app.py

import gradio as gr
import genai  # Assuming this is the correct library for Gemini API
import sympy as sp

# Set up the Gemini model
model = genai.GenerativeModel("gemini-1.5-flash")

# Function for algebraic simplification
def algebra_simplification(expression):
    try:
        expr = sp.sympify(expression)
        simplified_expr = sp.simplify(expr)
        return str(simplified_expr)
    except Exception as e:
        return f"Error: {str(e)}"

# Function for solving algebraic equations
def algebra_solve(equation):
    try:
        eq = sp.sympify(equation)
        variables = list(eq.free_symbols)
        solutions = sp.solve(eq, *variables)
        return str(solutions)
    except Exception as e:
        return f"Error: {str(e)}"

# Function to handle the chat with Gemini
def process_math_problem(math_problem):
    chat = model.start_chat(
        history=[
            {"role": "user", "parts": "Hello"},
            {"role": "model", "parts": "Great to meet you. What would you like to know?"},
        ]
    )
    
    # Send the math problem to Gemini
    response = chat.send_message(math_problem)
    
    # Return Gemini's response
    return response.text

# Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# Gemini Algebra Solver")
    
    # Single input field for math problems
    input_problem = gr.Textbox(label="Enter a Math Problem", placeholder="e.g., Simplify (x^2 - 4)/(x - 2) or Solve x^2 - 4 = 0")
    output_solution = gr.Textbox(label="Solution")
    
    # Button to trigger the solution process
    solve_button = gr.Button("Solve")
    solve_button.click(fn=process_math_problem, inputs=input_problem, outputs=output_solution)

# Launch the Gradio interface
demo.launch()