config.py

import os
from dotenv import load_dotenv
from supabase import create_client
import requests
import time
from sentence_transformers import SentenceTransformer  # Import the transformer model

# Load environment variables from .env file
load_dotenv()

# Supabase API Config
SUPABASE_URL = "https://lmpazoxzucnlqqxjoihi.supabase.co"
SUPABASE_KEY = os.getenv("SUPABASE_API_KEY")
if not SUPABASE_KEY:
    raise ValueError("SUPABASE_KEY is not set in the environment variables.")
supabase = create_client(SUPABASE_URL, SUPABASE_KEY)

# Load Sentence Transformer Model (scoring)
embedding_model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")

HF_MODELS = {
    "gemma": "https://router.huggingface.co/hf-inference/models/Falconsai/text_summarization"
}

HF_API_TOKEN = os.getenv("HF_API_TOKEN")
if not HF_API_TOKEN:
    raise ValueError("Missing Hugging Face API key. Check your .env file.")

HF_HEADERS = {"Authorization": f"Bearer {HF_API_TOKEN}"}

def query(payload, model="gemma", retries=3, delay=5):
    """
    Sends a request to the Hugging Face API with retries.
    
    :param payload: The input data for inference.
    :param model: The model name ('gemma' for summarization).
    :param retries: Number of times to retry if the request fails.
    :param delay: Delay in seconds before retrying.
    :return: The model's response in JSON format, or None if all retries fail.
    """
    if model not in HF_MODELS:
        raise ValueError("Invalid model name. Choose 'gemma' for summarization.")

    api_url = HF_MODELS[model]

    for attempt in range(retries):
        try:
            response = requests.post(api_url, headers=HF_HEADERS, json=payload)

            if response.status_code == 401:
                print(f"Error querying Hugging Face model '{model}': 401 Unauthorized. Check API key.")
                return None

            if response.status_code == 402:
                print(f"Error querying Hugging Face model '{model}': 402 Payment Required. Free tier may not support this model.")
                return None

            if response.status_code == 500:
                print(f"Server error (500) on attempt {attempt + 1}. Retrying in {delay} seconds...")
                time.sleep(delay)
                continue

            response.raise_for_status()
            return response.json()

        except requests.exceptions.RequestException as e:
            print(f"Error querying Hugging Face model '{model}': {e}")
            time.sleep(delay)

    print("All retry attempts failed.")
    return None