Temp

outlines/models/anthropic.py

@@ -11,9 +11,11 @@
 class AnthropicTypeAdapter(ModelTypeAdapter):
     """Type adapter for the Anthropic clients.
 
-    `AnthropicTypeAdapter` is responsible for preparing the arguments to Anthropic's
-    `messages.create` methods: the input (prompt and possibly image).
-    Anthropic does not support defining the output type, so `format_output_type` is not implemented.
+    `AnthropicTypeAdapter` is responsible for preparing the arguments to
+    Anthropic's `messages.create` methods: the input (prompt and possibly
+    image).
+    Anthropic does not support defining the output type, so
+    `format_output_type` is not implemented.
 
     """
 

outlines/models/base.py

@@ -8,27 +8,31 @@ class ModelTypeAdapter(ABC):
     A type adapter instance must be given as a value to the `type_adapter`
     attribute when instantiating a model.
     The type adapter is responsible for formatting the input and output types
-    passed to the model to match the specific format expected by the associated model.
+    passed to the model to match the specific format expected by the
+    associated model.
 
     """
 
     @abstractmethod
     def format_input(self, model_input):
-        """Format the user input to the expected input format of the model.
+        """Format the user input to the expected format of the model.
 
-        For API-based models, it typically means creating the `messages` argument passed to the client.
-        For local models, it can mean casting the input from str to list for instance.
-        This method is also used to validate that the input type provided by the user is supported by the model.
+        For API-based models, it typically means creating the `messages`
+        argument passed to the client. For local models, it can mean casting
+        the input from str to list for instance.
+        This method is also used to validate that the input type provided by
+        the user is supported by the model.
 
         """
         ...
 
     @abstractmethod
     def format_output_type(self, output_type):
-        """Format the output type provided by the user to the expected output type format of the model.
+        """Format the output type to the expected format of the model.
 
-        For API-based models, this typically means creating a `response_format` argument.
-        For local models, it means formatting the logits processor to create the object type expected by the model.
+        For API-based models, this typically means creating a `response_format`
+        argument. For local models, it means formatting the logits processor to
+        create the object type expected by the model.
 
         """
         ...
@@ -37,10 +41,12 @@ def format_output_type(self, output_type):
 class Model(ABC):
     """Base class for all models.
 
-    This class defines a shared `__call__` method that can be used to call the model directly.
-    All models inheriting from this class must define a `type_adapter` attribute of type `ModelTypeAdapter`.
-    The methods of the `type_adapter` attribute are used in the `generate` method to format
-    the input and output types received by the model.
+    This class defines a shared `__call__` method that can be used to call the
+    model directly.
+    All models inheriting from this class must define a `type_adapter`
+    attribute of type `ModelTypeAdapter`. The methods of the `type_adapter`
+    attribute are used in the `generate` method to format the input and output
+    types received by the model.
 
     """
 
@@ -50,10 +56,9 @@ class Model(ABC):
     def __call__(self, model_input, output_type=None, **inference_kwargs):
         """Call the model.
 
-        Users can call the model directly, in which case we will create a generator instance with
-        the output type provided and call it.
+        Users can call the model directly, in which case we will create a
+        generator instance with the output type provided and call it.
         Thus, those commands are equivalent:
-
         ```python
         generator = Generator(model, Foo)
         generator("prompt")
@@ -72,8 +77,8 @@ def __call__(self, model_input, output_type=None, **inference_kwargs):
     def generate(self, model_input, output_type=None, **inference_kwargs):
         """Generate a response from the model.
 
-        The output_type argument contains a logits processor for local models while it contains
-        a type (Json, Enum...) for the API-based models.
+        The output_type argument contains a logits processor for local models
+        while it contains a type (Json, Enum...) for the API-based models.
 
         """
         ...

outlines/models/llamacpp.py

@@ -98,9 +98,9 @@ def __setstate__(self, state):
 class LlamaCppTypeAdapter(ModelTypeAdapter):
     """Type adapter for the `llama-cpp-python` library.
 
-    `LlamaCppTypeAdapter` is responsible for preparing the arguments to `llama-cpp-python`'s
-    `Llama.__call__` method: the input (a string prompt), as well as the logits processor
-    (an instance of `LogitsProcessorList`).
+    `LlamaCppTypeAdapter` is responsible for preparing the arguments to
+    `llama-cpp-python`'s `Llama.__call__` method: the input (a string prompt),
+    as well as the logits processor (an instance of `LogitsProcessorList`).
 
     """
 
@@ -124,7 +124,7 @@ def format_str_input(self, model_input: str):
         return model_input
 
     def format_output_type(self, output_type):
-        """Generate the logits processor argument to pass to the model (a `LogitsProcessorList`).
+        """Generate the logits processor argument to pass to the model.
 
         Argument
         --------

outlines/models/openai.py

@@ -15,8 +15,8 @@ class OpenAITypeAdapter(ModelTypeAdapter):
     """Type adapter for the OpenAI clients.
 
     `OpenAITypeAdapter` is responsible for preparing the arguments to OpenAI's
-    `completions.create` methods: the input (prompt and possibly image), as well
-    as the output type (only JSON).
+    `completions.create` methods: the input (prompt and possibly image), as
+    well as the output type (only JSON).
 
     """