agentconnect.core.types module

Core type definitions for the AgentConnect framework.

This module provides the fundamental types, enumerations, and data structures used throughout the framework, including agent identities, capabilities, and message types.

class ModelProvider(value)

Bases: str, Enum

Supported AI model providers.

This enum defines the supported model providers for AI agents.

OPENAI = 'openai'
ANTHROPIC = 'anthropic'
GROQ = 'groq'
GOOGLE = 'google'
class ModelName(value)

Bases: str, Enum

Supported model names for each provider.

This enum defines the specific model names available for each provider.

GPT4_5_PREVIEW = 'gpt-4.5-preview-2025-02-27'
GPT4_1 = 'gpt-4.1'
GPT4_1_MINI = 'gpt-4.1-mini'
GPT4O = 'gpt-4o'
GPT4O_MINI = 'gpt-4o-mini'
O1 = 'o1'
O1_MINI = 'o1-mini'
O3 = 'o3'
O3_MINI = 'o3-mini'
O4_MINI = 'o4-mini'
CLAUDE_3_7_SONNET = 'claude-3-7-sonnet-latest'
CLAUDE_3_5_SONNET = 'claude-3-5-sonnet-latest'
CLAUDE_3_5_HAIKU = 'claude-3-5-haiku-latest'
CLAUDE_3_OPUS = 'claude-3-opus-latest'
CLAUDE_3_SONNET = 'claude-3-sonnet-20240229'
CLAUDE_3_HAIKU = 'claude-3-haiku-20240307'
LLAMA33_70B_VTL = 'llama-3.3-70b-versatile'
LLAMA3_1_8B_INSTANT = 'llama-3.1-8b-instant'
LLAMA_GUARD3_8B = 'llama-guard-3-8b'
LLAMA3_70B = 'llama3-70b-8192'
LLAMA3_8B = 'llama3-8b-8192'
MIXTRAL = 'mixtral-8x7b-32768'
GEMMA2_90B = 'gemma2-9b-it'
GEMINI2_5_PRO = 'gemini-2.5-pro'
GEMINI2_5_FLASH = 'gemini-2.5-flash'
GEMINI2_5_FLASH_LITE = 'gemini-2.5-flash-lite'
GEMINI2_FLASH = 'gemini-2.0-flash'
GEMINI2_FLASH_LITE = 'gemini-2.0-flash-lite'
GEMINI2_PRO_EXP = 'gemini-2.0-pro-exp-02-05'
GEMINI2_FLASH_THINKING_EXP = 'gemini-2.0-flash-thinking-exp-01-21'
classmethod get_default_for_provider(provider)

Get the default model for a given provider.

Parameters:

provider (ModelProvider) – The model provider to get the default model for

Return type:

ModelName

Returns:

The default model name for the provider

Raises:

ValueError – If no default model is defined for the provider

class AgentType(value)

Bases: str, Enum

Types of agents in the system.

This enum defines the different types of agents that can exist in the system.

HUMAN = 'human'
AI = 'ai'
class InteractionMode(value)

Bases: str, Enum

Supported interaction modes between agents.

This enum defines the different ways agents can interact with each other.

HUMAN_TO_AGENT = 'human_to_agent'
AGENT_TO_AGENT = 'agent_to_agent'
class ProtocolVersion(value)

Bases: str, Enum

Supported protocol versions for agent communication.

This enum defines the different protocol versions that can be used for communication between agents.

V1_0 = '1.0'
V1_1 = '1.1'
class VerificationStatus(value)

Bases: str, Enum

Status of agent identity verification.

This enum defines the different states of agent identity verification.

PENDING = 'pending'
VERIFIED = 'verified'
FAILED = 'failed'
class Capability(name, description, input_schema=None, output_schema=None, version='1.0')

Bases: object

Capability definition for agents.

This class defines a capability that an agent can provide, including its name, description, and input/output schemas.

Parameters:
name

Name of the capability

description

Description of what the capability does

input_schema

Schema for the input data

output_schema

Schema for the output data

version

Version of the capability

name: str
description: str
input_schema: Optional[Dict[str, str]] = None
output_schema: Optional[Dict[str, str]] = None
version: str = '1.0'
class AgentIdentity(did, public_key, private_key=None, verification_status=VerificationStatus.PENDING, created_at=<factory>, metadata=<factory>)

Bases: object

Decentralized Identity for Agents.

This class provides identity management for agents, including cryptographic keys for signing and verification.

Parameters:
did

Decentralized Identifier

public_key

Public key for verification

private_key

Private key for signing (optional)

verification_status

Status of identity verification

created_at

When the identity was created

metadata

Additional information about the identity

did: str
public_key: str
private_key: Optional[str] = None
verification_status: VerificationStatus = 'pending'
created_at: datetime
metadata: Dict
classmethod create_key_based()

Create a new key-based identity for an agent.

This method generates a new RSA key pair and creates a key-based decentralized identifier (DID) for the agent.

Return type:

AgentIdentity

Returns:

A new AgentIdentity with generated keys and DID

sign_message(message)

Sign a message using the private key.

Parameters:

message (str) – The message to sign

Return type:

str

Returns:

Base64-encoded signature

Raises:

ValueError – If the private key is not available

verify_signature(message, signature)

Verify a message signature using the public key.

Parameters:

  • message (str) – The message that was signed

  • signature (str) – The base64-encoded signature to verify

Return type:

bool

Returns:

True if the signature is valid, False otherwise

to_dict()

Convert identity to dictionary format.

Return type:

Dict

Returns:

Dictionary representation of the identity

classmethod from_dict(data)

Create identity from dictionary format.

Parameters:

data (Dict) – Dictionary containing identity data

Return type:

AgentIdentity

Returns:

AgentIdentity instance created from the dictionary

class AgentMetadata(agent_id, agent_type, identity, organization_id=None, capabilities=<factory>, interaction_modes=<factory>, payment_address=None, metadata=<factory>)

Bases: object

Metadata for an agent.

This class contains metadata about an agent, including its ID, type, capabilities, and interaction modes.

Parameters:
agent_id

Unique identifier for the agent

agent_type

Type of agent (human, AI)

identity

Agent’s decentralized identity

organization_id

ID of the organization the agent belongs to

capabilities

List of capability names the agent provides

interaction_modes

Supported interaction modes

payment_address

Agent’s primary wallet address for receiving payments

metadata

Additional information about the agent

agent_id: str
agent_type: AgentType
identity: AgentIdentity
organization_id: Optional[str] = None
capabilities: List[str]
interaction_modes: List[InteractionMode]
payment_address: Optional[str] = None
metadata: Dict
class Skill(**data)

Bases: BaseModel

Skill model for agents.

This class defines a skill that an agent can possess, including its name and description.

Parameters:

  • name (str)

  • description (str | None)

name

Name of the skill

description

Optional description of what the skill entails

name: str
description: Optional[str]
model_config: ClassVar[ConfigDict] = {}

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

class AgentProfile(**data)

Bases: BaseModel

Comprehensive profile for an agent.

This class provides a complete profile of an agent, including its capabilities, skills, and other metadata needed for discovery and interaction.

Parameters:
agent_id

Unique identifier for the agent

agent_type

Type of agent (human, AI)

name

Name of the agent

summary

Brief summary of the agent’s purpose

description

Detailed description of the agent

version

Version of the agent

documentation_url

URL to the agent’s documentation

organization

Organization or entity providing the agent (e.g., ‘Acme Corp’, ‘did:org:123’). Using a verifiable ID is recommended for robustness.

developer

Individual or team that developed the agent (e.g., ‘Alice’, ‘did:person:abc’). Using a verifiable ID is recommended.

url

Endpoint URL for the agent

auth_schemes

List of supported authentication schemes

default_input_modes

List of supported input modes

default_output_modes

List of supported output modes

capabilities

List of capabilities the agent provides

skills

List of skills the agent possesses

examples

Example inputs/outputs or use cases

tags

Keywords for filtering

payment_address

Agent’s primary wallet address for receiving payments

custom_metadata

Additional custom metadata about the agent

reputation_score

Optional reputation score (excluded from serialization)

agent_id: str
agent_type: AgentType
name: Optional[str]
summary: Optional[str]
description: Optional[str]
version: Optional[str]
documentation_url: Optional[str]
organization: Optional[str]
developer: Optional[str]
url: Optional[str]
auth_schemes: List[str]
default_input_modes: List[str]
default_output_modes: List[str]
capabilities: List[Capability]
skills: List[Skill]
examples: List[str]
tags: List[str]
payment_address: Optional[str]
custom_metadata: Dict[str, Any]
reputation_score: Optional[float]
model_config: ClassVar[ConfigDict] = {}

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

class MessageType(value)

Bases: str, Enum

Types of messages that can be exchanged between agents.

This enum defines the different types of messages that can be sent between agents in the system.

TEXT = 'text'
COMMAND = 'command'
RESPONSE = 'response'
ERROR = 'error'
VERIFICATION = 'verification'
CAPABILITY = 'capability'
PROTOCOL = 'protocol'
STOP = 'stop'
SYSTEM = 'system'
COOLDOWN = 'cooldown'
IGNORE = 'ignore'
REQUEST_COLLABORATION = 'request_collaboration'
COLLABORATION_RESPONSE = 'collaboration_response'
COLLABORATION_ERROR = 'collaboration_error'
class NetworkMode(value)

Bases: str, Enum

Network modes for agent communication.

This enum defines the different network modes that can be used for agent communication.

STANDALONE = 'standalone'
NETWORKED = 'networked'
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