docstrings added (#11988)

Added docstrings. Some docsctrings formatting.

libs/langchain/langchain/chat_models/bedrock.py

@@ -34,6 +34,8 @@ class ChatPromptAdapter:
 
 
 class BedrockChat(BaseChatModel, BedrockBase):
+    """A chat model that uses the Bedrock API."""
+
     @property
     def _llm_type(self) -> str:
         """Return type of chat model."""

libs/langchain/langchain/chat_models/fake.py

@@ -14,6 +14,8 @@ from langchain.schema.output import ChatGeneration, ChatGenerationChunk
 
 
 class FakeMessagesListChatModel(BaseChatModel):
+    """Fake ChatModel for testing purposes."""
+
     responses: List[BaseMessage]
     sleep: Optional[float] = None
     i: int = 0

libs/langchain/langchain/chat_models/litellm.py

@@ -162,6 +162,8 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
 
 
 class ChatLiteLLM(BaseChatModel):
+    """A chat model that uses the LiteLLM API."""
+
     client: Any  #: :meta private:
     model: str = "gpt-3.5-turbo"
     model_name: Optional[str] = None

libs/langchain/langchain/document_loaders/base_o365.py

@@ -44,6 +44,7 @@ class _FileType(str, Enum):
 
 
 def fetch_mime_types(file_types: Sequence[_FileType]) -> Dict[str, str]:
+    """Fetch the mime types for the specified file types."""
     mime_types_mapping = {}
     for file_type in file_types:
         if file_type.value == "doc":
@@ -58,6 +59,8 @@ def fetch_mime_types(file_types: Sequence[_FileType]) -> Dict[str, str]:
 
 
 class O365BaseLoader(BaseLoader, BaseModel):
+    """Base class for all loaders that uses O365 Package"""
+
     settings: _O365Settings = Field(default_factory=_O365Settings)
     """Settings for the Office365 API client."""
     auth_with_token: bool = False

libs/langchain/langchain/llms/bedrock.py

@@ -141,6 +141,8 @@ class LLMInputOutputAdapter:
 
 
 class BedrockBase(BaseModel, ABC):
+    """Base class for Bedrock models."""
+
     client: Any  #: :meta private:
 
     region_name: Optional[str] = None

libs/langchain/langchain/llms/cohere.py

@@ -63,6 +63,8 @@ def acompletion_with_retry(llm: Cohere, **kwargs: Any) -> Any:
 
 
 class BaseCohere(Serializable):
+    """Base class for Cohere models."""
+
     client: Any  #: :meta private:
     async_client: Any  #: :meta private:
     model: Optional[str] = Field(default=None)

libs/langchain/langchain/llms/minimax.py

@@ -54,6 +54,8 @@ class _MinimaxEndpointClient(BaseModel):
 
 
 class MinimaxCommon(BaseModel):
+    """Common parameters for Minimax large language models."""
+
     _client: _MinimaxEndpointClient
     model: str = "abab5.5-chat"
     """Model name to use."""

libs/langchain/langchain/llms/titan_takeoff.py

@@ -10,6 +10,8 @@ from langchain.schema.output import GenerationChunk
 
 
 class TitanTakeoff(LLM):
+    """Wrapper around Titan Takeoff APIs."""
+
     base_url: str = "http://localhost:8000"
     """Specifies the baseURL to use for the Titan Takeoff API. 
     Default = http://localhost:8000.

libs/langchain/langchain/retrievers/google_vertex_ai_search.py

@@ -319,6 +319,8 @@ class GoogleVertexAISearchRetriever(BaseRetriever, _BaseGoogleVertexAISearchRetr
 class GoogleVertexAIMultiTurnSearchRetriever(
     BaseRetriever, _BaseGoogleVertexAISearchRetriever
 ):
+    """`Google Vertex AI Search` retriever for multi-turn conversations."""
+
     _client: ConversationalSearchServiceClient
 
     class Config:

libs/langchain/langchain/schema/runnable/base.py

@@ -981,6 +981,8 @@ class Runnable(Generic[Input, Output], ABC):
 
 
 class RunnableSerializable(Serializable, Runnable[Input, Output]):
+    """A Runnable that can be serialized to JSON."""
+
     def configurable_fields(
         self, **kwargs: AnyConfigurableField
     ) -> RunnableSerializable[Input, Output]:

libs/langchain/langchain/schema/runnable/configurable.py

@@ -37,6 +37,8 @@ from langchain.schema.runnable.utils import (
 
 
 class DynamicRunnable(RunnableSerializable[Input, Output]):
+    """A Serializable Runnable that can be dynamically configured."""
+
     default: RunnableSerializable[Input, Output]
 
     class Config:
@@ -198,6 +200,8 @@ class DynamicRunnable(RunnableSerializable[Input, Output]):
 
 
 class RunnableConfigurableFields(DynamicRunnable[Input, Output]):
+    """A Runnable that can be dynamically configured."""
+
     fields: Dict[str, AnyConfigurableField]
 
     @property
@@ -261,6 +265,8 @@ class RunnableConfigurableFields(DynamicRunnable[Input, Output]):
 
 # Before Python 3.11 native StrEnum is not available
 class StrEnum(str, enum.Enum):
+    """A string enum."""
+
     pass
 
 
@@ -275,6 +281,8 @@ _enums_for_spec_lock = threading.Lock()
 
 
 class RunnableConfigurableAlternatives(DynamicRunnable[Input, Output]):
+    """A Runnable that can be dynamically configured."""
+
     which: ConfigurableField
 
     alternatives: Dict[str, RunnableSerializable[Input, Output]]
@@ -332,6 +340,8 @@ def make_options_spec(
     spec: Union[ConfigurableFieldSingleOption, ConfigurableFieldMultiOption],
     description: Optional[str],
 ) -> ConfigurableFieldSpec:
+    """Make a ConfigurableFieldSpec for a ConfigurableFieldSingleOption or
+    ConfigurableFieldMultiOption."""
     with _enums_for_spec_lock:
         if enum := _enums_for_spec.get(spec):
             pass

libs/langchain/langchain/tools/bearly/tool.py

@@ -12,12 +12,14 @@ from langchain.tools import Tool
 
 
 def strip_markdown_code(md_string: str) -> str:
+    """Strip markdown code from a string."""
     stripped_string = re.sub(r"^`{1,3}.*?\n", "", md_string, flags=re.DOTALL)
     stripped_string = re.sub(r"`{1,3}$", "", stripped_string)
     return stripped_string
 
 
 def head_file(path: str, n: int) -> List[str]:
+    """Get the first n lines of a file."""
     try:
         with open(path, "r") as f:
             return [str(line) for line in itertools.islice(f, n)]
@@ -26,11 +28,14 @@ def head_file(path: str, n: int) -> List[str]:
 
 
 def file_to_base64(path: str) -> str:
+    """Convert a file to base64."""
     with open(path, "rb") as f:
         return base64.b64encode(f.read()).decode()
 
 
 class BearlyInterpreterToolArguments(BaseModel):
+    """Arguments for the BearlyInterpreterTool."""
+
     python_code: str = Field(
         ...,
         example="print('Hello World')",
@@ -58,12 +63,16 @@ print() any output and results so you can capture the output."""
 
 
 class FileInfo(BaseModel):
+    """Information about a file to be uploaded."""
+
     source_path: str
     description: str
     target_path: str
 
 
 class BearlyInterpreterTool:
+    """Tool for evaluating python code in a sandbox environment."""
+
     api_key: str
     endpoint = "https://exec.bearly.ai/v1/interpreter"
     name = "bearly_interpreter"

libs/langchain/langchain/tools/python/tool.py

@@ -24,6 +24,7 @@ def _get_default_python_repl() -> PythonREPL:
 
 def sanitize_input(query: str) -> str:
     """Sanitize input to the python REPL.
+
     Remove whitespace, backtick & python (if llm mistakes python console as terminal)
 
     Args:
@@ -99,6 +100,8 @@ class PythonREPLTool(BaseTool):
 
 
 class PythonInputs(BaseModel):
+    """Python inputs."""
+
     query: str = Field(description="code snippet to run")
 
 

libs/langchain/langchain/utilities/anthropic.py

@@ -14,11 +14,13 @@ def _get_anthropic_client() -> Any:
 
 
 def get_num_tokens_anthropic(text: str) -> int:
+    """Get the number of tokens in a string of text."""
     client = _get_anthropic_client()
     return client.count_tokens(text=text)
 
 
 def get_token_ids_anthropic(text: str) -> List[int]:
+    """Get the token ids for a string of text."""
     client = _get_anthropic_client()
     tokenizer = client.get_tokenizer()
     encoded_text = tokenizer.encode(text)

libs/langchain/langchain/utilities/arcee.py

@@ -12,18 +12,22 @@ from langchain.schema.retriever import Document
 
 
 class ArceeRoute(str, Enum):
+    """Routes available for the Arcee API as enumerator."""
+
     generate = "models/generate"
     retrieve = "models/retrieve"
     model_training_status = "models/status/{id_or_name}"
 
 
 class DALMFilterType(str, Enum):
+    """Filter types available for a DALM retrieval as enumerator."""
+
     fuzzy_search = "fuzzy_search"
     strict_search = "strict_search"
 
 
 class DALMFilter(BaseModel):
-    """Filters available for a dalm retrieval and generation
+    """Filters available for a DALM retrieval and generation.
 
     Arguments:
         field_name: The field to filter on. Can be 'document' or 'name' to filter
@@ -56,6 +60,8 @@ class DALMFilter(BaseModel):
 
 
 class ArceeWrapper:
+    """Wrapper for Arcee API."""
+
     def __init__(
         self,
         arcee_api_key: str,
@@ -64,6 +70,16 @@ class ArceeWrapper:
         model_kwargs: Optional[Dict[str, Any]],
         model_name: str,
     ):
+        """Initialize ArceeWrapper.
+
+        Arguments:
+            arcee_api_key: API key for Arcee API.
+            arcee_api_url: URL for Arcee API.
+            arcee_api_version: Version of Arcee API.
+            model_kwargs: Keyword arguments for Arcee API.
+            model_name: Name of an Arcee model.
+
+        """
         self.arcee_api_key = arcee_api_key
         self.model_kwargs = model_kwargs
         self.arcee_api_url = arcee_api_url
@@ -150,7 +166,7 @@ class ArceeWrapper:
         Args:
             prompt: Prompt to generate text from.
             size: The max number of context results to retrieve. Defaults to 3.
-            (Can be less if filters are provided).
+              (Can be less if filters are provided).
             filters: Filters to apply to the context dataset.
         """
 
@@ -174,7 +190,7 @@ class ArceeWrapper:
         Args:
             query: Query to submit to the model
             size: The max number of context results to retrieve. Defaults to 3.
-            (Can be less if filters are provided).
+              (Can be less if filters are provided).
             filters: Filters to apply to the context dataset.
         """
 

libs/langchain/langchain/utilities/clickup.py

@@ -14,6 +14,8 @@ DEFAULT_URL = "https://api.clickup.com/api/v2"
 
 @dataclass
 class Component:
+    """Base class for all components."""
+
     @classmethod
     def from_data(cls, data: Dict[str, Any]) -> "Component":
         raise NotImplementedError()
@@ -21,6 +23,8 @@ class Component:
 
 @dataclass
 class Task(Component):
+    """Class for a task."""
+
     id: int
     name: str
     text_content: str
@@ -63,6 +67,8 @@ class Task(Component):
 
 @dataclass
 class CUList(Component):
+    """Component class for a list."""
+
     folder_id: float
     name: str
     content: Optional[str] = None
@@ -88,6 +94,8 @@ class CUList(Component):
 
 @dataclass
 class Member(Component):
+    """Component class for a member."""
+
     id: int
     username: str
     email: str
@@ -105,6 +113,8 @@ class Member(Component):
 
 @dataclass
 class Team(Component):
+    """Component class for a team."""
+
     id: int
     name: str
     members: List[Member]
@@ -117,6 +127,8 @@ class Team(Component):
 
 @dataclass
 class Space(Component):
+    """Component class for a space."""
+
     id: int
     name: str
     private: bool
@@ -141,11 +153,12 @@ class Space(Component):
 def parse_dict_through_component(
     data: dict, component: Type[Component], fault_tolerant: bool = False
 ) -> Dict:
-    """This is a helper function that helps us parse a dictionary by creating
-    a component and then turning it back into a dictionary. This might seem
-    silly but it's a nice way to:
-    1. Extract and format data from a dictionary according to a schema
-    2. Provide a central place to do this in a fault tolerant way
+    """Parse a dictionary by creating
+    a component and then turning it back into a dictionary.
+
+    This helps with two things
+    1. Extract and format data from a dictionary according to schema
+    2. Provide a central place to do this in a fault-tolerant way
 
     """
     try:
@@ -163,6 +176,16 @@ def parse_dict_through_component(
 def extract_dict_elements_from_component_fields(
     data: dict, component: Type[Component]
 ) -> dict:
+    """Extract elements from a dictionary.
+
+    Args:
+        data: The dictionary to extract elements from.
+        component: The component to extract elements from.
+
+    Returns:
+        A dictionary containing the elements from the input dictionary that are also
+        in the component.
+    """
     output = {}
     for attribute in fields(component):
         if attribute.name in data:
@@ -173,8 +196,8 @@ def extract_dict_elements_from_component_fields(
 def load_query(
     query: str, fault_tolerant: bool = False
 ) -> Tuple[Optional[Dict], Optional[str]]:
-    """
-    Attempts to parse a JSON string and return the parsed object.
+    """Attempts to parse a JSON string and return the parsed object.
+
     If parsing fails, returns an error message.
 
     :param query: The JSON string to parse.
@@ -194,6 +217,7 @@ def load_query(
 
 
 def fetch_first_id(data: dict, key: str) -> Optional[int]:
+    """Fetch the first id from a dictionary."""
     if key in data and len(data[key]) > 0:
         if len(data[key]) > 1:
             warnings.warn(f"Found multiple {key}: {data[key]}. Defaulting to first.")
@@ -202,6 +226,7 @@ def fetch_first_id(data: dict, key: str) -> Optional[int]:
 
 
 def fetch_data(url: str, access_token: str, query: Optional[dict] = None) -> dict:
+    """Fetch data from a URL."""
     headers = {"Authorization": access_token}
     response = requests.get(url, headers=headers, params=query)
     response.raise_for_status()
@@ -209,24 +234,28 @@ def fetch_data(url: str, access_token: str, query: Optional[dict] = None) -> dic
 
 
 def fetch_team_id(access_token: str) -> Optional[int]:
+    """Fetch the team id."""
     url = f"{DEFAULT_URL}/team"
     data = fetch_data(url, access_token)
     return fetch_first_id(data, "teams")
 
 
 def fetch_space_id(team_id: int, access_token: str) -> Optional[int]:
+    """Fetch the space id."""
     url = f"{DEFAULT_URL}/team/{team_id}/space"
     data = fetch_data(url, access_token, query={"archived": "false"})
     return fetch_first_id(data, "spaces")
 
 
 def fetch_folder_id(space_id: int, access_token: str) -> Optional[int]:
+    """Fetch the folder id."""
     url = f"{DEFAULT_URL}/space/{space_id}/folder"
     data = fetch_data(url, access_token, query={"archived": "false"})
     return fetch_first_id(data, "folders")
 
 
 def fetch_list_id(space_id: int, folder_id: int, access_token: str) -> Optional[int]:
+    """Fetch the list id."""
     if folder_id:
         url = f"{DEFAULT_URL}/folder/{folder_id}/list"
     else:
@@ -259,6 +288,7 @@ class ClickupAPIWrapper(BaseModel):
     def get_access_code_url(
         cls, oauth_client_id: str, redirect_uri: str = "https://google.com"
     ) -> str:
+        """Get the URL to get an access code."""
         url = f"https://app.clickup.com/api?client_id={oauth_client_id}"
         return f"{url}&redirect_uri={redirect_uri}"
 
@@ -266,6 +296,7 @@ class ClickupAPIWrapper(BaseModel):
     def get_access_token(
         cls, oauth_client_id: str, oauth_client_secret: str, code: str
     ) -> Optional[str]:
+        """Get the access token."""
         url = f"{DEFAULT_URL}/oauth/token"
 
         params = {
@@ -291,9 +322,7 @@ class ClickupAPIWrapper(BaseModel):
 
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
-        """
-        Validate that api key and python package exists in environment
-        """
+        """Validate that api key and python package exists in environment."""
         values["access_token"] = get_from_dict_or_env(
             values, "access_token", "CLICKUP_ACCESS_TOKEN"
         )
@@ -309,10 +338,7 @@ class ClickupAPIWrapper(BaseModel):
         return values
 
     def attempt_parse_teams(self, input_dict: dict) -> Dict[str, List[dict]]:
-        """
-        Parse appropriate content from the list of teams
-        """
-
+        """Parse appropriate content from the list of teams."""
         parsed_teams: Dict[str, List[dict]] = {"teams": []}
         for team in input_dict["teams"]:
             try:
@@ -326,6 +352,7 @@ class ClickupAPIWrapper(BaseModel):
     def get_headers(
         self,
     ) -> Mapping[str, Union[str, bytes]]:
+        """Get the headers for the request."""
         if not isinstance(self.access_token, str):
             raise TypeError(f"Access Token: {self.access_token}, must be str.")
 
@@ -339,9 +366,7 @@ class ClickupAPIWrapper(BaseModel):
         return {"archived": "false"}
 
     def get_authorized_teams(self) -> Dict[Any, Any]:
-        """
-        Get all teams for the user
-        """
+        """Get all teams for the user."""
         url = f"{DEFAULT_URL}/team"
 
         response = requests.get(url, headers=self.get_headers())
@@ -353,7 +378,7 @@ class ClickupAPIWrapper(BaseModel):
 
     def get_folders(self) -> Dict:
         """
-        Get all the folders for the team
+        Get all the folders for the team.
         """
         url = f"{DEFAULT_URL}/team/" + str(self.team_id) + "/space"
         params = self.get_default_params()
@@ -362,7 +387,7 @@ class ClickupAPIWrapper(BaseModel):
 
     def get_task(self, query: str, fault_tolerant: bool = True) -> Dict:
         """
-        Retrieve a specific task
+        Retrieve a specific task.
         """
 
         params, error = load_query(query, fault_tolerant=True)
@@ -385,7 +410,7 @@ class ClickupAPIWrapper(BaseModel):
 
     def get_lists(self) -> Dict:
         """
-        Get all available lists
+        Get all available lists.
         """
 
         url = f"{DEFAULT_URL}/folder/{self.folder_id}/list"
@@ -410,7 +435,7 @@ class ClickupAPIWrapper(BaseModel):
 
     def get_spaces(self) -> Dict:
         """
-        Get all spaces for the team
+        Get all spaces for the team.
         """
         url = f"{DEFAULT_URL}/team/{self.team_id}/space"
         response = requests.get(
@@ -422,7 +447,7 @@ class ClickupAPIWrapper(BaseModel):
 
     def get_task_attribute(self, query: str) -> Dict:
         """
-        Update an attribute of a specified task
+        Update an attribute of a specified task.
         """
 
         task = self.get_task(query, fault_tolerant=True)
@@ -440,7 +465,7 @@ found in task keys {task.keys()}. Please call again with one of the key names.""
 
     def update_task(self, query: str) -> Dict:
         """
-        Update an attribute of a specified task
+        Update an attribute of a specified task.
         """
         query_dict, error = load_query(query, fault_tolerant=True)
         if query_dict is None:
@@ -461,7 +486,7 @@ found in task keys {task.keys()}. Please call again with one of the key names.""
 
     def update_task_assignees(self, query: str) -> Dict:
         """
-        Add or remove assignees of a specified task
+        Add or remove assignees of a specified task.
         """
         query_dict, error = load_query(query, fault_tolerant=True)
         if query_dict is None:
@@ -500,7 +525,7 @@ found in task keys {task.keys()}. Please call again with one of the key names.""
 
     def create_task(self, query: str) -> Dict:
         """
-        Creates a new task
+        Creates a new task.
         """
         query_dict, error = load_query(query, fault_tolerant=True)
         if query_dict is None:
@@ -519,7 +544,7 @@ found in task keys {task.keys()}. Please call again with one of the key names.""
 
     def create_list(self, query: str) -> Dict:
         """
-        Creates a new list
+        Creates a new list.
         """
         query_dict, error = load_query(query, fault_tolerant=True)
         if query_dict is None:
@@ -543,7 +568,7 @@ found in task keys {task.keys()}. Please call again with one of the key names.""
 
     def create_folder(self, query: str) -> Dict:
         """
-        Creates a new folder
+        Creates a new folder.
         """
 
         query_dict, error = load_query(query, fault_tolerant=True)
@@ -566,6 +591,7 @@ found in task keys {task.keys()}. Please call again with one of the key names.""
         return data
 
     def run(self, mode: str, query: str) -> str:
+        """Run the API."""
         if mode == "get_task":
             output = self.get_task(query)
         elif mode == "get_task_attribute":

libs/langchain/langchain/vectorstores/azure_cosmos_db.py

@@ -29,9 +29,14 @@ if TYPE_CHECKING:
 
 # Before Python 3.11 native StrEnum is not available
 class CosmosDBSimilarityType(str, Enum):
-    COS = "COS"  # CosineSimilarity
-    IP = "IP"  # inner - product
-    L2 = "L2"  # Euclidean distance
+    """Cosmos DB Similarity Type as enumerator."""
+
+    COS = "COS"
+    """CosineSimilarity"""
+    IP = "IP"
+    """inner - product"""
+    L2 = "L2"
+    """Euclidean distance"""
 
 
 CosmosDBDocumentType = TypeVar("CosmosDBDocumentType", bound=Dict[str, Any])