recommand_config.py

from config import LING_1T, LING_FLASH_2_0, RING_1T, RING_FLASH_2_0, LING_MINI_2_0, RING_MINI_2_0, get_model_display_name
from i18n import get_text

def get_recommended_inputs(lang: str):
    """
    Generates the list of recommended inputs based on the selected language,
    ordered by model complexity.
    """
    
    # Structure: (key_prefix, model, temperature)
    recommendation_setup = [
        # Complex "Thinking" Model
        ("complex_reasoning", RING_1T, 0.3), 
        # Complex "Creative" Model
        ("long_form_creative", LING_1T, 0.6), # Lower temp for Ling
        # Mid-tier "Thinking" Model
        ("technical_analysis", RING_FLASH_2_0, 0.5),
        # Mid-tier "Creative" Model
        ("short_form_creative", LING_FLASH_2_0, 0.7), # Lower temp for Ling
        # Quick "Thinking" Model
        ("quick_qa", RING_MINI_2_0, 0.4),
        # Quick "Creative" Model
        ("simple_email", LING_MINI_2_0, 0.6), # Lower temp for Ling
    ]

    result = []
    for key_prefix, model, temp in recommendation_setup:
        result.append({
            "task": get_text(f"rec_{key_prefix}_task", lang),
            "model": get_model_display_name(model),
            "system_prompt": get_text(f"rec_{key_prefix}_system_prompt", lang),
            "user_message": get_text(f"rec_{key_prefix}_user_message", lang),
            "temperature": temp,
        })
        
    return result