@spec _calculate_keys(SnakeBridge.Ref.t(), term(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• args (term())
• kwargs (term())

Returns

• term()

@spec _copy_and_set_values(SnakeBridge.Ref.t(), term(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• args (term())
• kwargs (term())

Returns

• term()

@spec _get_value(SnakeBridge.Ref.t(), term(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• args (term())
• kwargs (term())

Returns

• term()

@spec _iter(SnakeBridge.Ref.t(), term(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• args (term())
• kwargs (term())

Returns

• term()

@spec _setattr_handler(SnakeBridge.Ref.t(), String.t(), term(), keyword()) ::
  {:ok, term() | nil} | {:error, Snakepit.Error.t()}

Get a handler for setting an attribute on the model instance.

Parameters

• name (String.t())
• value (term())

Returns

• term() | nil

@spec append(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, t()} | {:error, Snakepit.Error.t()}

Return a new REPLHistory with the entry appended.

Parameters

• reasoning (String.t() keyword-only default: '')
• code (String.t() keyword-only, required)
• output (String.t() keyword-only, required)

Returns

• Dspy.Primitives.ReplTypes.REPLHistory.t()

@spec construct(SnakeBridge.Ref.t(), [term()], keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• fields_set (term() default: None)
• values (term())

Returns

• term()

@spec copy(SnakeBridge.Ref.t(), term(), term(), term(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

Returns a copy of the model.

!!! warning "Deprecated"

This method is now deprecated; use `model_copy` instead.

If you need include or exclude, use:

python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data)

## Parameters

- include - Optional set or mapping specifying which fields to include in the copied model. - exclude - Optional set or mapping specifying which fields to exclude in the copied model. - update - Optional dictionary of field-value pairs to override field values in the copied model. - deep - If True, the values of fields that are Pydantic models will be deep-copied.

## Returns

- term()

@spec dict(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, %{optional(String.t()) => term()}} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• include ((((MapSet.t(integer()) | MapSet.t(String.t())) | term()) | term()) | nil keyword-only default: None)

• exclude ((((MapSet.t(integer()) | MapSet.t(String.t())) | term()) | term()) | nil keyword-only default: None)

• by_alias (boolean() keyword-only default: False)
• exclude_unset (boolean() keyword-only default: False)
• exclude_defaults (boolean() keyword-only default: False)
• exclude_none (boolean() keyword-only default: False)

Returns

• %{optional(String.t()) => term()}

@spec format(SnakeBridge.Ref.t(), [term()], keyword()) ::
  {:ok, String.t()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• max_output_chars (integer() default: 5000)

Returns

• String.t()

@spec from_orm(SnakeBridge.Ref.t(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• obj (term())

Returns

• term()

@spec json(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, String.t()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• include ((((MapSet.t(integer()) | MapSet.t(String.t())) | term()) | term()) | nil keyword-only default: None)

• exclude ((((MapSet.t(integer()) | MapSet.t(String.t())) | term()) | term()) | nil keyword-only default: None)

• by_alias (boolean() keyword-only default: False)
• exclude_unset (boolean() keyword-only default: False)
• exclude_defaults (boolean() keyword-only default: False)
• exclude_none (boolean() keyword-only default: False)

• encoder (term() | nil keyword-only default: PydanticUndefined)

• models_as_dict (boolean() keyword-only default: PydanticUndefined)
• dumps_kwargs (term())

Returns

• String.t()

@spec model_construct(SnakeBridge.Ref.t(), [term()], keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

`model_construct()` generally respects the `model_config.extra` setting on the provided model.
That is, if `model_config.extra == 'allow'`, then all extra passed values are added to the model instance's `__dict__`
and `__pydantic_extra__` fields. If `model_config.extra == 'ignore'` (the default), then all extra passed values are ignored.
Because no validation is performed with a call to `model_construct()`, having `model_config.extra == 'forbid'` does not result in
an error if extra values are passed, but they will be ignored.

Parameters

• _fields_set - A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.
• values - Trusted or pre-validated data dictionary.

Returns

• term()

@spec model_copy(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, term()} | {:error, Snakepit.Error.t()}

!!! abstract "Usage Documentation"

model_copy

Returns a copy of the model.

!!! note

The underlying instance's [`__dict__`][object.__dict__] attribute is copied. This
might have unexpected side effects if you store anything in it, on top of the model
fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters

• update - Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.
• deep - Set to True to make a deep copy of the model.

Returns

• term()

@spec model_dump(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, %{optional(String.t()) => term()}} | {:error, Snakepit.Error.t()}

!!! abstract "Usage Documentation"

model_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters

• mode - The mode in which to_python should run. If mode is 'json', the output will only contain JSON serializable types. If mode is 'python', the output may contain non-JSON-serializable Python objects.
• include - A set of fields to include in the output.
• exclude - A set of fields to exclude from the output.
• context - Additional context to pass to the serializer.
• by_alias - Whether to use the field's alias in the dictionary key if defined.
• exclude_unset - Whether to exclude fields that have not been explicitly set.
• exclude_defaults - Whether to exclude fields that are set to their default value.
• exclude_none - Whether to exclude fields that have a value of None.
• exclude_computed_fields - Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.
• round_trip - If True, dumped values should be valid as input for non-idempotent types such as Json[T].
• warnings - How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
• fallback - A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.
• serialize_as_any - Whether to serialize fields with duck-typing serialization behavior.

Returns

• %{optional(String.t()) => term()}

@spec model_dump_json(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, String.t()} | {:error, Snakepit.Error.t()}

!!! abstract "Usage Documentation"

model_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters

• indent - Indentation to use in the JSON output. If None is passed, the output will be compact.
• ensure_ascii - If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.
• include - Field(s) to include in the JSON output.
• exclude - Field(s) to exclude from the JSON output.
• context - Additional context to pass to the serializer.
• by_alias - Whether to serialize using field aliases.
• exclude_unset - Whether to exclude fields that have not been explicitly set.
• exclude_defaults - Whether to exclude fields that are set to their default value.
• exclude_none - Whether to exclude fields that have a value of None.
• exclude_computed_fields - Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.
• round_trip - If True, dumped values should be valid as input for non-idempotent types such as Json[T].
• warnings - How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
• fallback - A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.
• serialize_as_any - Whether to serialize fields with duck-typing serialization behavior.

Returns

• String.t()

@spec model_json_schema(SnakeBridge.Ref.t(), [term()], keyword()) ::
  {:ok, %{optional(String.t()) => term()}} | {:error, Snakepit.Error.t()}

Generates a JSON schema for a model class.

Parameters

• by_alias - Whether to use attribute aliases or not.
• ref_template - The reference template.
• union_format - The format to use when combining schemas from unions together. Can be one of:
• schema_generator - To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications
• mode - The mode in which to generate the schema.

Returns

• %{optional(String.t()) => term()}

@spec model_parametrized_name(SnakeBridge.Ref.t(), {term(), term()}, keyword()) ::
  {:ok, String.t()} | {:error, Snakepit.Error.t()}

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters

• params - Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Raises

• ArgumentError - Raised when trying to generate concrete names for non-generic models.

Returns

• String.t()

@spec model_post_init(SnakeBridge.Ref.t(), term(), keyword()) ::
  {:ok, nil} | {:error, Snakepit.Error.t()}

Override this method to perform additional initialization after __init__ and model_construct.

This is useful if you want to do some validation that requires the entire model to be initialized.

Parameters

• context (term())

Returns

• nil

@spec model_rebuild(SnakeBridge.Ref.t(), term(), term(), term(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters

• force - Whether to force the rebuilding of the model schema, defaults to False.
• raise_errors - Whether to raise errors, defaults to True.
• _parent_namespace_depth - The depth level of the parent namespace, defaults to 2.
• _types_namespace - The types namespace, defaults to None.

Returns

• term()

@spec model_validate(SnakeBridge.Ref.t(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

Validate a pydantic model instance.

Parameters

• obj - The object to validate.
• strict - Whether to enforce types strictly.
• extra - Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
• from_attributes - Whether to extract data from object attributes.
• context - Additional context to pass to the validator.
• by_alias - Whether to use the field's alias when validating against the provided input data.
• by_name - Whether to use the field's name when validating against the provided input data.

Raises

• ValidationError - If the object could not be validated.

Returns

• term()

@spec model_validate_json(SnakeBridge.Ref.t(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

!!! abstract "Usage Documentation"

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters

• json_data - The JSON data to validate.
• strict - Whether to enforce types strictly.
• extra - Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
• context - Extra variables to pass to the validator.
• by_alias - Whether to use the field's alias when validating against the provided input data.
• by_name - Whether to use the field's name when validating against the provided input data.

Raises

• ValidationError - If json_data is not a JSON string or the object could not be validated.

Returns

• term()

@spec model_validate_strings(SnakeBridge.Ref.t(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

Validate the given object with string data against the Pydantic model.

Parameters

• obj - The object containing string data to validate.
• strict - Whether to enforce types strictly.
• extra - Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
• context - Extra variables to pass to the validator.
• by_alias - Whether to use the field's alias when validating against the provided input data.
• by_name - Whether to use the field's name when validating against the provided input data.

Returns

• term()

@spec new(keyword()) :: {:ok, SnakeBridge.Ref.t()} | {:error, Snakepit.Error.t()}

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters

• data (term())

@spec parse_file(
  SnakeBridge.Ref.t(),
  term(),
  term(),
  term(),
  term(),
  term(),
  keyword()
) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• path (term())
• content_type (term())
• encoding (term())
• proto (term())
• allow_pickle (term())

Returns

• term()

@spec parse_obj(SnakeBridge.Ref.t(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• obj (term())

Returns

• term()

@spec parse_raw(
  SnakeBridge.Ref.t(),
  term(),
  term(),
  term(),
  term(),
  term(),
  keyword()
) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• b (term())
• content_type (term())
• encoding (term())
• proto (term())
• allow_pickle (term())

Returns

• term()

@spec schema(SnakeBridge.Ref.t(), [term()], keyword()) ::
  {:ok, %{optional(String.t()) => term()}} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• by_alias (boolean() default: True)
• ref_template (String.t() default: '#/$defs/{model}')

Returns

• %{optional(String.t()) => term()}

@spec schema_json(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, String.t()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• by_alias (boolean() keyword-only default: True)
• ref_template (String.t() keyword-only default: '#/$defs/{model}')
• dumps_kwargs (term())

Returns

• String.t()

@spec serialize_model(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, String.t()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Returns

• String.t()

@spec update_forward_refs(
  SnakeBridge.Ref.t(),
  keyword()
) :: {:ok, nil} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• localns (term())

Returns

• nil

@spec validate(SnakeBridge.Ref.t(), term(), keyword()) ::
  {:ok, term()} | {:error, Snakepit.Error.t()}

REPL data types for RLM and interpreter interactions.

These types represent the state and history of REPL-based execution:

• REPLVariable: Metadata about variables available in the REPL
• REPLEntry: A single interaction (reasoning, code, output)
• REPLHistory: Container for the full interaction history

Parameters

• value (term())

Returns

• term()