Update readme.

+<div align="center">
+
+# 📊 Weibo Public Opinion Multi-Agent Analysis System
+
+<img src="static/image/logo_compressed.png" alt="Weibo Public Opinion Analysis System Logo" width="600">
+
+[![GitHub Stars](https://img.shields.io/github/stars/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/stargazers)
+[![GitHub Forks](https://img.shields.io/github/forks/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/network)
+[![GitHub Issues](https://img.shields.io/github/issues/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/issues)
+[![GitHub License](https://img.shields.io/github/license/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/blob/main/LICENSE)
+
+[English](./README-EN.md) | [中文文档](./README.md)
+
+</div>
+
+<div align="center">
+<img src="static/image/banner_compressed.png" alt="banner" width="800">
+</div>
+
+## 📝 Project Overview
+
+**Weibo Public Opinion Multi-Agent Analysis System** is an innovative public opinion analysis platform built from scratch, utilizing multi-agent collaborative architecture to provide accurate, real-time, and comprehensive Weibo public opinion monitoring and analysis services. The system achieves full-process automation from data collection and sentiment analysis to report generation through the collaboration of five specialized AI agents.
+
+### 🚀 Key Features
+
+- **Multi-Agent Collaborative Architecture**: 5 specialized agents working together to complete the full process of public opinion analysis
+- **Comprehensive Data Collection**: Integrating Weibo crawlers, news search, multimedia content, and other multi-dimensional data sources
+- **Deep Sentiment Analysis**: Precise multilingual sentiment recognition based on fine-tuned BERT/GPT-2/Qwen models
+- **Intelligent Report Generation**: Automatically generate structured HTML analysis reports with custom template support
+- **Agent Forum Communication**: ForumEngine provides information sharing and collaborative decision-making platform for agents
+- **High-Performance Asynchronous Processing**: Support concurrent processing of multiple public opinion tasks with real-time status monitoring
+- **Cloud Data Support**: Convenient cloud database service with 100,000+ daily real data
+
+## 🏗️ System Architecture
+
+### Overall Architecture Diagram
+
+```mermaid
+graph TB
+    subgraph "Frontend Display Layer"
+        UI[Web Interface<br/>Flask + Streamlit]
+    end
+    
+    subgraph "Multi-Agent Collaboration Layer"
+        QE[QueryEngine<br/>News Search Agent]
+        ME[MediaEngine<br/>Multimedia Search Agent]
+        IE[InsightEngine<br/>Deep Insight Agent]
+        RE[ReportEngine<br/>Report Generation Agent]
+        Forum[ForumEngine<br/>Agent Forum Communication Center]
+    end
+    
+    subgraph "Data Processing Layer"
+        MS[MindSpider<br/>Weibo Crawler System]
+        SA[SentimentAnalysis<br/>Sentiment Analysis Model Collection]
+        DB[(MySQL<br/>Database)]
+    end
+    
+    subgraph "External Service Layer"
+        LLM[LLM API<br/>DeepSeek/Kimi/Gemini]
+        Search[Search API<br/>Tavily/Bocha]
+    end
+    
+    UI --> QE
+    UI --> ME
+    UI --> IE
+    UI --> RE
+    
+    QE --> Search
+    ME --> Search
+    IE --> MS
+    IE --> SA
+    
+    QE --> LLM
+    ME --> LLM
+    IE --> LLM
+    RE --> LLM
+    
+    MS --> DB
+    SA --> DB
+    
+    %% Agent Forum Communication Mechanism
+    QE <--> Forum
+    ME <--> Forum
+    IE <--> Forum
+    RE <--> Forum
+```
+
+### Agent Collaboration Workflow
+
+The system's core workflow is based on multi-agent collaboration:
+
+1. **QueryEngine (News Query Agent)**: Uses Tavily API to search authoritative news reports, providing official information sources
+2. **MediaEngine (Multimedia Search Agent)**: Conducts multimodal content search through Bocha API to gather social media perspectives
+3. **InsightEngine (Deep Insight Agent)**: Queries local Weibo database, combines multiple sentiment analysis models for deep analysis
+4. **ForumEngine (Forum Monitoring Agent)**: Real-time monitoring of agent log outputs, extracts key information and promotes collaboration
+5. **ReportEngine (Report Generation Agent)**: Based on analysis results from all agents, uses Gemini LLM to generate comprehensive HTML reports
+
+### Project Code Structure
+
+```
+Weibo_PublicOpinion_AnalysisSystem/
+├── QueryEngine/                    # News Query Engine Agent
+│   ├── agent.py                   # Agent main logic
+│   ├── llms/                      # LLM interface wrapper
+│   ├── nodes/                     # Processing nodes
+│   ├── tools/                     # Search tools
+│   └── utils/                     # Utility functions
+├── MediaEngine/                    # Multimedia Search Engine Agent
+│   ├── agent.py                   # Agent main logic
+│   ├── llms/                      # LLM interfaces
+│   ├── tools/                     # Search tools
+│   └── ...                       # Other modules
+├── InsightEngine/                 # Data Insight Engine Agent
+│   ├── agent.py                   # Agent main logic
+│   ├── llms/                      # LLM interface wrapper
+│   │   ├── deepseek.py           # DeepSeek API
+│   │   ├── kimi.py               # Kimi API
+│   │   ├── openai_llm.py         # OpenAI format API
+│   │   └── base.py               # LLM base class
+│   ├── nodes/                     # Processing nodes
+│   │   ├── first_search_node.py  # First search node
+│   │   ├── reflection_node.py    # Reflection node
+│   │   ├── summary_nodes.py      # Summary nodes
+│   │   ├── search_node.py        # Search node
+│   │   ├── sentiment_node.py     # Sentiment analysis node
+│   │   └── insight_node.py       # Insight generation node
+│   ├── tools/                     # Database query and analysis tools
+│   │   ├── media_crawler_db.py   # Database query tool
+│   │   └── sentiment_analyzer.py # Sentiment analysis integration tool
+│   ├── state/                     # State management
+│   │   ├── __init__.py
+│   │   └── state.py              # Agent state definition
+│   ├── prompts/                   # Prompt templates
+│   │   ├── __init__.py
+│   │   └── prompts.py            # Various prompts
+│   └── utils/                     # Utility functions
+│       ├── __init__.py
+│       ├── config.py             # Configuration management
+│       └── helpers.py            # Helper functions
+├── ReportEngine/                  # Report Generation Engine Agent
+│   ├── agent.py                   # Agent main logic
+│   ├── llms/                      # LLM interfaces
+│   │   └── gemini.py             # Gemini API dedicated
+│   ├── nodes/                     # Report generation nodes
+│   │   ├── template_selection.py # Template selection node
+│   │   └── html_generation.py    # HTML generation node
+│   ├── report_template/           # Report template library
+│   │   ├── 社会公共热点事件分析.md
+│   │   ├── 商业品牌舆情监测.md
+│   │   └── ...                   # More templates
+│   └── flask_interface.py         # Flask API interface
+├── ForumEngine/                   # Forum Communication Engine Agent
+│   └── monitor.py                 # Log monitoring and forum management
+├── MindSpider/                    # Weibo Crawler System
+│   ├── main.py                    # Crawler main program
+│   ├── BroadTopicExtraction/      # Topic extraction module
+│   │   ├── get_today_news.py     # Today's news fetching
+│   │   └── topic_extractor.py    # Topic extractor
+│   ├── DeepSentimentCrawling/     # Deep sentiment crawling
+│   │   ├── MediaCrawler/         # Media crawler core
+│   │   └── platform_crawler.py  # Platform crawler management
+│   └── schema/                    # Database schema
+│       └── init_database.py      # Database initialization
+├── SentimentAnalysisModel/        # Sentiment Analysis Model Collection
+│   ├── WeiboSentiment_Finetuned/  # Fine-tuned BERT/GPT-2 models
+│   ├── WeiboMultilingualSentiment/ # Multilingual sentiment analysis
+│   ├── WeiboSentiment_SmallQwen/   # Small Qwen model
+│   └── WeiboSentiment_MachineLearning/ # Traditional machine learning methods
+├── SingleEngineApp/               # Individual Agent Streamlit apps
+│   ├── query_engine_streamlit_app.py
+│   ├── media_engine_streamlit_app.py
+│   └── insight_engine_streamlit_app.py
+├── templates/                     # Flask templates
+│   └── index.html                # Main interface template
+├── static/                        # Static resources
+├── logs/                         # Runtime log directory
+├── app.py                        # Flask main application entry
+├── config.py                     # Global configuration file
+└── requirements.txt              # Python dependency list
+```
+
+## 🚀 Quick Start
+
+### System Requirements
+
+- **Operating System**: Windows 10/11 (Linux/macOS also supported)
+- **Python Version**: 3.11+
+- **Conda**: Anaconda or Miniconda
+- **Database**: MySQL 8.0+ (or choose our cloud database service)
+- **Memory**: 8GB+ recommended
+
+### 1. Create Conda Environment
+
+```bash
+# Create conda environment named pytorch_python11
+conda create -n pytorch_python11 python=3.11
+conda activate pytorch_python11
+```
+
+### 2. Install Dependencies
+
+```bash
+# Install basic dependencies
+pip install -r requirements.txt
+
+# 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
+```
+
+### 3. Install Playwright Browser Drivers
+
+```bash
+# Install browser drivers (for crawler functionality)
+playwright install chromium
+```
+
+### 4. System Configuration
+
+#### 4.1 Configure API Keys
+
+Edit the `config.py` file and fill in your API keys:
+
+```python
+# MySQL Database Configuration
+DB_HOST = "localhost"
+DB_PORT = 3306
+DB_USER = "your_username"
+DB_PASSWORD = "your_password"
+DB_NAME = "weibo_analysis"
+DB_CHARSET = "utf8mb4"
+
+# DeepSeek API (Apply at: https://www.deepseek.com/)
+DEEPSEEK_API_KEY = "your_deepseek_api_key"
+
+# Tavily Search API (Apply at: https://www.tavily.com/)
+TAVILY_API_KEY = "your_tavily_api_key"
+
+# Kimi API (Apply at: https://www.kimi.com/)
+KIMI_API_KEY = "your_kimi_api_key"
+
+# Gemini API (Apply at: https://api.chataiapi.com/)
+GEMINI_API_KEY = "your_gemini_api_key"
+
+# Bocha Search API (Apply at: https://open.bochaai.com/)
+BOCHA_Web_Search_API_KEY = "your_bocha_api_key"
+
+# Silicon Flow API (Apply at: https://siliconflow.cn/)
+GUIJI_QWEN3_API_KEY = "your_guiji_api_key"
+```
+
+#### 4.2 Database Initialization
+
+**Option 1: Use Local Database**
+```bash
+# Local MySQL database initialization
+cd MindSpider
+python schema/init_database.py
+```
+
+**Option 2: Use Cloud Database Service (Recommended)**
+
+We provide convenient cloud database service with 100,000+ daily real Weibo data, currently **free application** during the promotion period!
+
+- Real Weibo data, updated in real-time
+- Pre-processed sentiment annotation data
+- Multi-dimensional tag classification
+- High-availability cloud service
+- Professional technical support
+
+**Contact us to apply for free cloud database access: 📧 670939375@qq.com**
+
+### 5. Launch System
+
+#### 5.1 Complete System Launch (Recommended)
+
+```bash
+# In project root directory, activate conda environment
+conda activate pytorch_python11
+
+# Start main application (automatically starts all agents)
+python app.py
+```
+
+Visit http://localhost:5000 to use the complete system
+
+#### 5.2 Launch Individual Agents
+
+```bash
+# Start QueryEngine
+streamlit run SingleEngineApp/query_engine_streamlit_app.py --server.port 8503
+
+# Start MediaEngine  
+streamlit run SingleEngineApp/media_engine_streamlit_app.py --server.port 8502
+
+# Start InsightEngine
+streamlit run SingleEngineApp/insight_engine_streamlit_app.py --server.port 8501
+```
+
+#### 5.3 Standalone Crawler System
+
+```bash
+# Enter crawler directory
+cd MindSpider
+
+# Project initialization
+python main.py --setup
+
+# Run complete crawler workflow
+python main.py --complete --date 2024-01-20
+
+# Run topic extraction only
+python main.py --broad-topic --date 2024-01-20
+
+# Run deep crawling only
+python main.py --deep-sentiment --platforms xhs dy wb
+```
+
+## 💾 Database Configuration
+
+### Local Database Configuration
+
+1. **Install MySQL 8.0+**
+2. **Create Database**:
+   ```sql
+   CREATE DATABASE weibo_analysis CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
+   ```
+3. **Run Initialization Script**:
+   ```bash
+   cd MindSpider
+   python schema/init_database.py
+   ```
+
+### Auto-Crawling Configuration
+
+Configure automatic crawling tasks for continuous data updates:
+
+```python
+# Configure crawler parameters in MindSpider/config.py
+CRAWLER_CONFIG = {
+    'max_pages': 200,         # Maximum pages to crawl
+    'delay': 1,               # Request delay (seconds)
+    'timeout': 30,            # Timeout (seconds)
+    'platforms': ['xhs', 'dy', 'wb', 'bili'],  # Crawling platforms
+    'daily_keywords': 100,    # Daily keywords count
+    'max_notes_per_keyword': 50,  # Max content per keyword
+    'use_proxy': False,       # Whether to use proxy
+}
+```
+
+### Cloud Database Service (Recommended)
+
+**Why Choose Our Cloud Database Service?**
+
+- **Rich Data Sources**: 100,000+ daily real Weibo data covering hot topics across all industries
+- **High-Quality Annotations**: Professional team manually annotated sentiment data with 95%+ accuracy
+- **Multi-Dimensional Analysis**: Including topic classification, sentiment tendency, influence scoring and other multi-dimensional tags
+- **Real-Time Updates**: 24/7 continuous data collection ensuring timeliness
+- **Technical Support**: Professional team providing technical support and customization services
+
+**Application Method**:
+📧 Email Contact: 670939375@qq.com
+📝 Email Subject: Apply for Weibo Public Opinion Cloud Database Access
+📝 Email Content: Please describe your use case and expected data volume requirements
+
+**Promotion Period Benefits**:
+- Free basic cloud database access
+- Free technical support and deployment guidance
+- Priority access to new features
+
+## ⚙️ Advanced Configuration
+
+### Modify Key Parameters
+
+#### Agent Configuration Parameters
+
+Each agent has dedicated configuration files that can be adjusted according to needs:
+
+```python
+# QueryEngine/utils/config.py
+class Config:
+    max_reflections = 2           # Reflection rounds
+    max_search_results = 15       # Maximum search results
+    max_content_length = 8000     # Maximum content length
+    
+# MediaEngine/utils/config.py  
+class Config:
+    comprehensive_search_limit = 10  # Comprehensive search limit
+    web_search_limit = 15           # Web search limit
+    
+# InsightEngine/utils/config.py
+class Config:
+    default_search_topic_globally_limit = 200    # Global search limit
+    default_get_comments_limit = 500             # Comment retrieval limit
+    max_search_results_for_llm = 50              # Max results for LLM
+```
+
+#### Sentiment Analysis Model Configuration
+
+```python
+# InsightEngine/tools/sentiment_analyzer.py
+SENTIMENT_CONFIG = {
+    'model_type': 'multilingual',     # Options: 'bert', 'multilingual', 'qwen'
+    'confidence_threshold': 0.8,      # Confidence threshold
+    'batch_size': 32,                 # Batch size
+    'max_sequence_length': 512,       # Max sequence length
+}
+```
+
+### Integrate Different LLM Models
+
+The system supports multiple LLM providers, switchable in each agent's configuration:
+
+```python
+# Configure in each Engine's utils/config.py
+class Config:
+    default_llm_provider = "deepseek"  # Options: "deepseek", "openai", "kimi", "gemini"
+    
+    # DeepSeek configuration
+    deepseek_api_key = "your_api_key"
+    deepseek_model = "deepseek-chat"
+    
+    # OpenAI compatible configuration
+    openai_api_key = "your_api_key"
+    openai_model = "gpt-3.5-turbo"
+    openai_base_url = "https://api.openai.com/v1"
+    
+    # Kimi configuration
+    kimi_api_key = "your_api_key"  
+    kimi_model = "moonshot-v1-8k"
+    
+    # Gemini configuration
+    gemini_api_key = "your_api_key"
+    gemini_model = "gemini-pro"
+```
+
+### Change Sentiment Analysis Models
+
+The system integrates multiple sentiment analysis methods, selectable based on needs:
+
+#### 1. BERT-based Fine-tuned Model (Highest Accuracy)
+
+```bash
+# Use BERT Chinese model
+cd SentimentAnalysisModel/WeiboSentiment_Finetuned/BertChinese-Lora
+python predict.py --text "This product is really great"
+```
+
+#### 2. GPT-2 LoRA Fine-tuned Model (Faster Speed)
+
+```bash
+cd SentimentAnalysisModel/WeiboSentiment_Finetuned/GPT2-Lora
+python predict.py --text "I'm not feeling great today"
+```
+
+#### 3. Small Qwen Model (Balanced)
+
+```bash
+cd SentimentAnalysisModel/WeiboSentiment_SmallQwen
+python predict_universal.py --text "This event was very successful"
+```
+
+#### 4. Traditional Machine Learning Methods (Lightweight)
+
+```bash
+cd SentimentAnalysisModel/WeiboSentiment_MachineLearning
+python predict.py --model_type "svm" --text "Service attitude needs improvement"
+```
+
+#### 5. Multilingual Sentiment Analysis (Supports 22 Languages)
+
+```bash
+cd SentimentAnalysisModel/WeiboMultilingualSentiment
+python predict.py --text "This product is amazing!" --lang "en"
+```
+
+### Integrate Custom Business Database
+
+#### 1. Modify Database Connection Configuration
+
+```python
+# Add your business database configuration in config.py
+BUSINESS_DB_HOST = "your_business_db_host"
+BUSINESS_DB_PORT = 3306
+BUSINESS_DB_USER = "your_business_user"
+BUSINESS_DB_PASSWORD = "your_business_password"
+BUSINESS_DB_NAME = "your_business_database"
+```
+
+#### 2. Create Custom Data Access Tools
+
+```python
+# InsightEngine/tools/custom_db_tool.py
+class CustomBusinessDBTool:
+    """Custom business database query tool"""
+    
+    def __init__(self):
+        self.connection_config = {
+            'host': config.BUSINESS_DB_HOST,
+            'port': config.BUSINESS_DB_PORT,
+            'user': config.BUSINESS_DB_USER,
+            'password': config.BUSINESS_DB_PASSWORD,
+            'database': config.BUSINESS_DB_NAME,
+        }
+    
+    def search_business_data(self, query: str, table: str):
+        """Query business data"""
+        # Implement your business logic
+        pass
+    
+    def get_customer_feedback(self, product_id: str):
+        """Get customer feedback data"""
+        # Implement customer feedback query logic
+        pass
+```
+
+#### 3. Integrate into InsightEngine
+
+```python
+# Integrate custom tools in InsightEngine/agent.py
+from .tools.custom_db_tool import CustomBusinessDBTool
+
+class DeepSearchAgent:
+    def __init__(self, config=None):
+        # ... other initialization code
+        self.custom_db_tool = CustomBusinessDBTool()
+    
+    def execute_custom_search(self, query: str):
+        """Execute custom business data search"""
+        return self.custom_db_tool.search_business_data(query, "your_table")
+```
+
+### Custom Report Templates
+
+#### 1. Create Template Files
+
+Create new Markdown templates in the `ReportEngine/report_template/` directory:
+
+```markdown
+<!-- Enterprise Brand Monitoring Report.md -->
+# Enterprise Brand Public Opinion Monitoring Report
+
+## 📊 Executive Summary
+{executive_summary}
+
+## 🔍 Brand Mention Analysis
+### Mention Volume Trends
+{mention_trend}
+
+### Sentiment Distribution
+{sentiment_distribution}
+
+## 📈 Competitor Analysis
+{competitor_analysis}
+
+## 🎯 Key Insights Summary
+{key_insights}
+
+## ⚠️ Risk Alerts
+{risk_alerts}
+
+## 📋 Improvement Recommendations
+{recommendations}
+
+---
+*Report Type: Enterprise Brand Public Opinion Monitoring*  
+*Generation Time: {generation_time}*  
+*Data Sources: {data_sources}*
+```
+
+#### 2. Use in Web Interface
+
+The system supports uploading custom template files (.md or .txt format), selectable when generating reports.
+
+## 🤝 Contributing Guide
+
+We welcome all forms of contributions!
+
+### How to Contribute
+
+1. **Fork the project** to your GitHub account
+2. **Create Feature branch**: `git checkout -b feature/AmazingFeature`
+3. **Commit changes**: `git commit -m 'Add some AmazingFeature'`
+4. **Push to branch**: `git push origin feature/AmazingFeature`
+5. **Open Pull Request**
+
+### Contribution Types
+
+- 🐛 Bug fixes
+- ✨ New feature development
+- 📚 Documentation improvements
+- 🎨 UI/UX improvements
+- ⚡ Performance optimization
+- 🧪 Test case additions
+
+### Development Standards
+
+- Code follows PEP8 standards
+- Commit messages use clear Chinese/English descriptions
+- New features need corresponding test cases
+- Update related documentation
+
+## 📄 License
+
+This project is licensed under the [MIT License](LICENSE). Please see the LICENSE file for details.
+
+## 🎉 Support & Contact
+
+### Get Help
+
+- **Project Homepage**: [GitHub Repository](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem)
+- **Issue Reporting**: [Issues Page](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/issues)
+- **Feature Requests**: [Discussions Page](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/discussions)
+
+### Contact Information
+
+- 📧 **Email**: 670939375@qq.com
+- 💬 **QQ Group**: [Join Technical Discussion Group]
+- 🐦 **WeChat**: [Scan QR Code for Technical Support]
+
+### Business Cooperation
+
+- 🏢 **Enterprise Custom Development**
+- 📊 **Big Data Services**
+- 🎓 **Academic Collaboration**
+- 💼 **Technical Training**
+
+### Cloud Service Application
+
+**Free Cloud Database Service Application**:
+📧 Send email to: 670939375@qq.com  
+📝 Subject: Weibo Public Opinion Cloud Database Application  
+📝 Description: Your use case and requirements  
+
+## 👥 Contributors
+
+Thanks to these excellent contributors:
+
+[![Contributors](https://contrib.rocks/image?repo=666ghj/Weibo_PublicOpinion_AnalysisSystem)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/graphs/contributors)
+
+---
+
+<div align="center">
+
+**⭐ If this project helps you, please give us a star!**
+
+Made with ❤️ by [Weibo Public Opinion Analysis Team](https://github.com/666ghj)
+
+</div>

 <div align="center">
 <div align="center">
 
 
-  <!-- # 📊 Weibo Public Opinion Analysis System  -->
+<img src="static/image/logo_compressed.png" alt="Weibo Public Opinion Analysis System Logo" width="600">
 
 
-  <img src="https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/blob/main/static/image/logo_compressed.png" alt="Weibo Public Opinion Analysis System Logo" width="800">
+# 微舆 - 致力于打造简洁通用的舆情分析平台
 
 
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-  [![GitHub Contributors](https://img.shields.io/github/contributors/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/graphs/contributors)
-  [![GitHub License](https://img.shields.io/github/license/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/blob/main/LICENSE)
+[![GitHub Stars](https://img.shields.io/github/stars/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/stargazers)
+[![GitHub Forks](https://img.shields.io/github/forks/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/network)
+[![GitHub Issues](https://img.shields.io/github/issues/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/issues)
+[![GitHub License](https://img.shields.io/github/license/666ghj/Weibo_PublicOpinion_AnalysisSystem?style=flat-square)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/blob/main/LICENSE)
+
+[English](./README-EN.md) | [中文文档](./README.md)
 
 
 </div>
 </div>
 
 
 <div align="center">
 <div align="center">
-<img src="https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/blob/main/static/image/banner_compressed.png" alt="banner" width="800">
+<img src="static/image/system_schematic.png" alt="banner" width="800">
 </div>
 </div>
 
 
-## 项目概述
+## 📝 项目概述
 
 
-**Weibo舆情分析多智能体系统** 是一个从零构建的创新型舆情分析平台，采用多Agent协作架构，致力于提供准确、实时、全面的微博舆情监测与分析服务。系统通过多个专门化的AI Agent协同工作，实现了从数据采集、情感分析到报告生成的全流程自动化。
+**微博舆情分析多智能体系统**是一个从零构建的创新型舆情分析平台，采用多Agent协作架构，致力于提供准确、实时、全面的微博舆情监测与分析服务。系统通过五个专门化的AI Agent协同工作，实现了从数据采集、情感分析到报告生成的全流程自动化。
 
 
-### 核心特色
+### 🚀 核心亮点
 
 
-- **多智能体协作架构**：5个专门化Agent协同工作，各司其职
-- **全方位数据采集**：整合微博爬虫、新闻搜索、网络信息多维度数据源
-- **深度情感分析**：基于微调BERT/GPT-2/Qwen模型的精准情感识别
-- **智能报告生成**：自动生成结构化HTML分析报告
-- **Agent论坛交流**：Forum Engine提供Agent间信息共享和协作决策平台
-- **高性能异步处理**：支持并发处理多个舆情任务
+- **多智能体协作架构**：5个专门化Agent各司其职，协同工作完成舆情分析全流程
+- **全方位数据采集**：整合微博爬虫、新闻搜索、多媒体内容等多维度数据源
+- **深度情感分析**：基于微调BERT/GPT-2/Qwen模型的精准多语言情感识别
+- **智能报告生成**：自动生成结构化HTML分析报告，支持自定义模板
+- **Agent论坛交流**：ForumEngine提供Agent间信息共享和协作决策平台
+- **高性能异步处理**：支持并发处理多个舆情任务，实时状态监控
+- **云端数据支持**：提供便捷云数据库服务，日均10万+真实数据
 
 
-## 系统架构
+## 🏗️ 系统架构
 
 
 ### 整体架构图
 ### 整体架构图
 
 
@@ -49,7 +51,7 @@ graph TB
     
     
     subgraph "数据处理层"
     subgraph "数据处理层"
         MS[MindSpider<br/>微博爬虫系统]
         MS[MindSpider<br/>微博爬虫系统]
-        SA[SentimentAnalysis<br/>情感分析模型]
+        SA[SentimentAnalysis<br/>情感分析模型集合]
         DB[(MySQL<br/>数据库)]
         DB[(MySQL<br/>数据库)]
     end
     end
     
     
@@ -81,129 +83,110 @@ graph TB
     ME <--> Forum
     ME <--> Forum
     IE <--> Forum
     IE <--> Forum
     RE <--> Forum
     RE <--> Forum
-    
-    style UI fill:#e1f5fe
-    style QE fill:#fff3e0
-    style ME fill:#fff3e0
-    style IE fill:#fff3e0
-    style RE fill:#f3e5f5
-    style Forum fill:#e8f5e9
-    style MS fill:#fce4ec
-    style SA fill:#fce4ec
-    style DB fill:#fff9c4
-    style LLM fill:#e3f2fd
-    style Search fill:#e3f2fd
 ```
 ```
 
 
-### 数据流程图
+### Agent协作流程
 
 
-```mermaid
-sequenceDiagram
-    participant User as 用户
-    participant UI as Web界面
-    participant QE as QueryEngine
-    participant ME as MediaEngine
-    participant IE as InsightEngine
-    participant Forum as ForumEngine
-    participant RE as ReportEngine
-    participant DB as 数据库
-    
-    User->>UI: 输入查询关键词
-    UI->>QE: 发起搜索请求
-    UI->>ME: 发起搜索请求
-    UI->>IE: 发起搜索请求
-    
-    Note over QE,IE: Agent执行前先读取论坛信息
-    QE->>Forum: 读取论坛交流信息
-    ME->>Forum: 读取论坛交流信息
-    IE->>Forum: 读取论坛交流信息
-    
-    par 并行处理与持续思维链交流
-        Note over QE: 结构思考→反思搜索→持续交流
-        QE->>QE: 确定新闻搜索结构
-        QE->>Forum: 思维链交流(结构思考)
-        QE->>QE: 多步反思与搜索分析
-        QE->>Forum: 思维链交流(搜索进展)
-        QE->>QE: 生成汇总报告
-        QE->>Forum: 思维链交流(关键发现)
-    and
-        Note over ME: 结构思考→反思搜索→持续交流
-        ME->>ME: 确定多媒体搜索结构
-        ME->>Forum: 思维链交流(结构思考)
-        ME->>ME: 多步反思与搜索分析
-        ME->>Forum: 思维链交流(搜索进展)
-        ME->>ME: 生成汇总报告
-        ME->>Forum: 思维链交流(关键发现)
-    and
-        Note over IE: 结构思考→反思搜索→持续交流
-        IE->>IE: 确定洞察分析结构
-        IE->>Forum: 思维链交流(结构思考)
-        IE->>DB: 查询微博数据
-        IE->>IE: 多步反思与情感洞察
-        IE->>Forum: 思维链交流(洞察进展)
-        IE->>IE: 生成汇总报告
-        IE->>Forum: 思维链交流(关键发现)
-    end
+系统核心工作流程基于多Agent协作模式：
 
 
-    Note over Forum: 论坛汇总Agent交流信息
-    Forum->>RE: 触发报告生成
-    RE->>Forum: 读取所有Agent的交流信息
-    RE->>QE: 获取QueryEngine汇总报告
-    RE->>ME: 获取MediaEngine汇总报告
-    RE->>IE: 获取InsightEngine汇总报告
-    
-    Note over RE: ReportEngine智能报告生成
-    RE->>RE: 读取模板库与样式库并选择
-    RE->>RE: 分步思考生成报告各部分
-    RE->>RE: 整合生成最终报告
-    RE->>UI: 生成综合HTML报告
-    UI->>User: 展示分析结果
-```
+1. **QueryEngine（新闻查询Agent）**：使用Tavily API搜索权威新闻报道，提供官方信息源
+2. **MediaEngine（多媒体搜索Agent）**：通过Bocha API进行多模态内容搜索，获取社交媒体观点
+3. **InsightEngine（深度洞察Agent）**：查询本地微博数据库，结合多种情感分析模型进行深度分析
+4. **ForumEngine（论坛监控Agent）**：实时监控各Agent日志输出，提取关键信息并促进协作
+5. **ReportEngine（报告生成Agent）**：基于所有Agent的分析结果，使用Gemini LLM生成综合HTML报告
 
 
-## 项目结构
+### 项目代码结构
 
 
 ```
 ```
 Weibo_PublicOpinion_AnalysisSystem/
 Weibo_PublicOpinion_AnalysisSystem/
-├── QueryEngine/              # web查询引擎Agent
+├── QueryEngine/                    # 新闻查询引擎Agent
 │   ├── agent.py                   # Agent主逻辑
 │   ├── agent.py                   # Agent主逻辑
 │   ├── llms/                      # LLM接口封装
 │   ├── llms/                      # LLM接口封装
 │   ├── nodes/                     # 处理节点
 │   ├── nodes/                     # 处理节点
 │   ├── tools/                     # 搜索工具
 │   ├── tools/                     # 搜索工具
 │   └── utils/                     # 工具函数
 │   └── utils/                     # 工具函数
-├── MediaEngine/              # 媒体引擎Agent
-│   └── (类似结构)
-├── InsightEngine/            # 数据库引擎Agent
-│   └── (类似结构)
-├── ReportEngine/             # 报告生成Agent
-│   ├── report_template/     # 报告模板
-│   └── flask_interface.py   # API接口
-├── ForumEgine/              # 论坛交流Agent
-│   └── monitor.py           # 论坛交流管理器
+├── MediaEngine/                    # 多媒体搜索引擎Agent
+│   ├── agent.py                   # Agent主逻辑
+│   ├── llms/                      # LLM接口
+│   ├── tools/                     # 搜索工具
+│   └── ...                       # 其他模块
+├── InsightEngine/                 # 数据洞察引擎Agent
+│   ├── agent.py                   # Agent主逻辑
+│   ├── llms/                      # LLM接口封装
+│   │   ├── deepseek.py           # DeepSeek API
+│   │   ├── kimi.py               # Kimi API
+│   │   ├── openai_llm.py         # OpenAI格式API
+│   │   └── base.py               # LLM基类
+│   ├── nodes/                     # 处理节点
+│   │   ├── first_search_node.py  # 首次搜索节点
+│   │   ├── reflection_node.py    # 反思节点
+│   │   ├── summary_nodes.py      # 总结节点
+│   │   ├── search_node.py        # 搜索节点
+│   │   ├── sentiment_node.py     # 情感分析节点
+│   │   └── insight_node.py       # 洞察生成节点
+│   ├── tools/                     # 数据库查询和分析工具
+│   │   ├── media_crawler_db.py   # 数据库查询工具
+│   │   └── sentiment_analyzer.py # 情感分析集成工具
+│   ├── state/                     # 状态管理
+│   │   ├── __init__.py
+│   │   └── state.py              # Agent状态定义
+│   ├── prompts/                   # 提示词模板
+│   │   ├── __init__.py
+│   │   └── prompts.py            # 各类提示词
+│   └── utils/                     # 工具函数
+│       ├── __init__.py
+│       ├── config.py             # 配置管理
+│       └── helpers.py            # 辅助函数
+├── ReportEngine/                  # 报告生成引擎Agent
+│   ├── agent.py                   # Agent主逻辑
+│   ├── llms/                      # LLM接口
+│   │   └── gemini.py             # Gemini API专用
+│   ├── nodes/                     # 报告生成节点
+│   │   ├── template_selection.py # 模板选择节点
+│   │   └── html_generation.py    # HTML生成节点
+│   ├── report_template/           # 报告模板库
+│   │   ├── 社会公共热点事件分析.md
+│   │   ├── 商业品牌舆情监测.md
+│   │   └── ...                   # 更多模板
+│   └── flask_interface.py         # Flask API接口
+├── ForumEngine/                   # 论坛交流引擎Agent
+│   └── monitor.py                 # 日志监控和论坛管理
 ├── MindSpider/                    # 微博爬虫系统
 ├── MindSpider/                    # 微博爬虫系统
-│   ├── BroadTopicExtraction/   # 话题提取
-│   ├── DeepSentimentCrawling/  # 深度爬取
+│   ├── main.py                    # 爬虫主程序
+│   ├── BroadTopicExtraction/      # 话题提取模块
+│   │   ├── get_today_news.py     # 今日新闻获取
+│   │   └── topic_extractor.py    # 话题提取器
+│   ├── DeepSentimentCrawling/     # 深度情感爬取
+│   │   ├── MediaCrawler/         # 媒体爬虫核心
+│   │   └── platform_crawler.py  # 平台爬虫管理
 │   └── schema/                    # 数据库结构
 │   └── schema/                    # 数据库结构
-├── SentimentAnalysisModel/   # 情感分析模型
-│   ├── BertTopicDetection_Finetuned/
-│   ├── WeiboSentiment_Finetuned/
-│   └── WeiboSentiment_MachineLearning/
-├── SingleEngineApp/         # Streamlit应用
+│       └── init_database.py      # 数据库初始化
+├── SentimentAnalysisModel/        # 情感分析模型集合
+│   ├── WeiboSentiment_Finetuned/  # 微调BERT/GPT-2模型
+│   ├── WeiboMultilingualSentiment/ # 多语言情感分析
+│   ├── WeiboSentiment_SmallQwen/   # 小型Qwen模型
+│   └── WeiboSentiment_MachineLearning/ # 传统机器学习方法
+├── SingleEngineApp/               # 单独Agent的Streamlit应用
+│   ├── query_engine_streamlit_app.py
+│   ├── media_engine_streamlit_app.py
+│   └── insight_engine_streamlit_app.py
 ├── templates/                     # Flask模板
 ├── templates/                     # Flask模板
+│   └── index.html                # 主界面模板
 ├── static/                        # 静态资源
 ├── static/                        # 静态资源
-├── logs/                    # 运行日志
-├── app.py                   # 主应用入口
-├── config.py                # 配置文件
-└── requirements.txt         # 依赖包
+├── logs/                         # 运行日志目录
+├── app.py                        # Flask主应用入口
+├── config.py                     # 全局配置文件
+└── requirements.txt              # Python依赖包清单
 ```
 ```
 
 
-## 快速开始
+## 🚀 快速开始
 
 
 ### 环境要求
 ### 环境要求
 
 
-- **操作系统**: Windows 10/11
+- **操作系统**: Windows 10/11（Linux/macOS也支持）
 - **Python版本**: 3.11+
 - **Python版本**: 3.11+
 - **Conda**: Anaconda或Miniconda
 - **Conda**: Anaconda或Miniconda
-- **数据库**: MySQL 8.0+
+- **数据库**: MySQL 8.0+（可选择我们的云数据库服务）
 - **内存**: 建议8GB以上
 - **内存**: 建议8GB以上
 
 
 ### 1. 创建Conda环境
 ### 1. 创建Conda环境
@@ -220,14 +203,14 @@ conda activate pytorch_python11
 # 基础依赖安装
 # 基础依赖安装
 pip install -r requirements.txt
 pip install -r requirements.txt
 
 
-# 如果需要情感分析功能，安装PyTorch（根据CUDA版本选择）
+# 如果需要本地情感分析功能，安装PyTorch
 # CPU版本
 # CPU版本
 pip install torch torchvision torchaudio
 pip install torch torchvision torchaudio
 
 
-# CUDA 11.8版本
+# CUDA 11.8版本（如有GPU）
 pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
 pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
 
 
-# 安装transformers（用于BERT/GPT模型）
+# 安装transformers等AI相关依赖
 pip install transformers scikit-learn xgboost
 pip install transformers scikit-learn xgboost
 ```
 ```
 
 
@@ -272,16 +255,30 @@ BOCHA_Web_Search_API_KEY = "your_bocha_api_key"
 GUIJI_QWEN3_API_KEY = "your_guiji_api_key"
 GUIJI_QWEN3_API_KEY = "your_guiji_api_key"
 ```
 ```
 
 
-#### 4.2 初始化数据库
+#### 4.2 数据库初始化
 
 
+**选择1：使用本地数据库**
 ```bash
 ```bash
+# 本地MySQL数据库初始化
 cd MindSpider
 cd MindSpider
 python schema/init_database.py
 python schema/init_database.py
 ```
 ```
 
 
+**选择2：使用云数据库服务（推荐）**
+
+我们提供便捷的云数据库服务，包含日均10万+真实微博数据，目前推广期间**免费申请**！
+
+- 真实微博数据，实时更新
+- 预处理的情感标注数据
+- 多维度标签分类
+- 高可用云端服务
+- 专业技术支持
+
+**联系我们申请免费云数据库访问：📧 670939375@qq.com**
+
 ### 5. 启动系统
 ### 5. 启动系统
 
 
-#### 方式一：完整系统启动（推荐）
+#### 5.1 完整系统启动（推荐）
 
 
 ```bash
 ```bash
 # 在项目根目录下，激活conda环境
 # 在项目根目录下，激活conda环境
@@ -291,9 +288,9 @@ conda activate pytorch_python11
 python app.py
 python app.py
 ```
 ```
 
 
-访问 http://localhost:5000 即可使用系统
+访问 http://localhost:5000 即可使用完整系统
 
 
-#### 方式二：单独启动某个Agent
+#### 5.2 单独启动某个Agent
 
 
 ```bash
 ```bash
 # 启动QueryEngine
 # 启动QueryEngine
@@ -306,147 +303,353 @@ streamlit run SingleEngineApp/media_engine_streamlit_app.py --server.port 8502
 streamlit run SingleEngineApp/insight_engine_streamlit_app.py --server.port 8501
 streamlit run SingleEngineApp/insight_engine_streamlit_app.py --server.port 8501
 ```
 ```
 
 
-## 使用指南
+#### 5.3 爬虫系统单独使用
+
+```bash
+# 进入爬虫目录
+cd MindSpider
+
+# 项目初始化
+python main.py --setup
+
+# 运行完整爬虫流程
+python main.py --complete --date 2024-01-20
 
 
-### 基础使用流程
+# 仅运行话题提取
+python main.py --broad-topic --date 2024-01-20
 
 
-1. **启动系统**：运行 `python app.py`，系统会自动启动所有Agent
+# 仅运行深度爬取
+python main.py --deep-sentiment --platforms xhs dy wb
+```
 
 
-2. **输入查询**：在Web界面搜索框输入要分析的舆情关键词
+## 💾 数据库配置
 
 
-3. **Agent协作**：
-   - QueryEngine：搜索新闻和官方报道，将关键发现发布到论坛
-   - MediaEngine：搜索多媒体内容，与其他Agent分享重要信息
-   - InsightEngine：分析微博数据和情感，在论坛中交流洞察
-   - ForumEngine：提供Agent间交流平台，汇总协作信息
+### 本地数据库配置
 
 
-4. **查看结果**：
-   - Agent论坛交流：查看Agent间的实时信息交换
-   - 分析报告：查看基于Agent协作的综合HTML报告
+1. **安装MySQL 8.0+**
+2. **创建数据库**：
+   ```sql
+   CREATE DATABASE weibo_analysis CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
+   ```
+3. **运行初始化脚本**：
+   ```bash
+   cd MindSpider
+   python schema/init_database.py
+   ```
 
 
-### 高级配置
+### 自动爬取配置
 
 
-#### 配置爬虫系统
+配置自动爬取任务，实现数据的持续更新：
 
 
-1. **配置爬虫参数**：
 ```python
 ```python
-# MindSpider/config.py
+# MindSpider/config.py 中配置爬虫参数
 CRAWLER_CONFIG = {
 CRAWLER_CONFIG = {
-    'max_pages': 100,        # 最大爬取页数
+    'max_pages': 200,         # 最大爬取页数
     'delay': 1,               # 请求延迟（秒）
     'delay': 1,               # 请求延迟（秒）
     'timeout': 30,            # 超时时间（秒）
     'timeout': 30,            # 超时时间（秒）
+    'platforms': ['xhs', 'dy', 'wb', 'bili'],  # 爬取平台
+    'daily_keywords': 100,    # 每日关键词数量
+    'max_notes_per_keyword': 50,  # 每关键词最大内容数
     'use_proxy': False,       # 是否使用代理
     'use_proxy': False,       # 是否使用代理
 }
 }
 ```
 ```
 
 
-2. **运行爬虫**：
-```bash
-cd MindSpider
-python main.py --topic "话题关键词" --days 7
-```
+### 云数据库服务（推荐）
+
+**为什么选择我们的云数据库服务？**
+
+- **丰富数据源**：日均10万+真实微博数据，涵盖各行业热点话题
+- **高质量标注**：专业团队人工标注的情感数据，准确率95%+
+- **多维度分析**：包含话题分类、情感倾向、影响力评分等多维标签
+- **实时更新**：24小时不间断数据采集，确保时效性
+- **技术支持**：专业团队提供技术支持和定制化服务
+
+**申请方式**：
+📧 邮件联系：670939375@qq.com
+📝 邮件标题：申请微博舆情云数据库访问
+📝 邮件内容：请说明您的使用场景和预期数据量需求
+
+**推广期福利**：
+- 免费提供基础版云数据库访问
+- 免费技术支持和部署指导
+- 优先体验新功能特性
+
+## ⚙️ 高级配置
 
 
-#### 配置情感分析模型
+### 修改关键参数
 
 
-1. **选择模型**：
-   - BERT微调模型（精度高）
-   - GPT-2 LoRA（速度快）
-   - Qwen小模型（平衡型）
-   - 机器学习基线（轻量级）
+#### Agent配置参数
+
+每个Agent都有专门的配置文件，可根据需求调整：
+
+```python
+# QueryEngine/utils/config.py
+class Config:
+    max_reflections = 2           # 反思轮次
+    max_search_results = 15       # 最大搜索结果数
+    max_content_length = 8000     # 最大内容长度
+    
+# MediaEngine/utils/config.py  
+class Config:
+    comprehensive_search_limit = 10  # 综合搜索限制
+    web_search_limit = 15           # 网页搜索限制
+    
+# InsightEngine/utils/config.py
+class Config:
+    default_search_topic_globally_limit = 200    # 全局搜索限制
+    default_get_comments_limit = 500             # 评论获取限制
+    max_search_results_for_llm = 50              # 传给LLM的最大结果数
+```
+
+#### 情感分析模型配置
 
 
-2. **模型切换**：
 ```python
 ```python
 # InsightEngine/tools/sentiment_analyzer.py
 # InsightEngine/tools/sentiment_analyzer.py
-MODEL_TYPE = "bert"  # 可选: "bert", "gpt2", "qwen", "ml"
+SENTIMENT_CONFIG = {
+    'model_type': 'multilingual',     # 可选: 'bert', 'multilingual', 'qwen'
+    'confidence_threshold': 0.8,      # 置信度阈值
+    'batch_size': 32,                 # 批处理大小
+    'max_sequence_length': 512,       # 最大序列长度
+}
 ```
 ```
 
 
-#### 自定义报告模板
+### 接入不同的LLM模型
 
 
-在 `ReportEngine/report_template/` 目录下创建新模板：
+系统支持多种LLM提供商，可在各Agent的配置中切换：
 
 
-```markdown
-# 自定义报告模板
-## 舆情概览
-${overview}
+```python
+# 在各Engine的utils/config.py中配置
+class Config:
+    default_llm_provider = "deepseek"  # 可选: "deepseek", "openai", "kimi", "gemini"
+    
+    # DeepSeek配置
+    deepseek_api_key = "your_api_key"
+    deepseek_model = "deepseek-chat"
+    
+    # OpenAI兼容配置
+    openai_api_key = "your_api_key"
+    openai_model = "gpt-3.5-turbo"
+    openai_base_url = "https://api.openai.com/v1"
+    
+    # Kimi配置
+    kimi_api_key = "your_api_key"  
+    kimi_model = "moonshot-v1-8k"
+    
+    # Gemini配置
+    gemini_api_key = "your_api_key"
+    gemini_model = "gemini-pro"
+```
 
 
-## 情感分析
-${sentiment_analysis}
+### 更改情感分析模型
 
 
-## 关键观点
-${key_insights}
+系统集成了多种情感分析方法，可根据需求选择：
 
 
-## 趋势预测
-${trend_prediction}
+#### 1. 基于BERT的微调模型（精度最高）
+
+```bash
+# 使用BERT中文模型
+cd SentimentAnalysisModel/WeiboSentiment_Finetuned/BertChinese-Lora
+python predict.py --text "这个产品真的很不错"
 ```
 ```
 
 
-### 监控与日志
+#### 2. GPT-2 LoRA微调模型（速度较快）
 
 
-#### 查看系统日志
+```bash
+cd SentimentAnalysisModel/WeiboSentiment_Finetuned/GPT2-Lora
+python predict.py --text "今天心情不太好"
+```
 
 
-所有日志文件位于 `logs/` 目录：
-- `query.log`: QueryEngine运行日志
-- `media.log`: MediaEngine运行日志  
-- `insight.log`: InsightEngine运行日志
-- `forum.log`: ForumEngine论坛交流日志
-- `report.log`: ReportEngine生成日志
+#### 3. 小型Qwen模型（平衡型）
 
 
-#### Agent论坛交流
+```bash
+cd SentimentAnalysisModel/WeiboSentiment_SmallQwen
+python predict_universal.py --text "这次活动办得很成功"
+```
 
 
-ForumEngine提供多Agent协作交流功能：
-1. Agent行动前读取论坛交流信息
-2. Agent思考后决定是否分享关键发现
-3. 汇总所有Agent的交流信息
-4. 为ReportEngine提供协作数据基础
+#### 4. 传统机器学习方法（轻量级）
 
 
-## 故障排除
+```bash
+cd SentimentAnalysisModel/WeiboSentiment_MachineLearning
+python predict.py --model_type "svm" --text "服务态度需要改进"
+```
 
 
-### 常见问题
+#### 5. 多语言情感分析（支持22种语言）
 
 
-#### 1. 端口占用
 ```bash
 ```bash
-# 查看端口占用（Windows）
-netstat -ano | findstr :5000
-netstat -ano | findstr :8501
+cd SentimentAnalysisModel/WeiboMultilingualSentiment
+python predict.py --text "This product is amazing!" --lang "en"
+```
+
+### 接入自定义业务数据库
+
+#### 1. 修改数据库连接配置
 
 
-# 结束占用进程
-taskkill /F /PID <进程ID>
+```python
+# config.py 中添加您的业务数据库配置
+BUSINESS_DB_HOST = "your_business_db_host"
+BUSINESS_DB_PORT = 3306
+BUSINESS_DB_USER = "your_business_user"
+BUSINESS_DB_PASSWORD = "your_business_password"
+BUSINESS_DB_NAME = "your_business_database"
 ```
 ```
 
 
-#### 2. 编码问题
+#### 2. 创建自定义数据访问工具
+
 ```python
 ```python
-# 在代码开头添加
-import sys
-import os
-os.environ['PYTHONIOENCODING'] = 'utf-8'
-os.environ['PYTHONUTF8'] = '1'
+# InsightEngine/tools/custom_db_tool.py
+class CustomBusinessDBTool:
+    """自定义业务数据库查询工具"""
+    
+    def __init__(self):
+        self.connection_config = {
+            'host': config.BUSINESS_DB_HOST,
+            'port': config.BUSINESS_DB_PORT,
+            'user': config.BUSINESS_DB_USER,
+            'password': config.BUSINESS_DB_PASSWORD,
+            'database': config.BUSINESS_DB_NAME,
+        }
+    
+    def search_business_data(self, query: str, table: str):
+        """查询业务数据"""
+        # 实现您的业务逻辑
+        pass
+    
+    def get_customer_feedback(self, product_id: str):
+        """获取客户反馈数据"""
+        # 实现客户反馈查询逻辑
+        pass
 ```
 ```
 
 
-#### 3. Playwright安装失败
-```bash
-# 手动安装
-python -m playwright install chromium --with-deps
+#### 3. 集成到InsightEngine
+
+```python
+# InsightEngine/agent.py 中集成自定义工具
+from .tools.custom_db_tool import CustomBusinessDBTool
+
+class DeepSearchAgent:
+    def __init__(self, config=None):
+        # ... 其他初始化代码
+        self.custom_db_tool = CustomBusinessDBTool()
+    
+    def execute_custom_search(self, query: str):
+        """执行自定义业务数据搜索"""
+        return self.custom_db_tool.search_business_data(query, "your_table")
+```
+
+### 自定义报告模板
+
+#### 1. 创建模板文件
+
+在 `ReportEngine/report_template/` 目录下创建新的Markdown模板：
+
+```markdown
+<!-- 企业品牌监测报告.md -->
+# 企业品牌舆情监测报告
+
+## 📊 执行摘要
+{executive_summary}
+
+## 🔍 品牌提及分析
+### 提及量趋势
+{mention_trend}
+
+### 情感分布
+{sentiment_distribution}
+
+## 📈 竞品对比分析
+{competitor_analysis}
+
+## 🎯 关键观点摘要
+{key_insights}
+
+## ⚠️ 风险预警
+{risk_alerts}
+
+## 📋 改进建议
+{recommendations}
+
+---
+*报告类型：企业品牌舆情监测*  
+*生成时间：{generation_time}*  
+*数据来源：{data_sources}*
 ```
 ```
 
 
-#### 4. MySQL连接失败
-- 检查MySQL服务是否启动
-- 确认用户权限配置
-- 检查防火墙设置
+#### 2. 在Web界面中使用
 
 
-## 贡献指南
+系统支持上传自定义模板文件（.md或.txt格式），可在生成报告时选择使用。
+
+## 🤝 贡献指南
 
 
 我们欢迎所有形式的贡献！
 我们欢迎所有形式的贡献！
 
 
-1. Fork项目
-2. 创建Feature分支 (`git checkout -b feature/AmazingFeature`)
-3. 提交更改 (`git commit -m 'Add some AmazingFeature'`)
-4. 推送到分支 (`git push origin feature/AmazingFeature`)
-5. 开启Pull Request
+### 如何贡献
+
+1. **Fork项目**到您的GitHub账号
+2. **创建Feature分支**：`git checkout -b feature/AmazingFeature`
+3. **提交更改**：`git commit -m 'Add some AmazingFeature'`
+4. **推送到分支**：`git push origin feature/AmazingFeature`
+5. **开启Pull Request**
+
+### 贡献类型
+
+- 🐛 Bug修复
+- ✨ 新功能开发
+- 📚 文档完善
+- 🎨 UI/UX改进
+- ⚡ 性能优化
+- 🧪 测试用例添加
+
+### 开发规范
+
+- 代码遵循PEP8规范
+- 提交信息使用清晰的中英文描述
+- 新功能需要包含相应的测试用例
+- 更新相关文档
+
+## 📄 许可证
+
+本项目采用 [MIT许可证](LICENSE)。详细信息请参阅LICENSE文件。
+
+## 🎉 支持与联系
+
+### 获取帮助
+
+- **项目主页**：[GitHub仓库](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem)
+- **问题反馈**：[Issues页面](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/issues)
+- **功能建议**：[Discussions页面](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/discussions)
+
+### 联系方式
 
 
-## 许可证
+- 📧 **邮箱**：670939375@qq.com
+- 💬 **QQ群**：[加入技术交流群]
+- 🐦 **微信**：[扫码添加技术支持]
 
 
-本项目采用 MIT 许可证。详见 [LICENSE](LICENSE) 文件。
+### 商务合作
 
 
-## 联系我们
+- 🏢 **企业定制开发**
+- 📊 **大数据服务**
+- 🎓 **学术合作**
+- 💼 **技术培训**
 
 
-- 项目地址：[https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem)
-- 邮箱：670939375@qq.com
-- Issues：[项目Issues](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/issues)
+### 云服务申请
+
+**免费云数据库服务申请**：
+📧 发送邮件至：670939375@qq.com  
+📝 标题：微博舆情云数据库申请  
+📝 说明：您的使用场景和需求  
+
+## 👥 贡献者
+
+感谢以下优秀的贡献者们：
+
+[![Contributors](https://contrib.rocks/image?repo=666ghj/Weibo_PublicOpinion_AnalysisSystem)](https://github.com/666ghj/Weibo_PublicOpinion_AnalysisSystem/graphs/contributors)
+
+---
+
+<div align="center">
+
+**⭐ 如果这个项目对您有帮助，请给我们一个星标！**
+
+Made with ❤️ by [微博舆情分析团队](https://github.com/666ghj)
+
+</div>