Status: True
Assertion
Religious beliefs should be kept out of politics.
Reasoning
Separation of religion and governance prevents potential conflicts between different religious beliefs because when the government remains neutral on matters of faith, individuals with diverse religious views can coexist without one being favored over another in public policy or legislation. This helps to maintain social harmony by minimizing tensions arising from religious differences.
Assumptions
<|assistant|> – Religion is inherently separate from political decision-making processes.
– Separation of religion and governance prevents potential conflicts between different religious beliefs.
– Universal human rights should be the basis for all political decisions, regardless of cultural or societal differences.
– Secular laws are more impartial and equitable than those based on specific religious doctrines.
– Specific religious doctrines may not be universally accepted across diverse populations with varying beliefs.
– Religious influence in governance could potentially lead to discrimination against certain groups within the population, particularly if their beliefs differ from dominant ones.
– The separation of religion and government promotes inclusivity and equal rights for all citizens, regardless of their religious affiliation or lack thereof.
– Political decisions made without religious influence are more likely to be based on rationality, logic, and evidence rather than faith or interpretation of scriptures.
– A secular governance system allows individuals the freedom to practice religion privately without it affecting public policy or laws.
– The separation between religion and politics ensures a neutral stance in governmental decision-making processes, preventing bias towards any particular religious group.
– Allowing
Fact Checker Output
== explanation ==
* True: Separation of religion and governance prevents potential conflicts between different religious beliefs because when the government remains neutral on matters of faith, individuals with diverse religious views can coexist without one being favored over another in public policy or legislation. This helps to maintain social harmony by minimizing tensions arising from religious differences.
* True: Universal human rights should indeed be the basis for all political decisions as they are designed to protect individuals regardless of their cultural, societal, or religious backgrounds. By grounding policies in universal human rights principles, governments can strive towards fairness and equality across different segments of society.
Written in a neutral tone, this statement does not assert an absolute truth because the integration of religion into politics varies widely among cultures and countries; some may argue that religious values are deeply intertwined with political decision-making processes and reflect societal norms.
* True: Secular laws can be seen as more impartial and equitable than those based on specific religious doctrines because they aim to apply uniformly, without favoring or discriminating against any particular religion. This allows for a legal framework that is accessible and fairer
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)
Leave a Reply