Refactor to classmethods

src/distilabel/llms/base.py

@@ -17,7 +17,6 @@
 import logging
 import sys
 from abc import ABC, abstractmethod
-from functools import cached_property
 from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
 
 from pydantic import BaseModel, ConfigDict, Field, PrivateAttr
@@ -112,17 +111,17 @@ def generate(
         """
         pass
 
-    @property
-    def generate_parameters(self) -> List["inspect.Parameter"]:
+    @classmethod
+    def generate_parameters(cls) -> List["inspect.Parameter"]:
         """Returns the parameters of the `generate` method.
 
         Returns:
             A list containing the parameters of the `generate` method.
         """
-        return list(inspect.signature(self.generate).parameters.values())
+        return list(inspect.signature(cls.generate).parameters.values())
 
-    @property
-    def runtime_parameters_names(self) -> "RuntimeParametersNames":
+    @classmethod
+    def runtime_parameters_names(cls) -> "RuntimeParametersNames":
         """Returns the runtime parameters of the `LLM`, which are combination of the
         attributes of the `LLM` type hinted with `RuntimeParameter` and the parameters
         of the `generate` method that are not `input` and `num_generations`.
@@ -131,19 +130,20 @@ def runtime_parameters_names(self) -> "RuntimeParametersNames":
             A dictionary with the name of the runtime parameters as keys and a boolean
             indicating if the parameter is optional or not.
         """
-        runtime_parameters = super().runtime_parameters_names
+        runtime_parameters = super().runtime_parameters_names()
         runtime_parameters["generation_kwargs"] = {}
 
         # runtime parameters from the `generate` method
-        for param in self.generate_parameters:
+        for param in cls.generate_parameters():
             if param.name in ["input", "inputs", "num_generations"]:
                 continue
             is_optional = param.default != inspect.Parameter.empty
             runtime_parameters["generation_kwargs"][param.name] = is_optional
 
         return runtime_parameters
 
-    def get_runtime_parameters_info(self) -> List[Dict[str, Any]]:
+    @classmethod
+    def get_runtime_parameters_info(cls) -> List[Dict[str, Any]]:
         """Gets the information of the runtime parameters of the `LLM` such as the name
         and the description. This function is meant to include the information of the runtime
         parameters in the serialized data of the `LLM`.
@@ -159,7 +159,7 @@ def get_runtime_parameters_info(self) -> List[Dict[str, Any]]:
             if runtime_parameter_info["name"] == "generation_kwargs"
         )
 
-        generate_docstring_args = self.generate_parsed_docstring["args"]
+        generate_docstring_args = cls.generate_parsed_docstring()["args"]
 
         generation_kwargs_info["keys"] = []
         for key, value in generation_kwargs_info["optional"].items():
@@ -172,14 +172,14 @@ def get_runtime_parameters_info(self) -> List[Dict[str, Any]]:
 
         return runtime_parameters_info
 
-    @cached_property
-    def generate_parsed_docstring(self) -> "Docstring":
+    @classmethod
+    def generate_parsed_docstring(cls) -> "Docstring":
         """Returns the parsed docstring of the `generate` method.
 
         Returns:
             The parsed docstring of the `generate` method.
         """
-        return parse_google_docstring(self.generate)
+        return parse_google_docstring(cls.generate)
 
     def get_last_hidden_states(self, inputs: List["ChatType"]) -> List["HiddenState"]:
         """Method to get the last hidden states of the model for a list of inputs.
@@ -208,23 +208,23 @@ class AsyncLLM(LLM):
 
     _event_loop: "asyncio.AbstractEventLoop" = PrivateAttr(default=None)
 
-    @property
-    def generate_parameters(self) -> List[inspect.Parameter]:
+    @classmethod
+    def generate_parameters(cls) -> List[inspect.Parameter]:
         """Returns the parameters of the `agenerate` method.
 
         Returns:
             A list containing the parameters of the `agenerate` method.
         """
-        return list(inspect.signature(self.agenerate).parameters.values())
+        return list(inspect.signature(cls.agenerate).parameters.values())
 
-    @cached_property
-    def generate_parsed_docstring(self) -> "Docstring":
+    @classmethod
+    def generate_parsed_docstring(cls) -> "Docstring":
         """Returns the parsed docstring of the `agenerate` method.
 
         Returns:
             The parsed docstring of the `agenerate` method.
         """
-        return parse_google_docstring(self.agenerate)
+        return parse_google_docstring(cls.agenerate)
 
     @property
     def event_loop(self) -> "asyncio.AbstractEventLoop":

src/distilabel/mixins/runtime_parameters.py

@@ -44,8 +44,8 @@ class RuntimeParametersMixin(BaseModel):
 
     _runtime_parameters: Dict[str, Any] = PrivateAttr(default_factory=dict)
 
-    @property
-    def runtime_parameters_names(self) -> RuntimeParametersNames:
+    @classmethod
+    def runtime_parameters_names(cls) -> RuntimeParametersNames:
         """Returns a dictionary containing the name of the runtime parameters of the class
         as keys and whether the parameter is required or not as values.
 
@@ -56,19 +56,24 @@ def runtime_parameters_names(self) -> RuntimeParametersNames:
 
         runtime_parameters = {}
 
-        for name, field_info in self.model_fields.items():  # type: ignore
+        for name, field_info in cls.model_fields.items():  # type: ignore
             is_runtime_param, is_optional = _is_runtime_parameter(field_info)
             if is_runtime_param:
                 runtime_parameters[name] = is_optional
                 continue
 
-            attr = getattr(self, name)
-            if isinstance(attr, RuntimeParametersMixin):
-                runtime_parameters[name] = attr.runtime_parameters_names
+            klass = field_info.annotation
+            if (
+                klass
+                and inspect.isclass(klass)
+                and issubclass(RuntimeParametersMixin, klass)
+            ):
+                runtime_parameters[name] = klass.runtime_parameters_names()
 
         return runtime_parameters
 
-    def get_runtime_parameters_info(self) -> List[Dict[str, Any]]:
+    @classmethod
+    def get_runtime_parameters_info(cls) -> List[Dict[str, Any]]:
         """Gets the information of the runtime parameters of the class such as the name and
         the description. This function is meant to include the information of the runtime
         parameters in the serialized data of the class.
@@ -77,21 +82,25 @@ def get_runtime_parameters_info(self) -> List[Dict[str, Any]]:
             A list containing the information for each runtime parameter of the class.
         """
         runtime_parameters_info = []
-        for name, field_info in self.model_fields.items():  # type: ignore
-            if name not in self.runtime_parameters_names:
+        for name, field_info in cls.model_fields.items():  # type: ignore
+            if name not in cls.runtime_parameters_names():
                 continue
 
-            attr = getattr(self, name)
-            if isinstance(attr, RuntimeParametersMixin):
+            klass = field_info.annotation
+            if (
+                klass
+                and inspect.isclass(klass)
+                and issubclass(RuntimeParametersMixin, klass)
+            ):
                 runtime_parameters_info.append(
                     {
                         "name": name,
-                        "runtime_parameters_info": attr.get_runtime_parameters_info(),
+                        "runtime_parameters_info": klass.get_runtime_parameters_info(),
                     }
                 )
                 continue
 
-            info = {"name": name, "optional": self.runtime_parameters_names[name]}
+            info = {"name": name, "optional": cls.runtime_parameters_names()[name]}
             if field_info.description is not None:
                 info["description"] = field_info.description
             runtime_parameters_info.append(info)
@@ -106,9 +115,9 @@ def set_runtime_parameters(self, runtime_parameters: Dict[str, Any]) -> None:
             runtime_parameters: A dictionary containing the values of the runtime parameters
                 to set.
         """
-        runtime_parameters_names = list(self.runtime_parameters_names.keys())
+        runtime_parameters_names = list(self.runtime_parameters_names().keys())
         for name, value in runtime_parameters.items():
-            if name not in self.runtime_parameters_names:
+            if name not in self.runtime_parameters_names():
                 # Check done just to ensure the unit tests for the mixin run
                 if getattr(self, "pipeline", None):
                     closest = difflib.get_close_matches(