diff --git a/src/ragas/experimental/prompt.py b/src/ragas/experimental/prompt.py
index 3e2b7bfcd..6c3ddd917 100644
--- a/src/ragas/experimental/prompt.py
+++ b/src/ragas/experimental/prompt.py
@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import inspect
 import typing as t
 from abc import ABC, abstractmethod
 
@@ -188,3 +189,25 @@ async def generate(
             callbacks=callbacks,
         )
         return llm_result.generations[0][0].text
+
+
+class PromptMixin:
+    def get_prompts(self) -> t.Dict[str, PydanticPrompt]:
+        prompts = {}
+        for name, value in inspect.getmembers(self):
+            if isinstance(value, PydanticPrompt):
+                prompts.update({name: value})
+        return prompts
+
+    def set_prompts(self, **prompts):
+        available_prompts = self.get_prompts()
+        for key, value in prompts.items():
+            if key not in available_prompts:
+                raise ValueError(
+                    f"Prompt with name '{key}' does not exist. Use get_prompts() to see available prompts."
+                )
+            if not isinstance(value, PydanticPrompt):
+                raise ValueError(
+                    f"Prompt with name '{key}' must be an instance of 'ragas.prompt.PydanticPrompt'"
+                )
+            setattr(self, key, value)
diff --git a/src/ragas/experimental/testset/simulators/base.py b/src/ragas/experimental/testset/simulators/base.py
index dd35383eb..12b86a4f3 100644
--- a/src/ragas/experimental/testset/simulators/base.py
+++ b/src/ragas/experimental/testset/simulators/base.py
@@ -7,6 +7,7 @@
 
 from pydantic import BaseModel
 
+from ragas.experimental.prompt import PromptMixin
 from ragas.callbacks import new_group
 from ragas.experimental.testset.graph import KnowledgeGraph, Node
 from ragas.llms import BaseRagasLLM, llm_factory
@@ -40,7 +41,7 @@ class BaseScenario(BaseModel):
 
 
 @dataclass
-class BaseSimulator(ABC, t.Generic[Scenario]):
+class BaseSimulator(ABC, t.Generic[Scenario], PromptMixin):
     name: str = ""
     llm: BaseRagasLLM = field(default_factory=llm_factory)
 
diff --git a/src/ragas/experimental/testset/transforms/base.py b/src/ragas/experimental/testset/transforms/base.py
index 67e1b08b8..25ce7384a 100644
--- a/src/ragas/experimental/testset/transforms/base.py
+++ b/src/ragas/experimental/testset/transforms/base.py
@@ -3,12 +3,17 @@
 from abc import ABC, abstractmethod
 from dataclasses import dataclass, field
 
+from ragas.experimental.prompt import PromptMixin
 from ragas.experimental.testset.graph import KnowledgeGraph, Node, Relationship
 from ragas.llms import BaseRagasLLM, llm_factory
 
 logger = logging.getLogger(__name__)
 
 
+def default_filter(node: Node) -> bool:
+    return True
+
+
 @dataclass
 class BaseGraphTransformation(ABC):
     """
@@ -90,7 +95,9 @@ class Extractor(BaseGraphTransformation):
         Abstract method to extract a specific property from a node.
     """
 
-    filter_nodes: t.Callable[[Node], bool] = lambda _: True
+    filter_nodes: t.Callable[[Node], bool] = field(
+        default_factory=lambda: default_filter
+    )
 
     async def transform(
         self, kg: KnowledgeGraph
@@ -180,7 +187,7 @@ def filter(self, kg: KnowledgeGraph) -> KnowledgeGraph:
 
 
 @dataclass
-class LLMBasedExtractor(Extractor):
+class LLMBasedExtractor(Extractor, PromptMixin):
     llm: BaseRagasLLM = field(default_factory=llm_factory)
     merge_if_possible: bool = True
 
diff --git a/src/ragas/metrics/base.py b/src/ragas/metrics/base.py
index a1ac702f2..dedbe612a 100644
--- a/src/ragas/metrics/base.py
+++ b/src/ragas/metrics/base.py
@@ -27,12 +27,10 @@
     from ragas.embeddings import BaseRagasEmbeddings
     from ragas.llms import BaseRagasLLM
 
-import inspect
-
 from pysbd import Segmenter
 from pysbd.languages import LANGUAGE_CODES
 
-from ragas.experimental.prompt import PydanticPrompt as Prompt
+from ragas.experimental.prompt import PromptMixin
 
 logger = logging.getLogger(__name__)
 
@@ -60,7 +58,8 @@ class Metric(ABC):
 
     @property
     @abstractmethod
-    def name(self) -> str: ...
+    def name(self) -> str:
+        ...
 
     @property
     def required_columns(self) -> t.Dict[str, t.Set[str]]:
@@ -147,11 +146,12 @@ 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
-class MetricWithLLM(Metric):
+class MetricWithLLM(Metric, PromptMixin):
     llm: t.Optional[BaseRagasLLM] = None
 
     def init(self, run_config: RunConfig):
@@ -166,26 +166,6 @@ def init(self, run_config: RunConfig):
             )
         self.llm.set_run_config(run_config)
 
-    def get_prompts(self) -> t.Dict[str, Prompt]:
-        prompts = {}
-        for name, value in inspect.getmembers(self):
-            if isinstance(value, Prompt):
-                prompts.update({name: value})
-        return prompts
-
-    def set_prompts(self, **prompts):
-        available_prompts = self.get_prompts()
-        for key, value in prompts.items():
-            if key not in available_prompts:
-                raise ValueError(
-                    f"Prompt with name '{key}' does not exist in the metric {self.name}. Use get_prompts() to see available prompts."
-                )
-            if not isinstance(value, Prompt):
-                raise ValueError(
-                    f"Prompt with name '{key}' must be an instance of 'Prompt'"
-                )
-            setattr(self, key, value)
-
 
 @dataclass
 class MetricWithEmbeddings(Metric):
@@ -254,7 +234,8 @@ async def _single_turn_ascore(
         self,
         sample: SingleTurnSample,
         callbacks: Callbacks,
-    ) -> float: ...
+    ) -> float:
+        ...
 
 
 class MultiTurnMetric(Metric):
@@ -306,7 +287,8 @@ async def _multi_turn_ascore(
         self,
         sample: MultiTurnSample,
         callbacks: Callbacks,
-    ) -> float: ...
+    ) -> float:
+        ...
 
 
 class Ensember: