Update app.py

app.py

@@ -1,62 +1,15 @@
 import spacy
-import sympy as sp
-import gradio as gr
+import os
 
-# Load the spaCy model for English language processing
-nlp = spacy.load("en_core_web_sm")
+# Ensure model is downloaded before usage
+def load_spacy_model():
+    if not os.path.exists("en_core_web_sm"):
+        os.system("python -m spacy download en_core_web_sm")
+    return spacy.load("en_core_web_sm")
 
-# Function to extract mathematical expressions from the question
-def extract_expression(question):
-    doc = nlp(question)
-    tokens = []
-    
-    for token in doc:
-        # Look for numbers, mathematical operators, or symbols
-        if token.like_num or token.text in ['+', '-', '=', '*', '/', '^', 'x', 'y']:
-            tokens.append(token.text)
-    
-    # Join the tokens to form the mathematical expression
-    expression = " ".join(tokens)
-    
-    if "=" in expression:
-        return expression
-    else:
-        return "Could not parse a valid equation from the input."
+# Cache the model to avoid reloading on every request
+@st.cache_resource
+def get_nlp_model():
+    return load_spacy_model()
 
-# Function to solve mathematical expressions
-def solve_math_question(question):
-    try:
-        expression = extract_expression(question)
-        if "Could not parse" in expression:
-            return expression
-        
-        # Separate left and right sides of the equation
-        left_side, right_side = expression.split("=")
-        
-        # Create symbolic variables
-        y = sp.Symbol('y')  # Assuming we are solving for y (expandable for other variables)
-        
-        # SymPy solves the equation
-        solution = sp.solve(sp.Eq(sp.sympify(left_side), sp.sympify(right_side)), y)
-        return f"The solution is: {solution}"
-    
-    except Exception as e:
-        return f"Error solving the equation: {str(e)}"
-
-# Gradio interface
-def chatbot_interface(question):
-    # Restrict input to mathematical questions only
-    if not any(char.isdigit() for char in question):
-        return "This chatbot only answers questions related to mathematics. Please ask a mathematical question."
-    
-    return solve_math_question(question)
-
-# Define Gradio interface
-iface = gr.Interface(fn=chatbot_interface,
-                     inputs=gr.Textbox(label="Enter your mathematical question:"),
-                     outputs=gr.Textbox(label="Answer"),
-                     title="Math Chatbot (Open Source)",
-                     description="Ask any mathematical question and get an answer. Non-mathematical questions will be restricted.")
-
-# Run the Gradio app
-iface.launch()
+nlp = get_nlp_model()