class langgraph_agent_toolkit.core.settings.Settings(_case_sensitive=None, _nested_model_default_partial_update=None, _env_prefix=None, _env_file=PosixPath('.'), _env_file_encoding=None, _env_ignore_empty=None, _env_nested_delimiter=None, _env_nested_max_split=None, _env_parse_none_str=None, _env_parse_enums=None, _cli_prog_name=None, _cli_parse_args=None, _cli_settings_source=None, _cli_parse_none_str=None, _cli_hide_none_type=None, _cli_avoid_json=None, _cli_enforce_required=None, _cli_use_class_docs_for_groups=None, _cli_exit_on_error=None, _cli_prefix=None, _cli_flag_prefix_char=None, _cli_implicit_flags=None, _cli_ignore_unknown_args=None, _cli_kebab_case=None, _cli_shortcuts=None, _secrets_dir=None, *, ENV_MODE=None, HOST='0.0.0.0', PORT=8080, AUTH_SECRET=None, USE_FAKE_MODEL=False, OPENAI_API_KEY=None, OPENAI_API_BASE_URL=None, OPENAI_API_VERSION=None, OPENAI_MODEL_NAME=None, AZURE_OPENAI_API_KEY=None, AZURE_OPENAI_ENDPOINT=None, AZURE_OPENAI_API_VERSION=None, AZURE_OPENAI_MODEL_NAME=None, AZURE_OPENAI_DEPLOYMENT_NAME=None, ANTHROPIC_MODEL_NAME=None, ANTHROPIC_API_KEY=None, GOOGLE_VERTEXAI_MODEL_NAME=None, GOOGLE_VERTEXAI_API_KEY=None, GOOGLE_GENAI_MODEL_NAME=None, GOOGLE_GENAI_API_KEY=None, AWS_BEDROCK_MODEL_NAME=None, DEEPSEEK_MODEL_NAME=None, DEEPSEEK_API_KEY=None, OLLAMA_MODEL_NAME=None, OLLAMA_BASE_URL=None, OBSERVABILITY_BACKEND=None, AGENT_PATHS=['langgraph_agent_toolkit.agents.blueprints.react.agent:react_agent', 'langgraph_agent_toolkit.agents.blueprints.chatbot.agent:chatbot_agent', 'langgraph_agent_toolkit.agents.blueprints.react_so.agent:react_agent_so'], LANGCHAIN_TRACING_V2=False, LANGCHAIN_PROJECT='default', LANGCHAIN_ENDPOINT='https://api.smith.langchain.com', LANGCHAIN_API_KEY=None, LANGFUSE_SECRET_KEY=None, LANGFUSE_PUBLIC_KEY=None, LANGFUSE_HOST='https://cloud.langfuse.com', MEMORY_BACKEND=MemoryBackends.SQLITE, SQLITE_DB_PATH='checkpoints.db', POSTGRES_USER=None, POSTGRES_PASSWORD=None, POSTGRES_HOST=None, POSTGRES_PORT=None, POSTGRES_DB=None, POSTGRES_POOL_SIZE=200, POSTGRES_MIN_SIZE=10, POSTGRES_MAX_IDLE=300, MODEL_CONFIGS=<factory>)

Bases: BaseSettings

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:

• _case_sensitive (bool | None)

• _nested_model_default_partial_update (bool | None)

• _env_prefix (str | None)

• _env_file (DotenvType | None)

• _env_file_encoding (str | None)

• _env_ignore_empty (bool | None)

• _env_nested_delimiter (str | None)

• _env_nested_max_split (int | None)

• _env_parse_none_str (str | None)

• _env_parse_enums (bool | None)

• _cli_prog_name (str | None)

• _cli_parse_args (bool | list[str] | tuple[str, ...] | None)

• _cli_settings_source (CliSettingsSource[Any] | None)

• _cli_parse_none_str (str | None)

• _cli_hide_none_type (bool | None)

• _cli_avoid_json (bool | None)

• _cli_enforce_required (bool | None)

• _cli_use_class_docs_for_groups (bool | None)

• _cli_exit_on_error (bool | None)

• _cli_prefix (str | None)

• _cli_flag_prefix_char (str | None)

• _cli_implicit_flags (bool | None)

• _cli_ignore_unknown_args (bool | None)

• _cli_kebab_case (bool | None)

• _cli_shortcuts (Mapping[str, str | list[str]] | None)

• _secrets_dir (PathType | None)

• ENV_MODE (str | None)

• HOST (str)

• PORT (int)

• AUTH_SECRET (SecretStr | None)

• USE_FAKE_MODEL (bool)

• OPENAI_API_KEY (SecretStr | None)

• OPENAI_API_BASE_URL (str | None)

• OPENAI_API_VERSION (str | None)

• OPENAI_MODEL_NAME (str | None)

• AZURE_OPENAI_API_KEY (SecretStr | None)

• AZURE_OPENAI_ENDPOINT (str | None)

• AZURE_OPENAI_API_VERSION (str | None)

• AZURE_OPENAI_MODEL_NAME (str | None)

• AZURE_OPENAI_DEPLOYMENT_NAME (str | None)

• ANTHROPIC_MODEL_NAME (str | None)

• ANTHROPIC_API_KEY (SecretStr | None)

• GOOGLE_VERTEXAI_MODEL_NAME (str | None)

• GOOGLE_VERTEXAI_API_KEY (SecretStr | None)

• GOOGLE_GENAI_MODEL_NAME (str | None)

• GOOGLE_GENAI_API_KEY (SecretStr | None)

• AWS_BEDROCK_MODEL_NAME (str | None)

• DEEPSEEK_MODEL_NAME (str | None)

• DEEPSEEK_API_KEY (SecretStr | None)

• OLLAMA_MODEL_NAME (str | None)

• OLLAMA_BASE_URL (str | None)

• OBSERVABILITY_BACKEND (ObservabilityBackend | None)

• AGENT_PATHS (list[str])

• LANGCHAIN_TRACING_V2 (bool)

• LANGCHAIN_PROJECT (str)

• LANGCHAIN_ENDPOINT (Annotated[str, BeforeValidator(func=~langgraph_agent_toolkit.helper.utils.check_str_is_http, json_schema_input_type=PydanticUndefined)])

• LANGCHAIN_API_KEY (SecretStr | None)

• LANGFUSE_SECRET_KEY (SecretStr | None)

• LANGFUSE_PUBLIC_KEY (SecretStr | None)

• LANGFUSE_HOST (Annotated[str, BeforeValidator(func=~langgraph_agent_toolkit.helper.utils.check_str_is_http, json_schema_input_type=PydanticUndefined)])

• MEMORY_BACKEND (MemoryBackends)

• SQLITE_DB_PATH (str)

• POSTGRES_USER (str | None)

• POSTGRES_PASSWORD (SecretStr | None)

• POSTGRES_HOST (str | None)

• POSTGRES_PORT (int | None)

• POSTGRES_DB (str | None)

• POSTGRES_POOL_SIZE (int)

• POSTGRES_MIN_SIZE (int)

• POSTGRES_MAX_IDLE (int)

• MODEL_CONFIGS (Dict[str, Dict[str, Any]])

model_config: ClassVar[SettingsConfigDict] = {'arbitrary_types_allowed': True, 'case_sensitive': False, 'cli_avoid_json': False, 'cli_enforce_required': False, 'cli_exit_on_error': True, 'cli_flag_prefix_char': '-', 'cli_hide_none_type': False, 'cli_ignore_unknown_args': False, 'cli_implicit_flags': False, 'cli_kebab_case': False, 'cli_parse_args': None, 'cli_parse_none_str': None, 'cli_prefix': '', 'cli_prog_name': None, 'cli_shortcuts': None, 'cli_use_class_docs_for_groups': False, 'enable_decoding': True, 'env_file': '', 'env_file_encoding': 'utf-8', 'env_ignore_empty': True, 'env_nested_delimiter': None, 'env_nested_max_split': None, 'env_parse_enums': None, 'env_parse_none_str': None, 'env_prefix': '', 'extra': 'ignore', 'json_file': None, 'json_file_encoding': None, 'nested_model_default_partial_update': False, 'protected_namespaces': ('model_validate', 'model_dump', 'settings_customise_sources'), 'secrets_dir': None, 'toml_file': None, 'validate_default': False, 'yaml_config_section': None, 'yaml_file': None, 'yaml_file_encoding': None}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

ENV_MODE: str | None

HOST: str

PORT: int

AUTH_SECRET: SecretStr | None

USE_FAKE_MODEL: bool

OPENAI_API_KEY: SecretStr | None

OPENAI_API_BASE_URL: str | None

OPENAI_API_VERSION: str | None

OPENAI_MODEL_NAME: str | None

AZURE_OPENAI_API_KEY: SecretStr | None

AZURE_OPENAI_ENDPOINT: str | None

AZURE_OPENAI_API_VERSION: str | None

AZURE_OPENAI_MODEL_NAME: str | None

AZURE_OPENAI_DEPLOYMENT_NAME: str | None

ANTHROPIC_MODEL_NAME: str | None

ANTHROPIC_API_KEY: SecretStr | None

GOOGLE_VERTEXAI_MODEL_NAME: str | None

GOOGLE_VERTEXAI_API_KEY: SecretStr | None

GOOGLE_GENAI_MODEL_NAME: str | None

GOOGLE_GENAI_API_KEY: SecretStr | None

AWS_BEDROCK_MODEL_NAME: str | None

DEEPSEEK_MODEL_NAME: str | None

DEEPSEEK_API_KEY: SecretStr | None

OLLAMA_MODEL_NAME: str | None

OLLAMA_BASE_URL: str | None

OBSERVABILITY_BACKEND: ObservabilityBackend | None

AGENT_PATHS: list[str]

LANGCHAIN_TRACING_V2: bool

LANGCHAIN_PROJECT: str

LANGCHAIN_ENDPOINT: Annotated[str, BeforeValidator(func=check_str_is_http, json_schema_input_type=PydanticUndefined)]

LANGCHAIN_API_KEY: SecretStr | None

LANGFUSE_SECRET_KEY: SecretStr | None

LANGFUSE_PUBLIC_KEY: SecretStr | None

LANGFUSE_HOST: Annotated[str, BeforeValidator(func=check_str_is_http, json_schema_input_type=PydanticUndefined)]

MEMORY_BACKEND: MemoryBackends

SQLITE_DB_PATH: str

POSTGRES_USER: str | None

POSTGRES_PASSWORD: SecretStr | None

POSTGRES_HOST: str | None

POSTGRES_PORT: int | None

POSTGRES_DB: str | None

POSTGRES_POOL_SIZE: int

POSTGRES_MIN_SIZE: int

POSTGRES_MAX_IDLE: int

MODEL_CONFIGS: Dict[str, Dict[str, Any]]

get_model_config(config_key)

Get a model configuration by key.

Parameters:

config_key (str) – The key of the model configuration to get

Returns:

The model configuration dict if found, None otherwise

Return type:

Dict[str, Any] | None

setup()

Initialize all settings.

Return type:

None

property BASE_URL: str

is_dev()

Return type:

bool

__init__(_case_sensitive=None, _nested_model_default_partial_update=None, _env_prefix=None, _env_file=ENV_FILE_SENTINEL, _env_file_encoding=None, _env_ignore_empty=None, _env_nested_delimiter=None, _env_nested_max_split=None, _env_parse_none_str=None, _env_parse_enums=None, _cli_prog_name=None, _cli_parse_args=None, _cli_settings_source=None, _cli_parse_none_str=None, _cli_hide_none_type=None, _cli_avoid_json=None, _cli_enforce_required=None, _cli_use_class_docs_for_groups=None, _cli_exit_on_error=None, _cli_prefix=None, _cli_flag_prefix_char=None, _cli_implicit_flags=None, _cli_ignore_unknown_args=None, _cli_kebab_case=None, _cli_shortcuts=None, _secrets_dir=None, **values)

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:

• _case_sensitive (bool | None)

• _nested_model_default_partial_update (bool | None)

• _env_prefix (str | None)

• _env_file (Path | str | Sequence[Path | str] | None)

• _env_file_encoding (str | None)

• _env_ignore_empty (bool | None)

• _env_nested_delimiter (str | None)

• _env_nested_max_split (int | None)

• _env_parse_none_str (str | None)

• _env_parse_enums (bool | None)

• _cli_prog_name (str | None)

• _cli_parse_args (bool | list[str] | tuple[str, ...] | None)

• _cli_settings_source (CliSettingsSource[Any] | None)

• _cli_parse_none_str (str | None)

• _cli_hide_none_type (bool | None)

• _cli_avoid_json (bool | None)

• _cli_enforce_required (bool | None)

• _cli_use_class_docs_for_groups (bool | None)

• _cli_exit_on_error (bool | None)

• _cli_prefix (str | None)

• _cli_flag_prefix_char (str | None)

• _cli_implicit_flags (bool | None)

• _cli_ignore_unknown_args (bool | None)

• _cli_kebab_case (bool | None)

• _cli_shortcuts (Mapping[str, str | list[str]] | None)

• _secrets_dir (Path | str | Sequence[Path | str] | None)

• values (Any)

Return type:

None

classmethod construct(_fields_set=None, **values)

Parameters:

• _fields_set (set[str] | None)

• values (Any)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

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 (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to include in the copied model.

• exclude (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to exclude in the copied model.

• update (Dict[str, Any] | None) – Optional dictionary of field-value pairs to override field values in the copied model.

• deep (bool) – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

Return type:

Self

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Parameters:

• include (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None)

• exclude (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None)

• by_alias (bool)

• exclude_unset (bool)

• exclude_defaults (bool)

• exclude_none (bool)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Parameters:

obj (Any)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Parameters:

• include (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None)

• exclude (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None)

• by_alias (bool)

• exclude_unset (bool)

• exclude_defaults (bool)

• exclude_none (bool)

• encoder (Callable[[Any], Any] | None)

• models_as_dict (bool)

• dumps_kwargs (Any)

Return type:

str

model_computed_fields = {'BASE_URL': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}

classmethod model_construct(_fields_set=None, **values)

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 (set[str] | None) – 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 (Any) – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

Return type:

Self

model_copy(*, update=None, deep=False)

!!! abstract “Usage Documentation”

[model_copy](../concepts/serialization.md#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 (Mapping[str, Any] | None) – 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 (bool) – Set to True to make a deep copy of the model.

Returns:

New model instance.

Return type:

Self

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=None, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, fallback=None, serialize_as_any=False)

!!! abstract “Usage Documentation”

[model_dump](../concepts/serialization.md#modelmodel_dump)

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

Parameters:

• mode (Literal['json', 'python'] | str) – 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 (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None) – A set of fields to include in the output.

• exclude (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool | None) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (bool | Literal['none', 'warn', 'error']) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• fallback (Callable[[Any], Any] | None) – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Returns:

A dictionary representation of the model.

Return type:

dict[str, Any]

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=None, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, fallback=None, serialize_as_any=False)

!!! abstract “Usage Documentation”

[model_dump_json](../concepts/serialization.md#modelmodel_dump_json)

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

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None) – Field(s) to include in the JSON output.

• exclude (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool | None) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (bool | Literal['none', 'warn', 'error']) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• fallback (Callable[[Any], Any] | None) – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Returns:

A JSON string representation of the model.

Return type:

str

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to “allow”.

model_fields = {'AGENT_PATHS': FieldInfo(annotation=list[str], required=False, default=['langgraph_agent_toolkit.agents.blueprints.react.agent:react_agent', 'langgraph_agent_toolkit.agents.blueprints.chatbot.agent:chatbot_agent', 'langgraph_agent_toolkit.agents.blueprints.react_so.agent:react_agent_so']), 'ANTHROPIC_API_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'ANTHROPIC_MODEL_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'AUTH_SECRET': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'AWS_BEDROCK_MODEL_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'AZURE_OPENAI_API_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'AZURE_OPENAI_API_VERSION': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'AZURE_OPENAI_DEPLOYMENT_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'AZURE_OPENAI_ENDPOINT': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'AZURE_OPENAI_MODEL_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'DEEPSEEK_API_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'DEEPSEEK_MODEL_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ENV_MODE': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'GOOGLE_GENAI_API_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'GOOGLE_GENAI_MODEL_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'GOOGLE_VERTEXAI_API_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'GOOGLE_VERTEXAI_MODEL_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'HOST': FieldInfo(annotation=str, required=False, default='0.0.0.0'), 'LANGCHAIN_API_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'LANGCHAIN_ENDPOINT': FieldInfo(annotation=str, required=False, default='https://api.smith.langchain.com', metadata=[BeforeValidator(func=<function check_str_is_http>, json_schema_input_type=PydanticUndefined)]), 'LANGCHAIN_PROJECT': FieldInfo(annotation=str, required=False, default='default'), 'LANGCHAIN_TRACING_V2': FieldInfo(annotation=bool, required=False, default=False), 'LANGFUSE_HOST': FieldInfo(annotation=str, required=False, default='https://cloud.langfuse.com', metadata=[BeforeValidator(func=<function check_str_is_http>, json_schema_input_type=PydanticUndefined)]), 'LANGFUSE_PUBLIC_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'LANGFUSE_SECRET_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'MEMORY_BACKEND': FieldInfo(annotation=MemoryBackends, required=False, default=<MemoryBackends.SQLITE: 'sqlite'>), 'MODEL_CONFIGS': FieldInfo(annotation=Dict[str, Dict[str, Any]], required=False, default_factory=dict), 'OBSERVABILITY_BACKEND': FieldInfo(annotation=Union[ObservabilityBackend, NoneType], required=False, default=None), 'OLLAMA_BASE_URL': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'OLLAMA_MODEL_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'OPENAI_API_BASE_URL': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'OPENAI_API_KEY': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'OPENAI_API_VERSION': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'OPENAI_MODEL_NAME': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'PORT': FieldInfo(annotation=int, required=False, default=8080), 'POSTGRES_DB': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'POSTGRES_HOST': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'POSTGRES_MAX_IDLE': FieldInfo(annotation=int, required=False, default=300, description='Maximum number of idle connections'), 'POSTGRES_MIN_SIZE': FieldInfo(annotation=int, required=False, default=10, description='Minimum number of connections in the pool'), 'POSTGRES_PASSWORD': FieldInfo(annotation=Union[SecretStr, NoneType], required=False, default=None), 'POSTGRES_POOL_SIZE': FieldInfo(annotation=int, required=False, default=200, description='Maximum number of connections in the pool'), 'POSTGRES_PORT': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'POSTGRES_USER': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SQLITE_DB_PATH': FieldInfo(annotation=str, required=False, default='checkpoints.db'), 'USE_FAKE_MODEL': FieldInfo(annotation=bool, required=False, default=False)}

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template=DEFAULT_REF_TEMPLATE, schema_generator=GenerateJsonSchema, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Returns:

The JSON schema for the given model class.

Return type:

dict[str, Any]

classmethod model_parametrized_name(params)

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[type[Any], ...]) – 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.

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

Return type:

str

model_post_init(context, /)

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 (Any)

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

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 (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (MappingNamespace | None) – The types namespace, defaults to None.

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

Return type:

bool | None

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None, by_alias=None, by_name=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

• by_alias (bool | None) – Whether to use the field’s alias when validating against the provided input data.

• by_name (bool | None) – Whether to use the field’s name when validating against the provided input data.

Raises:

ValidationError – If the object could not be validated.

Returns:

The validated model instance.

Return type:

Self

classmethod model_validate_json(json_data, *, strict=None, context=None, by_alias=None, by_name=None)

!!! abstract “Usage Documentation”

[JSON Parsing](../concepts/json.md#json-parsing)

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

• by_alias (bool | None) – Whether to use the field’s alias when validating against the provided input data.

• by_name (bool | None) – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

Raises:

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

Return type:

Self

classmethod model_validate_strings(obj, *, strict=None, context=None, by_alias=None, by_name=None)

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

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

• by_alias (bool | None) – Whether to use the field’s alias when validating against the provided input data.

• by_name (bool | None) – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

Return type:

Self

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Parameters:

• path (str | Path)

• content_type (str | None)

• encoding (str)

• proto (DeprecatedParseProtocol | None)

• allow_pickle (bool)

Return type:

Self

classmethod parse_obj(obj)

Parameters:

obj (Any)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Parameters:

• b (str | bytes)

• content_type (str | None)

• encoding (str)

• proto (DeprecatedParseProtocol | None)

• allow_pickle (bool)

Return type:

Self

classmethod schema(by_alias=True, ref_template=DEFAULT_REF_TEMPLATE)

Parameters:

• by_alias (bool)

• ref_template (str)

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template=DEFAULT_REF_TEMPLATE, **dumps_kwargs)

Parameters:

• by_alias (bool)

• ref_template (str)

• dumps_kwargs (Any)

Return type:

str

classmethod settings_customise_sources(settings_cls, init_settings, env_settings, dotenv_settings, file_secret_settings)

Define the sources and their order for loading the settings values.

Parameters:

• settings_cls (type[BaseSettings]) – The Settings class.

• init_settings (PydanticBaseSettingsSource) – The InitSettingsSource instance.

• env_settings (PydanticBaseSettingsSource) – The EnvSettingsSource instance.

• dotenv_settings (PydanticBaseSettingsSource) – The DotEnvSettingsSource instance.

• file_secret_settings (PydanticBaseSettingsSource) – The SecretsSettingsSource instance.

Returns:

A tuple containing the sources and their order for loading the settings values.

Return type:

tuple[PydanticBaseSettingsSource, …]

classmethod update_forward_refs(**localns)

Parameters:

localns (Any)

Return type:

None

classmethod validate(value)

Parameters:

value (Any)

Return type:

Self