v0.0.3 Release

README.md

@@ -32,9 +32,6 @@ It can be used in a RAG system to prevent the model from hallucinating or genera
 In this example we apply the RagContextValidator to validate the relevance of the retrieved context to the user's query.
 
 ```python
-from validator.prompts.prompts import RagContextRelevancePrompt
-from validator.main import MLcubeRagContextValidator
-from guardrails import Guard
 
 # Define the guard with the MLcubeRagContextValidator,
 # specifying the relevance prompt generator to enable
@@ -88,11 +85,6 @@ In this example we evaluate the usefulness of the retrieved context to the user'
 
 ```python
 
-from validator.prompts.prompts import (
-    RagContextRelevancePrompt,
-    RagContextUsefulnessPrompt,
-)
-
 guard = Guard().use(
     MLcubeRagContextValidator(
         rag_context_eval_prompt=RagContextUsefulnessPrompt(),

benchmark/benchmark_llm_rag_context.py

@@ -45,7 +45,7 @@
 
 sys.path.append(".")
 from guardrails import Guard
-from validator.prompts.prompts import (
+from validator.prompts import (
     Ml3RagContextEvalBasePrompt,
     RagContextUsefulnessPrompt,
 )

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "rag-context-evaluator"
-version = "0.0.2"
+version = "0.0.3"
 description = "ML3 RAG Context Evaluator"
 authors = [
     {name = "MLcube", email = "info@mlcube.com"}

tests/test_validator.py

@@ -3,7 +3,7 @@
 import sys
 
 sys.path.append(".")
-from validator.prompts.prompts import RagContextUsefulnessPrompt
+from validator.prompts import RagContextUsefulnessPrompt
 
 from validator.main import MLcubeRagContextValidator
 

validator/main.py

@@ -8,10 +8,10 @@
     register_validator,
 )
 import litellm
-from validator.prompts.prompts import (
+from .prompts import (
     Ml3RagContextEvalBasePrompt,
 )
-from validator.models import RagRatingResponse
+from .models import RagRatingResponse
 from langchain import chat_models
 
 logger = logging.getLogger(__name__)

validator/prompts/prompts.py → validator/prompts.py

@@ -1,6 +1,6 @@
 from abc import ABC, abstractmethod
-from validator.enums import TextLanguage
-from validator.prompts.prompt_hub import (
+from .enums import TextLanguage
+from .prompt_hub import (
     RAG_CONTEXT_RELEVANCE_PROMPT,
     RAG_CONTEXT_USEFULNESS_PROMPT,
 )