import os
import time
import openai
import requests
import schedule
from rich import print



# Load environment variables
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
OPENAI_BASE_URL = os.getenv("OPENAI_BASE_URL", "https://api.helpingai.co/v1")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY must be set in .env file")


# Initialize OpenAI client
client = openai.OpenAI(
    api_key=OPENAI_API_KEY,
    base_url=OPENAI_BASE_URL
)


# Hardcoded list of models
MODELS = [
    "HelpingAI2.5-10B",
    "HelpingAI2.5-2B",
    "HelpingAI2.5-5B",
    "HelpingAI-flash",
    "HelpingAI2-9B",
    "HelpingAI2-6B",
    "HelpingAI-15B",
    "HELVETE",
    "HELVETE-X",
    "Priya-3B",
    "HelpingAI2.5-10B-1M",
    "Cipher-20B",
    "HelpingAI2-3B"
]


# Function to make a request to a model with retry mechanism
def make_request(model_name):
    max_retries = 3
    retry_delay = 10  # seconds
    for attempt in range(max_retries):
        try:
            print(f"Requesting model: {model_name}")
            response = client.chat.completions.create(
                model=model_name,
                messages=[{"role": "user", "content": "Hello, how are you?"}]
            )
            print(f"Response from {model_name}: {response.choices[0].message.content}\n")
            break # Break if successful
        except Exception as e:
            print(f"Error with model {model_name}: {e}")
            if attempt < max_retries - 1:
                print(f"Retrying in {retry_delay} seconds...")
                time.sleep(retry_delay)
            else:
                print("Max retries reached. Could not get a response.")


def job():
    for model in MODELS:
        make_request(model)


if __name__ == "__main__":
    schedule.every(5).minutes.do(job)
    while True:
        schedule.run_pending()
        time.sleep(1)