app.py

import gradio as gr
import os
import re
import time
import base64 # image has to be converted to base64 
from openai import OpenAI #openrouter access
from together import Together
from PIL import Image  #pillow for image processing
import io

### function to create math solution from math problem text

def generate_math_solution_openrouter(api_key, problem_text, history=None):
    if not api_key.strip():
        return "Please enter your OpenRouter API key.", history

    if not problem_text.strip():
        return "Please enter a math problem so that I can solve it for you!", 

    try:
        client=OpenAI(
            base_url="https://openrouter.ai/api/v1",
            api_key=api_key,
        )

        messages= [
            {"role": "system", "content": 
             """You are an expert math tutor who explains concepts clearly and thoroughly.
             Analyze the given math problem and provide a detailed step-by-step solution.
             For each step:
             1. Show the mathematical operation
             2. Explain why this step is necessary
             3. Connect it to relevant mathematical concepts
             
             Format your response with clear section headers using markdown.
             Begin with an "Initial Analysis" section, follow with numbered steps,
             and conclude with a "Final Answer" section."""},
        ]

        if history:
            for exchange in history:
                messages.append({"role": "user", "content": exchange[0]}) #asks a math prob
                if exchange[1]:  # Check if there's a response
                    messages.append({"role": "assistant", "content": exchange[1]}) #AI responses with a solution

        # Add the current problem
        messages.append({"role": "user", "content": f"Solve this math problem step-by-step: {problem_text}"}) 

        # Create the completion
        completion = client.chat.completions.create(
            model="deepseek/deepseek-r1-0528:free",
            messages=messages,
            extra_headers={
                "HTTP-Referer": "https://advancedmathtutor.edu",
                "X-Title": "Advanced Math Tutor",
            }
        )

        solution=completion.choices[0].message.content

        # Update history
        if history is None: #no convo
            history = [] #my all convo saved here
        history.append((problem_text, solution)) #now i update my convo history

        return solution, history

    except Exception as e:
        error_message = f"Error: {str(e)}"
        return error_message, history


#image processing 

def image_to_base64(image_path):
    if image_path is None:
        return None
    
    try:
        with open(image_path, "rb") as img_file:
            return base64.b64encode(img_file.read()).decode("utf-8")
    except Exception as e:
        print(f"Error converting image to base64: {str(e)}")
        return None

#### function for a math problem that uses image data (Together)

def generate_math_solution_together(api_key, problem_text, image_path=None, history=None):
    if not api_key.strip():
        return "Please enter your Together AI API key.", history
    
    if not problem_text.strip() and image_path is None:
        return "Please enter a math problem or upload an image of a math problem.", history

    try:
        client = Together(api_key=api_key)

        messages= [
            {"role": "system", "content": 
             """You are an expert math tutor who explains concepts clearly and thoroughly.
             Analyze the given math problem and provide a detailed step-by-step solution.
             For each step:
             1. Show the mathematical operation
             2. Explain why this step is necessary
             3. Connect it to relevant mathematical concepts
             
             Format your response with clear section headers using markdown.
             Begin with an "Initial Analysis" section, follow with numbered steps,
             and conclude with a "Final Answer" section."""},
        ]

        # Add conversation history if it exists
        if history:
            for exchange in history:
                messages.append({"role": "user", "content": exchange[0]})
                if exchange[1]:  # Check if there's a response
                    messages.append({"role": "assistant", "content": exchange[1]})

        # Prepare the user message content
        user_message_content = []  # WE are going to add some instructions regarding how to solve the math problem in the image

        # calculate the area of a circle with radius 6 cm (Image of a problem)

        #problem text / user message = Before calculating area convert radius of 6 cm to meter first

        # Add text content if provided
        if problem_text.strip(): #image+instruction
            user_message_content.append({
                "type": "text",
                "text": f"Solve this math problem: {problem_text}" #Before calculating area convert radius of 6 cm to meter first
            })
        else: #image
            user_message_content.append({
                "type": "text",
                "text": "Solve this math problem from the image:"
            })

        # Add image if provided
        if image_path:
            # Convert image to base64
            base64_image = image_to_base64(image_path)
            if base64_image:
                user_message_content.append({
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/jpeg;base64,{base64_image}"
                    }
                })

        # Add the user message with content
        messages.append({
            "role": "user", #conversation saved with image data+usermessage/instruction
            "content": user_message_content
        })

        
        response=client.chat.completions.create( #TOgether
            model="meta-llama/Llama-Vision-Free",
            messages=messages,
            stream=False
        )

        solution=response.choices[0].message.content #problem----> ans syntax

        # Update history - for simplicity, just store the text problem
        if history is None:
            history = []
        history.append((problem_text if problem_text.strip() else "Image problem", solution))
        
        return solution, history

    except Exception as e:
        error_message = f"Error: {str(e)}"
        return error_message, history

def create_demo(): #interface design complete
    with gr.Blocks(theme=gr.themes.Ocean(primary_hue="blue")) as demo:
        gr.Markdown("# 📚 Advanced Math Tutor")
        gr.Markdown("""
        This application provides step-by-step solutions to math problems using advanced AI models.
        Choose between OpenRouter's Phi-4-reasoning-plus for text-based problems or Together AI's 
        Llama-Vision for problems with images.
        """)

        with gr.Tabs():
            with gr.TabItem("Text Problem Solver (OpenRouter)"):
                with gr.Row():
                    with gr.Column(scale=1): #left side column design complete
                        openrouter_api_key = gr.Textbox(
                            label="OpenRouter API Key", 
                            placeholder="Enter your OpenRouter API key (starts with sk-or-)",
                            type="password"
                        )
                        text_problem_input = gr.Textbox(
                            label="Math Problem", 
                            placeholder="Enter your math problem here...", #Solve the quadratic equation: 3x² + 5x - 2 = 0"
                            lines=5
                        )
                        example_problems = gr.Examples(
                            examples=[
                                ["Solve the quadratic equation: 3x² + 5x - 2 = 0"],
                                ["Find the derivative of f(x) = x³ln(x)"],
                                ["Calculate the area of a circle with radius 5 cm"],
                                ["Find all values of x that satisfy the equation: log₂(x-1) + log₂(x+3) = 5"]
                            ],
                            inputs=[text_problem_input],
                            label="Example Problems"
                        )
                        with gr.Row():
                            openrouter_submit_btn = gr.Button("Solve Problem", variant="primary")
                            openrouter_clear_btn = gr.Button("Clear")
                    
                    with gr.Column(scale=2):
                        openrouter_solution_output = gr.Markdown(label="Solution")

                    # Store conversation history (invisible to user)
                    openrouter_conversation_history = gr.State(value=None)

                    # Button actions
                    openrouter_submit_btn.click(
                        fn=generate_math_solution_openrouter, #text problem solve
                        inputs=[openrouter_api_key, text_problem_input, openrouter_conversation_history],
                        outputs=[openrouter_solution_output, openrouter_conversation_history]
                    )

                    openrouter_clear_btn.click(
                        fn=lambda: ("", None),
                        inputs=[],
                        outputs=[openrouter_solution_output, openrouter_conversation_history]
                    )

            with gr.TabItem("Image Problem Solver (Together AI)"):
                with gr.Row():
                    with gr.Column(scale=1):
                        together_api_key = gr.Textbox(
                            label="Together AI API Key", 
                            placeholder="Enter your Together AI API key",
                            type="password"
                        )
                        together_problem_input = gr.Textbox(
                            label="Problem Description/Instruction (Optional)", 
                            placeholder="Enter additional context for the image problem...",
                            lines=3
                        )
                        together_image_input = gr.Image(
                            label="Upload Math Problem Image",
                            type="filepath"
                        )
                        with gr.Row():
                            together_submit_btn = gr.Button("Solve Problem", variant="primary")
                            together_clear_btn = gr.Button("Clear")

                    with gr.Column(scale=2):
                        together_solution_output = gr.Markdown(label="Solution")

                    # Store conversation history (invisible to user)
                    together_conversation_history = gr.State(value=None)

                    # Button actions
                    together_submit_btn.click(
                        fn=generate_math_solution_together,
                        inputs=[together_api_key, together_problem_input, together_image_input, together_conversation_history],
                        outputs=[together_solution_output, together_conversation_history]
                    )
                    
                    together_clear_btn.click(
                        fn=lambda: ("", None),
                        inputs=[],
                        outputs=[together_solution_output, together_conversation_history]
                    )

            
        # Footer
        gr.Markdown("""
        ---
        ### About
        This application uses Microsoft's Phi-4-reasoning-plus model via OpenRouter for text-based problems
        and Llama-Vision-Free via Together AI for image-based problems. 
        Your API keys are required but not stored permanently.
        """)

    return demo

# Launch the app
if __name__ == "__main__":
    demo = create_demo()
    demo.launch()