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9574228 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 | import gradio as gr
import sympy as sp
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
MODEL_ID = "Qwen/Qwen2.5-1.5B-Instruct"
SYSTEM_PROMPT = """
You are a helpful tutor who always avoid hashtags, emojis, or social media style text.
"""
tok = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
MODEL_ID,
torch_dtype=torch.float32, # CPU
device_map=None
)
model.eval()
def level_style(level: str, step: bool) -> str:
if level == "Beginner":
return (
"Simple and short answer to the questions."
"Use short sentences and sometimes give small examples. "
+ ("Show each step clearly." if step else "Keep it short and clear.")
)
elif level == "Intermediate":
return (
"Explain with moderate detail. Use correct terminology but keep it approachable. "
+ ("Give step-by-step reasoning." if step else "Keep it short and clear.")
)
else: # Advanced
return (
"Use precise and technical language. Assume the user has strong background knowledge involving the matter."
+ ("Show reasoning steps briefly." if step else "Be concise and analytical.")
)
def verify_math(expr_str: str) -> str:
try:
expr = sp.sympify(expr_str)
simplified = sp.simplify(expr)
return f"Simplified: ${sp.latex(simplified)}$"
except Exception as e:
return f"Could not verify with SymPy: {e}"
def generate(question: str, level: str, step_by_step: bool) -> str:
if not question.strip():
return "Please enter a question."
style = level_style(level, step_by_step)
prompt = f"System: {SYSTEM_PROMPT}\n{style}\nUser: {question}\nAssistant:"
inputs = tok(prompt, return_tensors="pt")
with torch.no_grad():
out = model.generate(
**inputs,
max_new_tokens=192, # was 384
do_sample=True, # False was True
temperature=0.7,
top_p=0.9,
repetition_penalty=1.2,
no_repeat_ngram_size=3,
pad_token_id=tok.eos_token_id
)
text = tok.decode(out[0], skip_special_tokens=True)
if "Assistant:" in text:
text = text.split("Assistant:", 1)[1].strip()
is_math = any(ch in question for ch in "+-*/=^") or question.lower().startswith(("simplify","derive","integrate"))
sympy_note = verify_math(question) if is_math else "No math verification needed."
return f"{text}\n\n---\n**SymPy check:** {sympy_note}\n_Status: Transformers CPU_"
# Building app and IU
def build_app():
with gr.Blocks(title="LearnLoop — CPU Space") as demo:
# CSS styles and adding colours
gr.HTML("""
<style>
.gradio-container {
background-color: #EDF6FA !important; /* haalea sininen */
padding: 24px;
border-radius: 12px;
box-shadow: 0 4px 12px rgba(0,0,0,0.05);
}
/* buttons */
button {
border-radius: 8px;
transition: all 0.2s ease-in-out;
font-weight: 500;
letter-spacing: 0.5px;
}
button:hover {
opacity: 0.9;
transform: translateY(-1px);
}
button:active {
filter: brightness(85%);
transform: scale(0.98);
}
/* Explain ja Reset buttons */
#explain-btn {
background-color: #5499C7;
color: white;
border: 2px solid #2E86C1;
}
#reset-btn {
background-color: #EC7063;
color: white;
border: 2px solid #CB4335;
}
#explain-btn:hover, #reset-btn:hover {
opacity: 0.85;
}
#explain-btn:active, #reset-btn:active {
filter: brightness(85%);
transform: scale(0.98);
}
</style>
""")
# prints using instructions
gr.Markdown("""
# **LearnL**<span style="font-size:1.2em; color: #21618C">∞</span>**p — AI Tutor**
This app uses the [Qwen 2.5 model](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct)
to explain questions at different skill levels. It can also verify
mathematical expressions using the SymPy library.
**How to use:**
1️⃣ Type your question or a mathematical expression.
2️⃣ Select your level (Beginner, Intermediate, Advanced).
3️⃣ Choose whether you want a step-by-step explanation.
4️⃣ Press **"Explain"** or **Enter** on your keyboard.
5️⃣ If you want to enter a new question, you can press **"Reset"** or simply **type a new question**.
💬 You can ask your question in **English**.
""")
# User's feed
q = gr.Textbox(label="Your question", placeholder="e.g., simplify (x^2 - 1)/(x - 1)", elem_id="question-box")
level = gr.Dropdown(choices=["Beginner", "Intermediate", "Advanced"], value="Beginner", label="Level")
step = gr.Checkbox(value=True, label="Step-by-step")
# Results
loading = gr.Markdown(visible=False) # spinner hided at first
out = gr.Markdown()
# Buttons next to each other
with gr.Row():
btn = gr.Button("Explain", elem_id="explain-btn")
reset_btn = gr.ClearButton([q, out, loading], value="Reset", elem_id="reset-btn")
# connect to generate function with spinner
def wrapped_generate(q_val, level_val, step_val):
# Näytetään spinner ensin
loading_text = "⏳ Generating explanation..."
result = generate(q_val, level_val, step_val)
# hide spinner when ready
return "", result
btn.click(fn=wrapped_generate, inputs=[q, level, step], outputs=[loading, out])
q.submit(fn=wrapped_generate, inputs=[q, level, step], outputs=[loading, out])
return demo
# start the app
if __name__ == "__main__":
build_app().launch() |