style: refs work (#379)

mdrxy · web-flow · commit be67d034610a · 2025-10-22T11:50:37.000-04:00
diff --git a/libs/community/langchain_community/callbacks/clearml_callback.py b/libs/community/langchain_community/callbacks/clearml_callback.py
@@ -323,7 +323,7 @@ def analyze_text(self, text: str) -> dict:
             text (str): The text to analyze.
 
         Returns:
-            (dict): A dictionary containing the complexity metrics.
+            `dict` containing the complexity metrics.
         """
         resp = {}
         textstat = import_textstat()
diff --git a/libs/community/langchain_community/callbacks/comet_ml_callback.py b/libs/community/langchain_community/callbacks/comet_ml_callback.py
@@ -377,7 +377,7 @@ def _get_complexity_metrics(self, text: str) -> dict:
             text (str): The text to analyze.
 
         Returns:
-            (dict): A dictionary containing the complexity metrics.
+            `dict` containing the complexity metrics.
         """
         resp = {}
         if self.complexity_metrics:
@@ -397,7 +397,7 @@ def _get_custom_metrics(
             gen_idx (int): List index of the generated output
 
         Returns:
-            dict: A dictionary containing the custom metrics.
+            dict: `dict` containing the custom metrics.
         """
 
         resp = {}
diff --git a/libs/community/langchain_community/callbacks/flyte_callback.py b/libs/community/langchain_community/callbacks/flyte_callback.py
@@ -48,7 +48,7 @@ def analyze_text(
         nlp (spacy.lang): The spacy language model to use for visualization.
 
     Returns:
-        (dict): A dictionary containing the complexity metrics and visualization
+        `dict` containing the complexity metrics and visualization
             files serialized to HTML string.
     """
     resp: Dict[str, Any] = {}
diff --git a/libs/community/langchain_community/callbacks/mlflow_callback.py b/libs/community/langchain_community/callbacks/mlflow_callback.py
@@ -87,7 +87,7 @@ def analyze_text(
         textstat: The textstat library to use for complexity metrics calculation.
 
     Returns:
-        (dict): A dictionary containing the complexity metrics and visualization
+        `dict` containing the complexity metrics and visualization
             files serialized to  HTML string.
     """
     resp: Dict[str, Any] = {}
diff --git a/libs/community/langchain_community/callbacks/tracers/wandb.py b/libs/community/langchain_community/callbacks/tracers/wandb.py
@@ -424,8 +424,8 @@ def create_trace(
                 If provided, the created trace is added as a child to the parent trace.
 
             Returns:
-                Optional[Trace]: The created trace.
-                 If an error occurs during the creation of the trace, None is returned.
+                The created trace. If an error occurs during the creation of the trace,
+                    None is returned.
 
             Raises:
                 Exception: If an error occurs during the creation of the trace,
@@ -443,7 +443,7 @@ def get_metadata_dict(r: "Run") -> Dict[str, Any]:
                     r (Run): The run from which to extract metadata.
 
                 Returns:
-                    Dict[str, Any]: A dictionary containing the extracted metadata.
+                    `dict` containing the extracted metadata.
                 """
                 run_dict = json.loads(r.json())
                 metadata_dict = run_dict.get("metadata", {})
diff --git a/libs/community/langchain_community/callbacks/wandb_callback.py b/libs/community/langchain_community/callbacks/wandb_callback.py
@@ -56,7 +56,7 @@ def analyze_text(
         output_dir (str): The directory to save the visualization files to.
 
     Returns:
-        (dict): A dictionary containing the complexity metrics and visualization
+        `dict` containing the complexity metrics and visualization
             files serialized in a wandb.Html element.
     """
     resp = {}
diff --git a/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py b/libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py
@@ -343,7 +343,7 @@ class Joke(BaseModel):
     """  # noqa: E501
 
     init_kwargs: Dict[str, Any] = Field(default_factory=dict)
-    """init kwargs for qianfan client init, such as `query_per_second` which is 
+    """init kwargs for qianfan client init, such as `query_per_second` which is
         associated with qianfan resource object to limit QPS"""
 
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
@@ -375,7 +375,7 @@ class Joke(BaseModel):
     model: Optional[str] = Field(default=None)
     """Model name.
     you could get from https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu
-    
+
     preset models are mapping to an endpoint.
     `model` will be ignored if `endpoint` is set.
     Default is set by `qianfan` SDK, not here
@@ -475,8 +475,7 @@ def _convert_prompt_msg_params(
             resulting dictionary.
 
         Returns:
-            Dict[str, Any]: A dictionary containing the message content and default
-            parameters.
+            `dict` containing the message content and default parameters.
 
         """
         messages_dict: Dict[str, Any] = {
diff --git a/libs/community/langchain_community/chat_models/oci_data_science.py b/libs/community/langchain_community/chat_models/oci_data_science.py
@@ -319,7 +319,7 @@ def _headers(
                 the request is asynchronous.
 
         Returns:
-            Dict: A dictionary containing the appropriate headers for the request.
+            `dict` containing the appropriate headers for the request.
         """
         return {
             "route": DEFAULT_INFERENCE_ENDPOINT_CHAT,
@@ -829,7 +829,7 @@ class ChatOCIModelDeploymentVLLM(ChatOCIModelDeployment):
     """Number of most likely tokens to consider at each step."""
 
     min_p: Optional[float] = 0.0
-    """Float that represents the minimum probability for a token to be considered. 
+    """Float that represents the minimum probability for a token to be considered.
     Must be in [0,1]. 0 to disable this."""
 
     repetition_penalty: Optional[float] = 1.0
@@ -853,7 +853,7 @@ class ChatOCIModelDeploymentVLLM(ChatOCIModelDeployment):
     the EOS token is generated."""
 
     min_tokens: Optional[int] = 0
-    """Minimum number of tokens to generate per output sequence before 
+    """Minimum number of tokens to generate per output sequence before
     EOS or stop_token_ids can be generated"""
 
     stop_token_ids: Optional[List[int]] = None
@@ -871,7 +871,7 @@ class ChatOCIModelDeploymentVLLM(ChatOCIModelDeployment):
     tool_choice: Optional[str] = None
     """Whether to use tool calling.
     Defaults to None, tool calling is disabled.
-    Tool calling requires model support and the vLLM to be configured 
+    Tool calling requires model support and the vLLM to be configured
     with `--tool-call-parser`.
     Set this to `auto` for the model to make tool calls automatically.
     Set this to `required` to force the model to always call one or more tools.
@@ -991,9 +991,9 @@ class ChatOCIModelDeploymentTGI(ChatOCIModelDeployment):
     """Total probability mass of tokens to consider at each step."""
 
     top_logprobs: Optional[int] = None
-    """An integer between 0 and 5 specifying the number of most 
-    likely tokens to return at each token position, each with an 
-    associated log probability. logprobs must be set to true if 
+    """An integer between 0 and 5 specifying the number of most
+    likely tokens to return at each token position, each with an
+    associated log probability. logprobs must be set to true if
     this parameter is used."""
 
     @property
diff --git a/libs/community/langchain_community/document_loaders/csv_loader.py b/libs/community/langchain_community/document_loaders/csv_loader.py
@@ -14,7 +14,7 @@
 
 
 class CSVLoader(BaseLoader):
-    """Load a `CSV` file into a list of Documents.
+    """Load a `CSV` file into a list of `Document` objects.
 
     Each document represents one row of the CSV file. Every row is converted
     into a key/value pair and outputted to a new line in the document's
diff --git a/libs/community/langchain_community/document_loaders/datadog_logs.py b/libs/community/langchain_community/document_loaders/datadog_logs.py
@@ -80,7 +80,7 @@ def load(self) -> List[Document]:
         Get logs from Datadog.
 
         Returns:
-            A list of Document objects.
+            A list of `Document` objects.
                 - page_content
                 - metadata
                     - id
diff --git a/libs/community/langchain_community/document_loaders/docugami.py b/libs/community/langchain_community/document_loaders/docugami.py
@@ -109,7 +109,7 @@ def _parse_dgml(
         document_name: Optional[str] = None,
         additional_doc_metadata: Optional[Mapping] = None,
     ) -> List[Document]:
-        """Parse a single DGML document into a list of Documents."""
+        """Parse a single DGML document into a list of `Document` objects."""
         try:
             from lxml import etree
         except ImportError:
diff --git a/libs/community/langchain_community/document_loaders/pebblo.py b/libs/community/langchain_community/document_loaders/pebblo.py
@@ -208,7 +208,7 @@ def _add_semantic_to_docs(self, classified_docs: Dict) -> List[Document]:
                 classified documents with pb_id as key.
 
         Returns:
-            List[Document]: A list of Document objects with added semantic metadata.
+            A list of `Document` objects with added semantic metadata.
         """
         indexed_docs = {
             doc.pb_id: Document(page_content=doc.page_content, metadata=doc.metadata)
@@ -226,10 +226,10 @@ def _add_semantic_to_docs(self, classified_docs: Dict) -> List[Document]:
 
     def _unindex_docs(self) -> List[Document]:
         """
-        Converts a list of IndexedDocument objects to a list of Document objects.
+        Converts a list of `IndexedDocument` objects to a list of `Document` objects.
 
         Returns:
-            List[Document]: A list of Document objects.
+            A list of `Document` objects.
         """
         docs = [
             Document(page_content=doc.page_content, metadata=doc.metadata)
@@ -243,7 +243,7 @@ def _add_semantic_to_doc(self, doc: Document, classified_doc: dict) -> Document:
 
         Args:
             doc (Document): A Document object.
-            classified_doc (dict): A dictionary containing the classified document.
+            classified_doc: `dict` containing the classified document.
 
         Returns:
             Document: The Document object with added semantic metadata.
diff --git a/libs/community/langchain_community/document_loaders/sharepoint.py b/libs/community/langchain_community/document_loaders/sharepoint.py
@@ -181,8 +181,8 @@ def get_extended_metadata(self, file_id: str) -> Dict:
         Args:
             file_id (str): The ID of the file.
         Returns:
-            dict: A dictionary containing the extended metadata of the file,
-                  including size, owner, and full path.
+            `dict` containing the extended metadata of the file, including size, owner,
+                and full path.
         """
         data = self._fetch_access_token()
         access_token = data.get("access_token")
diff --git a/libs/community/langchain_community/document_loaders/wikipedia.py b/libs/community/langchain_community/document_loaders/wikipedia.py
@@ -44,10 +44,10 @@ def __init__(
 
     def lazy_load(self) -> Iterator[Document]:
         """
-        Loads the query result from Wikipedia into a list of Documents.
+        Loads the query result from Wikipedia into a list of `Document` objects.
 
         Returns:
-            A list of Document objects representing the loaded
+            A list of `Document` objects representing the loaded
                 Wikipedia pages.
         """
         client = WikipediaAPIWrapper(  # type: ignore[call-arg]
diff --git a/libs/community/langchain_community/document_transformers/beautiful_soup_transformer.py b/libs/community/langchain_community/document_transformers/beautiful_soup_transformer.py
@@ -42,15 +42,15 @@ def transform_documents(
         **kwargs: Any,
     ) -> Sequence[Document]:
         """
-        Transform a list of Document objects by cleaning their HTML content.
+        Transform a list of `Document` objects by cleaning their HTML content.
 
         Args:
-            documents: A sequence of Document objects containing HTML content.
+            documents: A sequence of `Document` objects containing HTML content.
             unwanted_tags: A list of tags to be removed from the HTML.
             tags_to_extract: A list of tags whose content will be extracted.
-            remove_lines: If set to True, unnecessary lines will be removed.
+            remove_lines: If set to `True`, unnecessary lines will be removed.
             unwanted_classnames: A list of class names to be removed from the HTML
-            remove_comments: If set to True, comments will be removed.
+            remove_comments: If set to `True`, comments will be removed.
 
         Returns:
             A sequence of Document objects with transformed content.
diff --git a/libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py b/libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py
@@ -122,7 +122,7 @@ def _headers(
                 the request is asynchronous.
 
         Returns:
-            Dict: A dictionary containing the appropriate headers for the request.
+            `dict` containing the appropriate headers for the request.
         """
         headers = self.default_headers or {}
         if is_async:
@@ -497,7 +497,7 @@ def _headers(
                 the request is asynchronous.
 
         Returns:
-            Dict: A dictionary containing the appropriate headers for the request.
+            Dict: `dict` containing the appropriate headers for the request.
         """
         return {
             "route": DEFAULT_INFERENCE_ENDPOINT,
diff --git a/libs/community/langchain_community/utilities/clickup.py b/libs/community/langchain_community/utilities/clickup.py
@@ -183,8 +183,8 @@ def extract_dict_elements_from_component_fields(
         component: The component to extract elements from.
 
     Returns:
-        A dictionary containing the elements from the input dictionary that are also
-        in the component.
+        `dict` containing the elements from the input dictionary that are also in the
+            component.
     """
     output = {}
     for attribute in fields(component):
@@ -212,7 +212,7 @@ def load_query(
         if fault_tolerant:
             return (
                 None,
-                f"""Input must be a valid JSON. Got the following error: {str(e)}. 
+                f"""Input must be a valid JSON. Got the following error: {str(e)}.
 "Please reformat and try again.""",
             )
         else:
@@ -460,7 +460,7 @@ def get_task_attribute(self, query: str) -> Dict:
 
         if params["attribute_name"] not in task:
             return {
-                "Error": f"""attribute_name = {params["attribute_name"]} was not 
+                "Error": f"""attribute_name = {params["attribute_name"]} was not
 found in task keys {task.keys()}. Please call again with one of the key names."""
             }
 
diff --git a/libs/community/langchain_community/utilities/github.py b/libs/community/langchain_community/utilities/github.py
@@ -373,9 +373,8 @@ def get_issue(self, issue_number: int) -> Dict[str, Any]:
         Parameters:
             issue_number(int): The number for the github issue
         Returns:
-            dict: A dictionary containing the issue's title,
-            body, comments as a string, and the username of the user
-            who opened the issue
+            `dict` containing the issue's title, body, comments as a string, and the
+                username of the user who opened the issue
         """
         issue = self.github_repo_instance.get_issue(number=issue_number)
         page = 0
@@ -408,8 +407,7 @@ def list_pull_request_files(self, pr_number: int) -> List[Dict[str, Any]]:
             pr_number(int): The number of the pull request on Github
 
         Returns:
-            dict: A dictionary containing the issue's title,
-            body, and comments as a string
+            `dict` containing the issue's title, body, and comments as a string
         """
         tiktoken = _import_tiktoken()
         MAX_TOKENS_FOR_FILES = 3_000
@@ -472,8 +470,7 @@ def get_pull_request(self, pr_number: int) -> Dict[str, Any]:
             pr_number(int): The number for the Github pull
             max_tokens(int): The maximum number of tokens in the response
         Returns:
-            dict: A dictionary containing the pull's title, body,
-            and comments as a string
+            `dict` containing the pull's title, body, and comments as a string
         """
         max_tokens = 2_000
         pull = self.github_repo_instance.get_pull(number=pr_number)
@@ -538,7 +535,7 @@ def create_pull_request(self, pr_query: str) -> str:
             str: A success or failure message
         """
         if self.github_base_branch == self.active_branch:
-            return """Cannot make a pull request because 
+            return """Cannot make a pull request because
             commits are already in the main or master branch."""
         else:
             try:
diff --git a/libs/community/langchain_community/utilities/gitlab.py b/libs/community/langchain_community/utilities/gitlab.py
@@ -24,11 +24,11 @@ class GitLabAPIWrapper(BaseModel):
     gitlab_personal_access_token: Optional[str] = None
     """Personal access token for the GitLab service, used for authentication."""
     gitlab_branch: Optional[str] = None
-    """The specific branch in the GitLab repository where the bot will make 
+    """The specific branch in the GitLab repository where the bot will make
         its commits. Defaults to 'main'.
     """
     gitlab_base_branch: Optional[str] = None
-    """The base branch in the GitLab repository, used for comparisons. 
+    """The base branch in the GitLab repository, used for comparisons.
         Usually 'main' or 'master'. Defaults to 'main'.
     """
 
@@ -125,8 +125,7 @@ def get_issue(self, issue_number: int) -> Dict[str, Any]:
         Parameters:
             issue_number(int): The number for the gitlab issue
         Returns:
-            dict: A dictionary containing the issue's title,
-            body, and comments as a string
+            `dict` containing the issue's title, body, and comments as a string
         """
         issue = self.gitlab_repo_instance.issues.get(issue_number)
         page = 0
@@ -163,7 +162,7 @@ def create_pull_request(self, pr_query: str) -> str:
             str: A success or failure message
         """
         if self.gitlab_base_branch == self.gitlab_branch:
-            return """Cannot make a pull request because 
+            return """Cannot make a pull request because
             commits are already in the master branch"""
         else:
             try:
diff --git a/libs/community/langchain_community/vectorstores/databricks_vector_search.py b/libs/community/langchain_community/vectorstores/databricks_vector_search.py
@@ -574,7 +574,7 @@ def similarity_search_by_vector_with_score(
     def _parse_search_response(
         self, search_resp: Dict, ignore_cols: Optional[List[str]] = None
     ) -> List[Tuple[Document, float]]:
-        """Parse the search response into a list of Documents with score."""
+        """Parse the search response into a list of `Document` objects with score."""
         if ignore_cols is None:
             ignore_cols = []
 
diff --git a/libs/community/langchain_community/vectorstores/faiss.py b/libs/community/langchain_community/vectorstores/faiss.py
@@ -1447,11 +1447,11 @@ def filter_func(filter: Dict[str, Any]) -> Callable[[Dict[str, Any]], bool]:
             supports logical operators ($and, $or, $not) and field-level filtering.
 
             Args:
-                filter (Dict[str, Any]): A dictionary containing filter conditions.
-                Can include:
-                    - Logical operators ($and, $or, $not) with lists of sub-filters
-                    - Field-level conditions with comparison or sequence operators
-                    - Direct field-value mappings for equality comparison
+                `dict` containing filter conditions.
+                    Can include:
+                        - Logical operators ($and, $or, $not) with lists of sub-filters
+                        - Field-level conditions with comparison or sequence operators
+                        - Direct field-value mappings for equality comparison
 
             Returns:
                 Callable[[Dict[str, Any]], bool]: A function that takes a document
diff --git a/libs/community/langchain_community/vectorstores/tidb_vector.py b/libs/community/langchain_community/vectorstores/tidb_vector.py
