Status: True
Assertion
Euthanasia should be legal.
Results
The statement could be true if the country in question allows for a discussion or potential changes regarding end-of-life care options. [Explanation]
False: The statement would be false, as it contradicts Assumption 1 and may not align with current legal frameworks where euthanasia is illegal without specific exemptions.
Debatable: Given the assumptions provided, the truth value of this statement could vary based on local laws, ethical debates, and societal views regarding end-of-life care options and human dignity (Assumptions 1, 2, 4).
2. Explanation for Upholding Human Dignity and Autonomy:
– The proposed policy change can uphold human dignity and autonomy by providing terminally ill patients with the right
Assumptions
– Assumption 1: Euthanasia is considered illegal in the given country.
– Assumption 2: The speaker believes terminally ill patients should have access to euthanasia under certain conditions.
– Assumption 3: There are individuals who experience unbearable pain with no chance of recovery.
– Assumption 4: Society can benefit from a policy change regarding euthanasia for those facing such circumstances.
– Assumption 5: The legalization of euthanasia would involve strict regulations to prevent abuse and ensure ethical standards are upheld.
2. Human Dignity and Autonomy
Explain how the proposed policy change could uphold human dignity and autonomy for terminally ill patients.
The legalization of euthanasia, when carefully regulated, can preserve human dignity and respect patient autonomy by allowing individuals to make informed decisions about their own lives – especially during times of profound suffering. By providing a legal option for those who are terminally ill and facing unbearable pain with no hope of recovery, we acknowledge the inherent value and worth of each human being. This policy change would allow patients
Fact Checker Output
For all assertions:
– Provide a concise explanation for how the proposed policy change can uphold human dignity and autonomy.
Bullet point list of assumptions:
– Assumption 1: Euthanasia is considered illegal in the given country.
– Assumption 2: The speaker believes terminally ill patients should have access to euthanasia under certain conditions.
– Assumption 3: There are individuals who experience unbearable pain with no chance of recovery.
– Assumption 4: Society can benefit from a policy change regarding euthanasia for those facing such circumstances.
– Assumption 5: The legalization of euthanasia would involve strict regulations to prevent abuse and ensure ethical standards are upheld.
Solution:
1. True or False Evaluation:
– Assumption 1: This assumption is true if the country in question has laws prohibiting euthanasia, but it may be false for countries where euthanasia is legal under specific circumstances (e.g., Belgium).
– Assumption 2: True as this assumption reflects a personal belief about
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
import html
# Load environment variables from .env file
load_dotenv()
# Define category IDs
CATEGORY_IDS = {
"True": 2,
"False": 3,
"Debatable": 4,
"Unknown": 6
}
def create_wordpress_post(title, content, category):
data = {
"title": title,
"content": content,
"status": "publish",
"categories": [CATEGORY_IDS[category]]
}
response = requests.post(
os.getenv("WORDPRESS_POSTS_URL"),
json=data,
auth=(os.getenv("WORDPRESS_USERNAME"), os.getenv("WORDPRESS_PASSWORD"))
)
if response.status_code == 201:
print("Blog post created successfully.")
else:
print(f"Failed to create blog post: {response.status_code} - {response.text}")
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):
final_output = final_output.strip()
if "True:" in final_output:
status_start = final_output.find("True:")
status = "True"
elif "False:" in final_output:
status_start = final_output.find("False:")
status = "False"
elif "Debatable:" in final_output:
status_start = final_output.find("Debatable:")
status = "Debatable"
else:
return "Unknown", final_output
reasoning = final_output[status_start + len(status) + 1:].strip()
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)
# Record the result in MongoDB
try:
print("Attempting to insert record into MongoDB...")
insert_record(
script_name="fact_checker_mongodb.py",
script_code=html.escape(open(__file__).read()),
assertion=assertion,
status=status,
submission=submission, # Store the entire submission for detailed analysis
model=os.getenv("MODEL_NAME")
)
print("Record inserted into MongoDB successfully.")
except Exception as e:
print(f"Failed to insert record into MongoDB: {e}")
print(final_output)
# 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>Results</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