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| import openai | |
| import os | |
| def get_api_key(local = False): | |
| if local: | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| return os.getenv('OPEN_API_KEY') | |
| def get_user_input(prompt): | |
| return input(prompt) | |
| def choose_cooperation_type(): | |
| choice = get_user_input("Please choose the cooperation type: \n" | |
| +"1. Sequential: human provide an answer first and then AI provide the answer based on it.\n" | |
| +"2. Parallel: human and AI give answers seperately and then AI does the merge.\n") | |
| if choice == '1': | |
| return 'sequential' | |
| elif choice == '2': | |
| return 'parallel' | |
| else: | |
| print("Invalid choice. Please try again.") | |
| return choose_cooperation_type() | |
| def describe_task(): | |
| task_description = get_user_input("Please describe your task: ") | |
| if task_description.strip() == "": | |
| # print("Task description cannot be empty. Please try again.") | |
| # return describe_task() | |
| task_description = "Write a poem about the moon in 3 lines." | |
| return task_description | |
| def generate_text_with_gpt(prompts, api_key = None): | |
| """Generate text using the GPT-3 model.""" | |
| if api_key: | |
| openai.api_key = api_key | |
| try: | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "system", "content": "Please assist."}, | |
| {"role": "user", "content": prompts} | |
| ] | |
| ) | |
| return response['choices'][0]['message']['content'] | |
| except Exception as e: | |
| print(f"Error occurred when generating texts: {e}") | |
| return "" | |
| def generate_ai_initial_answer(task_description, api_key=None): | |
| prompt = f"Given the task: {task_description}, provide an answer: " | |
| return generate_text_with_gpt(prompt, api_key) | |
| def merge_texts_parallel(task_description, human_text, ai_text, api_key = None): | |
| prompt = f"Given the task: {task_description}, there are two answers provided:\n" + \ | |
| f"The first answer: {human_text}\nThe second answer: {ai_text}\n" + \ | |
| f"Merge the two answers into one in a coherent way: " | |
| return generate_text_with_gpt(prompt, api_key) | |
| def merge_texts_sequential(task_description, human_text, api_key = None): | |
| prompt = f"Given the task:{task_description}, here is the answer provided by the human: {human_text}\n" + \ | |
| f"Refine this response and ensure the final answer aligns with the human's intent:" | |
| return generate_text_with_gpt(prompt, api_key) | |
| def modify_with_suggestion(task_description, text, suggestions, api_key = None): | |
| prompt = f"Given the task:{task_description}, the answer provided is: {text}\n" + \ | |
| f"Modify the answer based on the following suggestions: {suggestions}" | |
| return generate_text_with_gpt(prompt, api_key) | |
| def get_evaluation_with_gpt(task_description, text, api_key=None): | |
| prompt = ( | |
| f"Given the task: {task_description}, the provided answer is: {text}\n" | |
| f"Please evaluate the answer based on the following criteria, using a scale from 0 to 10, where:\n" | |
| f"0-2 reflects very poor quality, with minimal value or relevance.\n" | |
| f"3-4 indicates below-average quality with significant shortcomings.\n" | |
| f"5 represents acceptable quality.\n" | |
| f"6-8 signifies good to very good quality, showing substantial thought and accuracy.\n" | |
| f"9-10 represents exceptional quality, with outstanding insight or depth.\n\n" | |
| f"Provide both a score and a brief comment (1 sentence) for each criterion.\n" | |
| f"Please format the output exactly as follows:\n" | |
| f"Novelty: [Score]\nComment: [Short comment on Novelty]\n" | |
| f"Implementability: [Score]\nComment: [Short comment on Feasibility]\n" | |
| f"Defensibility: [Score]\nComment: [Short comment on Defensibility]\n" | |
| f"Overall Score: [Score]\nOverall Comment: [Overall feedback on the answer]\n" | |
| ) | |
| return generate_text_with_gpt(prompt, api_key) |