newest_model.py

import argparse
import os
from typing import Any

import requests
from dotenv import load_dotenv


load_dotenv()

GROQ_MODELS_URL = "https://api.groq.com/openai/v1/models"

# Models selected from Groq's rate-limit table for this workload: relevant
# chat/reasoning models with at least 1K requests per day.
PREFERRED_PRODUCTION_CHAT_MODELS = [
    "llama-3.3-70b-versatile",
    "openai/gpt-oss-120b",
    "qwen/qwen3-32b",
    "llama-3.1-8b-instant",
    "openai/gpt-oss-20b",
    "meta-llama/llama-4-scout-17b-16e-instruct",
    "meta-llama/llama-prompt-guard-2-22m",
    "meta-llama/llama-prompt-guard-2-86m"
]

EXCLUDED_MODEL_TERMS = [
    "whisper",
    "tts",
    "audio",
    "moderation",
    "embed",
    "compound",
    "safeguard"
]

PREFERRED_MODEL_IDS = {model_id.lower() for model_id in PREFERRED_PRODUCTION_CHAT_MODELS}


def fetch_groq_models(api_key: str) -> list[dict[str, Any]]:
    """Fetch the current Groq model catalog using the OpenAI-compatible API."""
    headers = {
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
    }
    response = requests.get(GROQ_MODELS_URL, headers=headers, timeout=30)
    response.raise_for_status()
    return response.json().get("data", [])


def is_active_chat_model(model: dict[str, Any]) -> bool:
    """Keep only active preferred chat models that are suitable for judging."""
    model_id = str(model.get("id", "")).lower()
    if not model_id:
        return False
    if model.get("active") is False:
        return False
    if model_id not in PREFERRED_MODEL_IDS:
        return False
    return not any(term in model_id for term in EXCLUDED_MODEL_TERMS)


def rank_model(model: dict[str, Any]) -> tuple[int, int, int, str]:
    """Sort models by preferred production order, then by recency/capacity."""
    model_id = str(model.get("id", ""))
    model_id_lower = model_id.lower()

    try:
        preferred_rank = [item.lower() for item in PREFERRED_PRODUCTION_CHAT_MODELS].index(model_id_lower)
    except ValueError:
        preferred_rank = len(PREFERRED_PRODUCTION_CHAT_MODELS)

    created = int(model.get("created") or 0)
    context_window = int(model.get("context_window") or 0)

    # Lower tuple wins. Known production models come first; unknown active chat
    # models then prefer newer creation dates and larger context windows.
    return (preferred_rank, -created, -context_window, model_id)


def select_groq_chat_models(limit: int = len(PREFERRED_PRODUCTION_CHAT_MODELS), strategy: str = "stable") -> list[str]:
    """Return a comma-ready fallback list for GROQ_MODEL."""
    api_key = os.getenv("GROQ_API_KEY")
    if not api_key:
        raise RuntimeError("GROQ_API_KEY is missing. Add it to .env first.")

    models = fetch_groq_models(api_key)
    chat_models = [model for model in models if is_active_chat_model(model)]

    if strategy == "latest":
        ranked_models = sorted(
            chat_models,
            key=lambda model: (
                -int(model.get("created") or 0),
                -int(model.get("context_window") or 0),
                str(model.get("id", "")),
            ),
        )
    else:
        ranked_models = sorted(chat_models, key=rank_model)

    return [model["id"] for model in ranked_models[:limit]]


def main() -> None:
    """CLI entry point used when refreshing the recommended Groq model list."""
    parser = argparse.ArgumentParser(description="Select currently available Groq chat models.")
    parser.add_argument("--limit", type=int, default=len(PREFERRED_PRODUCTION_CHAT_MODELS), help="Number of fallback models to print.")
    parser.add_argument(
        "--strategy",
        choices=["stable", "latest"],
        default="stable",
        help="stable prefers known production chat models; latest picks newest active chat models.",
    )
    args = parser.parse_args()

    models = select_groq_chat_models(limit=args.limit, strategy=args.strategy)
    if not models:
        raise RuntimeError("No active Groq chat models were returned by the Models API.")

    print("Recommended GROQ_MODEL value:")
    print(f"GROQ_MODEL={','.join(models)}")
    print("\nSelected fallback order:")
    for index, model_id in enumerate(models, start=1):
        print(f"{index}. {model_id}")


if __name__ == "__main__":
    main()