Spaces:
Running
Running
| import gradio as gr | |
| import os | |
| import re | |
| import time | |
| import base64 | |
| from openai import OpenAI | |
| from together import Together | |
| from PIL import Image | |
| import io | |
| 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.", history | |
| 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]}) # asking a math prob solution | |
| if exchange[1]: # Check if there's a response | |
| messages.append({"role": "assistant", "content": exchange[1]}) # getting the step by step solution of asked math prob | |
| # Add the current problem | |
| messages.append({"role": "user", "content": f"Solve this math problem step-by-step: {problem_text}"}) # what is 2+2? = problem_text | |
| # calling the model | |
| completion=client.chat.completions.create( | |
| model="microsoft/phi-4-reasoning-plus:free", | |
| messages=messages, | |
| extra_headers={ | |
| "HTTP-Referer": "https://advancedmathtutor.edu", | |
| "X-Title": "Advanced Math Tutor", | |
| } | |
| ) | |
| solution=completion.choices[0].message.content # finally you are getting solution of math prob here | |
| # Update history | |
| if history is None: | |
| history = [] | |
| history.append((problem_text, solution)) # user: what is 2+2? => LLM: 4 | |
| return solution, history | |
| except Exception as e: | |
| error_message = f"Error: {str(e)}" | |
| return error_message, history | |
| # Function to convert image to base64 | |
| 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 to generate math solution using Together AI with support for images | |
| 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 # image upload + text details to help solve the problem in image | |
| user_message_content = [] | |
| # Add text content if provided #extra info provided # image of 2+2=? + pls show detailed explanation | |
| if problem_text.strip(): | |
| user_message_content.append({ | |
| "type": "text", | |
| "text": f"Solve this math problem: {problem_text}" | |
| }) | |
| else: | |
| user_message_content.append({ #no extra info | |
| "type": "text", | |
| "text": "Solve this math problem from the image:" # image of 2+2=? | |
| }) | |
| # 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", #together url format for img support in case of image models | |
| "image_url": { | |
| "url": f"data:image/jpeg;base64,{base64_image}" | |
| } | |
| }) | |
| # Add the user message with content | |
| messages.append({ | |
| "role": "user", | |
| "content": user_message_content | |
| }) | |
| # Create the completion /calling the model | |
| response = client.chat.completions.create( | |
| model="meta-llama/Llama-Vision-Free", | |
| messages=messages, | |
| stream=False | |
| ) | |
| solution = response.choices[0].message.content | |
| # 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 | |
| ### what the gradio website interface will look like? answer korbo | |
| def create_demo(): | |
| with gr.Blocks(theme=gr.themes.Soft(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. | |
| """) | |
| ### pages/tabs = 2 tabs | |
| with gr.Tabs(): | |
| # Text-based problem solver (OpenRouter) | |
| with gr.TabItem("Text Problem Solver (OpenRouter)/PHI"): | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| 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...", | |
| 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, | |
| 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] | |
| ) | |
| # Image-based problem solver (Together AI) | |
| 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 (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] | |
| ) | |
| return demo | |
| ### launch the app | |
| if __name__ == "__main__": | |
| demo=create_demo() | |
| demo.launch() | |