Completed requirements.txt, fixed the Dockerfile, and updated the README. Significantly refactored the sentiment analyzer to be more robust against missing machine learning dependencies and controllable via a toggle.

InsightEngine/tools/sentiment_analyzer.py

@@ -3,14 +3,39 @@
 基于WeiboMultilingualSentiment模型为InsightEngine提供情感分析功能
 """
 
-import torch
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import os
 import sys
 from typing import List, Dict, Any, Optional, Union
 from dataclasses import dataclass
 import re
 
+try:
+    import torch
+    TORCH_AVAILABLE = True
+except ImportError:
+    torch = None  # type: ignore
+    TORCH_AVAILABLE = False
+
+try:
+    from transformers import AutoTokenizer, AutoModelForSequenceClassification
+    TRANSFORMERS_AVAILABLE = True
+except ImportError:
+    AutoTokenizer = None  # type: ignore
+    AutoModelForSequenceClassification = None  # type: ignore
+    TRANSFORMERS_AVAILABLE = False
+
+
+# INFO：若想跳过情感分析，可手动切换此开关为False
+SENTIMENT_ANALYSIS_ENABLED = True
+
+def _describe_missing_dependencies() -> str:
+    missing = []
+    if not TORCH_AVAILABLE:
+        missing.append("PyTorch")
+    if not TRANSFORMERS_AVAILABLE:
+        missing.append("Transformers")
+    return " / ".join(missing)
+
 # 添加项目根目录到路径，以便导入WeiboMultilingualSentiment
 project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 weibo_sentiment_path = os.path.join(project_root, "SentimentAnalysisModel", "WeiboMultilingualSentiment")
@@ -52,6 +77,7 @@ class WeiboMultilingualSentimentAnalyzer:
         self.device = None
         self.is_initialized = False
         self.is_disabled = False
+        self.disable_reason: Optional[str] = None
         
         # 情感标签映射（5级分类）
         self.sentiment_map = {
@@ -61,8 +87,52 @@ class WeiboMultilingualSentimentAnalyzer:
             3: "正面", 
             4: "非常正面"
         }
-        
-        print("WeiboMultilingualSentimentAnalyzer 已创建，调用 initialize() 来加载模型")
+
+        if not SENTIMENT_ANALYSIS_ENABLED:
+            self.disable("情感分析功能已在配置中关闭。")
+        elif not (TORCH_AVAILABLE and TRANSFORMERS_AVAILABLE):
+            missing = _describe_missing_dependencies() or "未知依赖"
+            self.disable(f"缺少依赖: {missing}，情感分析已禁用。")
+
+        if self.is_disabled:
+            reason = self.disable_reason or "Sentiment analysis disabled."
+            print(f"WeiboMultilingualSentimentAnalyzer initialized but disabled: {reason}")
+        else:
+            print("WeiboMultilingualSentimentAnalyzer 已创建，调用 initialize() 来加载模型")
+
+    def disable(self, reason: Optional[str] = None, drop_state: bool = False) -> None:
+        """Disable sentiment analysis, optionally clearing loaded resources."""
+        self.is_disabled = True
+        self.disable_reason = reason or "Sentiment analysis disabled."
+        if drop_state:
+            self.model = None
+            self.tokenizer = None
+            self.device = None
+            self.is_initialized = False
+
+    def enable(self) -> bool:
+        """Attempt to enable sentiment analysis; returns True if enabled."""
+        if not SENTIMENT_ANALYSIS_ENABLED:
+            self.disable("情感分析功能已在配置中关闭。")
+            return False
+        if not (TORCH_AVAILABLE and TRANSFORMERS_AVAILABLE):
+            missing = _describe_missing_dependencies() or "未知依赖"
+            self.disable(f"缺少依赖: {missing}，情感分析已禁用。")
+            return False
+        self.is_disabled = False
+        self.disable_reason = None
+        return True
+
+    def _select_device(self):
+        """Select the best available torch device."""
+        if not TORCH_AVAILABLE:
+            return None
+        if torch.cuda.is_available():
+            return torch.device("cuda")
+        mps_backend = getattr(torch.backends, "mps", None)
+        if mps_backend and getattr(mps_backend, "is_available", lambda: False)() and getattr(mps_backend, "is_built", lambda: False)():
+            return torch.device("mps")
+        return torch.device("cpu")
     
     def initialize(self) -> bool:
         """
@@ -72,7 +142,14 @@ class WeiboMultilingualSentimentAnalyzer:
             是否初始化成功
         """
         if self.is_disabled:
-            print("情感分析功能已禁用，跳过模型加载")
+            reason = self.disable_reason or "情感分析功能已禁用"
+            print(f"情感分析功能已禁用，跳过模型加载：{reason}")
+            return False
+
+        if not (TORCH_AVAILABLE and TRANSFORMERS_AVAILABLE):
+            missing = _describe_missing_dependencies() or "未知依赖"
+            self.disable(f"缺少依赖: {missing}，情感分析已禁用。", drop_state=True)
+            print(f"缺少依赖: {missing}，无法加载情感分析模型。")
             return False
 
         if self.is_initialized:
@@ -104,11 +181,23 @@ class WeiboMultilingualSentimentAnalyzer:
                 print(f"模型已保存到: {local_model_path}")
             
             # 设置设备
-            self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+            device = self._select_device()
+            if device is None:
+                raise RuntimeError("未检测到可用的计算设备")
+
+            self.device = device
             self.model.to(self.device)
             self.model.eval()
             self.is_initialized = True
-            self.is_disabled = False
+            self.enable()
+
+            device_type = getattr(self.device, "type", str(self.device))
+            if device_type == "cuda":
+                print("检测到可用 GPU，已优先使用 CUDA 进行推理。")
+            elif device_type == "mps":
+                print("检测到 Apple MPS 设备，已使用 MPS 进行推理。")
+            else:
+                print("未检测到 GPU，自动使用 CPU 进行推理。")
             
             print(f"模型加载成功! 使用设备: {self.device}")
             print("支持语言: 中文、英文、西班牙文、阿拉伯文、日文、韩文等22种语言")
@@ -117,14 +206,10 @@ class WeiboMultilingualSentimentAnalyzer:
             return True
             
         except Exception as e:
-            print(f"模型加载失败: {e}")
+            error_message = f"模型加载失败: {e}"
+            print(error_message)
             print("请检查网络连接或模型文件")
-            self.is_initialized = False
-            self.is_disabled = True
-            self.model = None
-            self.tokenizer = None
-            self.device = None
-            print("情感分析功能已禁用，将直接返回原始文本内容")
+            self.disable(error_message, drop_state=True)
             return False
     
     def _preprocess_text(self, text: str) -> str:
@@ -163,7 +248,7 @@ class WeiboMultilingualSentimentAnalyzer:
                 confidence=0.0,
                 probability_distribution={},
                 success=False,
-                error_message="情感分析功能已禁用",
+                error_message=self.disable_reason or "情感分析功能已禁用",
                 analysis_performed=False
             )
 
@@ -269,7 +354,7 @@ class WeiboMultilingualSentimentAnalyzer:
                     confidence=0.0,
                     probability_distribution={},
                     success=False,
-                    error_message="情感分析功能不可用",
+                    error_message=self.disable_reason or "情感分析功能不可用",
                     analysis_performed=False
                 )
                 for text in texts
@@ -318,7 +403,7 @@ class WeiboMultilingualSentimentAnalyzer:
         results: Optional[List[SentimentResult]] = None
     ) -> Dict[str, Any]:
         """
-        构建在情感分析不可用时的透传结�?
+        构建在情感分析不可用时的透传结果
         """
         total_items = len(texts) if texts is not None else len(original_data)
         response: Dict[str, Any] = {
@@ -400,7 +485,7 @@ class WeiboMultilingualSentimentAnalyzer:
         if self.is_disabled:
             return self._build_passthrough_analysis(
                 original_data=original_data,
-                reason="情感分析模型不可用",
+                reason=self.disable_reason or "情感分析模型不可用",
                 texts=texts_to_analyze
             )
         
@@ -409,7 +494,7 @@ class WeiboMultilingualSentimentAnalyzer:
         batch_result = self.analyze_batch(texts_to_analyze, show_progress=True)
         
         if not batch_result.analysis_performed:
-            reason = "情感分析功能不可用"
+            reason = self.disable_reason or "情感分析功能不可用"
             if batch_result.results:
                 candidate_error = next((r.error_message for r in batch_result.results if r.error_message), None)
                 if candidate_error:
@@ -486,6 +571,16 @@ class WeiboMultilingualSentimentAnalyzer:
 multilingual_sentiment_analyzer = WeiboMultilingualSentimentAnalyzer()
 
 
+def enable_sentiment_analysis() -> bool:
+    """Public helper to enable sentiment analysis at runtime."""
+    return multilingual_sentiment_analyzer.enable()
+
+
+def disable_sentiment_analysis(reason: Optional[str] = None, drop_state: bool = False) -> None:
+    """Public helper to disable sentiment analysis at runtime."""
+    multilingual_sentiment_analyzer.disable(reason=reason, drop_state=drop_state)
+
+
 def analyze_sentiment(text_or_texts: Union[str, List[str]], 
                      initialize_if_needed: bool = True) -> Union[SentimentResult, BatchSentimentResult]:
     """