naming updates; fix static analysis script

src/text_generation/services/guidelines/abstract_rag_guidelines_service.py

@@ -7,5 +7,5 @@ class AbstractRetrievalAugmentedGenerationGuidelinesService(abc.ABC):
         raise NotImplementedError
     
     @abc.abstractmethod
-    def create_context(self, user_prompt: str) -> str:
+    def create_guidelines_context(self, user_prompt: str) -> str:
         raise NotImplementedError

src/text_generation/services/guidelines/rag_guidelines_service.py

@@ -58,7 +58,7 @@ class RetrievalAugmentedGenerationGuidelinesService(
     
     # public methods
 
-    def create_context(self, user_prompt: str) -> str:
+    def create_guidelines_context(self, user_prompt: str) -> str:
         return self._create_context(user_prompt)
 
     def get_prompt_template(self):

src/text_generation/services/nlp/abstract_text_generation_completion_service.py

@@ -1,7 +1,7 @@
 import abc
 
 
-class AbstractLanguageModelResponseService(abc.ABC):
+class AbstractTextGenerationCompletionService(abc.ABC):
     @abc.abstractmethod
     def invoke(self, user_prompt: str) -> str:
         raise NotImplementedError

src/text_generation/services/nlp/fake_text_generation_completion_service.py

@@ -1,7 +1,7 @@
-from src.text_generation.services.nlp.abstract_language_model_response_service import AbstractLanguageModelResponseService
+from src.text_generation.services.nlp.abstract_text_generation_completion_service import AbstractTextGenerationCompletionService
 
 
-class FakeLanguageModelResponseService(AbstractLanguageModelResponseService):
+class FakeTextGenerationCompletionService(AbstractTextGenerationCompletionService):
     
     def invoke(self, user_prompt: str) -> str:
 

src/text_generation/services/nlp/retrieval_augmented_generation_completion_service.py

@@ -3,13 +3,12 @@ from langchain.prompts import PromptTemplate
 
 from src.text_generation.ports.abstract_embedding_model import AbstractEmbeddingModel
 from src.text_generation.ports.abstract_foundation_model import AbstractFoundationModel
-from src.text_generation.services.nlp.abstract_language_model_response_service import AbstractLanguageModelResponseService
+from src.text_generation.services.nlp.abstract_text_generation_completion_service import AbstractTextGenerationCompletionService
 from src.text_generation.services.guidelines.abstract_rag_guidelines_service import AbstractRetrievalAugmentedGenerationGuidelinesService
 from src.text_generation.services.utilities.abstract_response_processing_service import AbstractResponseProcessingService
 
 
-class RetrievalAugmentedGenerationResponseService(AbstractLanguageModelResponseService):
-
+class RetrievalAugmentedGenerationCompletionService(AbstractTextGenerationCompletionService):
     def __init__(
             self, 
             foundation_model: AbstractFoundationModel,
@@ -32,7 +31,7 @@ class RetrievalAugmentedGenerationResponseService(AbstractLanguageModelResponseS
             template=self.rag_guidelines_service.get_prompt_template(),
             input_variables=["context", "question"]
         )
-        context = self.rag_guidelines_service.create_context(user_prompt)
+        context = self.rag_guidelines_service.create_guidelines_context(user_prompt)
         chain = prompt | self.language_model_pipeline | StrOutputParser()
         raw_response = chain.invoke({
             "context": context,

src/text_generation/services/nlp/text_generation_completion_service.py

@@ -2,19 +2,21 @@ from langchain.prompts import PromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnablePassthrough
 
-from src.text_generation.services.nlp.abstract_language_model_response_service import AbstractLanguageModelResponseService
+from src.text_generation.common.constants import Constants
+from src.text_generation.services.nlp.abstract_text_generation_completion_service import AbstractTextGenerationCompletionService
 from src.text_generation.ports.abstract_foundation_model import AbstractFoundationModel
 
 
-class TextGenerationResponseService(AbstractLanguageModelResponseService):
+class TextGenerationCompletionService(AbstractTextGenerationCompletionService):
     
     def __init__(self, foundation_model: AbstractFoundationModel):
         super().__init__()
         self.language_model_pipeline = foundation_model.create_pipeline()
+        self.constants = Constants()
 
     def _extract_assistant_response(self, text):
-        if "<|assistant|>" in text:
-            return text.split("<|assistant|>")[-1].strip()
+        if self.constants.ASSISTANT_TOKEN in text:
+            return text.split(self.constants.ASSISTANT_TOKEN)[-1].strip()
         return text
 
     # TODO - get from config?