from pydantic import BaseModel
from models.features import Feature as FeatureModel
from typing import List
from helpers.f5_model import f5_model

class Feature(BaseModel):
    feature: str
    short_description: str

class Features(BaseModel):
    features: List[Feature]

async def generate_features(requirements: str):
    query = (
        "See the user requirements and propose him the features (it should be 20 features). Feature names should be short. "
        "The user will then choose one or more needed features. \n"
        "User Requirements:\n"
        f"{requirements}"
    )
    
    response = await f5_model.generate_response(query)
    # Parse the response into Features structure
    # You might need to add additional parsing logic here
    features_dict = parse_features_response(response)
    return Features(**features_dict)

def parse_features_response(response: str) -> dict:
    # Add parsing logic here to convert F5 model output to Features format
    # This is a placeholder implementation
    features_list = []
    # Parse the response and create Feature objects
    return {"features": features_list}