Linting/formatting changes

libs/aws/langchain_aws/__init__.py

@@ -15,13 +15,14 @@
     InMemoryVectorStore,
 )
 
+
 def setup_logging():
     import logging
     import os
 
     if os.environ.get("LANGCHAIN_AWS_DEBUG", "FALSE").lower() in ["true", "1"]:
         DEFAULT_LOG_FORMAT = (
-            "%(asctime)s %(levelname)s | [%(filename)s:%(lineno)s]" 
+            "%(asctime)s %(levelname)s | [%(filename)s:%(lineno)s]"
             "| %(name)s - %(message)s"
         )
         log_formatter = logging.Formatter(DEFAULT_LOG_FORMAT)
@@ -30,6 +31,7 @@ def setup_logging():
         logging.getLogger("langchain_aws").addHandler(log_handler)
         logging.getLogger("langchain_aws").setLevel(logging.DEBUG)
 
+
 setup_logging()
 
 __all__ = [

libs/aws/langchain_aws/chains/__init__.py

@@ -3,7 +3,4 @@
     create_neptune_sparql_qa_chain,
 )
 
-__all__ = [
-    "create_neptune_opencypher_qa_chain",
-    "create_neptune_sparql_qa_chain"
-]
+__all__ = ["create_neptune_opencypher_qa_chain", "create_neptune_sparql_qa_chain"]

libs/aws/langchain_aws/chains/graph_qa/__init__.py

@@ -1,7 +1,4 @@
 from .neptune_cypher import create_neptune_opencypher_qa_chain
 from .neptune_sparql import create_neptune_sparql_qa_chain
 
-__all__ = [
-    "create_neptune_opencypher_qa_chain",
-    "create_neptune_sparql_qa_chain"
-]
+__all__ = ["create_neptune_opencypher_qa_chain", "create_neptune_sparql_qa_chain"]

libs/aws/langchain_aws/chains/graph_qa/neptune_cypher.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import re
-from typing import Any, Optional, Union
+from typing import Optional, Union
 
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts.base import BasePromptTemplate

libs/aws/langchain_aws/chat_models/bedrock.py

@@ -1,3 +1,4 @@
+import logging
 import re
 from collections import defaultdict
 from operator import itemgetter
@@ -53,9 +54,8 @@
     get_num_tokens_anthropic,
     get_token_ids_anthropic,
 )
-import logging
 
-logger = logging.getLogger("langchain_aws")
+logger = logging.getLogger(__name__)
 
 
 def _convert_one_message_to_text_llama(message: BaseMessage) -> str:

libs/aws/langchain_aws/chat_models/bedrock_converse.py

@@ -1,5 +1,6 @@
 import base64
 import json
+import logging
 import os
 import re
 from operator import itemgetter
@@ -53,9 +54,8 @@
 from typing_extensions import Self
 
 from langchain_aws.function_calling import ToolsOutputParser
-import logging
 
-logger = logging.getLogger("langchain_aws")
+logger = logging.getLogger(__name__)
 _BM = TypeVar("_BM", bound=BaseModel)
 
 _DictOrPydanticClass = Union[Dict[str, Any], Type[_BM], Type]
@@ -519,7 +519,7 @@ def _generate(
             stop=stop, **_snake_to_camel_keys(kwargs, excluded_keys={"inputSchema"})
         )
         logger.debug(f"Input params: {params}")
-        logger.info(f"Using Bedrock Converse API to generate response")
+        logger.info("Using Bedrock Converse API to generate response")
         response = self.client.converse(
             messages=bedrock_messages, system=system, **params
         )

libs/aws/langchain_aws/graphs/__init__.py

@@ -7,7 +7,7 @@
 
 __all__ = [
     "BaseNeptuneGraph",
-    "NeptuneAnalyticsGraph", 
+    "NeptuneAnalyticsGraph",
     "NeptuneGraph",
-    "NeptuneRdfGraph"
+    "NeptuneRdfGraph",
 ]

libs/aws/langchain_aws/graphs/neptune_graph.py

@@ -7,9 +7,7 @@ def _format_triples(triples: List[dict]) -> List[str]:
     triple_template = "(:`{a}`)-[:`{e}`]->(:`{b}`)"
     triple_schema = []
     for t in triples:
-        triple = triple_template.format(
-            a=t["~from"], e=t["~type"], b=t["~to"]
-        )
+        triple = triple_template.format(a=t["~from"], e=t["~type"], b=t["~to"])
         triple_schema.append(triple)
 
     return triple_schema
@@ -21,7 +19,9 @@ def _format_node_properties(n_labels: dict) -> List:
     for label, props_item in n_labels.items():
         props = props_item["properties"]
         np = {
-            "properties": [{"property": k, "type": v["datatypes"][0]} for k, v in props.items()],
+            "properties": [
+                {"property": k, "type": v["datatypes"][0]} for k, v in props.items()
+            ],
             "labels": label,
         }
         node_properties.append(np)
@@ -36,7 +36,9 @@ def _format_edge_properties(e_labels: dict) -> List:
         props = props_item["properties"]
         np = {
             "type": label,
-            "properties": [{"property": k, "type": v["datatypes"][0]} for k, v in props.items()],
+            "properties": [
+                {"property": k, "type": v["datatypes"][0]} for k, v in props.items()
+            ],
         }
         edge_properties.append(np)
 
@@ -210,7 +212,7 @@ def __init__(
         graph_identifier: str,
         client: Any = None,
         credentials_profile_name: Optional[str] = None,
-        region_name: Optional[str] = None
+        region_name: Optional[str] = None,
     ) -> None:
         """Create a new Neptune Analytics graph wrapper instance."""
 
@@ -331,6 +333,7 @@ def _refresh_schema(self) -> None:
         {triple_schema}
         """
 
+
 class NeptuneGraph(BaseNeptuneGraph):
     """Neptune wrapper for graph operations.
 

libs/aws/langchain_aws/llms/bedrock.py

@@ -37,9 +37,8 @@
     get_num_tokens_anthropic,
     get_token_ids_anthropic,
 )
-import logging
 
-logger = logging.getLogger("langchain_aws")
+logger = logging.getLogger(__name__)
 
 AMAZON_BEDROCK_TRACE_KEY = "amazon-bedrock-trace"
 GUARDRAILS_BODY_KEY = "amazon-bedrock-guardrailAction"
@@ -828,7 +827,7 @@ def _prepare_input_and_invoke(
 
         try:
             logger.debug(f"Request body sent to bedrock: {request_options}")
-            logger.info(f"Using Bedrock Invoke API to generate response")
+            logger.info("Using Bedrock Invoke API to generate response")
             response = self.client.invoke_model(**request_options)
 
             (