Update app.py

app.py

@@ -1,50 +1,68 @@
-"""
-HF Space · WFGY 1-click Variance Gate  (貼上就能部署)
-"""
+# HF Space · WFGY demo (all-English, no comments in other languages)
 
-import io, numpy as np, gradio as gr, matplotlib.pyplot as plt
+import io
+import numpy as np
+import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 from wfgy_sdk import get_engine
 from wfgy_sdk.evaluator import compare_logits, plot_histogram
 
-MODEL  = "sshleifer/tiny-gpt2"
-tok    = AutoTokenizer.from_pretrained(MODEL)
-mdl    = AutoModelForCausalLM.from_pretrained(MODEL)
-ENG    = get_engine()
+MODEL_ID = "sshleifer/tiny-gpt2"
 
-def run(prompt:str):
-    if not prompt.strip():
-        return "-", "-", "-", None
+tok = AutoTokenizer.from_pretrained(MODEL_ID)
+mdl = AutoModelForCausalLM.from_pretrained(MODEL_ID)
+eng = get_engine()
 
-    inp   = tok(prompt, return_tensors="pt")
-    rawL  = mdl(**inp).logits[0, -1].detach().cpu().numpy()
-    I, G  = np.random.randn(2, 256).astype(np.float32)
-    modL  = ENG.run(I, G, rawL)
+def run(prompt: str):
+    prompt = prompt.strip()
+    if not prompt:
+        return "", "", "No prompt — nothing to show", None
 
-    mets  = compare_logits(rawL, modL)
-    head  = f"▼ Var {mets['var_drop']*100:.1f}% | KL {mets['kl']:.2f}"
+    ids = tok(prompt, return_tensors="pt").input_ids
+    logits_raw = mdl(ids).logits[0, -1].detach().cpu().numpy()
 
-    # ── 圖表轉成 PNG buffer ──
-    fig   = plot_histogram(rawL, modL)
-    buf   = io.BytesIO(); fig.savefig(buf, format="png"); buf.seek(0)
+    # toy fingerprints just for the demo
+    G = np.random.randn(256).astype(np.float32)
+    I = G + np.random.normal(scale=0.05, size=256).astype(np.float32)
 
-    raw_txt = prompt + tok.decode(int(rawL.argmax()))
-    mod_txt = prompt + tok.decode(int(modL.argmax()))
-    return raw_txt, mod_txt, head, buf
+    logits_mod = eng.run(I, G, logits_raw)
+    m = compare_logits(logits_raw, logits_mod)
+
+    headline = f"▼ var {m['var_drop']*100:.1f} % | KL {m['kl']:.3f}"
+
+    fig = plot_histogram(logits_raw, logits_mod)
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png")
+    buf.seek(0)
+
+    raw_txt = prompt + tok.decode(int(logits_raw.argmax()))
+    mod_txt = prompt + tok.decode(int(logits_mod.argmax()))
+    return raw_txt, mod_txt, headline, buf
+
+
+with gr.Blocks(title="WFGY Variance Gate") as demo:
+    gr.Markdown(
+        "# 🧠 WFGY simulation demo\n"
+        "Type any prompt – watch variance shrink in real time."
+    )
 
-with gr.Blocks(title="WFGY 1-Click Variance Gate") as demo:
-    gr.Markdown("# 🧠 WFGY 模擬實驗\n*輸入任意 Prompt，立刻觀看 Logit 直方圖*")
     prompt = gr.Textbox(label="Prompt", value="Explain Schrödinger's cat")
-    run_b  = gr.Button("🚀 Run")
+    btn = gr.Button("🚀 Run")
 
     with gr.Row():
-        raw  = gr.Textbox(label="Raw GPT-2")
-        mod  = gr.Textbox(label="After WFGY")
+        raw_box = gr.Textbox(label="Raw GPT-2")
+        mod_box = gr.Textbox(label="After WFGY")
+
+    headline = gr.Markdown()
+    img = gr.Image(label="Logit histogram")
 
-    head = gr.Markdown()
-    img  = gr.Image(label="Logit Histogram")
+    btn.click(run, prompt, [raw_box, mod_box, headline, img])
 
-    run_b.click(run, prompt, [raw, mod, head, img])
+    gr.Markdown(
+        "---\n"
+        "### ⭐ Help unlock **WFGY 2.0**\n"
+        "10 000 stars on GitHub by **2025-08-01** → next-gen release."
+    )
 
 if __name__ == "__main__":
-    demo.queue(default_concurrency_limit=2).launch()
+    demo.queue(concurrency_count=2).launch()