coinbase_agentkit.action_providers.hyperboliclabs.ai package

Submodules

coinbase_agentkit.action_providers.hyperboliclabs.ai.action_provider module

Hyperbolic AI action provider.

This module provides actions for interacting with Hyperbolic AI services. It includes functionality for text, image and audio generation.

class coinbase_agentkit.action_providers.hyperboliclabs.ai.action_provider.AIActionProvider(api_key=None)

Bases: ActionProvider

Action provider for generating text, images and audio via AI.

description = 'Action provider for generating text, images and audio via AI.'

generate_audio(args)

Generate audio from text using specified language and speaker.

Parameters:

args (dict[str, Any]) – Input arguments for the action.

Returns:

A message containing the action response or error details.

Return type:

str

generate_image(args)

Generate images using specified model.

Parameters:

args (dict[str, Any]) – Input arguments for the action.

Returns:

A message containing the action response or error details.

Return type:

str

generate_text(args)

Generate text using specified language model.

Parameters:

args (dict[str, Any]) – Input arguments for the action.

Returns:

A message containing the action response or error details.

Return type:

str

coinbase_agentkit.action_providers.hyperboliclabs.ai.action_provider.ai_action_provider(api_key=None)

Create a new instance of the AIActionProvider.

Parameters:

api_key (Optional[str]) – Optional API key for authentication. If not provided, will attempt to read from HYPERBOLIC_API_KEY environment variable.

Return type:

AIActionProvider

Returns:

A new AI action provider instance.

Raises:

ValueError – If API key is not provided and not found in environment.

coinbase_agentkit.action_providers.hyperboliclabs.ai.schemas module

Schemas for Hyperbolic AI actions.

This module provides simplified schemas for AI action inputs.

class coinbase_agentkit.action_providers.hyperboliclabs.ai.schemas.GenerateAudioSchema(**data)

Bases: BaseModel

Schema for generate_audio action.

language: str

model_config: ClassVar[ConfigDict] = {}

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

speaker: str

speed: float | None

text: str

class coinbase_agentkit.action_providers.hyperboliclabs.ai.schemas.GenerateImageSchema(**data)

Bases: BaseModel

Schema for generate_image action.

height: int

model_config: ClassVar[ConfigDict] = {}

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

model_name: str

negative_prompt: str | None

num_images: int

prompt: str

steps: int

width: int

class coinbase_agentkit.action_providers.hyperboliclabs.ai.schemas.GenerateTextSchema(**data)

Bases: BaseModel

Schema for generate_text action.

model: str

model_config: ClassVar[ConfigDict] = {}

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

prompt: str

system_prompt: str | None

coinbase_agentkit.action_providers.hyperboliclabs.ai.service module

Service for AI-related operations.

class coinbase_agentkit.action_providers.hyperboliclabs.ai.service.AIService(api_key)

Bases: Base

AI service for Hyperbolic platform.

generate_audio(request)

Generate audio using specified model.

Parameters:

request (AudioGenerationRequest) – The AudioGenerationRequest object containing the request parameters.

Returns:

The audio generation response.

Return type:

AudioGenerationResponse

generate_image(request)

Generate images using specified model.

Parameters:

request (ImageGenerationRequest) – The ImageGenerationRequest object containing the request parameters.

Returns:

The image generation response.

Return type:

ImageGenerationResponse

generate_text(request)

Generate text using specified model.

Parameters:

request (ChatCompletionRequest) – The ChatCompletionRequest object containing the request parameters.

Returns:

The chat completion response.

Return type:

ChatCompletionResponse

coinbase_agentkit.action_providers.hyperboliclabs.ai.types module

Types for Hyperbolic AI services.

This module provides type definitions for AI API communication.

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.AudioGenerationRequest(**data)

Bases: BaseModel

Request model for audio generation API.

language: str | None

model_config: ClassVar[ConfigDict] = {}

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

noise_scale: float | None

noise_scale_w: float | None

sdp_ratio: float | None

speaker: str | None

speed: float | None

text: str

classmethod validate_language(v)

Wrap a classmethod, staticmethod, property or unbound function and act as a descriptor that allows us to detect decorated items from the class’ attributes.

This class’ __get__ returns the wrapped item’s __get__ result, which makes it transparent for classmethods and staticmethods.

wrapped

The decorator that has to be wrapped.

decorator_info

The decorator info.

shim

A wrapper function to wrap V1 style function.

classmethod validate_speaker(v, values)

Wrap a classmethod, staticmethod, property or unbound function and act as a descriptor that allows us to detect decorated items from the class’ attributes.

This class’ __get__ returns the wrapped item’s __get__ result, which makes it transparent for classmethods and staticmethods.

wrapped

The decorator that has to be wrapped.

decorator_info

The decorator info.

shim

A wrapper function to wrap V1 style function.

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.AudioGenerationResponse(**data)

Bases: BaseModel

Response model for audio generation API.

audio: str

duration: float | None

model_config: ClassVar[ConfigDict] = {}

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

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ChatCompletionRequest(**data)

Bases: BaseModel

Request model for chat completion API.

frequency_penalty: float | None

logit_bias: dict[str, float] | None

logprobs: int | None

max_tokens: int | None

messages: list[ChatMessage]

min_p: float | None

model: str

model_config: ClassVar[ConfigDict] = {}

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

n: int | None

presence_penalty: float | None

repetition_penalty: float | None

seed: int | None

stop: list[str] | None

stream: bool | None

temperature: float | None

top_k: int | None

top_logprobs: int | None

top_p: float | None

user: str | None

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ChatCompletionResponse(**data)

Bases: BaseModel

Response model for chat completion API.

choices: list[ChatCompletionResponseChoice]

created: int

id: str

model: str

model_config: ClassVar[ConfigDict] = {}

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

object: str

usage: ChatCompletionResponseUsage | None

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ChatCompletionResponseChoice(**data)

Bases: BaseModel

A single choice in the chat completion response.

finish_reason: str | None

index: int

message: ChatCompletionResponseMessage

model_config: ClassVar[ConfigDict] = {}

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

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ChatCompletionResponseMessage(**data)

Bases: BaseModel

A message in the chat completion response.

content: str

model_config: ClassVar[ConfigDict] = {}

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

role: str

classmethod validate_role(v)

Wrap a classmethod, staticmethod, property or unbound function and act as a descriptor that allows us to detect decorated items from the class’ attributes.

This class’ __get__ returns the wrapped item’s __get__ result, which makes it transparent for classmethods and staticmethods.

wrapped

The decorator that has to be wrapped.

decorator_info

The decorator info.

shim

A wrapper function to wrap V1 style function.

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ChatCompletionResponseUsage(**data)

Bases: BaseModel

Token usage information.

completion_tokens: int

model_config: ClassVar[ConfigDict] = {}

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

prompt_tokens: int

total_tokens: int

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ChatMessage(**data)

Bases: BaseModel

A single message in a chat conversation.

content: str

model_config: ClassVar[ConfigDict] = {}

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

role: str

classmethod validate_role(v)

Wrap a classmethod, staticmethod, property or unbound function and act as a descriptor that allows us to detect decorated items from the class’ attributes.

This class’ __get__ returns the wrapped item’s __get__ result, which makes it transparent for classmethods and staticmethods.

wrapped

The decorator that has to be wrapped.

decorator_info

The decorator info.

shim

A wrapper function to wrap V1 style function.

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.GeneratedImage(**data)

Bases: BaseModel

A single generated image with its metadata.

image: str

index: int

model_config: ClassVar[ConfigDict] = {}

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

random_seed: int

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ImageGenerationRequest(**data)

Bases: BaseModel

Request model for image generation API.

backend: str

cfg_scale: float | None

controlnet_image: str | None

controlnet_name: str | None

enable_refiner: bool

height: int

loras: dict[str, float] | None

model_config: ClassVar[ConfigDict] = {}

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

model_name: str

negative_prompt: str | None

num_images: int

prompt: str

seed: int | None

steps: int

style_preset: str | None

width: int

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ImageGenerationResponse(**data)

Bases: BaseModel

Response model for image generation API.

images: list[GeneratedImage]

inference_time: float | None

model_config: ClassVar[ConfigDict] = {}

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

class coinbase_agentkit.action_providers.hyperboliclabs.ai.types.ImageMetadata(**data)

Bases: BaseModel

Metadata for a generated image.

cfg_scale: float | None

model_config: ClassVar[ConfigDict] = {}

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

negative_prompt: str | None

prompt: str | None

seed: int | None

steps: int | None

coinbase_agentkit.action_providers.hyperboliclabs.ai.utils module

Utility functions for Hyperbolic AI services.

This module provides utility functions for handling AI service operations such as saving generated data.

coinbase_agentkit.action_providers.hyperboliclabs.ai.utils.save_base64_data(base64_data, output_path)

Save base64 encoded data to a file.

Parameters:

• base64_data (str) – The base64 encoded data string

• output_path (str) – Path where to save the file

Returns:

The absolute path to the saved file

Return type:

str

Raises:

• ValueError – If the base64 data is invalid

• OSError – If there’s an error saving the file

coinbase_agentkit.action_providers.hyperboliclabs.ai.utils.save_text(text, output_path)

Save text data to a file and return a preview.

Parameters:

• text (str) – The text to save

• output_path (str) – Path where to save the text file

Returns:

The absolute path to the saved text file

Return type:

str

Raises:

OSError – If there’s an error saving the file

Module contents

Hyperbolic AI action provider module.

This module provides actions for interacting with Hyperbolic AI services, including text, image, and audio generation.

class coinbase_agentkit.action_providers.hyperboliclabs.ai.AIActionProvider(api_key=None)

Bases: ActionProvider

Action provider for generating text, images and audio via AI.

description = 'Action provider for generating text, images and audio via AI.'

generate_audio(args)

Generate audio from text using specified language and speaker.

Parameters:

args (dict[str, Any]) – Input arguments for the action.

Returns:

A message containing the action response or error details.

Return type:

str

generate_image(args)

Generate images using specified model.

Parameters:

args (dict[str, Any]) – Input arguments for the action.

Returns:

A message containing the action response or error details.

Return type:

str

generate_text(args)

Generate text using specified language model.

Parameters:

args (dict[str, Any]) – Input arguments for the action.

Returns:

A message containing the action response or error details.

Return type:

str

coinbase_agentkit.action_providers.hyperboliclabs.ai.ai_action_provider(api_key=None)

Create a new instance of the AIActionProvider.

Parameters:

api_key (Optional[str]) – Optional API key for authentication. If not provided, will attempt to read from HYPERBOLIC_API_KEY environment variable.

Return type:

AIActionProvider

Returns:

A new AI action provider instance.

Raises:

ValueError – If API key is not provided and not found in environment.