Create app.py

app.py

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+from flask import Flask, request, jsonify, render_template
+from dotenv import load_dotenv
+import os
+
+# Import chatbot logic
+from chatbot import Chatbot
+
+# Load environment variables from .env file
+load_dotenv()
+
+app = Flask(__name__)
+
+# Initialize the chatbot
+chatbot = Chatbot()
+
+@app.route('/')
+def home():
+    return render_template('index.html')
+
+@app.route('/ask', methods=['POST'])
+def ask():
+    # Get the user's message
+    user_message = request.form['message']
+
+    # Get the response from the chatbot
+    response = chatbot.get_response(user_message)
+
+    return jsonify({'response': response})
+
+if __name__ == '__main__':
+    app.run(debug=True)
+    from .math import solve_math_problem
+from .english import correct_grammar
+from .science import explain_science_concept
+from .python import solve_python_code
+
+class Chatbot:
+    def __init__(self):
+        pass
+
+    def get_response(self, user_input):
+        # Determine the subject and return the appropriate response
+        if 'math' in user_input.lower():
+            return solve_math_problem(user_input)
+        elif 'grammar' in user_input.lower() or 'english' in user_input.lower():
+            return correct_grammar(user_input)
+        elif 'science' in user_input.lower():
+            return explain_science_concept(user_input)
+        elif 'python' in user_input.lower() or 'code' in user_input.lower():
+            return solve_python_code(user_input)
+        else:
+            return "Sorry, I don't understand. Can you please clarify your question?"
+            from sympy import symbols, Eq, solve
+
+def solve_math_problem(user_input):
+    # For simplicity, assume the user asks a solvable equation like 'solve x + 5 = 10'
+    try:
+        # Create symbolic variable x
+        x = symbols('x')
+
+        # Parse and solve the equation
+        equation = Eq(eval(user_input), 0)  # Simplified eval, you can make it more complex
+        solution = solve(equation, x)
+        
+        return f"The solution to {user_input} is {solution}"
+    except Exception as e:
+        return "Sorry, I couldn't solve the math problem. Please check your input."
+        from textblob import TextBlob
+
+def correct_grammar(user_input):
+    blob = TextBlob(user_input)
+    corrected = blob.correct()
+    
+    return f"Corrected sentence: {corrected}"
+    def explain_science_concept(user_input):
+    # Placeholder logic, can be expanded to integrate an external knowledge base or API
+    return f"Here's an explanation about {user_input}. [This can be extended further with a real knowledge base]."
+
+
+
+