guardrail analyzed response, etc.

src/text_generation/domain/guardrail_analyzed_response.py

@@ -0,0 +1,11 @@
+class GuardrailAnalyzedResponse:
+        def __init__(
+                    self, 
+                    score: float,
+                    cosine_similarity_risk_threshold: float,
+                    original: str,
+                    final: str):
+            self.score = score
+            self.is_malicious = score >= cosine_similarity_risk_threshold
+            self.original = original
+            self.final = final

src/text_generation/entrypoints/http_api_controller.py

@@ -69,7 +69,7 @@ class HttpApiController:
             return [response_body]
 
         response_text = self.text_generation_response_service.invoke(user_prompt=prompt)
-        score = self.generated_text_guardrail_service.analyze(response_text)
+        score = self.generated_text_guardrail_service.is_text_malicious(response_text)
         response_body = self.format_response(response_text)
         
         http_status_code = 200 # make enum
@@ -96,7 +96,7 @@ class HttpApiController:
             return [response_body]
 
         response_text = self.rag_response_service.invoke(user_prompt=prompt)
-        score = self.generated_text_guardrail_service.analyze(response_text)
+        score = self.generated_text_guardrail_service.is_text_malicious(response_text)
         response_body = self.format_response(response_text)
         
         http_status_code = 200 # make enum

src/text_generation/services/guardrails/abstract_generated_text_guardrail_service.py

@@ -3,5 +3,5 @@ import abc
 
 class AbstractGeneratedTextGuardrailService(abc.ABC):
     @abc.abstractmethod
-    def analyze(self, model_generated_text: str) -> float:
+    def is_text_malicious(self, model_generated_text: str) -> float:
         raise NotImplementedError

src/text_generation/services/guardrails/generated_text_guardrail_service.py

@@ -1,3 +1,4 @@
+from src.text_generation.domain.guardrail_analyzed_response import GuardrailAnalyzedResponse
 from src.text_generation.services.guardrails.abstract_generated_text_guardrail_service import AbstractGeneratedTextGuardrailService
 from src.text_generation.services.nlp.abstract_semantic_similarity_service import AbstractSemanticSimilarityService
 
@@ -12,6 +13,12 @@ class GeneratedTextGuardrailService(AbstractGeneratedTextGuardrailService):
         self.semantic_similarity_service.use_comparison_texts(comparison_texts)
         self.cosine_similarity_risk_threshold: float = 0.5
 
-    def analyze(self, model_generated_text: str) -> float:
+    def is_text_malicious(self, model_generated_text: str) -> GuardrailAnalyzedResponse:
         score: float = self.semantic_similarity_service.analyze(text=model_generated_text)
-        return score >= self.cosine_similarity_risk_threshold
+        response = GuardrailAnalyzedResponse(
+            score=score,
+            cosine_similarity_risk_threshold=self.cosine_similarity_risk_threshold,
+            original=model_generated_text,
+            final="test")
+        return response
+