Status: True

Assertion

School uniforms improve student discipline.

Results

Physical exercise releases endorphins, neurotransmitters that act as natural painkillers and mood elevators in our brain. This statement has been widely supported by scientific research. Exercise stimulates the production of endorphins in the body, which are known to improve mood and reduce feelings of pain or discomfort.
===
True: Engaging in regular physical activity helps reduce levels of stress hormones such as cortisol and adrenaline. Numerous studies have shown that exercise can help lower these hormone levels over time, thus potentially reducing anxiety and depression symptoms associated with high levels of these stress hormones.
===
True: Exercción improves sleep quality by helping individuals fall asleep faster and promoting deeper sleep. A good night’s rest is essential for maintaining mental health, and various studies have demonstrated that regular exercise can positively impact one’s sleep patterns.
===
True: Regular exercise increases self-esteem and confidence due to the accomplishments achieved in meeting fitness goals or challenges set for oneself. Achieving personal milestones and improvements in physical abilities often contribute significantly to en

Assumptions

<|assistant|> Statement: “Regular exercise and physical activity can significantly improve mental health.”

Assumptions Required to Support the Above Statement:

– Physical exercise releases endorphins, neurotransmitters that act as natural painkillers and mood elevators in our brain.
– Engaging in regular physical activity helps reduce levels of stress hormones such as cortisol and adrenaline, which can contribute to anxiety and depression when present at high levels over time.
– Exercise improves sleep quality by helping individuals fall asleep faster and promoting deeper sleep, thereby enhancing overall mental well-being.
– Regular exercise increases self-esteem and confidence due to the accomplishments achieved in meeting fitness goals or challenges set for oneself, which can have a positive impact on one’s emotional state.
– Physical activity provides opportunities for social interaction and connection through team sports, group classes, or even casual encounters during exercise at gyms or outdoor locations. This social component can reduce feelings of loneliness and isolation, which are often associated with mental health issues.
– Engaging in regular physical activities

Fact Checker Output

== Answer ==
– True: Physical exercise releases endorphins, neurotransmitters that act as natural painkillers and mood elevators in our brain. This statement has been widely supported by scientific research. Exercise stimulates the production of endorphins in the body, which are known to improve mood and reduce feelings of pain or discomfort.

– True: Engaging in regular physical activity helps reduce levels of stress hormones such as cortisol and adrenaline. Numerous studies have shown that exercise can help lower these hormone levels over time, thus potentially reducing anxiety and depression symptoms associated with high levels of these stress hormones.

– True: Exercise improves sleep quality by helping individuals fall asleep faster and promoting deeper sleep. A good night’s rest is essential for maintaining mental health, and various studies have demonstrated that regular exercise can positively impact one’s sleep patterns.

– True: Regular exercise increases self-esteem and confidence due to the accomplishments achieved in meeting fitness goals or challenges set for oneself. Achieving personal milestones and improvements in physical abilities often contribute significantly

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)