feat: Adding transforms for testset generation

src/ragas/experimental/metrics/_faithfulness.py

@@ -7,7 +7,7 @@
 import numpy as np
 from pydantic import BaseModel, Field
 
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.metrics.base import (
     MetricType,
     MetricWithLLM,

src/ragas/metrics/_aspect_critic.py

@@ -8,7 +8,7 @@
 from pydantic import BaseModel, Field
 
 from ragas.dataset_schema import MultiTurnSample, SingleTurnSample
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.metrics.base import (
     MetricType,
     MetricWithLLM,

src/ragas/metrics/_domain_specific_rubrics.py

@@ -7,7 +7,7 @@
 from pydantic import BaseModel, Field
 
 from ragas.dataset_schema import MultiTurnSample, SingleTurnSample
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.metrics.base import (
     MetricType,
     MetricWithLLM,

src/ragas/metrics/_factual_correctness.py

@@ -9,7 +9,7 @@
 from numpy.typing import NDArray
 from pydantic import BaseModel, Field
 
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.experimental.metrics._faithfulness import (
     NLIStatementInput,
     NLIStatementPrompt,

src/ragas/metrics/_goal_accuracy.py

@@ -6,7 +6,7 @@
 from pydantic import BaseModel, Field
 
 from ragas.dataset_schema import MultiTurnSample
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.metrics.base import MetricType, MetricWithLLM, MultiTurnMetric
 
 if t.TYPE_CHECKING:

src/ragas/metrics/_instance_specific_rubrics.py

@@ -4,7 +4,7 @@
 from dataclasses import dataclass, field
 
 from ragas.dataset_schema import MultiTurnSample, SingleTurnSample
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.metrics._domain_specific_rubrics import (
     MultiTurnWithoutReferenceInput,
     MultiTurnWithoutReferencePrompt,

src/ragas/metrics/_simple_criteria.py

@@ -8,7 +8,7 @@
 from pydantic import BaseModel, Field
 
 from ragas.dataset_schema import MultiTurnSample, SingleTurnSample
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.metrics.base import (
     MetricType,
     MetricWithLLM,

src/ragas/metrics/_sql_semantic_equivalence.py

@@ -7,7 +7,7 @@
 from pydantic import BaseModel, Field
 
 from ragas.dataset_schema import SingleTurnSample
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.metrics.base import MetricType, MetricWithLLM, SingleTurnMetric
 
 if t.TYPE_CHECKING:

src/ragas/metrics/_topic_adherence.py

@@ -8,7 +8,7 @@
 from pydantic import BaseModel, Field
 
 from ragas.dataset_schema import MultiTurnSample
-from ragas.experimental.llms.prompt import PydanticPrompt
+from ragas.experimental.prompt import PydanticPrompt
 from ragas.metrics.base import MetricType, MetricWithLLM, MultiTurnMetric
 
 if t.TYPE_CHECKING:

src/ragas/metrics/base.py

@@ -32,7 +32,7 @@
 from pysbd import Segmenter
 from pysbd.languages import LANGUAGE_CODES
 
-from ragas.experimental.llms.prompt import PydanticPrompt as Prompt
+from ragas.experimental.prompt import PydanticPrompt as Prompt
 
 logger = logging.getLogger(__name__)
 
@@ -60,8 +60,7 @@ class Metric(ABC):
 
     @property
     @abstractmethod
-    def name(self) -> str:
-        ...
+    def name(self) -> str: ...
 
     @property
     def required_columns(self) -> t.Dict[str, t.Set[str]]:
@@ -148,8 +147,7 @@ async def ascore(
         return score
 
     @abstractmethod
-    async def _ascore(self, row: t.Dict, callbacks: Callbacks) -> float:
-        ...
+    async def _ascore(self, row: t.Dict, callbacks: Callbacks) -> float: ...
 
 
 @dataclass
@@ -256,8 +254,7 @@ async def _single_turn_ascore(
         self,
         sample: SingleTurnSample,
         callbacks: Callbacks,
-    ) -> float:
-        ...
+    ) -> float: ...
 
 
 class MultiTurnMetric(Metric):
@@ -309,8 +306,7 @@ async def _multi_turn_ascore(
         self,
         sample: MultiTurnSample,
         callbacks: Callbacks,
-    ) -> float:
-        ...
+    ) -> float: ...
 
 
 class Ensember: