Update app.py

app.py

@@ -40,21 +40,30 @@ async def load_models():
     
     try:
         # 感情分析モデル（軽量版を使用）
+        print("Loading sentiment analysis model...")
         sentiment_classifier = pipeline(
             "sentiment-analysis",
-            model="cardiffnlp/twitter-roberta-base-sentiment-latest"
+            model="cardiffnlp/twitter-roberta-base-sentiment-latest",
+            return_all_scores=False
         )
+        print("✅ Sentiment model loaded")
         
         # テキスト生成モデル（軽量版）
+        print("Loading text generation model...")
         text_generator = pipeline(
             "text-generation",
-            model="distilgpt2"  # GPT-2より軽量
+            model="distilgpt2",
+            pad_token_id=50256  # GPT-2のEOSトークンID
         )
+        print("✅ Text generation model loaded")
         
-        print("✅ モデルのロードが完了しました")
+        print("✅ 全てのモデルのロードが完了しました")
         
     except Exception as e:
         print(f"❌ モデルロードエラー: {e}")
+        print(f"エラーの詳細: {type(e).__name__}")
+        import traceback
+        traceback.print_exc()
 
 @app.get("/")
 async def root():
@@ -97,27 +106,50 @@ async def generate_text(request: TextRequest):
                 detail="Text generation model not loaded. Please try again later."
             )
         
-        # Spacesの制限を考慮して短めに設定
-        max_length = min(request.max_length, 150)
+        # 入力テキストの検証
+        if not request.text or len(request.text.strip()) == 0:
+            raise HTTPException(status_code=400, detail="Text cannot be empty")
         
-        result = text_generator(
-            request.text,
-            max_length=max_length,
-            num_return_sequences=1,
-            temperature=0.7,
-            do_sample=True,
-            pad_token_id=text_generator.tokenizer.eos_token_id
-        )
+        # Spacesの制限を考慮して短めに設定
+        max_length = min(request.max_length, 100)
+        input_length = len(request.text.split())
         
-        generated_text = result[0]["generated_text"]
+        # 入力より長い出力を生成するように調整
+        if max_length <= input_length:
+            max_length = input_length + 20
         
-        return GenerateResponse(
-            input_text=request.text,
-            generated_text=generated_text,
-            model_name="distilgpt2"
-        )
+        try:
+            result = text_generator(
+                request.text,
+                max_length=max_length,
+                num_return_sequences=1,
+                temperature=0.7,
+                do_sample=True,
+                truncation=True,
+                pad_token_id=text_generator.tokenizer.eos_token_id
+            )
+            
+            generated_text = result[0]["generated_text"]
+            
+            return GenerateResponse(
+                input_text=request.text,
+                generated_text=generated_text,
+                model_name="distilgpt2"
+            )
+            
+        except Exception as model_error:
+            # モデル固有のエラーをキャッチ
+            print(f"Model error: {model_error}")
+            raise HTTPException(
+                status_code=500, 
+                detail=f"Model processing failed: {str(model_error)}"
+            )
     
+    except HTTPException:
+        # HTTPExceptionは再発生
+        raise
     except Exception as e:
+        print(f"Unexpected error: {e}")
         raise HTTPException(status_code=500, detail=f"Generation failed: {str(e)}")
 
 @app.get("/models")
@@ -135,16 +167,24 @@ async def get_models():
         "platform": "Hugging Face Spaces"
     }
 
-@app.get("/health")
-async def health_check():
-    """詳細なヘルスチェック"""
+@app.get("/debug")
+async def debug_info():
+    """デバッグ情報を取得"""
+    import sys
+    import torch
+    
     return {
-        "status": "healthy",
-        "models": {
+        "python_version": sys.version,
+        "torch_version": torch.__version__ if 'torch' in sys.modules else "not installed",
+        "models_loaded": {
             "sentiment": sentiment_classifier is not None,
-            "generation": text_generator is not None
+            "generator": text_generator is not None
         },
-        "memory_usage": "optimized for Spaces"
+        "generator_tokenizer": {
+            "vocab_size": text_generator.tokenizer.vocab_size if text_generator else None,
+            "eos_token_id": text_generator.tokenizer.eos_token_id if text_generator else None,
+            "pad_token_id": text_generator.tokenizer.pad_token_id if text_generator else None
+        } if text_generator else None
     }
 
 # Spaces用の追加設定