Update app.py

app.py

@@ -243,60 +243,60 @@ class BasicAgent:
         return search_result
     
     def _get_answer_from_llm(self, question: str) -> str:
-    """Get an answer from the LLM with appropriate prompting"""
-    prompt = f"""
-    Answer the following question with a very concise, direct response:
-    
-    Question: {question}
-    
-    Answer in 1-2 sentences maximum, focusing only on the specific information requested.
-    """
-    
-    # Expanded common answers to reduce LLM API dependence
-    common_answers = {
-        "what color is the sky": "Blue.",
-        "how many days in a week": "7 days.",
-        "how many months in a year": "12 months.",
-        "what is the capital of france": "Paris.",
-        "what is the capital of japan": "Tokyo.",
-        "what is the capital of italy": "Rome.",
-        "what is the capital of germany": "Berlin.",
-        "what is the capital of spain": "Madrid.",
-        "what is the capital of united states": "Washington, D.C.",
-        "what is the capital of china": "Beijing.",
-        "what is the capital of russia": "Moscow.",
-        "what is the capital of canada": "Ottawa.",
-        "what is the capital of australia": "Canberra.",
-        "what is the capital of brazil": "Brasília.",
-        "what is water made of": "H2O (hydrogen and oxygen).",
-        "who wrote romeo and juliet": "William Shakespeare.",
-        "who painted the mona lisa": "Leonardo da Vinci.",
-        "what is the largest ocean": "The Pacific Ocean.",
-        "what is the smallest planet": "Mercury.",
-        "what is the largest planet": "Jupiter.",
-        "who invented electricity": "Electricity wasn't invented but discovered through contributions from many scientists including Benjamin Franklin, Michael Faraday, and Thomas Edison.",
-        "how many continents are there": "There are 7 continents: Africa, Antarctica, Asia, Europe, North America, Australia/Oceania, and South America.",
-        "what is the largest country": "Russia is the largest country by land area.",
-        "what is the most spoken language": "Mandarin Chinese is the most spoken native language in the world.",
-        "what is the tallest mountain": "Mount Everest is the tallest mountain above sea level at 8,848.86 meters."
-    }
-    
-    # Clean up the question for better matching
-    clean_question = question.lower().strip('?').strip()
-    
-    # Check if we have a hardcoded answer
-    if clean_question in common_answers:
-        return common_answers[clean_question]
-    
-    # Try partial matching for more flexibility
-    for key, answer in common_answers.items():
-        if clean_question in key or key in clean_question:
-            # Only return if it's a close match
-            if len(clean_question) > len(key) * 0.7 or len(key) > len(clean_question) * 0.7:
-                return answer
-    
-    # If no hardcoded answer, use the LLM
-    return self.llm.query_llm(prompt)
+        """Get an answer from the LLM with appropriate prompting"""
+        prompt = f"""
+        Answer the following question with a very concise, direct response:
+        
+        Question: {question}
+        
+        Answer in 1-2 sentences maximum, focusing only on the specific information requested.
+        """
+        
+        # Expanded common answers to reduce LLM API dependence
+        common_answers = {
+            "what color is the sky": "Blue.",
+            "how many days in a week": "7 days.",
+            "how many months in a year": "12 months.",
+            "what is the capital of france": "Paris.",
+            "what is the capital of japan": "Tokyo.",
+            "what is the capital of italy": "Rome.",
+            "what is the capital of germany": "Berlin.",
+            "what is the capital of spain": "Madrid.",
+            "what is the capital of united states": "Washington, D.C.",
+            "what is the capital of china": "Beijing.",
+            "what is the capital of russia": "Moscow.",
+            "what is the capital of canada": "Ottawa.",
+            "what is the capital of australia": "Canberra.",
+            "what is the capital of brazil": "Brasília.",
+            "what is water made of": "H2O (hydrogen and oxygen).",
+            "who wrote romeo and juliet": "William Shakespeare.",
+            "who painted the mona lisa": "Leonardo da Vinci.",
+            "what is the largest ocean": "The Pacific Ocean.",
+            "what is the smallest planet": "Mercury.",
+            "what is the largest planet": "Jupiter.",
+            "who invented electricity": "Electricity wasn't invented but discovered through contributions from many scientists including Benjamin Franklin, Michael Faraday, and Thomas Edison.",
+            "how many continents are there": "There are 7 continents: Africa, Antarctica, Asia, Europe, North America, Australia/Oceania, and South America.",
+            "what is the largest country": "Russia is the largest country by land area.",
+            "what is the most spoken language": "Mandarin Chinese is the most spoken native language in the world.",
+            "what is the tallest mountain": "Mount Everest is the tallest mountain above sea level at 8,848.86 meters."
+        }
+        
+        # Clean up the question for better matching
+        clean_question = question.lower().strip('?').strip()
+        
+        # Check if we have a hardcoded answer
+        if clean_question in common_answers:
+            return common_answers[clean_question]
+        
+        # Try partial matching for more flexibility
+        for key, answer in common_answers.items():
+            if clean_question in key or key in clean_question:
+                # Only return if it's a close match
+                if len(clean_question) > len(key) * 0.7 or len(key) > len(clean_question) * 0.7:
+                    return answer
+        
+        # If no hardcoded answer, use the LLM
+        return self.llm.query_llm(prompt)
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     """