A more comprehensive large model analysis setup, front-end interface optimization.

2025-02-11 22:30:52 +08:00
parent 8ec05efe27
commit a60a0f3296
3 changed files with 357 additions and 51 deletions
@@ -14,9 +14,26 @@ class AIAnalyzer:
        
        openai.api_key = self.api_key
        
-        # 系统提示词，限制AI的输出格式
-        self.system_prompt = """你是一个专业的舆情分析助手。你的任务是分析每条消息的情感倾向、关键词和潜在影响。
-请严格按照以下JSON格式返回分析结果：
+        # 不同深度的分析提示词
+        self.prompt_templates = {
+            'basic': """你是一个专业的舆情分析助手。请对每条消息进行基础的情感分析。
+请按以下JSON格式返回：
+{
+    "analysis_results": [
+        {
+            "message_id": "消息ID",
+            "sentiment": "情感倾向 (积极/消极/中性)",
+            "sentiment_score": "情感分数 (0-1)",
+            "keywords": ["关键词1", "关键词2"],
+            "key_points": "简要概述",
+            "influence_analysis": "基础影响分析",
+            "risk_level": "风险等级 (低/中/高)",
+            "timestamp": "分析时间戳"
+        }
+    ]
+}""",
+            'standard': """你是一个专业的舆情分析助手。请对每条消息进行标准深度的分析。
+请按以下JSON格式返回：
 {
    "analysis_results": [
        {
@@ -30,41 +47,69 @@ class AIAnalyzer:
            "timestamp": "分析时间戳"
        }
    ]
-}
-请确保每个字段都有值，并保持JSON格式的一致性。"""
+}""",
+            'deep': """你是一个专业的舆情分析助手。请对每条消息进行深度分析。
+请按以下JSON格式返回：
+{
+    "analysis_results": [
+        {
+            "message_id": "消息ID",
+            "sentiment": "情感倾向 (积极/消极/中性)",
+            "sentiment_score": "情感分数 (0-1)",
+            "keywords": ["关键词1", "关键词2", "关键词3", "关键词4", "关键词5"],
+            "key_points": "详细的核心观点分析",
+            "influence_analysis": "深度影响分析，包括短期和长期影响",
+            "risk_factors": ["风险因素1", "风险因素2", "风险因素3"],
+            "risk_level": "风险等级 (低/中/高)",
+            "suggestions": ["建议1", "建议2", "建议3"],
+            "timestamp": "分析时间戳"
+        }
+    ]
+}"""
+        }

-    async def analyze_messages(self, messages: List[Dict]) -> List[Dict]:
+    async def analyze_messages(self, messages: List[Dict], batch_size: int = 50, 
+                             model_type: str = "gpt-3.5-turbo", 
+                             analysis_depth: str = "standard") -> List[Dict]:
        """分析一批消息并返回分析结果"""
        try:
-            # 构建输入消息
-            formatted_messages = []
-            for msg in messages:
-                formatted_messages.append(f"消息ID: {msg['id']}\n内容: {msg['content']}")
+            all_results = []
            
-            messages_text = "\n---\n".join(formatted_messages)
-            
-            # 调用OpenAI API
-            response = await openai.ChatCompletion.acreate(
-                model="gpt-3.5-turbo",
-                messages=[
-                    {"role": "system", "content": self.system_prompt},
-                    {"role": "user", "content": f"请分析以下消息:\n{messages_text}"}
-                ],
-                temperature=0.3,  # 降低随机性
-                max_tokens=2000,
-                n=1
-            )
-            
-            # 解析返回结果
-            try:
-                result = json.loads(response.choices[0].message.content)
-                # 验证结果格式
-                if not isinstance(result, dict) or 'analysis_results' not in result:
-                    raise ValueError("AI返回格式不正确")
-                return result['analysis_results']
-            except json.JSONDecodeError:
-                logging.error("AI返回结果解析失败")
-                return []
+            # 分批处理消息
+            for i in range(0, len(messages), batch_size):
+                batch = messages[i:i + batch_size]
+                formatted_messages = []
+                for msg in batch:
+                    formatted_messages.append(f"消息ID: {msg['id']}\n内容: {msg['content']}")
+                
+                messages_text = "\n---\n".join(formatted_messages)
+                
+                # 获取对应深度的提示词
+                system_prompt = self.prompt_templates.get(analysis_depth, self.prompt_templates['standard'])
+                
+                # 调用OpenAI API
+                response = await openai.ChatCompletion.acreate(
+                    model=model_type,
+                    messages=[
+                        {"role": "system", "content": system_prompt},
+                        {"role": "user", "content": f"请分析以下消息:\n{messages_text}"}
+                    ],
+                    temperature=0.3,  # 降低随机性
+                    max_tokens=2000 if analysis_depth != 'deep' else 3000,
+                    n=1
+                )
+                
+                try:
+                    result = json.loads(response.choices[0].message.content)
+                    if isinstance(result, dict) and 'analysis_results' in result:
+                        all_results.extend(result['analysis_results'])
+                    else:
+                        logging.error(f"API返回格式不正确: {response.choices[0].message.content}")
+                except json.JSONDecodeError as e:
+                    logging.error(f"JSON解析失败: {e}")
+                    continue
+                
+            return all_results
                
        except Exception as e:
            logging.error(f"AI分析过程出错: {e}")
@@ -72,7 +117,7 @@ class AIAnalyzer:
    
    def format_analysis_for_display(self, analysis: Dict) -> Dict:
        """将分析结果格式化为前端显示格式"""
-        return {
+        base_result = {
            'id': analysis['message_id'],
            'sentiment': analysis['sentiment'],
            'sentiment_score': f"{float(analysis['sentiment_score']):.2%}",
@@ -84,6 +129,15 @@ class AIAnalyzer:
                float(analysis['timestamp'])
            ).strftime('%Y-%m-%d %H:%M:%S')
        }
+        
+        # 如果是深度分析，添加额外信息
+        if 'risk_factors' in analysis:
+            base_result.update({
+                'risk_factors': analysis['risk_factors'],
+                'suggestions': analysis['suggestions']
+            })
+            
+        return base_result

 # 创建全局AI分析器实例
 ai_analyzer = AIAnalyzer() 
@@ -308,11 +308,33 @@ def articleChar(id):
@pb.route('/api/analyze_messages', methods=['POST'])
 async def analyze_messages():
    try:
-        # 获取最近50条消息
-        messages = getRecentMessages(50)  # 需要实现这个函数
+        # 获取请求参数
+        data = request.get_json()
+        batch_size = data.get('batch_size', 50)
+        model_type = data.get('model_type', 'gpt-3.5-turbo')
+        analysis_depth = data.get('analysis_depth', 'standard')
+        
+        # 获取最近的消息
+        messages = getRecentMessages(batch_size)
+        if not messages:
+            return jsonify({
+                'success': False,
+                'error': '没有找到需要分析的消息'
+            }), 404
        
        # 调用AI进行分析
-        analysis_results = await ai_analyzer.analyze_messages(messages)
+        analysis_results = await ai_analyzer.analyze_messages(
+            messages=messages,
+            batch_size=batch_size,
+            model_type=model_type,
+            analysis_depth=analysis_depth
+        )
+        
+        if not analysis_results:
+            return jsonify({
+                'success': False,
+                'error': '分析过程中出现错误'
+            }), 500
        
        # 保存到数据库
        with Session(engine) as session:
@@ -337,7 +359,14 @@ async def analyze_messages():
        
        return jsonify({
            'success': True,
-            'data': display_results
+            'data': display_results,
+            'meta': {
+                'total_messages': len(messages),
+                'analyzed_messages': len(analysis_results),
+                'batch_size': batch_size,
+                'model_type': model_type,
+                'analysis_depth': analysis_depth
+            }
        })
    
    except Exception as e:
@@ -454,11 +454,74 @@
                <div class="header-title">
                    <h4 class="card-title">AI深度分析</h4>
                </div>
-                <button class="btn btn-primary" onclick="requestAIAnalysis()">
-                    开始AI分析
-                </button>
+                <div class="analysis-controls">
+                    <!-- 批量处理设置 -->
+                    <div class="d-flex align-items-center">
+                        <div class="form-group mx-2 mb-0">
+                            <select id="batchSize" class="form-control form-control-sm">
+                                <option value="10">每批10条</option>
+                                <option value="20">每批20条</option>
+                                <option value="50" selected>每批50条</option>
+                                <option value="100">每批100条</option>
+                            </select>
+                        </div>
+                        <div class="form-group mx-2 mb-0">
+                            <select id="modelType" class="form-control form-control-sm">
+                                <option value="gpt-3.5-turbo" selected>GPT-3.5</option>
+                                <option value="gpt-4">GPT-4</option>
+                            </select>
+                        </div>
+                        <div class="form-group mx-2 mb-0">
+                            <select id="analysisDepth" class="form-control form-control-sm">
+                                <option value="basic">基础分析</option>
+                                <option value="standard" selected>标准分析</option>
+                                <option value="deep">深度分析</option>
+                            </select>
+                        </div>
+                        <div class="custom-control custom-switch mx-2">
+                            <input type="checkbox" class="custom-control-input" id="autoUpdate">
+                            <label class="custom-control-label" for="autoUpdate">自动更新</label>
+                        </div>
+                        <button class="btn btn-primary btn-sm" onclick="requestAIAnalysis()">
+                            开始分析
+                        </button>
+                    </div>
+                </div>
            </div>
            <div class="card-body">
+                <!-- 进度显示 -->
+                <div id="analysis-progress" class="mb-3" style="display: none;">
+                    <div class="progress">
+                        <div class="progress-bar progress-bar-striped progress-bar-animated" role="progressbar" style="width: 0%"></div>
+                    </div>
+                    <small class="text-muted mt-1 d-block">正在分析: <span id="progress-text">0/0</span></small>
+                </div>
+                
+                <!-- 分析结果过滤器 -->
+                <div class="mb-3">
+                    <div class="d-flex align-items-center">
+                        <div class="form-group mb-0 mr-2">
+                            <input type="text" class="form-control form-control-sm" id="keywordFilter" placeholder="按关键词过滤">
+                        </div>
+                        <div class="form-group mb-0 mr-2">
+                            <select class="form-control form-control-sm" id="sentimentFilter">
+                                <option value="">全部情感</option>
+                                <option value="积极">积极</option>
+                                <option value="消极">消极</option>
+                                <option value="中性">中性</option>
+                            </select>
+                        </div>
+                        <div class="form-group mb-0">
+                            <select class="form-control form-control-sm" id="riskFilter">
+                                <option value="">全部风险等级</option>
+                                <option value="高">高风险</option>
+                                <option value="中">中风险</option>
+                                <option value="低">低风险</option>
+                            </select>
+                        </div>
+                    </div>
+                </div>
+                
                <div id="ai-analysis-results" class="analysis-container">
                    <!-- 分析结果将在这里动态显示 -->
                </div>
@@ -467,7 +530,7 @@
    </div>
 </div>

-<!-- 添加必要的CSS样式 -->
+<!-- 更新CSS样式 -->
 <style>
 .analysis-container {
    max-height: 600px;
@@ -481,10 +544,12 @@
    margin-bottom: 15px;
    background-color: #fff;
    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+    transition: all 0.3s ease;
 }

 .analysis-card:hover {
    box-shadow: 0 4px 8px rgba(0,0,0,0.15);
+    transform: translateY(-2px);
 }

 .risk-level {
@@ -521,32 +586,167 @@
    padding: 4px 8px;
    border-radius: 16px;
    font-size: 0.9em;
+    transition: all 0.2s ease;
+}
+
+.keyword-tag:hover {
+    background-color: #1976d2;
+    color: #fff;
+}
+
+.sentiment-score {
+    display: inline-block;
+    padding: 2px 6px;
+    border-radius: 4px;
+    font-size: 0.9em;
+    margin-left: 8px;
+}
+
+.sentiment-positive {
+    background-color: #e8f5e9;
+    color: #2e7d32;
+}
+
+.sentiment-negative {
+    background-color: #ffebee;
+    color: #c62828;
+}
+
+.sentiment-neutral {
+    background-color: #f5f5f5;
+    color: #616161;
+}
+
+.progress {
+    height: 0.5rem;
+}
+
+.analysis-controls {
+    display: flex;
+    align-items: center;
+    flex-wrap: wrap;
+    gap: 10px;
+}
+
+@media (max-width: 768px) {
+    .analysis-controls {
+        flex-direction: column;
+        align-items: stretch;
+    }
 }
 </style>

-<!-- 添加必要的JavaScript代码 -->
+<!-- 更新JavaScript代码 -->
 <script>
+let currentAnalysis = {
+    inProgress: false,
+    totalMessages: 0,
+    processedMessages: 0,
+    autoUpdateInterval: null
+};
+
 async function requestAIAnalysis() {
+    if (currentAnalysis.inProgress) {
+        return;
+    }
+    
    try {
+        currentAnalysis.inProgress = true;
+        showProgress();
+        
+        const batchSize = parseInt(document.getElementById('batchSize').value);
+        const modelType = document.getElementById('modelType').value;
+        const analysisDepth = document.getElementById('analysisDepth').value;
+        
        const response = await fetch('/page/api/analyze_messages', {
            method: 'POST',
            headers: {
                'Content-Type': 'application/json'
-            }
+            },
+            body: JSON.stringify({
+                batch_size: batchSize,
+                model_type: modelType,
+                analysis_depth: analysisDepth
+            })
        });
        
        const result = await response.json();
        if (result.success) {
            displayAnalysisResults(result.data);
+            setupAutoUpdate();
        } else {
-            alert('分析失败: ' + result.error);
+            showError(result.error);
        }
    } catch (error) {
        console.error('AI分析请求失败:', error);
-        alert('请求失败，请稍后重试');
+        showError('请求失败，请稍后重试');
+    } finally {
+        currentAnalysis.inProgress = false;
+        hideProgress();
    }
 }

+function showProgress() {
+    const progressDiv = document.getElementById('analysis-progress');
+    progressDiv.style.display = 'block';
+    updateProgress(0, 100);
+}
+
+function hideProgress() {
+    const progressDiv = document.getElementById('analysis-progress');
+    progressDiv.style.display = 'none';
+}
+
+function updateProgress(current, total) {
+    const progressBar = document.querySelector('.progress-bar');
+    const progressText = document.getElementById('progress-text');
+    const percentage = (current / total) * 100;
+    
+    progressBar.style.width = `${percentage}%`;
+    progressText.textContent = `${current}/${total}`;
+}
+
+function setupAutoUpdate() {
+    const autoUpdate = document.getElementById('autoUpdate').checked;
+    if (autoUpdate && !currentAnalysis.autoUpdateInterval) {
+        currentAnalysis.autoUpdateInterval = setInterval(requestAIAnalysis, 300000); // 5分钟更新一次
+    } else if (!autoUpdate && currentAnalysis.autoUpdateInterval) {
+        clearInterval(currentAnalysis.autoUpdateInterval);
+        currentAnalysis.autoUpdateInterval = null;
+    }
+}
+
+function filterResults() {
+    const keyword = document.getElementById('keywordFilter').value.toLowerCase();
+    const sentiment = document.getElementById('sentimentFilter').value;
+    const risk = document.getElementById('riskFilter').value;
+    
+    const cards = document.querySelectorAll('.analysis-card');
+    cards.forEach(card => {
+        let show = true;
+        
+        // 关键词过滤
+        if (keyword) {
+            const content = card.textContent.toLowerCase();
+            show = show && content.includes(keyword);
+        }
+        
+        // 情感过滤
+        if (sentiment) {
+            const cardSentiment = card.querySelector('.sentiment-text').textContent;
+            show = show && cardSentiment.includes(sentiment);
+        }
+        
+        // 风险等级过滤
+        if (risk) {
+            const cardRisk = card.querySelector('.risk-level').textContent;
+            show = show && cardRisk.includes(risk);
+        }
+        
+        card.style.display = show ? 'block' : 'none';
+    });
+}
+
 function displayAnalysisResults(results) {
    const container = document.getElementById('ai-analysis-results');
    container.innerHTML = ''; // 清空现有结果
@@ -558,6 +758,10 @@ function displayAnalysisResults(results) {
        const riskLevelClass = 
            analysis.risk_level === '高' ? 'risk-high' :
            analysis.risk_level === '中' ? 'risk-medium' : 'risk-low';
+            
+        const sentimentClass = 
+            analysis.sentiment === '积极' ? 'sentiment-positive' :
+            analysis.sentiment === '消极' ? 'sentiment-negative' : 'sentiment-neutral';
        
        card.innerHTML = `
            <div class="d-flex justify-content-between align-items-center">
@@ -567,8 +771,9 @@ function displayAnalysisResults(results) {
                </span>
            </div>
            <div class="mb-2">
-                <strong>情感倾向:</strong> ${analysis.sentiment}
-                <span class="ml-2">(${analysis.sentiment_score})</span>
+                <strong>情感倾向:</strong> 
+                <span class="sentiment-text">${analysis.sentiment}</span>
+                <span class="sentiment-score ${sentimentClass}">${analysis.sentiment_score}</span>
            </div>
            <div class="keywords-container">
                ${analysis.keywords.split(',').map(keyword => 
@@ -590,10 +795,28 @@ function displayAnalysisResults(results) {
        
        container.appendChild(card);
    });
+    
+    // 应用当前的过滤器
+    filterResults();
 }

-// 页面加载完成后自动请求一次AI分析
-document.addEventListener('DOMContentLoaded', requestAIAnalysis);
+function showError(message) {
+    alert(message);
+}
+
+// 设置事件监听器
+document.addEventListener('DOMContentLoaded', () => {
+    // 自动更新切换
+    document.getElementById('autoUpdate').addEventListener('change', setupAutoUpdate);
+    
+    // 过滤器变化监听
+    document.getElementById('keywordFilter').addEventListener('input', filterResults);
+    document.getElementById('sentimentFilter').addEventListener('change', filterResults);
+    document.getElementById('riskFilter').addEventListener('change', filterResults);
+    
+    // 首次加载时请求分析
+    requestAIAnalysis();
+});
 </script>

 {% endblock %}