Update app.py

app.py

@@ -9,24 +9,20 @@ client = InferenceClient()
 
 
 def preprocess_latex(content):
-    # Example: Split the response into meaningful parts
-    lines = content.split("\n")
+    lines = content.split("\n")  # Split response into lines
     processed_lines = []
-
+    
     for line in lines:
-        if "[" in line and "]" in line:  # Treat as a mathematical expression
-            math_expr = line.strip("[]")
-            try:
-                # Parse and convert to LaTeX
-                processed_lines.append(f"$$ {math_expr} $$")
-            except:
-                processed_lines.append(line)  # Fallback to raw line if parsing fails
-        elif "(" in line and ")" in line:  # Treat as inline math
-            processed_lines.append(line.replace("(", "$").replace(")", "$"))
+        # Identify and format block math
+        if "[" in line and "]" in line:  # Treat as block math
+            math_expr = line[line.index("[") + 1:line.index("]")]  # Extract the math inside brackets
+            processed_lines.append(f"$$ {math_expr.strip()} $$")
+        elif "$" in line:  # Inline math expressions
+            processed_lines.append(line)  # Inline math is already wrapped
         else:
-            processed_lines.append(line)  # Plain text remains as-is
+            processed_lines.append(line)  # Plain text remains unchanged
 
-    return "\n".join(processed_lines)
+    return "\n".join(processed_lines)  # Join lines back into a single string
 
 # Function to generate and format AI response
 def generate_response(prompt_template, **kwargs):