Model

What it is

• Lightweight data holders for LangChain chat models and related metadata.
• Provides a base Model class and a ChatModel specialization with context_window and a model_type.

Public API

Enums

• ModelType
  • CHAT: Identifies chat-capable models.

Classes

• Model

  • Purpose: Store a langchain_core BaseChatModel instance plus identifying and descriptive metadata.
  • Constructor:
    • Model(model_id: str, provider: str, model: BaseChatModel, ..., default_parameters: Optional[dict] = None)
  • Key attributes (all set directly on the instance):
    • Required: model_id, provider, model
    • Optional metadata: name, owner, description, image, created_at, canonical_slug, hugging_face_id
    • Optional structured info: pricing, architecture, top_provider, per_request_limits, supported_parameters, default_parameters

• ChatModel(Model)

  • Purpose: A Model with chat-specific fields.
  • Class attributes:
    • model_type: ModelType = ModelType.CHAT
  • Additional instance attributes:
    • context_window: Optional[int] — maximum context length in tokens
  • Constructor:
    • ChatModel(model_id: str, provider: str, model: BaseChatModel, context_window: Optional[int] = None, ..., default_parameters: Optional[dict] = None)

Configuration/Dependencies

• Depends on:
  • langchain_core.language_models.chat_models.BaseChatModel (the wrapped chat model type)
  • pydantic.Field and typing.Annotated (used for type annotations/metadata only)
  • Standard library: datetime, enum, typing.Optional

Usage

from datetime import datetime
from naas_abi_core.models.Model import ChatModel
 
# `model` must be an actual LangChain BaseChatModel instance in real usage.
# Here we use a placeholder to show construction only.
model = object()  # replace with a real BaseChatModel
 
chat_model = ChatModel(
    model_id="gpt-4.1",
    provider="openai",
    model=model,  # should be a BaseChatModel
    context_window=128000,
    name="GPT-4.1",
    created_at=datetime.utcnow(),
)
 
print(chat_model.model_id)
print(chat_model.model_type)
print(chat_model.context_window)

Caveats

• These classes are not Pydantic BaseModels; the Field(...) metadata is not automatically enforced/validated at runtime.
• model is annotated as BaseChatModel, but there is no runtime type checking in __init__.