MathMentorPro / app.py
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import gradio as gr
from huggingface_hub import InferenceClient
import os
from sympy import symbols, Eq, solve, latex
# Initialize the Hugging Face Inference Client
client = InferenceClient()
def preprocess_latex(content):
# Example: Split the response into meaningful parts
lines = content.split("\n")
processed_lines = []
for line in lines:
if "[" in line and "]" in line: # Treat as a mathematical expression
math_expr = line.strip("[]")
try:
# Parse and convert to LaTeX
processed_lines.append(f"$$ {math_expr} $$")
except:
processed_lines.append(line) # Fallback to raw line if parsing fails
elif "(" in line and ")" in line: # Treat as inline math
processed_lines.append(line.replace("(", "$").replace(")", "$"))
else:
processed_lines.append(line) # Plain text remains as-is
return "\n".join(processed_lines)
# Function to generate and format AI response
def generate_response(prompt_template, **kwargs):
# Simulate processing/loading
prompt = os.getenv(prompt_template).format(**kwargs)
response = client.chat.completions.create(
model="Qwen/Qwen2.5-Math-1.5B-Instruct",
messages=[{"role": "user", "content": prompt}],
temperature=0.7,
max_tokens=1024,
top_p=0.8
)
response_content = response.choices[0].message["content"]
formatted_response = preprocess_latex(response_content)
return gr.update(value=f"{formatted_response}")
# Gradio app interface
with gr.Blocks() as app:
gr.Markdown("## Mathematical Insight Tutor")
gr.Markdown("An advanced AI-powered tutor to help you master math concepts with step-by-step explanations.")
def create_tab(tab_name, prompt_template, inputs):
with gr.Tab(tab_name):
input_fields = []
for inp in inputs:
if inp["type"] == "textbox":
input_fields.append(
gr.Textbox(lines=inp.get("lines", 1), label=inp["label"], placeholder=inp["placeholder"])
)
elif inp["type"] == "dropdown":
input_fields.append(
gr.Dropdown(choices=inp["choices"], label=inp["label"])
)
elif inp["type"] == "value":
input_fields.append(
gr.Textbox(label=inp["label"], placeholder=inp["placeholder"])
)
# Button and output
button = gr.Button(f"{tab_name} Execute")
output = gr.Markdown(label="Output", elem_id="latex-output")
# Link button to the response wrapper
button.click(
fn=lambda *args: generate_response(prompt_template, **dict(zip([inp["key"] for inp in inputs], args))),
inputs=input_fields,
outputs=output,
api_name=f"/{tab_name.lower().replace(' ', '_')}_execute"
)
# Tabs for functionalities
create_tab(
"Solve a Problem",
"PROMPT_SOLVE",
[
{"key": "problem", "type": "textbox", "label": "Enter Math Problem", "placeholder": "e.g., Solve for x: 2x + 5 = 15"},
{"key": "difficulty", "type": "dropdown", "label": "Difficulty Level", "choices": ["Beginner", "Intermediate", "Advanced"]}
]
)
create_tab(
"Generate a Hint",
"PROMPT_HINT",
[
{"key": "problem", "type": "textbox", "label": "Enter Math Problem for Hint", "placeholder": "e.g., Solve for x: 2x + 5 = 15"},
{"key": "difficulty", "type": "dropdown", "label": "Difficulty Level", "choices": ["Beginner", "Intermediate", "Advanced"]}
]
)
create_tab(
"Verify Solution",
"PROMPT_VERIFY",
[
{"key": "problem", "type": "textbox", "label": "Enter Math Problem", "placeholder": "e.g., Solve for x: 2x + 5 = 15"},
{"key": "solution", "type": "value", "label": "Enter Your Solution", "placeholder": "e.g., x = 5"}
]
)
create_tab(
"Generate Practice Question",
"PROMPT_GENERATE",
[
{"key": "topic", "type": "textbox", "label": "Enter Math Topic", "placeholder": "e.g., Algebra, Calculus"},
{"key": "difficulty", "type": "dropdown", "label": "Difficulty Level", "choices": ["Beginner", "Intermediate", "Advanced"]}
]
)
create_tab(
"Explain Concept",
"PROMPT_EXPLAIN",
[
{"key": "problem", "type": "textbox", "label": "Enter Math Problem", "placeholder": "e.g., Solve for x: 2x + 5 = 15"},
{"key": "difficulty", "type": "dropdown", "label": "Difficulty Level", "choices": ["Beginner", "Intermediate", "Advanced"]}
]
)
# Add custom CSS for LaTeX rendering
app.css = """
#latex-output {
font-family: "Computer Modern", serif;
font-size: 16px;
line-height: 1.5;
}
"""
# Launch the app
app.launch(debug=True)