Update app.py

app.py

@@ -26,7 +26,7 @@ class QuestionValidation:
         self.client = InferenceClient(model="HuggingFaceH4/zephyr-7b-beta", token=HF_TOKEN)
 
         self.llm2_model = "HuggingFaceH4/zephyr-7b-beta"
-        self.embedding_model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+        self.embedding_model = SentenceTransformer("sentence-transformers/paraphrase-MiniLM-L3-v2")
 
     def guess_question(self, answer: str) -> str:
         prompt = f"This was the answer: {answer}\nWhat question would likely have led to it?"
@@ -53,13 +53,46 @@ def search_web(query: str, max_results: int = 5) -> List[Dict[str, str]]:
     except Exception as e:
         return [{"error": str(e)}]
 
+import ast
+import operator as op
+
+OPERATORS = {
+    ast.Add: op.add,
+    ast.Sub: op.sub,
+    ast.Mult: op.mul,
+    ast.Div: op.truediv,
+    ast.Mod: op.mod,
+    ast.Pow: op.pow,
+    ast.USub: op.neg,
+    ast.UAdd: op.pos,
+    ast.FloorDiv: op.floordiv,
+}
+
 def evaluate_math_expression(expr: str) -> str:
     try:
-        result = eval(expr, {"__builtins__": {}})
+        node = ast.parse(expr, mode="eval")
+
+        def _eval(node):
+            if isinstance(node, ast.Expression):
+                return _eval(node.body)
+            elif isinstance(node, ast.Num):
+                return node.n
+            elif isinstance(node, ast.Constant): 
+                if isinstance(node.value, (int, float)):
+                    return node.value
+            elif isinstance(node, ast.BinOp):
+                return OPERATORS[type(node.op)](_eval(node.left), _eval(node.right))
+            elif isinstance(node, ast.UnaryOp):
+                return OPERATORS[type(node.op)](_eval(node.operand))
+            else:
+                raise ValueError(f"Unsupported expression: {ast.dump(node)}")
+
+        result = _eval(node)
         return str(result)
     except Exception as e:
         return f"Error evaluating expression: {e}"
 
+
 validator = QuestionValidation(hf_token=HF_TOKEN)
 
 validate_tool = FunctionTool.from_defaults(
@@ -93,7 +126,7 @@ llm = HuggingFaceLLM(
     generate_kwargs={"temperature": 0.7, "top_p": 0.95},
     tokenizer_name="HuggingFaceH4/zephyr-7b-beta",
     model_name="HuggingFaceH4/zephyr-7b-beta",
-    # device="cpu",  # or "cuda" if available
+    
 )
 
 agent = ReActAgent.from_tools(
@@ -127,7 +160,7 @@ iface_loop = gr.Interface(
     fn=question_loop_agent,
     inputs=gr.Textbox(lines=2, placeholder="Ask me a question..."),
     outputs="text",
-    title="🧠 Question Similarity Loop Agent",
+    title="Question Similarity Loop Agent",
     description="Loops until the guessed question has a similarity score > 0.6."
 )