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| import os | |
| import random | |
| import string | |
| from django.apps import AppConfig | |
| from django.conf import settings | |
| from jinja2 import Environment, FileSystemLoader | |
| import openai | |
| class AppNameConfig(AppConfig): | |
| default_auto_field = 'django.db.models.BigAutoField' | |
| name = 'app_name' | |
| def ready(self): | |
| # import models, functions, and libraries here | |
| from . import models, functions, libraries | |
| # idea-to-app logic | |
| if settings.IDEA_TO_APP: | |
| # generate a unique name for the new model | |
| model_name = ''.join(random.choices(string.ascii_lowercase + string.digits, k=10)) | |
| # merge the selected models and functions here | |
| # and save it as a new GGuf model | |
| gguf_model = functions.merge_models(models.CodeModel, models.ImageModel, 'function1', 'function3') | |
| # save the GGuf model under the unique name | |
| gguf_model.save(model_name) | |
| # return the merged model for preview/demo | |
| settings.IDEA_TO_APP_PREVIEW = gguf_model | |
| from django.db import models | |
| class CodeModel(models.Model): | |
| name = models.CharField(max_length=100) | |
| code = models.TextField() | |
| class ImageModel(models.Model): | |
| name = models.CharField(max_length=100) | |
| image = models.ImageField(upload_to='images/') | |
| def merge_models(model1, model2, function1, function3): | |
| # merge the selected models and functions here | |
| model1_objects = model1.objects.all() | |
| model2_objects = model2.objects.all() | |
| merged_objects = [] | |
| for obj1 in model1_objects: | |
| obj2 = model2_objects.filter(name=obj1.name).first() | |
| if obj2: | |
| merged_obj = { | |
| 'name': obj1.name, | |
| 'code': function1(obj1.code), | |
| 'image': function3(obj2.image), | |
| } | |
| merged_objects.append(merged_obj) | |
| return merged_objects | |
| import openai | |
| import jinja2 | |
| def function1(code): | |
| # translate natural language to executable code here | |
| # using the OpenAI API | |
| openai.api_key = 'YOUR_OPENAI_API_KEY' | |
| response = openai.Completion.create( | |
| engine='code-davinci-002', | |
| prompt=f'Translate this Python code to executable code: {code}'\ |