Completed requirements.txt, fixed the Dockerfile, and updated the README. Signif…

…icantly refactored the sentiment analyzer to be more robust against missing machine learning dependencies and controllable via a toggle.

@@ -43,8 +43,6 @@ WORKDIR /app
 # Install Python dependencies first to leverage Docker layer caching
 # Install Python dependencies first to leverage Docker layer caching
 COPY requirements.txt ./ 
 COPY requirements.txt ./ 
 RUN uv pip install --system -r requirements.txt && \
 RUN uv pip install --system -r requirements.txt && \
-    uv pip install --system torch torchvision torchaudio && \
-    uv pip install --system transformers scikit-learn xgboost && \
     python -m playwright install chromium
     python -m playwright install chromium
 
 
 # Copy application source
 # Copy application source

@@ -3,14 +3,39 @@
 基于WeiboMultilingualSentiment模型为InsightEngine提供情感分析功能
 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 os
 import sys
 import sys
 from typing import List, Dict, Any, Optional, Union
 from typing import List, Dict, Any, Optional, Union
 from dataclasses import dataclass
 from dataclasses import dataclass
 import re
 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
 # 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__))))
 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")
 weibo_sentiment_path = os.path.join(project_root, "SentimentAnalysisModel", "WeiboMultilingualSentiment")
@@ -52,6 +77,7 @@ class WeiboMultilingualSentimentAnalyzer:
         self.device = None
         self.device = None
         self.is_initialized = False
         self.is_initialized = False
         self.is_disabled = False
         self.is_disabled = False
+        self.disable_reason: Optional[str] = None
         
         
         # 情感标签映射（5级分类）
         # 情感标签映射（5级分类）
         self.sentiment_map = {
         self.sentiment_map = {
@@ -61,8 +87,52 @@ class WeiboMultilingualSentimentAnalyzer:
             3: "正面", 
             3: "正面", 
             4: "非常正面"
             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:
     def initialize(self) -> bool:
         """
         """
@@ -72,7 +142,14 @@ class WeiboMultilingualSentimentAnalyzer:
             是否初始化成功
             是否初始化成功
         """
         """
         if self.is_disabled:
         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
             return False
 
 
         if self.is_initialized:
         if self.is_initialized:
@@ -104,11 +181,23 @@ class WeiboMultilingualSentimentAnalyzer:
                 print(f"模型已保存到: {local_model_path}")
                 print(f"模型已保存到: {local_model_path}")
             
             
             # 设置设备
             # 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.to(self.device)
             self.model.eval()
             self.model.eval()
             self.is_initialized = True
             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(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")
             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
             return True
             
             
         except Exception as e:
         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")
             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
             return False
     
     
     def _preprocess_text(self, text: str) -> str:
     def _preprocess_text(self, text: str) -> str:
@@ -163,7 +248,7 @@ class WeiboMultilingualSentimentAnalyzer:
                 confidence=0.0,
                 confidence=0.0,
                 probability_distribution={},
                 probability_distribution={},
                 success=False,
                 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
                 analysis_performed=False
             )
             )
 
 
@@ -269,7 +354,7 @@ class WeiboMultilingualSentimentAnalyzer:
                     confidence=0.0,
                     confidence=0.0,
                     probability_distribution={},
                     probability_distribution={},
                     success=False,
                     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
                     analysis_performed=False
                 )
                 )
                 for text in texts
                 for text in texts
@@ -318,7 +403,7 @@ class WeiboMultilingualSentimentAnalyzer:
         results: Optional[List[SentimentResult]] = None
         results: Optional[List[SentimentResult]] = None
     ) -> Dict[str, Any]:
     ) -> 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)
         total_items = len(texts) if texts is not None else len(original_data)
         response: Dict[str, Any] = {
         response: Dict[str, Any] = {
@@ -400,7 +485,7 @@ class WeiboMultilingualSentimentAnalyzer:
         if self.is_disabled:
         if self.is_disabled:
             return self._build_passthrough_analysis(
             return self._build_passthrough_analysis(
                 original_data=original_data,
                 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
                 texts=texts_to_analyze
             )
             )
         
         
@@ -409,7 +494,7 @@ class WeiboMultilingualSentimentAnalyzer:
         batch_result = self.analyze_batch(texts_to_analyze, show_progress=True)
         batch_result = self.analyze_batch(texts_to_analyze, show_progress=True)
         
         
         if not batch_result.analysis_performed:
         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:
             if batch_result.results:
                 candidate_error = next((r.error_message for r in batch_result.results if r.error_message), None)
                 candidate_error = next((r.error_message for r in batch_result.results if r.error_message), None)
                 if candidate_error:
                 if candidate_error:
@@ -486,6 +571,16 @@ class WeiboMultilingualSentimentAnalyzer:
 multilingual_sentiment_analyzer = 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]], 
 def analyze_sentiment(text_or_texts: Union[str, List[str]], 
                      initialize_if_needed: bool = True) -> Union[SentimentResult, BatchSentimentResult]:
                      initialize_if_needed: bool = True) -> Union[SentimentResult, BatchSentimentResult]:
     """
     """

@@ -204,17 +204,7 @@ conda activate your_conda_name
 ```bash
 ```bash
 # Basic dependency installation
 # Basic dependency installation
 pip install -r requirements.txt
 pip install -r requirements.txt
-
-#========Below are optional========
-# If you need local sentiment analysis functionality, install PyTorch
-# CPU version
-pip install torch torchvision torchaudio
-
-# CUDA 11.8 version (if you have GPU)
-pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
-
-# Install transformers and other AI-related dependencies
-pip install transformers scikit-learn xgboost
+# If you do not want to use the local sentiment analysis model (which has low computational requirements and defaults to the CPU version), you can comment out the 'Machine Learning' section in this file before executing the command.
 ```
 ```
 
 
 ### 3. Install Playwright Browser Drivers
 ### 3. Install Playwright Browser Drivers

@@ -206,17 +206,7 @@ conda activate your_conda_name
 ```bash
 ```bash
 # 基础依赖安装
 # 基础依赖安装
 pip install -r requirements.txt
 pip install -r requirements.txt
-
-#========下面是可选项========
-# 如果需要本地情感分析功能，安装PyTorch
-# CPU版本
-pip install torch torchvision torchaudio
-
-# CUDA 11.8版本（如有GPU）
-pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
-
-# 安装transformers等AI相关依赖
-pip install transformers scikit-learn xgboost
+# 如果不想使用本地情感分析模型（算力需求很小，默认安装cpu版本），可以将该文件中的“机器学习”部分注释掉再执行指令
 ```
 ```
 
 
 ### 3. 安装Playwright浏览器驱动
 ### 3. 安装Playwright浏览器驱动