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| 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, # CPU | |
| 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() | |