ensemble_machine / utils.py
diana3135
separate ai and human task description
eed6b20
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-4o model."""
if api_key:
openai.api_key = api_key
try:
response = openai.ChatCompletion.create(
model="gpt-4o",
messages=[
{"role": "system", "content": "Please perform the tasks as instructed, following the instructions carefully."},
{"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 = (
"You are tasked with merging two answers into a single, coherent, and logically structured response. "
"Your response should synthesize the strengths of both answers, eliminate redundancy, and ensure a logical flow."
"Follow this structured chain of thought to guide your process:\n\n"
"1. Understand the Task: Start by carefully analyzing the task description to ensure your final response aligns fully with the objective.\n"
"2. Extract Key Points: Review both answers and identify the key ideas and arguments they present.\n"
"3. Resolve Redundancies and Conflicts: Compare the two answers to eliminate repetitive content and resolve any contradictions.\n"
"4. Integrate Seamlessly: Combine the extracted points into a single, unified response, ensuring a logical and coherent structure.\n"
"5. Refine for Clarity: Polish the final response for clarity, conciseness, and alignment with the task description below.\n\n"
"Task Description:\n"
f"{task_description}\n\n"
"Answer 1:\n"
f"{human_text}\n\n"
"Answer 2:\n"
f"{ai_text}\n\n"
"Provide the merged response below."
)
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 response provided by the human:\n"
f"{human_text}\n\n"
"Your task is to refine the human's response while ensuring that the final answer fully aligns with the objectives for this task."
"Follow this logical chain of thought:\n"
"1. Understand the Intent: Analyze the human's response to identify their key points and intended message.\n"
"2. Evaluate Clarity: Check for any ambiguities, gaps, or unclear phrasing in the response.\n"
"3. Improve Coherence: Ensure the response flows logically and connects ideas seamlessly.\n"
"4. Enhance Precision: Refine wording to be concise and impactful while preserving the human's original intent.\n"
"5. Check Alignment: Confirm that the final response accurately represents and strengthens the human's input without introducing unintended changes.\n\n"
"Provide the refined response below."
)
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 provided answer is:\n"
f"{text}\n\n"
f"The following suggestions have been made for improvement:\n"
f"{suggestions}\n\n"
"Your task is to modify the provided answer by systematically incorporating the suggestions while maintaining clarity, coherence, and alignment with the original task. "
"Follow this logical chain of thought:\n"
"1. Understand the Task: Reassess the original task description to ensure the modified answer remains aligned with the requirements.\n"
"2. Analyze the Suggestions: Break down each suggestion to understand its purpose and how it improves the original answer.\n"
"3. Apply Improvements: Integrate the suggestions into the answer thoughtfully, ensuring each one is addressed adequately.\n"
"4. Ensure Coherence: Verify that the modified answer flows logically and maintains a clear structure.\n"
"5. Preserve Integrity: Ensure the modified answer stays true to the original content while enhancing it as per the suggestions.\n\n"
"Provide the improved answer below, clearly marked as the revised version."
)
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:\n{text}\n\n"
"You are tasked with evaluating the answer using a scale from 0 to 10 based on specific criteria. "
"Follow a structured chain-of-thought approach for your evaluation to ensure thoroughness and objectivity:\n\n"
"1. Understand the Criteria: Carefully review each evaluation criterion to ensure you fully grasp what is being assessed:\n"
" - Novelty: The uniqueness and originality of the ideas.\n"
" - Feasibility: The practicality and implementability of suggested actions.\n"
" - Inimitability: How difficult for competitors to replicate.\n"
" - Alignment: How aligned the ideas are with Airbnb’s business objectives and 17 SDGs.\n\n"
"2. Analyze the Answer: Break down the answer into its key components and assess how well it meets each criterion.\n"
" - Identify strengths, weaknesses, and any gaps in the ideas provided.\n"
" - Consider the context of the task and whether the ideas are realistic and relevant.\n\n"
"3. Assign Scores: Use the following scale to score each criterion:\n"
" - 0-2: Poor fit; the idea demonstrates minimal relevance to the criteria.\n"
" - 3-5: Partial fit; the idea shows some relevance but contains significant shortcomings.\n"
" - 6-8: Good fit; the idea aligns well with the criteria, showing clear relevance and thoughtfulness.\n"
" - 9-10: Excellent fit; the idea fully aligns with the criteria, demonstrating exceptional insight.\n"
" - Note: Use the entire scoring range (0-10) and avoid defaulting to mid-range scores. If the provided answer is vague or off-topic, assign scores between 0-5.\n\n"
"4. Justify Each Score: Provide a brief explanation for each score, highlighting specific aspects of the answer that influenced your evaluation.\n\n"
"You should format your output exactly as follows:\n"
"Novelty: [Score] - [Justification]\n"
"Feasibility: [Score] - [Justification]\n"
"Inimitability: [Score] - [Justification]\n"
"Alignment: [Score] - [Justification]\n\n"
"Output your evaluation below:"
)
return generate_text_with_gpt(prompt, api_key)
def display_merged_output(session_index, session_manager):
session = session_manager.get_session(session_index)
return session['merged_final_answer']