f5_model_final / app /helpers /generate_features.py
EL GHAFRAOUI AYOUB
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6f14d8b
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}