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README.md

@@ -1,12 +1,44 @@
----
-title: Math
-emoji: 🌍
-colorFrom: indigo
-colorTo: green
-sdk: gradio
-sdk_version: 5.29.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Mathematics Question Generator
+emoji: 🧮
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 4.16.0
+app_file: app.py
+pinned: false
+---
+
+# Mathematics Question Generator
+
+This application generates customized mathematics questions on any topic you specify. Simply enter a mathematics chapter or concept you want to practice, and the AI will create questions with step-by-step solutions.
+
+## Features
+
+- Generate mathematics questions on any topic
+- Choose the number of questions (1-10)
+- Select difficulty level (elementary to advanced)
+- View detailed step-by-step solutions
+
+## How to Use
+
+1. Enter a mathematics topic (e.g., "Linear Algebra: Eigenvalues", "Calculus: Integration")
+2. Adjust the number of questions and difficulty level as needed
+3. Click "Generate Questions"
+4. Study the generated questions and their solutions
+
+## Setup Requirements
+
+This application requires a Hugging Face API token with access to the DeepSeek models. To set up your token:
+
+1. Generate a Hugging Face API token with read access from [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens)
+2. Add this token to your Space as a secret with the key `HUGGINGFACE_TOKEN`
+   - Go to your Space settings
+   - Click on "Secrets"
+   - Add a new secret with name `HUGGINGFACE_TOKEN` and your token as the value
+
+## About
+
+This application uses DeepSeek's mathematics-focused language model to generate high-quality mathematics questions tailored to your learning needs.
+
+Created by Kamagelo Mosia

app.py

@@ -1,345 +1,99 @@
 import gradio as gr
 import os
+import requests
 from huggingface_hub import InferenceClient
 
-# Define calculus topics and subtopics
-CALCULUS_TOPICS = {
-    "Limits": [
-        "Finding limits algebraically",
-        "One-sided limits",
-        "Limits at infinity",
-        "Limits that don't exist",
-        "Epsilon-delta proofs"
-    ],
-    "Derivatives": [
-        "Basic differentiation rules",
-        "Power rule",
-        "Product rule",
-        "Quotient rule",
-        "Chain rule",
-        "Implicit differentiation",
-        "Logarithmic differentiation",
-        "Higher-order derivatives"
-    ],
-    "Applications of Derivatives": [
-        "Related rates",
-        "Mean value theorem",
-        "Critical points",
-        "Curve sketching",
-        "Optimization problems",
-        "Linear approximation",
-        "Newton's method"
-    ],
-    "Integrals": [
-        "Indefinite integrals",
-        "Basic integration rules",
-        "Substitution method",
-        "Integration by parts",
-        "Partial fractions",
-        "Trigonometric integrals",
-        "Improper integrals"
-    ],
-    "Applications of Integrals": [
-        "Area between curves",
-        "Volume of solids of revolution",
-        "Arc length",
-        "Surface area",
-        "Work and energy problems",
-        "Center of mass"
-    ],
-    "Sequences and Series": [
-        "Convergence tests",
-        "Power series",
-        "Taylor and Maclaurin series",
-        "Radius of convergence"
-    ],
-    "Multivariable Calculus": [
-        "Partial derivatives",
-        "Directional derivatives",
-        "Gradient",
-        "Multiple integrals",
-        "Line integrals",
-        "Surface integrals"
-    ],
-    "Differential Equations": [
-        "First-order differential equations",
-        "Separable equations",
-        "Second-order differential equations",
-        "Systems of differential equations"
-    ]
-}
-
-# Initialize DeepSeek client
-def get_deepseek_client():
-    # You'll need to set up your HuggingFace token as an environment variable
-    client = InferenceClient(
-        model="deepseek-ai/deepseek-math-7b-instruct",
-        token=os.getenv("HUGGINGFACE_TOKEN")
-    )
+# Initialize the Hugging Face Inference client for DeepSeek
+def get_inference_client():
+    api_token = os.environ.get("HUGGINGFACE_TOKEN")
+    if not api_token:
+        return None
+    
+    client = InferenceClient(token=api_token)
     return client
 
-def generate_math_problems(topic, subtopic, difficulty, num_problems=3):
-    """Generate math problems with step-by-step solutions and explanations"""
-    client = get_deepseek_client()
+def generate_math_questions(chapter, num_questions=5, difficulty="medium"):
+    """Generate mathematics questions based on the provided chapter/topic"""
+    client = get_inference_client()
     
-    # Create a specific prompt with the selected topic, subtopic and difficulty
-    prompt = f"""
-    Create {num_problems} {difficulty} difficulty calculus problems about '{subtopic}' (under the general topic of '{topic}').
+    if not client:
+        return "Error: Hugging Face token not configured. Please set the HUGGINGFACE_TOKEN in your space settings."
     
-    For each problem:
-    1. Provide a clear and concise question.
-    2. Provide a detailed step-by-step solution that a student can follow.
-    3. Include explanations for each step.
-    4. Mark the final answer clearly.
+    prompt = f"""Generate {num_questions} {difficulty}-level mathematics questions about {chapter}.
     
-    Format:
-    ## Problem N:
-    [Problem description]
+    For each question:
+    1. Write a clear, well-defined question
+    2. Provide a step-by-step solution
+    3. Include the final answer
     
-    ### Solution:
-    [Step-by-step solution]
+    Format your response as:
+    
+    ## Question 1
+    [Question text]
     
-    ### Explanation:
-    [Explanation for the solution steps]
+    ### Solution
+    [Step-by-step solution]
     
-    ### Answer:
+    ### Answer
     [Final answer]
+    
+    ## Question 2
+    ...and so on
     """
     
     try:
         response = client.text_generation(
             prompt=prompt,
+            model="deepseek-ai/deepseek-math-7b-instruct",
             max_new_tokens=2048,
             temperature=0.7,
-            repetition_penalty=1.2,
-            do_sample=True
+            top_p=0.95,
         )
         return response
     except Exception as e:
-        return f"Error generating problems: {str(e)}"
-
-# Function to update subtopics based on main topic selection
-def update_subtopics(topic):
-    return gr.Dropdown(choices=CALCULUS_TOPICS.get(topic, []), value=CALCULUS_TOPICS.get(topic, [""])[0])
-
-# Function to handle Gradio input and output
-def create_problems(topic, subtopic, difficulty, num_problems):
-    if not topic or not subtopic:
-        return "Please select both a topic and subtopic to generate problems."
-    
-    try:
-        num_problems = int(num_problems)
-    except ValueError:
-        num_problems = 3  # Default to 3 problems if input is invalid
-    
-    return generate_math_problems(topic, subtopic, difficulty, num_problems)
-
-# Custom CSS with Google Fonts integration
-custom_css = """
-@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500&family=JetBrains+Mono&display=swap');
-
-:root {
-    --border-color: #e0e0e0;
-    --bg-color: #ffffff;
-    --text-color: #333333;
-    --hover-color: #f0f0f0;
-}
-
-body, .gradio-container {
-    font-family: 'Inter', sans-serif;
-    color: var(--text-color);
-}
-
-.header {
-    text-align: center;
-    padding: 1.5rem 0;
-    margin-bottom: 1rem;
-    border-bottom: 1px solid var(--border-color);
-}
-
-.header h1 {
-    font-weight: 500;
-    margin-bottom: 0.5rem;
-}
-
-.header p {
-    font-weight: 300;
-    opacity: 0.8;
-}
-
-.card {
-    border: 1px solid var(--border-color);
-    border-radius: 4px;
-    padding: 1.25rem;
-    margin-bottom: 1rem;
-    background-color: var(--bg-color);
-}
-
-.card h3 {
-    font-weight: 500;
-    margin-bottom: 1rem;
-    font-size: 1.1rem;
-}
-
-button.generate-btn {
-    width: 100%;
-    background-color: var(--bg-color);
-    border: 1px solid var(--border-color);
-    border-radius: 4px;
-    padding: 0.5rem;
-    cursor: pointer;
-    transition: background-color 0.2s ease;
-    font-family: 'Inter', sans-serif;
-    font-weight: 500;
-}
-
-button.generate-btn:hover {
-    background-color: var(--hover-color);
-}
-
-.output-box {
-    font-family: 'JetBrains Mono', monospace;
-    border: 1px solid var(--border-color);
-    border-radius: 4px;
-    padding: 1rem;
-    white-space: pre-wrap;
-    line-height: 1.5;
-}
+        return f"Error generating questions: {str(e)}\n\nPlease ensure your Hugging Face token has the necessary permissions."
 
-.output-box h2 {
-    font-weight: 500;
-    margin-top: 1.5rem;
-    padding-top: 1rem;
-    border-top: 1px solid var(--border-color);
-}
-
-.output-box h2:first-child {
-    margin-top: 0;
-    padding-top: 0;
-    border-top: none;
-}
-
-.output-box h3 {
-    font-weight: 500;
-    margin-top: 1rem;
-}
-
-/* Customizing Gradio elements */
-.gr-form, .gr-panel {
-    border: none !important;
-    box-shadow: none !important;
-}
-
-.gr-input, .gr-dropdown, .gr-radio {
-    border: 1px solid var(--border-color) !important;
-    border-radius: 4px !important;
-}
-
-.gr-input:focus, .gr-dropdown:focus {
-    border-color: #999 !important;
-    box-shadow: none !important;
-}
-
-.gr-slider-thumb {
-    background-color: #999 !important;
-}
-
-.footer {
-    text-align: center;
-    font-size: 0.8rem;
-    padding: 1rem 0;
-    border-top: 1px solid var(--border-color);
-    margin-top: 2rem;
-    opacity: 0.7;
-}
-"""
-
-# Define the Gradio interface with custom styling
-with gr.Blocks(css=custom_css) as demo:
-    # Header
-    gr.HTML(
-        """
-        <div class="header">
-            <h1>Calculus Problem Generator</h1>
-            <p>Generate problems with step-by-step solutions</p>
-        </div>
-        """
-    )
+# Create the Gradio interface
+with gr.Blocks(title="Mathematics Question Generator") as demo:
+    gr.Markdown("# 🧮 Mathematics Question Generator")
+    gr.Markdown("Enter a mathematics chapter or topic to generate practice questions with solutions.")
     
-    # Main content area
     with gr.Row():
-        # Left panel - Problem configuration
-        with gr.Column(scale=1):
-            with gr.Box(elem_classes="card"):
-                gr.Markdown("### Configure Problems")
-                
-                # Topic selection
-                topic_dropdown = gr.Dropdown(
-                    choices=list(CALCULUS_TOPICS.keys()),
-                    label="Topic",
-                    value=list(CALCULUS_TOPICS.keys())[0]
-                )
-                
-                # Subtopic selection (dynamically updated)
-                subtopic_dropdown = gr.Dropdown(
-                    choices=CALCULUS_TOPICS[list(CALCULUS_TOPICS.keys())[0]],
-                    label="Subtopic",
-                    value=CALCULUS_TOPICS[list(CALCULUS_TOPICS.keys())[0]][0]
+        with gr.Column(scale=3):
+            chapter_input = gr.Textbox(
+                label="Mathematics Topic/Chapter",
+                placeholder="e.g., Calculus: Integration by Parts",
+                info="Be specific for better results"
+            )
+            
+            with gr.Row():
+                num_questions = gr.Slider(
+                    minimum=1, 
+                    maximum=10, 
+                    value=5, 
+                    step=1, 
+                    label="Number of Questions"
                 )
                 
-                # Update subtopics when topic changes
-                topic_dropdown.change(
-                    fn=update_subtopics,
-                    inputs=topic_dropdown,
-                    outputs=subtopic_dropdown
-                )
-                
-                # Difficulty selection
-                difficulty_radio = gr.Radio(
-                    choices=["Basic", "Intermediate", "Advanced"],
-                    label="Difficulty",
-                    value="Intermediate"
-                )
-                
-                # Number of problems
-                num_problems_slider = gr.Slider(
-                    minimum=1,
-                    maximum=5,
-                    value=3,
-                    step=1,
-                    label="Number of Problems"
-                )
-                
-                # Generate button
-                generate_button = gr.Button("Generate Problems", elem_classes="generate-btn")
-
-        # Right panel - Output display
-        with gr.Column(scale=2):
-            with gr.Box(elem_classes="card"):
-                gr.Markdown("### Problems & Solutions")
-                
-                # Output display
-                output_md = gr.Markdown(
-                    elem_classes="output-box",
-                    value="Select options and click 'Generate Problems' to start."
+                difficulty = gr.Dropdown(
+                    choices=["elementary", "easy", "medium", "hard", "advanced"],
+                    value="medium",
+                    label="Difficulty Level"
                 )
+            
+            generate_button = gr.Button("Generate Questions", variant="primary")
     
-    # Footer
-    gr.HTML(
-        """
-        <div class="footer">
-            <p>Calculus Problem Generator | Educational Tool</p>
-        </div>
-        """
-    )
+    with gr.Row():
+        output = gr.Markdown(label="Generated Questions")
     
-    # Connect the generate button to the function
     generate_button.click(
-        fn=create_problems,
-        inputs=[topic_dropdown, subtopic_dropdown, difficulty_radio, num_problems_slider],
-        outputs=output_md
+        fn=generate_math_questions,
+        inputs=[chapter_input, num_questions, difficulty],
+        outputs=output
     )
+    
+    gr.Markdown("---")
+    gr.Markdown("Created by Kamagelo Mosia | Powered by DeepSeek and Hugging Face")
 
 # Launch the app
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio>=4.0.0
+huggingface_hub>=0.19.0
+requests>=2.31.0