Update app.py

app.py

@@ -3,54 +3,50 @@ WFGY Space – tiny-GPT-2 variance-gate demo
 ★ 10 k GitHub ⭐ before 2025-08-01 unlocks WFGY 2.0 ★
 """
 
-import io
-import numpy as np
-import pandas as pd
-import plotly.express as px
-import gradio as gr
+import io, numpy as np, pandas as pd, gradio as gr
 from PIL import Image
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
 from wfgy_sdk import get_engine
 from wfgy_sdk.evaluator import compare_logits, plot_histogram, softmax
 
-# ── tiny model (CPU-friendly) ─────────────────────────────────────────
+# tiny model for free-CPU Space
 tok = AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2")
 mdl = AutoModelForCausalLM.from_pretrained("sshleifer/tiny-gpt2")
 eng = get_engine()
 
-# ── paper benchmark table ─────────────────────────────────────────────
+# paper benchmarks table
 bench = pd.DataFrame({
     "Benchmark": ["MMLU","GSM8K","BBH","MathBench","TruthfulQA",
                   "XNLI","MLQA","LongBench","VQAv2","OK-VQA"],
-    "Baseline":  [61.0,78.0,79.3,72.2,62.4,59.5,78.1,51.4,69.1,65.7],
+    "Baseline":  [61,78,79.3,72.2,62.4,59.5,78.1,51.4,69.1,65.7],
     "WFGY":      [89.8,98.7,100.7,87.4,90.4,77.3,106.6,69.6,86.6,86.8]
 })
-bench["Abs_gain"]  = (bench["WFGY"] - bench["Baseline"]).round(1)
-bench["Rel_gain%"] = ((bench["Abs_gain"] / bench["Baseline"])*100).round(0)
+bench["Abs_gain"]  = (bench["WFGY"]-bench["Baseline"]).round(1)
+bench["Rel_gain%"] = ((bench["Abs_gain"]/bench["Baseline"])*100).round(0)
 bench_style = (
     bench.style
     .background_gradient(cmap="Greens", subset=["Abs_gain","Rel_gain%"])
     .format({"Abs_gain":"{:.1f}","Rel_gain%":"{:.0f}"})
 )
 
-# ── marketing banner markdown ─────────────────────────────────────────
+# marketing banner
 banner_md = """
 **📈 WFGY: One Click to Activate the AI Taiji Cycle**
 
-**📊 Semantic Accuracy ↑ 22.4 % | Reasoning Success ↑ 42.1 % | Stability ↑ 3.6 ×**
+**📊 Semantic Accuracy ↑ 22.4 % | Reasoning Success ↑ 42.1 % | Stability ↑ 3.6 ×**
 
 _No beliefs. Only experiments._  
-_WFGY 1.0 has already proven itself._
+WFGY 1.0 has already proven itself.
 
 ---
 
 ### 📜 Tutorial: How to Awaken the Soul of Your AI
-**Step 1 — Download** ([PDF](https://zenodo.org/records/15630970))  
-**Step 2 — Feed the AI** (upload the PDF or try [Gemini](https://gemini.google.com/))  
-**Step 3 — Give the Command** “**Answer using WFGY** + your question”  
+**Step 1 — Download** ([PDF](https://zenodo.org/records/15630970))  
+**Step 2 — Feed the AI** (upload, or try [Gemini](https://gemini.google.com/))  
+**Step 3 — Give the Command** “**Answer using WFGY** + your question”  
 Prompt examples: *TBD*  
-**Step 4 — Integrate the SDK** ([GitHub](https://github.com/onestardao/WFGY))
+**Step 4 — Integrate the SDK** ([GitHub](https://github.com/onestardao/WFGY))
 
 ---
 
@@ -58,23 +54,20 @@ Prompt examples: *TBD*
 _10 k ⭐ before 2025-08-01 unlocks WFGY 2.0._
 """
 
-# ── core run function ────────────────────────────────────────────────
+# run once
 def run(prompt: str):
-    p = prompt.strip()
-    if not p:
+    prompt = prompt.strip()
+    if not prompt:
         return "", "", "-", None
 
-    ids   = tok(p, return_tensors="pt")
+    ids   = tok(prompt, return_tensors="pt")
     raw_L = mdl(**ids).logits[0, -1].detach().cpu().numpy()
     I, G  = np.random.randn(2, 256).astype(np.float32)
     mod_L = eng.run(I, G, raw_L)
 
     m = compare_logits(raw_L, mod_L)
-    headline = (f"▼ var {m['var_drop']*100:.1f}% | "
-                f"KL {m['kl_divergence']:.3f} | "
-                f"top-1 {'kept' if m['top1'] else 'changed'}")
+    head = f"▼ var {m['var_drop']*100:.1f}% | KL {m['kl_divergence']:.3f} | top-1 {'kept' if m['top1'] else 'changed'}"
 
-    # top-5 token lists
     def top5(logits):
         p = softmax(logits)
         idx = p.argsort()[-5:][::-1]
@@ -86,10 +79,10 @@ def run(prompt: str):
     fig = plot_histogram(raw_L, mod_L)
     buf = io.BytesIO(); fig.savefig(buf, format="png"); buf.seek(0)
 
-    return raw_txt, mod_txt, headline, Image.open(buf)
+    return raw_txt, mod_txt, head, Image.open(buf)
 
-# ── Gradio UI ────────────────────────────────────────────────────────
-with gr.Blocks(title="WFGY variance gate demo") as demo:
+# UI
+with gr.Blocks(title="WFGY variance-gate demo") as demo:
     gr.Markdown(banner_md)
 
     prompt = gr.Textbox(label="Prompt", value="Explain Schrödinger's cat")
@@ -100,12 +93,12 @@ with gr.Blocks(title="WFGY variance gate demo") as demo:
         mod_box = gr.Textbox(label="WFGY top-5 tokens", lines=6)
 
     metrics = gr.Markdown()
-    hist    = gr.Image(label="Logit histogram")
+    img     = gr.Image(label="Logit histogram")
 
     gr.Markdown("### Paper benchmarks (fixed values from WFGY 1.0)")
     gr.DataFrame(bench_style, interactive=False, wrap=True)
 
-    btn.click(run, prompt, [raw_box, mod_box, metrics, hist])
+    btn.click(run, prompt, [raw_box, mod_box, metrics, img])
 
 if __name__ == "__main__":
-    demo.queue(default_concurrency_limit=2).launch()
+    demo.queue(default_concurrency_limit=2).launch()