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Implementation:Groq Groq python Model Type

From Leeroopedia
Knowledge Sources
Domains Model_Management, Type_System
Last Updated 2026-02-15 16:00 GMT

Overview

Concrete tool for representing AI model metadata in API responses provided by the Groq Python SDK's type system.

Description

The Model class is a Pydantic BaseModel representing an AI model available through the Groq API. It contains the model's identifier, creation timestamp, object type marker, and owning organization. This type is returned by client.models.retrieve() and as elements within client.models.list().

Usage

Access this type from response objects returned by the models API. The id field is used to specify which model to use in inference requests (chat completions, embeddings, transcriptions, etc.).

Code Reference

Source Location

Signature

class Model(BaseModel):
    """Describes an OpenAI model offering that can be used with the API."""

    id: str
    """The model identifier, which can be referenced in the API endpoints."""

    created: int
    """The Unix timestamp (in seconds) when the model was created."""

    object: Literal["model"]
    """The object type, which is always "model"."""

    owned_by: str
    """The organization that owns the model."""

Import

from groq.types import Model

I/O Contract

Fields

Name Type Required Description
id str Yes Model identifier (e.g. "llama-3.3-70b-versatile")
created int Yes Unix timestamp (seconds) of model creation
object Literal["model"] Yes Object type, always "model"
owned_by str Yes Organization that owns the model

Usage Examples

Listing and Inspecting Models

from groq import Groq

client = Groq()

# List all models and access Model type fields
response = client.models.list()
for model in response.data:
    print(f"ID: {model.id}")
    print(f"Created: {model.created}")
    print(f"Owner: {model.owned_by}")
    print()

# Retrieve a specific model
model = client.models.retrieve("llama-3.3-70b-versatile")
print(model.to_json())

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