Update app.py

app.py

@@ -11,7 +11,7 @@ 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
+from wfgy_sdk.evaluator import compare_logits, plot_histogram
 
 # tiny model (CPU)
 tok = AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2")
@@ -45,10 +45,10 @@ 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 1 — Download** ([PDF](https://doi.org/10.5281/zenodo.15657017))  
 **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*  
+Prompt examples: [https://doi.org/10.5281/zenodo.15657017](https://doi.org/10.5281/zenodo.15657017)  
 **Step 4 — Integrate the SDK** ([GitHub](https://github.com/onestardao/WFGY))
 
 ---
@@ -57,6 +57,12 @@ Prompt examples: *TBD*
 _10 k ⭐ before 2025-08-01 unlocks WFGY 2.0._
 """
 
+# own softmax implementation
+def softmax_np(logits: np.ndarray) -> np.ndarray:
+    z = logits - np.max(logits)
+    e = np.exp(z)
+    return e / np.sum(e)
+
 # inference
 def run(prompt: str):
     p = prompt.strip()
@@ -75,13 +81,12 @@ def run(prompt: str):
     )
 
     def top5(logits):
-        p = softmax(logits)
-        idx = p.argsort()[-5:][::-1]
+        p_arr = softmax_np(logits)
+        idx = np.argsort(p_arr)[-5:][::-1]
         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
+            prob = p_arr[i]
             lines.append("'{}': {:.2e}".format(token, prob))
         return "\n".join(lines)
 
@@ -115,5 +120,4 @@ 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()