Update app.py

app.py

@@ -630,23 +630,26 @@ def rephrase_for_search(query, model):
         template="""
         Your task is to rephrase the given conversational query into a concise, search-engine-friendly format.
         Remove any conversational elements and focus on the core information need.
+        Provide ONLY the rephrased query without any additional text or explanations.
         
         Conversational query: {query}
         
-        Rephrased query: """
+        Rephrased query:"""
     )
     
     chain = LLMChain(llm=model, prompt=rephrase_prompt)
     response = chain.run(query=query).strip()
     
-    # Extract only the rephrased query, ignoring any explanations
-    rephrased_query = response.split('\n')[0].strip()
+    # Remove any potential "Rephrased query:" prefix
+    rephrased_query = response.replace("Rephrased query:", "").strip()
     
-    # Check if the rephrased query is actually a rephrasing and not the original prompt
-    if rephrased_query.lower().startswith("rephrase") or len(rephrased_query) > len(query) * 2:
-        # If it's not a proper rephrasing, use a simple keyword extraction
-        keywords = ' '.join(query.lower().split())
-        return keywords
+    # If the rephrased query is too similar to the original, extract keywords
+    if rephrased_query.lower() == query.lower() or len(rephrased_query) > len(query) * 1.5:
+        # Simple keyword extraction: remove common words and punctuation
+        common_words = set(['the', 'a', 'an', 'in', 'on', 'at', 'to', 'for', 'of', 'with', 'by', 'from', 'up', 'about', 'into', 'over', 'after'])
+        keywords = [word.lower() for word in query.split() if word.lower() not in common_words]
+        keywords = [word for word in keywords if word.isalnum()]
+        return ' '.join(keywords)
     
     return rephrased_query