| import gradio as gr |
| import sympy as sp |
| import torch |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
| MODEL_ID = "Qwen/Qwen2.5-0.5B-Instruct" |
| SYSTEM_PROMPT = "You are a helpful tutor. Match the user's level." |
|
|
| tok = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True) |
| model = AutoModelForCausalLM.from_pretrained( |
| MODEL_ID, |
| torch_dtype=torch.float32, |
| device_map=None |
| ) |
| model.eval() |
|
|
| 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 = f"Level: {level}. {'Explain step-by-step.' if step_by_step else 'Be concise.'}" |
| 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, |
| do_sample=True, |
| temperature=0.7, |
| top_p=0.95, |
| 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_" |
|
|
| def build_app(): |
| with gr.Blocks(title="LearnLoop — CPU Space") as demo: |
| gr.Markdown("# LearnLoop — CPU-only demo") |
| q = gr.Textbox(label="Your question", placeholder="e.g., simplify (x^2 - 1)/(x - 1)") |
| level = gr.Dropdown(choices=["Beginner","Intermediate","Advanced"], value="Beginner", label="Level") |
| step = gr.Checkbox(value=True, label="Step-by-step") |
| btn = gr.Button("Explain"); out = gr.Markdown() |
| btn.click(generate, [q, level, step], out) |
| return demo |
|
|
| if __name__ == "__main__": |
| build_app().launch() |
|
|
