asynchronously. diff --git a/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/saver.py b/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/saver.py new file mode 100644 index 0000000..9803943 --- /dev/null +++ b/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/saver.py @@ -0,0 +1,373 @@ +from collections.abc import Iterator, Sequence +from contextlib import contextmanager +from typing import ( + Any, + Optional, +) + +from langchain_core.runnables import RunnableConfig +from pymongo import MongoClient, UpdateOne +from pymongo.database import Database as MongoDatabase + +from langgraph.checkpoint.base import ( + WRITES_IDX_MAP, + BaseCheckpointSaver, + ChannelVersions, + Checkpoint, + CheckpointMetadata, + CheckpointTuple, + get_checkpoint_id, +) + +from .utils import dumps_metadata, loads_metadata + + +class MongoDBSaver(BaseCheckpointSaver): + """A checkpoint saver that stores StateGraph checkpoints in a MongoDB database. + + Args: + client (MongoClient): The MongoDB connection. + db_name (Optional[str]): Database name + checkpoint_collection_name (Optional[str]): Name of Collection of Checkpoints + writes_collection_name (Optional[str]): Name of Collection of intermediate writes. + + Examples: + + >>> from langgraph.checkpoint.mongodb import MongoDBSaver + >>> from langgraph.graph import StateGraph + >>> from pymongo import MongoClient + >>> + >>> builder = StateGraph(int) + >>> builder.add_node("add_one", lambda x: x + 1) + >>> builder.set_entry_point("add_one") + >>> builder.set_finish_point("add_one") + >>> client = MongoClient("mongodb://localhost:27017") + >>> memory = MongoDBSaver(client) + >>> graph = builder.compile(checkpointer=memory) + >>> config = {"configurable": {"thread_id": "1"}} + >>> graph.get_state(config) + >>> result = graph.invoke(3, config) + >>> graph.get_state(config) + StateSnapshot(values=4, next=(), config={'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef8b22d-df71-6ddc-8001-7c821b5c45fd'}}, metadata={'source': 'loop', 'writes': {'add_one': 4}, 'step': 1, 'parents': {}}, created_at='2024-10-15T18:25:34.088329+00:00', parent_config={'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef8b22d-df6f-6eec-8000-20f621dcf3b7'}}, tasks=()) + """ + + client: MongoClient + db: MongoDatabase + + def __init__( + self, + client: MongoClient, + db_name: str = "checkpointing_db", + checkpoint_collection_name: str = "checkpoints", + writes_collection_name: str = "checkpoint_writes", + **kwargs: Any, + ) -> None: + super().__init__() + self.client = client + self.db = self.client[db_name] + self.checkpoint_collection = self.db[checkpoint_collection_name] + self.writes_collection = self.db[writes_collection_name] + + @classmethod + @contextmanager + def from_conn_string( + cls, + conn_string: Optional[str] = None, + db_name: str = "checkpointing_db", + checkpoint_collection_name: str = "checkpoints", + writes_collection_name: str = "checkpoint_writes", + **kwargs: Any, + ) -> Iterator["MongoDBSaver"]: + """Context manager to create a MongoDB checkpoint saver. + Args: + conn_string: MongoDB connection string. See [class:~pymongo.MongoClient]. + db_name: Database name. It will be created if it doesn't exist. + checkpoint_collection_name: Checkpoint Collection name. Created if it doesn't exist. + writes_collection_name: Collection name of intermediate writes. Created if it doesn't exist. + Yields: A new MongoDBSaver. + """ + client: Optional[MongoClient] = None + try: + client = MongoClient(conn_string) + yield MongoDBSaver( + client, + db_name, + checkpoint_collection_name, + writes_collection_name, + **kwargs, + ) + finally: + if client: + client.close() + + def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]: + """Get a checkpoint tuple from the database. + + This method retrieves a checkpoint tuple from the MongoDB database based on the + provided config. If the config contains a "checkpoint_id" key, the checkpoint with + the matching thread ID and checkpoint ID is retrieved. Otherwise, the latest checkpoint + for the given thread ID is retrieved. + + Args: + config (RunnableConfig): The config to use for retrieving the checkpoint. + + Returns: + Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found. + + Examples: + + Basic: + >>> config = {"configurable": {"thread_id": "1"}} + >>> checkpoint_tuple = memory.get_tuple(config) + >>> print(checkpoint_tuple) + CheckpointTuple(...) + + With checkpoint ID: + >>> config = { + ... "configurable": { + ... "thread_id": "1", + ... "checkpoint_ns": "", + ... "checkpoint_id": "1ef4f797-8335-6428-8001-8a1503f9b875", + ... } + ... } + >>> checkpoint_tuple = memory.get_tuple(config) + >>> print(checkpoint_tuple) + CheckpointTuple(...) + """ + thread_id = config["configurable"]["thread_id"] + checkpoint_ns = config["configurable"].get("checkpoint_ns", "") + if checkpoint_id := get_checkpoint_id(config): + query = { + "thread_id": thread_id, + "checkpoint_ns": checkpoint_ns, + "checkpoint_id": checkpoint_id, + } + else: + query = {"thread_id": thread_id, "checkpoint_ns": checkpoint_ns} + + result = self.checkpoint_collection.find( + query, sort=[("checkpoint_id", -1)], limit=1 + ) + for doc in result: + config_values = { + "thread_id": thread_id, + "checkpoint_ns": checkpoint_ns, + "checkpoint_id": doc["checkpoint_id"], + } + checkpoint = self.serde.loads_typed((doc["type"], doc["checkpoint"])) + serialized_writes = self.writes_collection.find(config_values) + pending_writes = [ + ( + doc["task_id"], + doc["channel"], + self.serde.loads_typed((doc["type"], doc["value"])), + ) + for doc in serialized_writes + ] + return CheckpointTuple( + {"configurable": config_values}, + checkpoint, + loads_metadata(doc["metadata"]), + ( + { + "configurable": { + "thread_id": thread_id, + "checkpoint_ns": checkpoint_ns, + "checkpoint_id": doc["parent_checkpoint_id"], + } + } + if doc.get("parent_checkpoint_id") + else None + ), + pending_writes, + ) + + def list( + self, + config: Optional[RunnableConfig], + *, + filter: Optional[dict[str, Any]] = None, + before: Optional[RunnableConfig] = None, + limit: Optional[int] = None, + ) -> Iterator[CheckpointTuple]: + """List checkpoints from the database. + + This method retrieves a list of checkpoint tuples from the MongoDB database based + on the provided config. The checkpoints are ordered by checkpoint ID in descending order (newest first). + + Args: + config (RunnableConfig): The config to use for listing the checkpoints. + filter (Optional[dict[str, Any]]): Additional filtering criteria for metadata. Defaults to None. + before (Optional[RunnableConfig]): If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None. + limit (Optional[int]): The maximum number of checkpoints to return. Defaults to None. + + Yields: + Iterator[CheckpointTuple]: An iterator of checkpoint tuples. + + Examples: + >>> from langgraph.checkpoint.mongodb import MongoDBSaver + >>> with MongoDBSaver.from_conn_string("mongodb://localhost:27017") as memory: + ... # Run a graph, then list the checkpoints + >>> config = {"configurable": {"thread_id": "1"}} + >>> checkpoints = list(memory.list(config, limit=2)) + >>> print(checkpoints) + [CheckpointTuple(...), CheckpointTuple(...)] + """ + query = {} + if config is not None: + if "thread_id" in config["configurable"]: + query["thread_id"] = config["configurable"]["thread_id"] + if "checkpoint_ns" in config["configurable"]: + query["checkpoint_ns"] = config["configurable"]["checkpoint_ns"] + + if filter: + for key, value in filter.items(): + query[f"metadata.{key}"] = dumps_metadata(value) + + if before is not None: + query["checkpoint_id"] = {"$lt": before["configurable"]["checkpoint_id"]} + + result = self.checkpoint_collection.find( + query, limit=0 if limit is None else limit, sort=[("checkpoint_id", -1)] + ) + + for doc in result: + config_values = { + "thread_id": doc["thread_id"], + "checkpoint_ns": doc["checkpoint_ns"], + "checkpoint_id": doc["checkpoint_id"], + } + serialized_writes = self.writes_collection.find(config_values) + pending_writes = [ + ( + wrt["task_id"], + wrt["channel"], + self.serde.loads_typed((wrt["type"], wrt["value"])), + ) + for wrt in serialized_writes + ] + + yield CheckpointTuple( + config={ + "configurable": { + "thread_id": doc["thread_id"], + "checkpoint_ns": doc["checkpoint_ns"], + "checkpoint_id": doc["checkpoint_id"], + } + }, + checkpoint=self.serde.loads_typed((doc["type"], doc["checkpoint"])), + metadata=loads_metadata(doc["metadata"]), + parent_config=( + { + "configurable": { + "thread_id": doc["thread_id"], + "checkpoint_ns": doc["checkpoint_ns"], + "checkpoint_id": doc["parent_checkpoint_id"], + } + } + if doc.get("parent_checkpoint_id") + else None + ), + pending_writes=pending_writes, + ) + + def put( + self, + config: RunnableConfig, + checkpoint: Checkpoint, + metadata: CheckpointMetadata, + new_versions: ChannelVersions, + ) -> RunnableConfig: + """Save a checkpoint to the database. + + This method saves a checkpoint to the MongoDB database. The checkpoint is associated + with the provided config and its parent config (if any). + + Args: + config (RunnableConfig): The config to associate with the checkpoint. + checkpoint (Checkpoint): The checkpoint to save. + metadata (CheckpointMetadata): Additional metadata to save with the checkpoint. + new_versions (ChannelVersions): New channel versions as of this write. + + Returns: + RunnableConfig: Updated configuration after storing the checkpoint. + + Examples: + + >>> from langgraph.checkpoint.mongodb import MongoDBSaver + >>> with MongoDBSaver.from_conn_string("mongodb://localhost:27017") as memory: + >>> config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}} + >>> checkpoint = {"ts": "2024-05-04T06:32:42.235444+00:00", "id": "1ef4f797-8335-6428-8001-8a1503f9b875", "data": {"key": "value"}} + >>> saved_config = memory.put(config, checkpoint, {"source": "input", "step": 1, "writes": {"key": "value"}}, {}) + >>> print(saved_config) + {'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef4f797-8335-6428-8001-8a1503f9b875'}} + """ + thread_id = config["configurable"]["thread_id"] + checkpoint_ns = config["configurable"]["checkpoint_ns"] + checkpoint_id = checkpoint["id"] + type_, serialized_checkpoint = self.serde.dumps_typed(checkpoint) + doc = { + "parent_checkpoint_id": config["configurable"].get("checkpoint_id"), + "type": type_, + "checkpoint": serialized_checkpoint, + "metadata": dumps_metadata(metadata), + } + upsert_query = { + "thread_id": thread_id, + "checkpoint_ns": checkpoint_ns, + "checkpoint_id": checkpoint_id, + } + self.checkpoint_collection.update_one(upsert_query, {"$set": doc}, upsert=True) + return { + "configurable": { + "thread_id": thread_id, + "checkpoint_ns": checkpoint_ns, + "checkpoint_id": checkpoint_id, + } + } + + def put_writes( + self, + config: RunnableConfig, + writes: Sequence[tuple[str, Any]], + task_id: str, + ) -> None: + """Store intermediate writes linked to a checkpoint. + + This method saves intermediate writes associated with a checkpoint to the MongoDB database. + + Args: + config (RunnableConfig): Configuration of the related checkpoint. + writes (Sequence[tuple[str, Any]]): List of writes to store, each as (channel, value) pair. + task_id (str): Identifier for the task creating the writes. + """ + thread_id = config["configurable"]["thread_id"] + checkpoint_ns = config["configurable"]["checkpoint_ns"] + checkpoint_id = config["configurable"]["checkpoint_id"] + set_method = ( # Allow replacement on existing writes only if there were errors. + "$set" if all(w[0] in WRITES_IDX_MAP for w in writes) else "$setOnInsert" + ) + operations = [] + for idx, (channel, value) in enumerate(writes): + upsert_query = { + "thread_id": thread_id, + "checkpoint_ns": checkpoint_ns, + "checkpoint_id": checkpoint_id, + "task_id": task_id, + "idx": WRITES_IDX_MAP.get(channel, idx), + } + type_, serialized_value = self.serde.dumps_typed(value) + operations.append( + UpdateOne( + upsert_query, + { + set_method: { + "channel": channel, + "type": type_, + "value": serialized_value, + } + }, + upsert=True, + ) + ) + self.writes_collection.bulk_write(operations) diff --git a/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/utils.py b/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/utils.py index 163393b..d3d4a73 100644 --- a/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/utils.py +++ b/libs/langgraph-checkpoint-mongodb/langgraph/checkpoint/mongodb/utils.py @@ -1,3 +1,8 @@ +""" +:private: +Utilities for langchain-checkpoint-mongod. +""" + from typing import Any, Union from langgraph.checkpoint.base import CheckpointMetadata diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..67c0982 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,35 @@ +[project] +name = "langchain-mongodb-monorepo" +version = "0.1.0" +description = "LangChain MongoDB mono-repo" +readme = "README.md" +requires-python = ">=3.9" 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