import json
import os

# Load JSON data from environment variable and parse it
json_data = os.getenv('PROMPT_TEMPLATES', '{}')
prompt_data = json.loads(json_data)

# Create dictionaries from the JSON data
metaprompt_explanations = {
    key: data["description"] 
    for key, data in prompt_data.items()
}

# Generate markdown explanation
explanation_markdown = "".join([
    f"- **{key}**: {value}\n" 
    for key, value in metaprompt_explanations.items()
])

# Define models list
models = [
    # Meta-Llama models (all support system)
    "meta-llama/Meta-Llama-3-70B-Instruct",
    "meta-llama/Meta-Llama-3-8B-Instruct",
    "meta-llama/Llama-3.1-70B-Instruct",
    "meta-llama/Llama-3.1-8B-Instruct",
    "meta-llama/Llama-3.2-3B-Instruct",
    "meta-llama/Llama-3.2-1B-Instruct",
    "meta-llama/Llama-2-13b-chat-hf",
    "meta-llama/Llama-2-7b-chat-hf",
    
    # HuggingFaceH4 models (support system)
    "HuggingFaceH4/zephyr-7b-beta",
    "HuggingFaceH4/zephyr-7b-alpha",
    
    # Qwen models (support system)
    "Qwen/Qwen2.5-72B-Instruct",
    "Qwen/Qwen2.5-1.5B",

    "microsoft/Phi-3.5-mini-instruct"
]

# Check for API token
api_token = os.getenv('HF_API_TOKEN')
if not api_token:
    raise ValueError("HF_API_TOKEN not found in environment variables")

# Store templates in a dictionary
meta_prompts = {
    key: data["template"]
    for key, data in prompt_data.items()
}