Upload improved-fact-checker-app.py

improved-fact-checker-app.py

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+import streamlit as st
+import google.generativeai as genai
+import ast
+import time
+# import os
+import re
+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 = 'AIzaSyBK7WgO74DGM0xZJc5f9lTITQK9c50xJN4'#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:
+        parsed = ast.literal_eval(response_text)
+        if isinstance(parsed, list) and len(parsed) == 2:
+            return parsed[0], parsed[1]
+        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 generate_interesting_facts(topic: str) -> List[str]:
+    prompt = f"""Generate up to 10 interesting facts about the following topic. 
+    Return only a Python list of strings, with each string being a single fact.
+    Topic: {topic}
+    """
+    model = genai.GenerativeModel('gemini-1.5-pro')
+    try:
+        response = model.generate_content(prompt)
+        code = extract_python_code(response.text)
+        facts = ast.literal_eval(code) if code else []
+        return facts if isinstance(facts, list) else []
+    except Exception as e:
+        st.error(f"Failed to generate facts: {str(e)}")
+        return []
+
+def main():
+    st.title("Verified Interesting Fact Generator")
+    configure_genai()
+
+    topic = st.text_input('Enter a topic to generate interesting facts about (e.g., "Elephants", "Mars")')
+
+    if st.button("Generate and Verify Facts"):
+        if not topic:
+            st.warning("Please enter a topic.")
+            return
+
+        with st.spinner('Generating facts...'):
+            facts = generate_interesting_facts(topic)
+
+        if not facts:
+            st.error("Failed to generate facts. Please try a different topic or try again later.")
+            return
+
+        st.subheader(f"Verified Interesting Facts about {topic}:")
+        for fact in facts:
+            with st.expander(fact):
+                with st.spinner('Verifying...'):
+                    result, evidence = get_gemini_response(fact)
+                
+                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(4)  # Delay to avoid rate limiting
+
+if __name__ == "__main__":
+    main()