Status: True
Assertion
Morality is relative, not absolute.
Reasoning
The statement reflects the concept of moral relativism as it acknowledges that moral judgments can vary based on personal experiences, cultural norms, and individual perspectives due to diverse human views on ethics and values across cultures, societies, and individuals.
Assumptions
– Moral values and principles may vary across cultures, societies, and individuals.
– There is no universally agreed upon set of ethical rules or moral norms that apply in all contexts.
– People’s beliefs about what is right or wrong are shaped by their cultural upbringing, personal experiences, and social interactions.
– Morality may evolve over time as societies change and adapt to new challenges, needs, and perspectives.
– There might be different moral frameworks that can coexist within the same society, such as utilitarianism, deontology or virtue ethics, each emphasizing different aspects of morality.
– Ethical decision-making may involve balancing conflicting values, principles, and interests in complex situations where there is no clear “right” answer.
Support=- The concept of moral relativism acknowledges the diversity of human perspectives on ethics and values.
– Individuals are capable of holding their own set of beliefs about morality based on personal experiences and cultural context, which may differ from others’ views.
– Cultural norms and practices play a significant role in shaping moral understanding and behavior within specific soci
Fact Checker Output
True: The concept of moral relativism acknowledges the diversity of human perspectives on ethics and values because different cultures, societies, and individuals may have varying beliefs about what is right or wrong based on their unique experiences, traditions, and social norms. This perspective recognizes that there isn’t a single objective standard to measure morality against, which can differ significantly across cultural contexts.
True: Individuals are capable of holding their own set of beliefs about morality based on personal experiences and cultural context because our upbringing, education, and life experiences shape how we perceive the world around us. These factors contribute to forming an individual’s moral compass that may differ from another person’s as they have encountered different situations or been raised in various environments.
True: Cultural norms and practices play a significant role in shaping moral understanding and behavior within specific societies because these shared beliefs, customs, and traditions help to define the collective values and expectations of members of that society. These cultural aspects can significantly influence how individuals perceive right or wrong and act accordingly based on what they have learned from their community.
True: Moral frameworks such as
Model Used
microsoft/Phi-3-mini-4k-instruct-gguf
Script Name
fact_checker_mongodb.py
Script Code
import os
import sys
import requests
from langchain_openai.llms import OpenAI
from langchain.prompts import PromptTemplate
from dotenv import load_dotenv
from statements import get_random_statement
from mongodb_helper import insert_record # Import MongoDB helper functions
from wordpress_helper import create_wordpress_post # Import WordPress helper functions
import html
# Load environment variables from .env file
load_dotenv()
def fact_check(assertion):
llm = OpenAI(temperature=0.7, model=os.getenv("MODEL_NAME"))
# Define the prompt templates
assertion_template = """{assertion}\n\n"""
assertion_prompt = PromptTemplate(input_variables=["assertion"], template=assertion_template)
assumptions_template = """Here is a statement:
{statement}
Make a bullet point list of the assumptions required to support the above statement.\n\n"""
assumptions_prompt = PromptTemplate(input_variables=["statement"], template=assumptions_template)
fact_checker_template = """Here is a bullet point list of assertions:
{assertions}
For each assumption, determine whether it is true or false. Explain your reasoning.\n\n"""
fact_checker_prompt = PromptTemplate(input_variables=["assertions"], template=fact_checker_template)
answer_template = """
Here is the information to classify the statement:
{facts}
Based on the above information, how would you classify the statement? Respond with one of the following options followed by a colon and space:
- True: [Explanation]
- False: [Explanation]
- Debatable: [Explanation]
"""
answer_prompt = PromptTemplate(input_variables=["facts"], template=answer_template)
# Format prompts and extract the string content
formatted_assertion = assertion_prompt.format_prompt(assertion=assertion).text
assertion_output = llm.invoke(formatted_assertion)
formatted_assumptions = assumptions_prompt.format_prompt(statement=assertion_output).text
assumptions_output = llm.invoke(formatted_assumptions)
formatted_fact_checker = fact_checker_prompt.format_prompt(assertions=assumptions_output).text
fact_checker_output = llm.invoke(formatted_fact_checker)
formatted_answer = answer_prompt.format_prompt(facts=fact_checker_output).text
final_output = llm.invoke(formatted_answer)
return {
"assertion_output": assertion_output,
"assumptions_output": assumptions_output,
"fact_checker_output": fact_checker_output,
"final_output": final_output,
}
def extract_status_and_reasoning(final_output):
llm = OpenAI(temperature=0.7, model=os.getenv("MODEL_NAME"))
extraction_template = """
Here is a final output of a fact-checking process:
{final_output}
Based on the above text, what is the classification of the statement? Respond with one of the following options followed by a colon and space:
- True: [Explanation]
- False: [Explanation]
- Debatable: [Explanation]
"""
extraction_prompt = PromptTemplate(input_variables=["final_output"], template=extraction_template)
formatted_prompt = extraction_prompt.format_prompt(final_output=final_output).text
extraction_output = llm.invoke(formatted_prompt).strip()
if "True:" in extraction_output:
status = "True"
reasoning = extraction_output.split("True:", 1)[1].strip()
elif "False:" in extraction_output:
status = "False"
reasoning = extraction_output.split("False:", 1)[1].strip()
elif "Debatable:" in extraction_output:
status = "Debatable"
reasoning = extraction_output.split("Debatable:", 1)[1].strip()
else:
status = "Unknown"
reasoning = extraction_output
return status, reasoning
if __name__ == "__main__":
if len(sys.argv) > 1:
assertion = sys.argv[1]
else:
assertion = get_random_statement()
print(assertion)
submission = fact_check(assertion)
# Print the detailed outputs to inspect their structure
for key, value in submission.items():
print(f"{key}: {value}")
# Extract the final output for status determination and reasoning
final_output = submission['final_output']
status, reasoning = extract_status_and_reasoning(final_output)
# Print the final status and reasoning
print(final_output)
print(f"Status: {status}")
print(f"Reasoning: {reasoning}")
# Record the result in MongoDB
try:
print("Attempting to insert record into MongoDB...")
insert_record(
script_name=__file__,
script_code=html.escape(open(__file__).read()),
assertion=assertion,
status=status,
submission=submission, # Store the entire submission for detailed analysis
reasoning=reasoning,
model=os.getenv("MODEL_NAME")
)
print("Record inserted into MongoDB successfully.")
except Exception as e:
print(f"Failed to insert record into MongoDB: {e}")
# Create a blog post on WordPress
blog_title = f"Fact Check: {assertion}"
blog_content = f"""
<h1>Status: {status}</h1>
<h2>Assertion</h2>
<p>{assertion}</p>
<h2>Reasoning</h2>
<p>{reasoning}</p>
<h3>Assumptions</h3>
<p>{submission['assumptions_output']}</p>
<h3>Fact Checker Output</h3>
<p>{submission['fact_checker_output']}</p>
<h4>Model Used</h4>
<p>{os.getenv("MODEL_NAME")}</p>
<h4>Script Name</h4>
<p>fact_checker_mongodb.py</p>
<h4>Script Code</h4>
<pre>{html.escape(open(__file__).read())}</pre>
"""
create_wordpress_post(blog_title, blog_content, status)
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