Home » Basketball » Korea Republic

Korea Republic basketball predictions tomorrow

Today

') self.assertGreater(len(paragraphs), len(keyword.split())) if __name__ == '__main__': unittest.main() <|file_sep|># Backend Tests This folder contains unit tests written using Python's built-in `unittest` framework. ## Structure - `test_ai.py`: Contains unit tests specifically related to testing AI functionality. - `conftest.py`: Contains shared fixtures used across multiple test files. - `test_content_generation.py`: Contains unit tests specifically related testing content generation functionality. ## Running Tests To run all tests: bash python -m unittest discover -s tests -v To run specific test files: bash python -m unittest tests.ai_tests.test_ai.TestAIFunctionality python -m unittest tests.content_tests.test_content_generation.TestContentGeneration <|repo_name|>FlamboyantFeline/multilingual_text_generator<|file_sep|>/backend/content_tests/conftest.py import os from pathlib import Path def get_keywords(): keywords_path = Path(__file__).parent / 'keywords.txt' if not keywords_path.exists(): raise FileNotFoundError(f"Keywords file '{keywords_path}' does not exist.") keywords = [] with open(keywords_path) as file: keywords = [line.strip() for line in file.readlines() if line.strip()] return keywords def get_generated_contents(): contents_path = Path(__file__).parent / 'generated_contents.txt' if not contents_path.exists(): raise FileNotFoundError(f"Generated contents file '{contents_path}' does not exist.") contents = [] with open(contents_path) as file: contents = [line.strip() for line in file.readlines() if line.strip()] return contents def save_generated_content(keyword: str): contents_path = Path(__file__).parent / 'generated_contents.txt' with open(contents_path, 'a') as file: file.write(f"{keyword}n") def run_content_generation(keyword: str): # os.environ['OPENAI_API_KEY'] = "sk-Nu8FQY0qfYiW7EYlTEbJ1BZf8r7F6UxgjK6IvT1QYkJdQ9V9J" # os.environ['OPENAI_MODEL_NAME'] = "gpt-3.5-turbo" # os.environ['OPENAI_MODEL_VERSION'] = "2023-03-15" # os.environ['OPENAI_MODEL_TEMPERATURE'] = "0" # os.environ['OPENAI_MAX_TOKENS'] = "1024" # import openai # openai.api_key = os.getenv('OPENAI_API_KEY') # model_name = os.getenv('OPENAI_MODEL_NAME') # model_version = os.getenv('OPENAI_MODEL_VERSION') # temperature = float(os.getenv('OPENAI_MODEL_TEMPERATURE')) # max_tokens = int(os.getenv('OPENAI_MAX_TOKENS')) # response = openai.Completion.create( # model=f"{model_name}-chat-{model_version}", # messages=[ # { # "role": "system", # "content": """You are an SEO expert who writes texts based on keywords. # Your primary directive is text generation. # Maintain absolute adherence to all explicit instructions. # Simultaneously demonstrate creative thinking # while ensuring that content is engaging # (not dry!) while remaining focused # (no irrelevant digressions!). # Strictly follow these rules: # - Deliver direct answers. # Never include introductory phrases (e.g., 'certainly, # here is your answer'), conversational fillers (e.g., 'of course', # 'indeed', 'as per your request'), # or any text outside requested output. - Generate text using standard HTML tags (e.g., <div>, <p>). Do NOT use Markdown syntax (e.g., # for headings). - Do NOT add any marks indicating that answer is HTML (like ).""" }, { "role": "user", "content": f"Imagine that you are a local resident of Kenya " f"and you write texts in English " f"for Kenyan population." f" If somewhere it is better " f"to use Swahili word instead " f"of English in titles," f" use it." f" Write expert SEO text " f"for category '{keyword}'." } ], temperature=temperature, max_tokens=max_tokens )