Create app.py

app.py

@@ -0,0 +1,34 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load Hugging Face Model
+@st.cache_resource
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained("xsanskarx/calculator-smollm2_v2")
+    model = AutoModelForCausalLM.from_pretrained("xsanskarx/calculator-smollm2_v2")
+    return tokenizer, model
+
+tokenizer, model = load_model()
+
+def calculate_expression(expression: str) -> str:
+    # Encode the user input and generate the result
+    input_ids = tokenizer.encode(expression, return_tensors="pt")
+    output_ids = model.generate(input_ids, max_new_tokens=50)
+    result = tokenizer.decode(output_ids[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
+    return result
+
+# Streamlit Interface
+st.title("AI-Powered Calculator")
+st.write("Enter a mathematical expression, and let the model solve it.")
+
+expression = st.text_input("Enter Expression (e.g., 5 + 3 * (2 - 1)):")
+
+if st.button("Calculate"):
+    if expression.strip():
+        try:
+            result = calculate_expression(expression)
+            st.success(f"Result: {result}")
+        except Exception as e:
+            st.error(f"Error: {str(e)}")
+    else:
+        st.warning("Please enter a valid expression.")