dataflow.llms.models

LLM Provider and Model Data Models.

This module defines Pydantic models for representing LLM providers, models, and their capabilities within the Haive dataflow system. These models are used for provider registration, capability tracking, and cost management.

Key Components:
  • Provider: LLM provider information and availability

  • Model: Comprehensive model specifications with capabilities

  • ModelCapabilities: Feature support matrix for each model

  • Pricing: Token-based pricing information

  • SearchPricing: Search-specific pricing tiers

Examples

Basic usage:

from haive.dataflow.llms.models import Provider, Model, ModelCapabilities

# Create a provider
provider = Provider(
    name="OpenAI",
    is_available=True,
    created_at="2024-01-01T00:00:00Z",
    updated_at="2024-01-01T00:00:00Z"
)

# Define model capabilities
capabilities = ModelCapabilities(
    supports_function_calling=True,
    supports_vision=True,
    supports_response_schema=True
)

# Create a model entry
model = Model(
    model_id="gpt-4-vision-preview",
    provider="OpenAI",
    mode="chat",
    litellm_provider="openai",
    max_tokens=128000,
    max_input_tokens=120000,
    max_output_tokens=8000,
    capabilities=capabilities
)
Advanced Usage:

With pricing information:

from haive.dataflow.llms.models import Pricing

pricing = Pricing(
    input_cost_per_token=0.00001,
    output_cost_per_token=0.00003,
    cache_read_input_token_cost=0.000005
)

model = Model(
    model_id="claude-3-opus",
    provider="Anthropic",
    mode="chat",
    litellm_provider="anthropic",
    max_tokens=200000,
    max_input_tokens=180000,
    max_output_tokens=20000,
    pricing=pricing
)

See also

  • haive.dataflow.registry: Model registration and discovery

  • haive.core.engine: Engine configuration using these models

  • haive.dataflow.providers: Provider implementation details

Notes

  • All token counts are measured in the model’s native tokenization

  • Pricing is in USD per token for standardized cost calculations

  • Capabilities enable automatic feature detection and routing

Classes

Model

!!! abstract "Usage Documentation"

ModelCapabilities

!!! abstract "Usage Documentation"

Pricing

!!! abstract "Usage Documentation"

Provider

!!! abstract "Usage Documentation"

SearchPricing

!!! abstract "Usage Documentation"

Module Contents

class dataflow.llms.models.Model(/, **data)

Bases: pydantic.BaseModel

!!! abstract “Usage Documentation”

[Models](../concepts/models.md)

A base class for creating Pydantic models.

Parameters:

data (Any)

__class_vars__

The names of the class variables defined on the model.

__private_attributes__

Metadata about the private attributes of the model.

__signature__

The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__

The core schema of the model.

__pydantic_custom_init__

Whether the model has a custom __init__ function.

__pydantic_decorators__

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

__pydantic_parent_namespace__

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__

The name of the post-init method for the model, if defined.

__pydantic_root_model__

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__

The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__

The names of fields explicitly set during instantiation.

__pydantic_private__

Values of private attributes set on the model instance.

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.

class dataflow.llms.models.ModelCapabilities(/, **data)

Bases: pydantic.BaseModel

!!! abstract “Usage Documentation”

[Models](../concepts/models.md)

A base class for creating Pydantic models.

Parameters:

data (Any)

__class_vars__

The names of the class variables defined on the model.

__private_attributes__

Metadata about the private attributes of the model.

__signature__

The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__

The core schema of the model.

__pydantic_custom_init__

Whether the model has a custom __init__ function.

__pydantic_decorators__

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

__pydantic_parent_namespace__

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__

The name of the post-init method for the model, if defined.

__pydantic_root_model__

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__

The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__

The names of fields explicitly set during instantiation.

__pydantic_private__

Values of private attributes set on the model instance.

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.

class dataflow.llms.models.Pricing(/, **data)

Bases: pydantic.BaseModel

!!! abstract “Usage Documentation”

[Models](../concepts/models.md)

A base class for creating Pydantic models.

Parameters:

data (Any)

__class_vars__

The names of the class variables defined on the model.

__private_attributes__

Metadata about the private attributes of the model.

__signature__

The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__

The core schema of the model.

__pydantic_custom_init__

Whether the model has a custom __init__ function.

__pydantic_decorators__

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

__pydantic_parent_namespace__

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__

The name of the post-init method for the model, if defined.

__pydantic_root_model__

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__

The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__

The names of fields explicitly set during instantiation.

__pydantic_private__

Values of private attributes set on the model instance.

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.

class dataflow.llms.models.Provider(/, **data)

Bases: pydantic.BaseModel

!!! abstract “Usage Documentation”

[Models](../concepts/models.md)

A base class for creating Pydantic models.

Parameters:

data (Any)

__class_vars__

The names of the class variables defined on the model.

__private_attributes__

Metadata about the private attributes of the model.

__signature__

The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__

The core schema of the model.

__pydantic_custom_init__

Whether the model has a custom __init__ function.

__pydantic_decorators__

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

__pydantic_parent_namespace__

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__

The name of the post-init method for the model, if defined.

__pydantic_root_model__

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__

The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__

The names of fields explicitly set during instantiation.

__pydantic_private__

Values of private attributes set on the model instance.

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.

class dataflow.llms.models.SearchPricing(/, **data)

Bases: pydantic.BaseModel

!!! abstract “Usage Documentation”

[Models](../concepts/models.md)

A base class for creating Pydantic models.

Parameters:

data (Any)

__class_vars__

The names of the class variables defined on the model.

__private_attributes__

Metadata about the private attributes of the model.

__signature__

The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__

The core schema of the model.

__pydantic_custom_init__

Whether the model has a custom __init__ function.

__pydantic_decorators__

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

__pydantic_parent_namespace__

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__

The name of the post-init method for the model, if defined.

__pydantic_root_model__

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__

The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__

The names of fields explicitly set during instantiation.

__pydantic_private__

Values of private attributes set on the model instance.

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.