Add demo

app.py

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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=384,
+            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()

requirements.txt

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+gradio>=4.44.0
+sympy
+transformers>=4.44.0
+torch>=2.2.0
+sentencepiece
+safetensors