Update app.py

app.py

@@ -3,9 +3,13 @@ WFGY Space – tiny-GPT-2 variance-gate demo
 ★ 10 k GitHub ⭐ before 2025-08-01 unlocks WFGY 2.0 ★
 """
 
-import io, numpy as np, pandas as pd, gradio as gr
+import io
+import numpy as np
+import pandas as pd
+import 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
 
@@ -14,7 +18,7 @@ tok = AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2")
 mdl = AutoModelForCausalLM.from_pretrained("sshleifer/tiny-gpt2")
 eng = get_engine()
 
-# ── paper benchmarks table ───────────────────────────────────────────
+# paper benchmarks
 bench = pd.DataFrame({
     "Benchmark": ["MMLU","GSM8K","BBH","MathBench","TruthfulQA",
                   "XNLI","MLQA","LongBench","VQAv2","OK-VQA"],
@@ -22,18 +26,18 @@ bench = pd.DataFrame({
     "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["Rel_gain%"] = ((bench["Abs_gain"] / bench["Baseline"]) * 100).round(0)
 bench_sty = (
     bench.style
     .background_gradient(cmap="Greens", subset=["Abs_gain","Rel_gain%"])
     .format({"Abs_gain":"{:.1f}","Rel_gain%":"{:.0f}"})
 )
 
-# ── marketing banner ────────────────────────────────────────────────
+# banner markdown
 banner = """
 **📈 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.
@@ -43,17 +47,17 @@ 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, or try [Gemini](https://gemini.google.com/))  
-**Step 3 — Give the Command** “**Answer using WFGY** + your question”  
+**Step 3 — Give the Command** (“Answer using WFGY” + your question)  
 Prompt examples: *TBD*  
 **Step 4 — Integrate the SDK** ([GitHub](https://github.com/onestardao/WFGY))
 
 ---
 
 🌟 **Star Reminder** → [Star the repo](https://github.com/onestardao/WFGY)  
-_10 k ⭐ before 2025-08-01 unlocks **WFGY 2.0**._
+_10 k ⭐ before 2025-08-01 unlocks WFGY 2.0._
 """
 
-# ── inference ────────────────────────────────────────────────────────
+# inference
 def run(prompt: str):
     p = prompt.strip()
     if not p:
@@ -64,23 +68,34 @@ def run(prompt: str):
     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)
-    head = f"▼ var {m['var_drop']*100:.1f}% | KL {m['kl_divergence']:.3f} | top-1 {'kept' if m['top1'] else 'changed'}"
+    m = compare_logits(raw_L, mod_L)
+    header = "▼ var {:.1f}% | KL {:.3f} | top-1 {}".format(
+        m["var_drop"]*100, m["kl_divergence"],
+        "kept" if m["top1"] else "changed"
+    )
 
     def top5(logits):
         p = softmax(logits)
         idx = p.argsort()[-5:][::-1]
-        return "\n".join([f\"'{tok.decode(int(i)).strip()}': {p[i]:.2e}\" for i in idx])
+        lines = []
+        for i in idx:
+            token = tok.decode(int(i)).strip()
+            prob = p[i]
+            # 使用科学计数法，两位小数：e.g. 1.23e-04
+            lines.append("'{}': {:.2e}".format(token, prob))
+        return "\n".join(lines)
 
     raw_txt = top5(raw_L)
     mod_txt = top5(mod_L)
 
     fig = plot_histogram(raw_L, mod_L)
-    buf = io.BytesIO(); fig.savefig(buf, format="png"); buf.seek(0)
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png")
+    buf.seek(0)
 
-    return raw_txt, mod_txt, head, Image.open(buf)
+    return raw_txt, mod_txt, header, Image.open(buf)
 
-# ── Gradio UI ────────────────────────────────────────────────────────
+# UI
 with gr.Blocks(title="WFGY variance-gate demo") as demo:
     gr.Markdown(banner)
 
@@ -100,4 +115,5 @@ with gr.Blocks(title="WFGY variance-gate demo") as demo:
     btn.click(run, prompt, [raw_box, mod_box, metrics, img])
 
 if __name__ == "__main__":
+    
     demo.queue(default_concurrency_limit=2).launch()