app.py

import streamlit as st
import google.generativeai as genai
import ast
import time
import re
import os
from typing import List, Tuple, Optional

def extract_python_code(text: str) -> Optional[str]:
    pattern = r"```python\n(.*?)```"
    match = re.search(pattern, text, re.DOTALL)
    return match.group(1).strip() if match else None

def configure_genai():
    secret_key = os.getenv("SECRET_KEY")
    if not secret_key:
        st.error("API key not found. Please set the SECRET_KEY environment variable.")
        st.stop()
    genai.configure(api_key=secret_key)

def parse_gemini_response(response_text: str) -> Tuple[str, str]:
    try:
        # First, try to parse as a single list
        parsed = ast.literal_eval(response_text)
        if isinstance(parsed, list) and len(parsed) == 2:
            return parsed[0], parsed[1]
        
        # If that fails, look for multiple lists
        matches = re.findall(r'\[.*?\]', response_text)
        if len(matches) >= 2:
            first_list = ast.literal_eval(matches[0])
            second_list = ast.literal_eval(matches[1])
            return first_list[0], second_list[0]
        
        # If no valid format is found, raise an exception
        raise ValueError("Unexpected response format")
    except Exception as e:
        return "Error", f"Failed to parse response: {str(e)}"

def get_gemini_response(input_text: str) -> Tuple[str, str]:
    prompt = """You are a fact checker. Given a text, respond with:
    1. 'true', 'false', or 'unsure' (if you are unsure or knowledge cutoff)
    2. Evidence in support or 'knowledge cutoff'
    
    Respond in this exact format: ['true/false/unsure', 'evidence or knowledge cutoff']
    Example input: 'Google was founded in 1998'
    Example output: ['true', 'Google was indeed founded in September 1998 by Larry Page and Sergey Brin']
    
    Now give a response in the exact described format for the following text:
    """
    model = genai.GenerativeModel('gemini-1.5-pro')
    try:
        response = model.generate_content(prompt + input_text)
        result, evidence = parse_gemini_response(response.text)
        return result, evidence
    except Exception as e:
        return "Error", f"Failed to get or parse the model's response: {str(e)}"

def break_down_text(text: str) -> List[str]:
    prompt = """Break down the following text into a list of individual factual statements that can be independently verified. Return only a Python list of strings.

    Example input: "The Eiffel Tower, built in 1889, is 324 meters tall and located in Paris, France."
    Example output: ["The Eiffel Tower was built in 1889", "The Eiffel Tower is 324 meters tall", "The Eiffel Tower is located in Paris, France"]

    Now break down the following text:
    """
    model = genai.GenerativeModel('gemini-1.5-pro')
    response = model.generate_content(prompt + text)
    
    code = extract_python_code(response.text)
    try:
        return ast.literal_eval(code) if code else []
    except (ValueError, SyntaxError):
        st.error(f"Failed to parse the breakdown response: {response.text}")
        return []

def main():
    st.title("Fact Checker")
    configure_genai()

    text = st.text_area('Paste the text to fact check (preferably about facts before 2021)', height=150)

    if st.button("Check Facts"):
        if not text:
            st.warning("Please enter some text to fact-check.")
            return

        statements = break_down_text(text)
        
        if not statements:
            st.error("Failed to break down the text into checkable statements. Please try rephrasing your input.")
            return

        st.subheader("Fact Checking Results:")
        for statement in statements:
            with st.expander(statement):
                with st.spinner('Checking...'):
                    result, evidence = get_gemini_response(statement)
                
                if result.lower() == "true":
                    st.success(f"Likely True: {evidence}")
                elif result.lower() == "false":
                    st.error(f"Likely False: {evidence}")
                elif result.lower() == "unsure":
                    st.warning(f"Uncertain: {evidence}")
                else:
                    st.error(f"Error in fact-checking: {evidence}")
                
            time.sleep(3)  # Delay to avoid rate limiting

if __name__ == "__main__":
    main()