Further Linting

src/ontogpt/clients/llm_client.py

@@ -20,6 +20,7 @@
 # Necessary to avoid repeated debug messages
 litellm.suppress_debug_info = True
 
+
 @dataclass
 class LLMClient:
 

src/ontogpt/engines/embedding_similarity_engine.py

@@ -2,7 +2,7 @@
 Embedding similarity engine.
 
 This module provides functionality for calculating the similarity between entities
-using embeddings and cosine similarity. It includes classes and methods for 
+using embeddings and cosine similarity. It includes classes and methods for
 searching for similar entities and retrieving textual representations of entities.
 
 Classes:

src/ontogpt/engines/mapping_engine.py

@@ -1,7 +1,11 @@
 """
 Mapping engine.
 
-This module provides the `MappingEngine` class, which is responsible for generating and resolving mappings between concepts in different ontologies. It utilizes various classes and enums to represent mapping tasks, categorized mappings, and confidence levels.
+This module provides the `MappingEngine` class,
+which is responsible for generating and resolving
+mappings between concepts in different ontologies.
+It utilizes various classes and enums to represent
+mapping tasks, categorized mappings, and confidence levels.
 
 Classes:
  MappingPredicate: Enum representing different types of mapping predicates.
@@ -14,11 +18,13 @@
  MappingEngine: Engine class for generating and resolving mappings.
 
 Functions:
- categorize_mapping: Categorizes a mapping between a subject and an object using a template.
+ categorize_mapping: Categorizes a mapping between a subject
+ and an object using a template.
  _parse: Parses the payload from the categorization process into a `CategorizedMapping`.
  categorize_mappings: Categorizes multiple mappings between subjects and object sources.
  run_tasks: Runs a collection of mapping tasks and categorizes the results.
- generate_tasks: Generates mapping tasks from a collection or specified subjects and object sources.
+ generate_tasks: Generates mapping tasks from a collection or
+ specified subjects and object sources.
  from_sssom: Generates tasks from an SSSOM file.
  categorize_sssom_mapping: Categorizes a single SSSOM mapping.
  _concept: Retrieves a concept from an ontology adapter.

src/ontogpt/engines/reasoner_engine.py

@@ -1,7 +1,12 @@
 """
 Reasoner engine.
 
-This module provides the implementation of the ReasonerEngine class, which is used to perform reasoning tasks using a Language Model (LLM). The engine takes an ontology and a query task as input, translates it into an LLM prompt, and performs reasoning over the ontology.
+This module provides the implementation of the
+ReasonerEngine class, which is used to perform
+reasoning tasks using a Language Model (LLM).
+The engine takes an ontology and a query task as input,
+translates it into an LLM prompt, and performs
+reasoning over the ontology.
 
 Classes:
  ReasonerResult: Represents the result of a reason query.
@@ -10,13 +15,15 @@
 
 Functions:
  flatten_list(lst): Flattens a nested list into a single list.
- reason(task, template_path=None, strict=False, evaluate=None): Performs reasoning over axioms and query entailments.
+ reason(task, template_path=None, strict=False, evaluate=None): Performs
+ reasoning over axioms and query entailments.
  reason_multiple(task_collection, **kwargs): Performs reasoning over multiple tasks.
  _parse_single_answer(payload, task): Parses a single answer from the payload.
  evaluate(result, task): Evaluates the result against the task.
 
 Usage:
- The ReasonerEngine can be used to perform reasoning tasks such as finding superclasses of a given class.
+ The ReasonerEngine can be used to perform reasoning tasks
+ such as finding superclasses of a given class.
  It can also provide explanations for the reasoning process.
 """
 

src/ontogpt/engines/synonym_engine.py

@@ -1,14 +1,18 @@
 """
 Synonym engine.
 
-This module defines the SynonymEngine class, which is responsible for generating synonyms for given named entities within a specified domain.
+This module defines the SynonymEngine class,
+which is responsible for generating synonyms
+for given named entities within a specified domain.
 
 Classes:
- SynonymEngine: Inherits from KnowledgeEngine and provides a method to retrieve synonyms.
+ SynonymEngine: Inherits from KnowledgeEngine and
+ provides a method to retrieve synonyms.
 
 Methods:
  synonyms(named_entity: str, domain: str) -> List[str]:
- Retrieves synonyms for the given named entity within the specified domain.
+ Retrieves synonyms for the given named entity
+ within the specified domain.
 """
 
 from dataclasses import dataclass

src/ontogpt/evaluation/maxo/eval_maxo.py

@@ -244,7 +244,9 @@ def eval(self) -> EvaluationObjectSetRE:
  if extraction.extracted_object is not None:
  # Process all multi-object triples to 1 to 1 triples
  # so they may be more directly compared
- for extracted_triple in extraction.extracted_object.action_annotation_relationships:
+ for (
+ extracted_triple
+ ) in extraction.extracted_object.action_annotation_relationships:
  new_triple = extracted_triple
  for object in extracted_triple.object:
  new_triple.object = [object]

src/ontogpt/utils/clinical_cases.py

@@ -30,4 +30,4 @@ def get_kanjee_prompt() -> str:
  " the diagnoses. Again, the goal is to be as specific as possible with each of the "
  "diagnoses. Do you have any questions, Dr. GPT-4?\n\nHere is the case:"
  )
- return prompt
+ return prompt

src/ontogpt/webapp/main.py

@@ -55,9 +55,7 @@ class Query(BaseModel):
 def get_engine(datamodel: str, llm_model: str):
  if datamodel not in engines:
  template_details = get_template_details(template=datamodel)
- engines[datamodel] = SPIRESEngine(
- model=llm_model, template_details=template_details
- )
+ engines[datamodel] = SPIRESEngine(model=llm_model, template_details=template_details)
  return engines[datamodel]