YapTrap Dashboard

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Check API Status | Health Check

\n \n \n `, 500);\n }\n});\n\n// Catch-all for undefined routes\napp.all('*', async (c) => {\n await SystemLogQueries.log('warn', 'http', `404 Not Found: ${c.req.method} ${c.req.path}`);\n \n return c.json({\n error: 'Not Found',\n message: `The requested endpoint ${c.req.method} ${c.req.path} was not found`,\n timestamp: new Date(),\n availableEndpoints: [\n 'GET /',\n 'GET /health',\n 'GET /api/status',\n 'POST /webhooks/slack',\n 'POST /webhooks/sms',\n 'POST /webhooks/email',\n 'POST /webhooks/whatsapp',\n 'GET /admin/*',\n 'POST /admin/*'\n ]\n }, 404);\n});\n\n// Startup logging\nconsole.log('🤖 YapTrap Backend Starting...');\nconsole.log('📊 Admin Dashboard: /');\nconsole.log('🔗 Webhook Endpoints: /webhooks/*');\nconsole.log('⚙️ Admin API: /admin/*');\nconsole.log('❤️ Health Check: /health');\n\n// Export the Hono app for Val Town\nexport default app.fetch;",[],[99,350],[99],{"_104":361,"_95":362,"_152":363,"_154":-5,"_155":138,"_156":364,"_158":159,"_106":365,"_100":32,"_161":162,"_163":-5,"_164":22,"_165":-5,"_166":366,"_98":384},"11e9a6ee-8ead-11f0-9849-0224a6c84d84","docs","e72cb351-71cf-4e1a-bbcd-0a5596e47ccc",3,["D",1757553442936],[367,376],{"_104":368,"_95":369,"_152":370,"_154":363,"_155":138,"_156":354,"_158":159,"_106":371,"_100":32,"_161":372,"_163":373,"_164":22,"_165":-5,"_166":374,"_98":375},"37753324-8ead-11f0-a4b9-0224a6c84d84","SDD.md","3775341e-8ead-11f0-a4b9-0224a6c84d84",["D",1757553505933],"file","# Software Design Document (SDD)\n# YapTrap Multi-Platform Chatbot System\n\n**Version:** 1.0 \n**Date:** December 2024 \n**Status:** Draft\n\n## 1. Introduction\n\n### 1.1 Purpose\nThis document describes the software design for YapTrap, detailing the system architecture, component design, and implementation approach that satisfies the requirements specified in the SRS.\n\n### 1.2 Scope\nThis design covers:\n- Overall system architecture and component relationships\n- Database schema and data flow design\n- Platform integration patterns and APIs\n- AI/LLM integration architecture\n- Administrative interface design\n- Monitoring and logging infrastructure\n\n### 1.3 Design Principles\n- **Modularity**: Clear separation of concerns with well-defined interfaces\n- **Scalability**: Horizontal scaling capabilities within Val Town constraints\n- **Reliability**: Defensive programming with comprehensive error handling\n- **Maintainability**: Clean code with extensive testing and documentation\n- **Security**: Security-first design with data protection throughout\n\n## 2. System Architecture\n\n### 2.1 High-Level Architecture\n\n```\n┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐\n│ Messaging │ │ YapTrap │ │ Admin │\n│ Platforms │◄──►│ Core System │◄──►│ Dashboard │\n│ │ │ │ │ │\n│ • Slack │ │ • Message Proc │ │ • Monitoring │\n│ • SMS/MMS │ │ • AI Engine │ │ • Configuration │\n│ • Email │ │ • Database │ │ • Analytics │\n│ • WhatsApp │ │ • Platform APIs │ │ • User Mgmt │\n└─────────────────┘ └─────────────────┘ └─────────────────┘\n │\n ┌─────────────────┐\n │ External │\n │ Services │\n │ │\n │ • LLM APIs │\n │ • Database │\n │ • Monitoring │\n └─────────────────┘\n```\n\n### 2.2 Component Architecture\n\n#### 2.2.1 Core Components\n- **Message Router**: Central message processing and routing\n- **Platform Handlers**: Platform-specific integration modules\n- **AI Engine**: LLM integration and response generation\n- **Personality Engine**: User profiling and adaptation logic\n- **Database Layer**: Data persistence and retrieval\n- **Admin Interface**: Web-based management dashboard\n- **Monitoring System**: Logging, metrics, and health monitoring\n\n#### 2.2.2 Val Town Deployment Structure\n```\nbackend/\n├── index.ts # Main HTTP entry point (Hono app)\n├── database/\n│ ├── schema.ts # Database schema definitions\n│ ├── queries.ts # Database query functions\n│ └── migrations.ts # Schema migrations\n├── platforms/\n│ ├── base.ts # Base platform handler interface\n│ ├── slack.ts # Slack integration\n│ ├── sms.ts # SMS/MMS via Telnyx\n│ ├── email.ts # Email via SendGrid\n│ └── whatsapp.ts # WhatsApp Business API\n├── ai/\n│ ├── engine.ts # LLM integration layer\n│ ├── personality.ts # Personality analysis and profiling\n│ └── context.ts # Conversation context management\n├── monitoring/\n│ ├── logger.ts # Centralized logging\n│ ├── metrics.ts # Performance and usage metrics\n│ └── health.ts # System health monitoring\n└── routes/\n ├── webhooks.ts # Platform webhook handlers\n ├── admin.ts # Admin API endpoints\n └── static.ts # Static file serving\n\nfrontend/\n├── index.html # Main admin dashboard\n├── components/\n│ ├── Dashboard.tsx # Main dashboard component\n│ ├── ConversationView.tsx\n│ ├── MetricsView.tsx\n│ └── ConfigView.tsx\n└── styles/\n └── main.css\n\nshared/\n├── types.ts # Shared TypeScript interfaces\n├── utils.ts # Common utility functions\n└── constants.ts # System constants and configuration\n```\n\n## 3. Database Design\n\n### 3.1 Schema Overview\n\n#### 3.1.1 Core Tables\n```sql\n-- Conversations: Track group conversations across platforms\nCREATE TABLE conversations (\n id TEXT PRIMARY KEY,\n platform TEXT NOT NULL,\n platform_id TEXT NOT NULL,\n name TEXT,\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n last_activity DATETIME,\n settings JSON,\n is_active BOOLEAN DEFAULT 1\n);\n\n-- Users: Individual participants across all conversations\nCREATE TABLE users (\n id TEXT PRIMARY KEY,\n platform TEXT NOT NULL,\n platform_user_id TEXT NOT NULL,\n display_name TEXT,\n personality_profile JSON,\n preferences JSON,\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP\n);\n\n-- Messages: All messages in conversations\nCREATE TABLE messages (\n id TEXT PRIMARY KEY,\n conversation_id TEXT NOT NULL,\n user_id TEXT,\n content TEXT NOT NULL,\n message_type TEXT DEFAULT 'user', -- 'user', 'yaptrap', 'system'\n platform_message_id TEXT,\n timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,\n metadata JSON,\n FOREIGN KEY (conversation_id) REFERENCES conversations(id),\n FOREIGN KEY (user_id) REFERENCES users(id)\n);\n\n-- Conversation Participants: Many-to-many relationship\nCREATE TABLE conversation_participants (\n conversation_id TEXT NOT NULL,\n user_id TEXT NOT NULL,\n joined_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n role TEXT DEFAULT 'member', -- 'member', 'admin', 'bot'\n is_active BOOLEAN DEFAULT 1,\n PRIMARY KEY (conversation_id, user_id),\n FOREIGN KEY (conversation_id) REFERENCES conversations(id),\n FOREIGN KEY (user_id) REFERENCES users(id)\n);\n\n-- System Logs: Comprehensive logging for monitoring\nCREATE TABLE system_logs (\n id TEXT PRIMARY KEY,\n timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,\n level TEXT NOT NULL, -- 'debug', 'info', 'warn', 'error'\n component TEXT NOT NULL,\n message TEXT NOT NULL,\n metadata JSON,\n conversation_id TEXT,\n user_id TEXT\n);\n\n-- Configuration: System and conversation-specific settings\nCREATE TABLE configuration (\n key TEXT PRIMARY KEY,\n value JSON NOT NULL,\n scope TEXT DEFAULT 'global', -- 'global', 'conversation', 'user'\n scope_id TEXT,\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,\n updated_by TEXT\n);\n```\n\n### 3.2 Data Flow Design\n\n#### 3.2.1 Message Processing Flow\n1. **Webhook Reception**: Platform sends message to webhook endpoint\n2. **Message Normalization**: Convert platform-specific format to internal format\n3. **User/Conversation Resolution**: Identify or create user and conversation records\n4. **Context Analysis**: Analyze message content and conversation context\n5. **Response Decision**: Determine if and how YapTrap should respond\n6. **Response Generation**: Generate appropriate response using AI engine\n7. **Platform Delivery**: Send response back through platform API\n8. **Logging**: Record all activities for monitoring and learning\n\n#### 3.2.2 Personality Learning Flow\n1. **Message Analysis**: Extract communication patterns and preferences\n2. **Profile Update**: Update user personality profile with new insights\n3. **Group Dynamics**: Analyze group interaction patterns\n4. **Adaptation**: Adjust YapTrap's behavior based on learned preferences\n\n## 4. Component Design\n\n### 4.1 Message Router (backend/routes/webhooks.ts)\n\n```typescript\ninterface MessageRouter {\n // Route incoming webhook messages to appropriate platform handlers\n routeMessage(platform: string, payload: any): Promise;\n \n // Process normalized messages through the AI pipeline\n processMessage(message: NormalizedMessage): Promise;\n \n // Determine response strategy based on context and configuration\n shouldRespond(context: ConversationContext): Promise;\n}\n```\n\n### 4.2 Platform Handler Interface (backend/platforms/base.ts)\n\n```typescript\ninterface PlatformHandler {\n // Normalize incoming platform messages to internal format\n normalizeMessage(payload: any): Promise;\n \n // Send response back to platform\n sendMessage(conversationId: string, content: string): Promise;\n \n // Handle platform-specific authentication and setup\n authenticate(): Promise;\n \n // Validate webhook signatures and requests\n validateWebhook(payload: any, signature: string): boolean;\n}\n```\n\n### 4.3 AI Engine (backend/ai/engine.ts)\n\n```typescript\ninterface AIEngine {\n // Generate contextual response based on conversation history\n generateResponse(context: ConversationContext): Promise;\n \n // Analyze message sentiment and intent\n analyzeMessage(message: NormalizedMessage): Promise;\n \n // Update conversation context with new message\n updateContext(context: ConversationContext, message: NormalizedMessage): Promise;\n}\n```\n\n### 4.4 Personality Engine (backend/ai/personality.ts)\n\n```typescript\ninterface PersonalityEngine {\n // Analyze user communication patterns\n analyzeUserPersonality(userId: string, messages: NormalizedMessage[]): Promise;\n \n // Update personality profile with new insights\n updatePersonalityProfile(userId: string, insights: PersonalityInsights): Promise;\n \n // Get personality-adapted response style\n getResponseStyle(userId: string, groupContext: GroupContext): Promise;\n}\n```\n\n## 5. API Design\n\n### 5.1 Webhook Endpoints\n\n```typescript\n// Platform webhook receivers\nPOST /webhooks/slack # Slack events and messages\nPOST /webhooks/sms # Telnyx SMS/MMS webhooks \nPOST /webhooks/email # SendGrid inbound email\nPOST /webhooks/whatsapp # WhatsApp Business API webhooks\n\n// Administrative endpoints\nGET /admin/conversations # List all conversations\nGET /admin/users # List all users\nGET /admin/metrics # System metrics and health\nPOST /admin/config # Update configuration\nGET /admin/logs # Stream system logs\n```\n\n### 5.2 Internal API Interfaces\n\n```typescript\n// Normalized message format across all platforms\ninterface NormalizedMessage {\n id: string;\n conversationId: string;\n userId: string;\n content: string;\n timestamp: Date;\n platform: string;\n messageType: 'text' | 'image' | 'file' | 'system';\n metadata: Record;\n}\n\n// Conversation context for AI processing\ninterface ConversationContext {\n conversationId: string;\n participants: User[];\n recentMessages: NormalizedMessage[];\n groupDynamics: GroupDynamics;\n yapTrapSettings: YapTrapSettings;\n}\n\n// User personality profile\ninterface PersonalityProfile {\n userId: string;\n communicationStyle: CommunicationStyle;\n interests: string[];\n responsePreferences: ResponsePreferences;\n groupRole: GroupRole;\n lastUpdated: Date;\n}\n```\n\n## 6. Security Design\n\n### 6.1 Authentication and Authorization\n- **Webhook Validation**: Verify all incoming webhooks using platform-specific signatures\n- **API Authentication**: Secure admin endpoints with authentication tokens\n- **Rate Limiting**: Implement rate limiting to prevent abuse\n- **Input Validation**: Sanitize and validate all input data\n\n### 6.2 Data Protection\n- **Encryption**: Encrypt sensitive data at rest and in transit\n- **Access Control**: Implement role-based access control for admin functions\n- **Audit Logging**: Log all data access and modifications\n- **Data Retention**: Implement configurable data retention policies\n\n## 7. Monitoring and Logging Design\n\n### 7.1 Logging Strategy\n- **Structured Logging**: Use consistent JSON format for all log entries\n- **Log Levels**: Implement debug, info, warn, error levels\n- **Contextual Logging**: Include conversation and user context in logs\n- **Performance Logging**: Track response times and system performance\n\n### 7.2 Metrics Collection\n- **Message Metrics**: Track message volume, response rates, engagement\n- **Performance Metrics**: Monitor response times, error rates, throughput\n- **User Metrics**: Track user satisfaction, personality learning accuracy\n- **System Metrics**: Monitor resource usage, health status\n\n## 8. Deployment Architecture\n\n### 8.1 Val Town Deployment\n- **Main Entry Point**: Single HTTP handler in `backend/index.ts`\n- **Environment Configuration**: Use Val Town environment variables\n- **Database**: SQLite for development, external database for production\n- **Static Assets**: Serve admin interface through Val Town\n\n### 8.2 External Dependencies\n- **Database**: External PostgreSQL or SQLite for data persistence\n- **LLM Services**: OpenAI, xAI, Claude APIs for AI functionality\n- **Platform APIs**: Direct integration with messaging platform APIs\n- **Monitoring**: External logging and metrics collection services\n\n## 9. Error Handling and Recovery\n\n### 9.1 Error Handling Strategy\n- **Graceful Degradation**: Continue operation with reduced functionality during failures\n- **Retry Logic**: Implement exponential backoff for transient failures\n- **Circuit Breakers**: Prevent cascade failures in external service calls\n- **Fallback Responses**: Provide default responses when AI services fail\n\n### 9.2 Recovery Procedures\n- **Automatic Recovery**: Self-healing for common failure scenarios\n- **Manual Intervention**: Clear procedures for manual recovery\n- **Data Recovery**: Backup and restore procedures for data loss\n- **Service Recovery**: Procedures for restoring service after outages\n\n## 10. Performance Considerations\n\n### 10.1 Scalability Design\n- **Stateless Design**: All components designed for horizontal scaling\n- **Caching Strategy**: Cache frequently accessed data and AI responses\n- **Database Optimization**: Efficient queries and indexing strategy\n- **Rate Limiting**: Protect against overload and abuse\n\n### 10.2 Performance Optimization\n- **Response Time**: Target sub-5-second response times\n- **Concurrent Processing**: Handle multiple conversations simultaneously\n- **Resource Management**: Efficient memory and CPU usage\n- **Network Optimization**: Minimize external API calls and data transfer\n\n---\n\n**Document Control:**\n- Author: Technical Architect\n- Reviewers: Senior Developer, DevOps Engineer\n- Approval: Technical Lead\n- Implementation Reference: All code must trace back to this design\n- Next Review: Upon major architectural changes",[],[362,369],{"_104":377,"_95":378,"_152":379,"_154":363,"_155":138,"_156":364,"_158":159,"_106":380,"_100":32,"_161":372,"_163":381,"_164":22,"_165":-5,"_166":382,"_98":383},"11e9861e-8ead-11f0-9849-0224a6c84d84","SRS.md","11e986e6-8ead-11f0-9849-0224a6c84d84",["D",1757553442936],"# Software Requirements Specification (SRS)\n# YapTrap Multi-Platform Chatbot System\n\n**Version:** 1.0 \n**Date:** December 2024 \n**Status:** Draft\n\n## 1. Introduction\n\n### 1.1 Purpose\nThis document specifies the requirements for YapTrap, an automated chatbot system designed to participate in multi-party conversations across various messaging platforms with personality-aware contextual engagement.\n\n### 1.2 Scope\nYapTrap will:\n- Monitor and participate in group conversations across multiple platforms\n- Learn and adapt to individual user personalities and group dynamics\n- Provide contextual, witty, and engaging responses\n- Offer administrative controls and monitoring capabilities\n- Self-monitor and improve through automated analysis\n\n### 1.3 Definitions and Acronyms\n- **YapTrap**: The core chatbot system\n- **Persona**: Simulated user personalities for testing and system improvement\n- **Platform Handler**: Service component managing specific messaging platform integration\n- **LLM**: Large Language Model for AI-powered responses\n\n## 2. Overall Description\n\n### 2.1 Product Perspective\nYapTrap operates as a distributed system with:\n- Core backend services running on Val Town\n- Platform-specific webhook handlers\n- Database for state and conversation management\n- Web-based administrative interface\n- Automated monitoring and improvement subsystems\n\n### 2.2 Product Functions\n1. **Message Processing**: Receive, analyze, and respond to messages\n2. **Personality Learning**: Build profiles of conversation participants\n3. **Context Generation**: Create relevant, engaging responses\n4. **Platform Integration**: Support multiple messaging platforms\n5. **Administration**: Provide monitoring and configuration capabilities\n6. **Self-Improvement**: Automated system analysis and enhancement\n\n### 2.3 User Classes\n- **End Users**: Participants in group conversations\n- **Administrators**: System operators managing YapTrap instances\n- **Developers**: Personnel maintaining and enhancing the system\n\n## 3. Functional Requirements\n\n### 3.1 Core Chatbot Functionality\n\n#### 3.1.1 Message Reception and Processing\n- **REQ-001**: System SHALL receive messages from supported platforms via webhooks\n- **REQ-002**: System SHALL parse and normalize messages across different platform formats\n- **REQ-003**: System SHALL maintain conversation context and history\n- **REQ-004**: System SHALL identify and track individual users across conversations\n\n#### 3.1.2 Personality Learning and Adaptation\n- **REQ-005**: System SHALL analyze user communication patterns and preferences\n- **REQ-006**: System SHALL build and maintain personality profiles for each user\n- **REQ-007**: System SHALL adapt response style based on group dynamics\n- **REQ-008**: System SHALL learn from user reactions to its messages\n\n#### 3.1.3 Response Generation\n- **REQ-009**: System SHALL generate contextually relevant responses using LLM integration\n- **REQ-010**: System SHALL provide witty, engaging, and appropriate content\n- **REQ-011**: System SHALL adjust response frequency based on configuration\n- **REQ-012**: System SHALL initiate conversations when threads go silent (configurable)\n\n### 3.2 Platform Integration\n\n#### 3.2.1 Supported Platforms\n- **REQ-013**: System SHALL support Slack via official Slack App API\n- **REQ-014**: System SHALL support SMS/MMS via Telnyx API\n- **REQ-015**: System SHALL support Email via SendGrid API\n- **REQ-016**: System SHALL support WhatsApp Business API (webhook-based)\n- **REQ-017**: System SHALL provide extensible architecture for additional platforms\n\n#### 3.2.2 Platform-Specific Requirements\n- **REQ-018**: Each platform handler SHALL normalize incoming messages to common format\n- **REQ-019**: Each platform handler SHALL format outgoing messages appropriately\n- **REQ-020**: System SHALL handle platform-specific authentication and authorization\n- **REQ-021**: System SHALL respect platform rate limits and usage policies\n\n### 3.3 Data Management\n\n#### 3.3.1 Database Requirements\n- **REQ-022**: System SHALL store conversation history with configurable retention\n- **REQ-023**: System SHALL maintain user personality profiles and preferences\n- **REQ-024**: System SHALL track group-specific settings and configurations\n- **REQ-025**: System SHALL log all system operations for monitoring and debugging\n\n#### 3.3.2 Data Privacy and Security\n- **REQ-026**: System SHALL encrypt sensitive data at rest and in transit\n- **REQ-027**: System SHALL provide data retention and deletion capabilities\n- **REQ-028**: System SHALL comply with applicable privacy regulations\n- **REQ-029**: System SHALL provide audit trails for all data access\n\n### 3.4 Administrative Interface\n\n#### 3.4.1 Web Dashboard\n- **REQ-030**: System SHALL provide web-based administrative interface\n- **REQ-031**: Dashboard SHALL display system health and operational metrics\n- **REQ-032**: Dashboard SHALL allow configuration of chatbot parameters\n- **REQ-033**: Dashboard SHALL provide conversation monitoring and analysis tools\n\n#### 3.4.2 Configuration Management\n- **REQ-034**: System SHALL support runtime configuration changes\n- **REQ-035**: System SHALL maintain configuration version history\n- **REQ-036**: System SHALL validate configuration changes before application\n- **REQ-037**: System SHALL provide rollback capabilities for configuration changes\n\n### 3.5 Monitoring and Self-Improvement\n\n#### 3.5.1 System Monitoring\n- **REQ-038**: System SHALL collect and analyze operational metrics\n- **REQ-039**: System SHALL detect and alert on system anomalies\n- **REQ-040**: System SHALL provide real-time log streaming capabilities\n- **REQ-041**: System SHALL generate automated system health reports\n\n#### 3.5.2 Automated Improvement\n- **REQ-042**: System SHALL analyze conversation effectiveness and user satisfaction\n- **REQ-043**: System SHALL identify opportunities for system enhancement\n- **REQ-044**: System SHALL generate improvement recommendations\n- **REQ-045**: System SHALL support automated testing of system changes\n\n## 4. Non-Functional Requirements\n\n### 4.1 Performance\n- **REQ-046**: System SHALL respond to messages within 5 seconds under normal load\n- **REQ-047**: System SHALL support concurrent conversations across multiple platforms\n- **REQ-048**: System SHALL handle message bursts without data loss\n- **REQ-049**: System SHALL scale automatically based on demand\n\n### 4.2 Reliability\n- **REQ-050**: System SHALL maintain 99.5% uptime availability\n- **REQ-051**: System SHALL implement graceful degradation during partial failures\n- **REQ-052**: System SHALL provide automatic recovery from transient failures\n- **REQ-053**: System SHALL maintain data consistency across all operations\n\n### 4.3 Security\n- **REQ-054**: System SHALL authenticate all API requests\n- **REQ-055**: System SHALL implement rate limiting to prevent abuse\n- **REQ-056**: System SHALL validate and sanitize all input data\n- **REQ-057**: System SHALL protect against common security vulnerabilities\n\n### 4.4 Maintainability\n- **REQ-058**: System SHALL provide comprehensive logging for debugging\n- **REQ-059**: System SHALL implement defensive programming practices\n- **REQ-060**: System SHALL include automated testing for all components\n- **REQ-061**: System SHALL support continuous integration and deployment\n\n## 5. External Interface Requirements\n\n### 5.1 User Interfaces\n- Web-based administrative dashboard\n- Platform-native messaging interfaces (via platform APIs)\n\n### 5.2 Hardware Interfaces\n- None (cloud-based deployment)\n\n### 5.3 Software Interfaces\n- Slack API v1.7+\n- Telnyx API v2\n- SendGrid API v3\n- WhatsApp Business API\n- OpenAI/xAI/Claude APIs for LLM integration\n\n### 5.4 Communication Interfaces\n- HTTPS for all API communications\n- WebSocket for real-time features\n- Webhook endpoints for platform integrations\n\n## 6. Constraints\n\n### 6.1 Technical Constraints\n- Must operate within Val Town serverless environment\n- Limited to stateless operations with external state storage\n- Must comply with platform API terms of service\n- Must handle intermittent connectivity and API limitations\n\n### 6.2 Business Constraints\n- Must respect user privacy and data protection requirements\n- Must operate within API rate limits and usage quotas\n- Must provide cost-effective operation at scale\n\n## 7. Assumptions and Dependencies\n\n### 7.1 Assumptions\n- Platform APIs will remain stable and accessible\n- LLM services will provide consistent response quality\n- Users will grant necessary permissions for bot operation\n\n### 7.2 Dependencies\n- Val Town platform availability and capabilities\n- Third-party API service availability\n- Database service reliability\n- LLM service availability and performance\n\n## 8. Acceptance Criteria\n\n### 8.1 Functional Acceptance\n- All functional requirements (REQ-001 through REQ-045) must be implemented and tested\n- System must successfully participate in conversations on all supported platforms\n- Administrative interface must provide complete system management capabilities\n\n### 8.2 Performance Acceptance\n- System must meet all performance requirements under specified load conditions\n- Response times must remain within acceptable limits during peak usage\n- System must demonstrate scalability and reliability metrics\n\n### 8.3 Security Acceptance\n- All security requirements must be implemented and verified\n- System must pass security audit and penetration testing\n- Data protection and privacy compliance must be demonstrated\n\n---\n\n**Document Control:**\n- Author: System Architect\n- Reviewers: Technical Lead, Product Owner\n- Approval: Project Manager\n- Next Review: Monthly or upon significant changes",[],[362,378],[362],{"_104":386,"_95":387,"_152":388,"_154":-5,"_155":138,"_156":389,"_158":159,"_106":390,"_100":32,"_161":162,"_163":-5,"_164":22,"_165":-5,"_166":391,"_98":400},"64bfaef8-8eae-11f0-927b-0224a6c84d84","frontend","d0304a61-5d62-4b65-b30a-46e54bc007e1",15,["D",1757554011410],[392],{"_104":393,"_95":394,"_152":395,"_154":388,"_155":138,"_156":389,"_158":159,"_106":396,"_100":32,"_161":372,"_163":397,"_164":22,"_165":-5,"_166":398,"_98":399},"64bf7a50-8eae-11f0-927b-0224a6c84d84","index.html","64bf7b72-8eae-11f0-927b-0224a6c84d84",["D",1757554011410],"\n\n\n \n \n YapTrap Admin Dashboard\n \n \n \n\n\n

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🤖 YapTrap

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System Configuration

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\n\n \n\n",[],[387,394],[387],{"_104":402,"_95":403,"_152":404,"_154":-5,"_155":138,"_156":405,"_158":159,"_106":406,"_100":32,"_161":162,"_163":-5,"_164":22,"_165":-5,"_166":407,"_98":425},"4983d192-8ead-11f0-84d9-0224a6c84d84","shared","3ce5910d-9c37-473e-97c0-f4535477aef7",5,["D",1757553536216],[408,416],{"_104":409,"_95":410,"_152":411,"_154":404,"_155":138,"_156":405,"_158":159,"_106":412,"_100":32,"_161":181,"_163":413,"_164":22,"_165":-5,"_166":414,"_98":415},"4983bda6-8ead-11f0-84d9-0224a6c84d84","types.ts","4983be82-8ead-11f0-84d9-0224a6c84d84",["D",1757553536216],"/**\n * Shared TypeScript interfaces and types for YapTrap system\n * Used across frontend, backend, and testing components\n */\n\n// Core message types\nexport interface NormalizedMessage {\n id: string;\n conversationId: string;\n userId: string;\n content: string;\n timestamp: Date;\n platform: Platform;\n messageType: MessageType;\n metadata: Record;\n}\n\nexport type Platform = 'slack' | 'sms' | 'email' | 'whatsapp' | 'messenger';\nexport type MessageType = 'text' | 'image' | 'file' | 'system';\nexport type UserRole = 'member' | 'admin' | 'bot';\nexport type LogLevel = 'debug' | 'info' | 'warn' | 'error';\n\n// User and conversation types\nexport interface User {\n id: string;\n platform: Platform;\n platformUserId: string;\n displayName: string;\n personalityProfile?: PersonalityProfile;\n preferences?: UserPreferences;\n createdAt: Date;\n updatedAt: Date;\n}\n\nexport interface Conversation {\n id: string;\n platform: Platform;\n platformId: string;\n name?: string;\n createdAt: Date;\n lastActivity?: Date;\n settings: ConversationSettings;\n isActive: boolean;\n participants: ConversationParticipant[];\n}\n\nexport interface ConversationParticipant {\n conversationId: string;\n userId: string;\n joinedAt: Date;\n role: UserRole;\n isActive: boolean;\n}\n\n// AI and personality types\nexport interface PersonalityProfile {\n userId: string;\n communicationStyle: CommunicationStyle;\n interests: string[];\n responsePreferences: ResponsePreferences;\n groupRole: GroupRole;\n confidence: number; // 0-1 confidence in profile accuracy\n lastUpdated: Date;\n}\n\nexport interface CommunicationStyle {\n formality: number; // 0-1 (casual to formal)\n humor: number; // 0-1 (serious to humorous)\n verbosity: number; // 0-1 (concise to verbose)\n emotiveness: number; // 0-1 (reserved to expressive)\n directness: number; // 0-1 (indirect to direct)\n}\n\nexport interface ResponsePreferences {\n engagementFrequency: number; // 0-1 (rarely to frequently)\n roastIntensity: number; // 0-1 (gentle to spicy)\n topicInterests: string[];\n avoidTopics: string[];\n preferredResponseTime: 'immediate' | 'delayed' | 'contextual';\n}\n\nexport type GroupRole = 'leader' | 'supporter' | 'joker' | 'analyst' | 'mediator' | 'observer';\n\n// Conversation context for AI processing\nexport interface ConversationContext {\n conversationId: string;\n participants: User[];\n recentMessages: NormalizedMessage[];\n groupDynamics: GroupDynamics;\n yapTrapSettings: YapTrapSettings;\n currentTopic?: string;\n sentiment: ConversationSentiment;\n}\n\nexport interface GroupDynamics {\n activityLevel: number; // 0-1 (quiet to very active)\n humorLevel: number; // 0-1 (serious to very humorous)\n conflictLevel: number; // 0-1 (harmonious to conflicted)\n topicFocus: number; // 0-1 (scattered to focused)\n dominantPersonalities: string[]; // User IDs of most active participants\n}\n\nexport interface ConversationSentiment {\n overall: number; // -1 to 1 (negative to positive)\n recent: number; // -1 to 1 (recent message sentiment)\n trend: 'improving' | 'declining' | 'stable';\n}\n\n// Configuration types\nexport interface YapTrapSettings {\n conversationId: string;\n engagementFrequency: number; // 0-1 (how often to respond)\n roastIntensity: number; // 0-1 (how spicy to get)\n responseDelay: number; // seconds to wait before responding\n silenceThreshold: number; // minutes of silence before initiating\n personalityAdaptation: boolean; // whether to adapt to group personality\n topicTracking: boolean; // whether to track conversation topics\n learningEnabled: boolean; // whether to learn from interactions\n}\n\nexport interface ConversationSettings {\n yapTrapEnabled: boolean;\n yapTrapSettings: YapTrapSettings;\n retentionDays: number;\n adminUsers: string[];\n customPrompts?: string[];\n}\n\nexport interface UserPreferences {\n notifications: boolean;\n dataRetention: number; // days\n personalityLearning: boolean;\n customInstructions?: string;\n}\n\n// Platform-specific types\nexport interface PlatformMessage {\n platform: Platform;\n rawPayload: any;\n signature?: string;\n timestamp: Date;\n}\n\nexport interface PlatformResponse {\n platform: Platform;\n conversationId: string;\n content: string;\n messageType: MessageType;\n metadata?: Record;\n}\n\n// API response types\nexport interface APIResponse {\n success: boolean;\n data?: T;\n error?: string;\n timestamp: Date;\n}\n\nexport interface PaginatedResponse extends APIResponse {\n pagination: {\n page: number;\n limit: number;\n total: number;\n hasMore: boolean;\n };\n}\n\n// Monitoring and logging types\nexport interface SystemLog {\n id: string;\n timestamp: Date;\n level: LogLevel;\n component: string;\n message: string;\n metadata?: Record;\n conversationId?: string;\n userId?: string;\n}\n\nexport interface SystemMetrics {\n timestamp: Date;\n messageVolume: number;\n responseRate: number;\n averageResponseTime: number;\n errorRate: number;\n activeConversations: number;\n activeUsers: number;\n platformBreakdown: Record;\n}\n\nexport interface HealthStatus {\n status: 'healthy' | 'degraded' | 'unhealthy';\n timestamp: Date;\n components: Record;\n uptime: number;\n}\n\nexport interface ComponentHealth {\n status: 'healthy' | 'degraded' | 'unhealthy';\n lastCheck: Date;\n responseTime?: number;\n errorRate?: number;\n message?: string;\n}\n\n// AI service types\nexport interface AIProvider {\n name: string;\n model: string;\n apiKey: string;\n baseUrl?: string;\n maxTokens?: number;\n temperature?: number;\n}\n\nexport interface AIResponse {\n content: string;\n confidence: number;\n reasoning?: string;\n metadata: {\n provider: string;\n model: string;\n tokensUsed: number;\n responseTime: number;\n };\n}\n\n// Configuration management\nexport interface ConfigurationItem {\n key: string;\n value: any;\n scope: 'global' | 'conversation' | 'user';\n scopeId?: string;\n updatedAt: Date;\n updatedBy: string;\n}\n\n// Error types\nexport interface YapTrapError {\n code: string;\n message: string;\n component: string;\n timestamp: Date;\n context?: Record;\n stack?: string;\n}\n\n// Webhook validation\nexport interface WebhookValidation {\n isValid: boolean;\n platform: Platform;\n signature?: string;\n timestamp?: Date;\n error?: string;\n}\n\n// Database query types\nexport interface QueryOptions {\n limit?: number;\n offset?: number;\n orderBy?: string;\n orderDirection?: 'ASC' | 'DESC';\n filters?: Record;\n}\n\nexport interface DatabaseResult {\n data: T[];\n total: number;\n hasMore: boolean;\n}\n\n// Testing types\nexport interface TestScenario {\n id: string;\n name: string;\n description: string;\n platform: Platform;\n inputMessages: NormalizedMessage[];\n expectedResponse?: string;\n expectedBehavior: string;\n tags: string[];\n}\n\nexport interface TestResult {\n scenarioId: string;\n passed: boolean;\n actualResponse?: string;\n actualBehavior: string;\n executionTime: number;\n timestamp: Date;\n error?: string;\n}",[],[403,410],{"_104":417,"_95":418,"_152":419,"_154":404,"_155":138,"_156":420,"_158":159,"_106":421,"_100":32,"_161":181,"_163":422,"_164":22,"_165":-5,"_166":423,"_98":424},"6220fc3e-8ead-11f0-9f90-0224a6c84d84","utils.ts","6220fce8-8ead-11f0-9f90-0224a6c84d84",6,["D",1757553577514],"/**\n * Shared utility functions for YapTrap system\n * These utilities work in both frontend and backend environments\n */\n\nimport type { \n NormalizedMessage, \n Platform, \n LogLevel, \n SystemLog,\n YapTrapError \n} from './types.ts';\n\n// ID generation utilities\nexport function generateId(prefix?: string): string {\n const timestamp = Date.now().toString(36);\n const random = Math.random().toString(36).substring(2);\n return prefix ? `${prefix}_${timestamp}_${random}` : `${timestamp}_${random}`;\n}\n\nexport function generateConversationId(platform: Platform, platformId: string): string {\n return `conv_${platform}_${platformId.replace(/[^a-zA-Z0-9]/g, '_')}`;\n}\n\nexport function generateUserId(platform: Platform, platformUserId: string): string {\n return `user_${platform}_${platformUserId.replace(/[^a-zA-Z0-9]/g, '_')}`;\n}\n\n// Date and time utilities\nexport function formatTimestamp(date: Date): string {\n return date.toISOString();\n}\n\nexport function parseTimestamp(timestamp: string): Date {\n return new Date(timestamp);\n}\n\nexport function getTimeDifference(start: Date, end: Date): number {\n return end.getTime() - start.getTime();\n}\n\nexport function isWithinTimeWindow(timestamp: Date, windowMinutes: number): boolean {\n const now = new Date();\n const diffMinutes = (now.getTime() - timestamp.getTime()) / (1000 * 60);\n return diffMinutes <= windowMinutes;\n}\n\n// String utilities\nexport function sanitizeString(input: string): string {\n return input\n .replace(/[<>]/g, '') // Remove potential HTML tags\n .replace(/javascript:/gi, '') // Remove javascript: protocols\n .trim();\n}\n\nexport function truncateString(str: string, maxLength: number): string {\n if (str.length <= maxLength) return str;\n return str.substring(0, maxLength - 3) + '...';\n}\n\nexport function extractMentions(content: string): string[] {\n const mentionRegex = /@(\\w+)/g;\n const mentions: string[] = [];\n let match;\n \n while ((match = mentionRegex.exec(content)) !== null) {\n mentions.push(match[1]);\n }\n \n return mentions;\n}\n\nexport function removeMentions(content: string): string {\n return content.replace(/@\\w+/g, '').trim();\n}\n\n// Validation utilities\nexport function isValidEmail(email: string): boolean {\n const emailRegex = /^[^\\s@]+@[^\\s@]+\\.[^\\s@]+$/;\n return emailRegex.test(email);\n}\n\nexport function isValidUrl(url: string): boolean {\n try {\n new URL(url);\n return true;\n } catch {\n return false;\n }\n}\n\nexport function isValidPlatform(platform: string): platform is Platform {\n const validPlatforms: Platform[] = ['slack', 'sms', 'email', 'whatsapp', 'messenger'];\n return validPlatforms.includes(platform as Platform);\n}\n\nexport function isValidLogLevel(level: string): level is LogLevel {\n const validLevels: LogLevel[] = ['debug', 'info', 'warn', 'error'];\n return validLevels.includes(level as LogLevel);\n}\n\n// Object utilities\nexport function deepClone(obj: T): T {\n return JSON.parse(JSON.stringify(obj));\n}\n\nexport function mergeObjects>(target: T, source: Partial): T {\n return { ...target, ...source };\n}\n\nexport function pickProperties(obj: T, keys: K[]): Pick {\n const result = {} as Pick;\n keys.forEach(key => {\n if (key in obj) {\n result[key] = obj[key];\n }\n });\n return result;\n}\n\nexport function omitProperties(obj: T, keys: K[]): Omit {\n const result = { ...obj };\n keys.forEach(key => {\n delete result[key];\n });\n return result;\n}\n\n// Array utilities\nexport function uniqueArray(array: T[]): T[] {\n return [...new Set(array)];\n}\n\nexport function groupBy(array: T[], key: K): Record {\n return array.reduce((groups, item) => {\n const groupKey = String(item[key]);\n if (!groups[groupKey]) {\n groups[groupKey] = [];\n }\n groups[groupKey].push(item);\n return groups;\n }, {} as Record);\n}\n\nexport function sortBy(array: T[], key: keyof T, direction: 'asc' | 'desc' = 'asc'): T[] {\n return [...array].sort((a, b) => {\n const aVal = a[key];\n const bVal = b[key];\n \n if (aVal < bVal) return direction === 'asc' ? -1 : 1;\n if (aVal > bVal) return direction === 'asc' ? 1 : -1;\n return 0;\n });\n}\n\n// Message utilities\nexport function normalizeMessageContent(content: string): string {\n return content\n .replace(/\\s+/g, ' ') // Normalize whitespace\n .replace(/[^\\w\\s.,!?;:'\"()-]/g, '') // Remove special characters\n .trim();\n}\n\nexport function extractKeywords(content: string): string[] {\n const words = content\n .toLowerCase()\n .replace(/[^\\w\\s]/g, '')\n .split(/\\s+/)\n .filter(word => word.length > 3); // Filter out short words\n \n return uniqueArray(words);\n}\n\nexport function calculateMessageSimilarity(msg1: string, msg2: string): number {\n const words1 = new Set(extractKeywords(msg1));\n const words2 = new Set(extractKeywords(msg2));\n \n const intersection = new Set([...words1].filter(word => words2.has(word)));\n const union = new Set([...words1, ...words2]);\n \n return union.size === 0 ? 0 : intersection.size / union.size;\n}\n\n// Logging utilities\nexport function createLogEntry(\n level: LogLevel,\n component: string,\n message: string,\n metadata?: Record,\n conversationId?: string,\n userId?: string\n): SystemLog {\n return {\n id: generateId('log'),\n timestamp: new Date(),\n level,\n component,\n message,\n metadata,\n conversationId,\n userId\n };\n}\n\nexport function formatLogMessage(log: SystemLog): string {\n const timestamp = log.timestamp.toISOString();\n const level = log.level.toUpperCase().padEnd(5);\n const component = log.component.padEnd(15);\n \n let message = `[${timestamp}] ${level} ${component} ${log.message}`;\n \n if (log.conversationId) {\n message += ` (conv: ${log.conversationId})`;\n }\n \n if (log.userId) {\n message += ` (user: ${log.userId})`;\n }\n \n return message;\n}\n\n// Error handling utilities\nexport function createError(\n code: string,\n message: string,\n component: string,\n context?: Record\n): YapTrapError {\n return {\n code,\n message,\n component,\n timestamp: new Date(),\n context,\n stack: new Error().stack\n };\n}\n\nexport function isYapTrapError(error: any): error is YapTrapError {\n return error && \n typeof error.code === 'string' && \n typeof error.message === 'string' && \n typeof error.component === 'string' &&\n error.timestamp instanceof Date;\n}\n\n// Rate limiting utilities\nexport function createRateLimitKey(identifier: string, window: string): string {\n const timestamp = Math.floor(Date.now() / 1000);\n const windowSeconds = parseTimeWindow(window);\n const windowStart = Math.floor(timestamp / windowSeconds) * windowSeconds;\n return `${identifier}:${windowStart}`;\n}\n\nexport function parseTimeWindow(window: string): number {\n const match = window.match(/^(\\d+)([smhd])$/);\n if (!match) throw new Error(`Invalid time window format: ${window}`);\n \n const value = parseInt(match[1]);\n const unit = match[2];\n \n switch (unit) {\n case 's': return value;\n case 'm': return value * 60;\n case 'h': return value * 3600;\n case 'd': return value * 86400;\n default: throw new Error(`Invalid time unit: ${unit}`);\n }\n}\n\n// Configuration utilities\nexport function getConfigValue(\n config: Record,\n key: string,\n defaultValue: T\n): T {\n const keys = key.split('.');\n let value = config;\n \n for (const k of keys) {\n if (value && typeof value === 'object' && k in value) {\n value = value[k];\n } else {\n return defaultValue;\n }\n }\n \n return value as T;\n}\n\nexport function setConfigValue(\n config: Record,\n key: string,\n value: any\n): Record {\n const keys = key.split('.');\n const result = deepClone(config);\n let current = result;\n \n for (let i = 0; i < keys.length - 1; i++) {\n const k = keys[i];\n if (!current[k] || typeof current[k] !== 'object') {\n current[k] = {};\n }\n current = current[k];\n }\n \n current[keys[keys.length - 1]] = value;\n return result;\n}\n\n// Retry utilities\nexport async function withRetry(\n fn: () => Promise,\n maxAttempts: number = 3,\n delayMs: number = 1000,\n backoffMultiplier: number = 2\n): Promise {\n let lastError: Error;\n \n for (let attempt = 1; attempt <= maxAttempts; attempt++) {\n try {\n return await fn();\n } catch (error) {\n lastError = error as Error;\n \n if (attempt === maxAttempts) {\n throw lastError;\n }\n \n const delay = delayMs * Math.pow(backoffMultiplier, attempt - 1);\n await sleep(delay);\n }\n }\n \n throw lastError!;\n}\n\nexport function sleep(ms: number): Promise {\n return new Promise(resolve => setTimeout(resolve, ms));\n}\n\n// Environment utilities (backend only - check for Deno)\nexport function getEnvVar(key: string, defaultValue?: string): string {\n // Check if we're in a Deno environment (backend)\n if (typeof Deno !== 'undefined') {\n return Deno.env.get(key) || defaultValue || '';\n }\n \n // Frontend environment - return empty string or default\n return defaultValue || '';\n}\n\nexport function isProduction(): boolean {\n return getEnvVar('NODE_ENV') === 'production' || getEnvVar('DENO_ENV') === 'production';\n}\n\nexport function isDevelopment(): boolean {\n return !isProduction();\n}\n\n// Performance utilities\nexport function measureTime(fn: () => T): { result: T; duration: number } {\n const start = performance.now();\n const result = fn();\n const duration = performance.now() - start;\n return { result, duration };\n}\n\nexport async function measureTimeAsync(fn: () => Promise): Promise<{ result: T; duration: number }> {\n const start = performance.now();\n const result = await fn();\n const duration = performance.now() - start;\n return { result, duration };\n}\n\n// Hash utilities (simple hash for non-cryptographic purposes)\nexport function simpleHash(str: string): string {\n let hash = 0;\n for (let i = 0; i < str.length; i++) {\n const char = str.charCodeAt(i);\n hash = ((hash << 5) - hash) + char;\n hash = hash & hash; // Convert to 32-bit integer\n }\n return Math.abs(hash).toString(36);\n}",[],[403,418],[403],{"_104":427,"_95":428,"_152":429,"_154":-5,"_155":138,"_156":430,"_158":159,"_106":431,"_100":32,"_161":372,"_163":432,"_164":22,"_165":-5,"_166":433,"_98":434},"f5236d92-8eac-11f0-8833-0224a6c84d84","README.md","f5236f04-8eac-11f0-8833-0224a6c84d84",2,["D",1757553394654],"# YapTrap - Multi-Platform Automated Chatbot System\n\nYapTrap is an intelligent chatbot designed to participate in multi-party conversations across various messaging platforms. It learns individual personalities, provides contextual roasts and witty remarks, and can engage in meaningful conversations when directly addressed.\n\n## Project Structure\n\n```\n├── docs/ # Project documentation\n│ ├── SRS.md # Software Requirements Specification\n│ ├── SDD.md # Software Design Document\n│ ├── STP.md # Software Test Plan\n│ └── RUNBOOK.md # Operational Deployment Plan\n├── backend/ # Core backend services\n│ ├── index.ts # Main HTTP entry point\n│ ├── database/ # Database operations\n│ ├── platforms/ # Platform-specific handlers\n│ ├── ai/ # LLM integration\n│ └── monitoring/ # System monitoring\n├── frontend/ # Admin web interface\n├── shared/ # Shared utilities and types\n└── tests/ # Test suites\n```\n\n## Supported Platforms\n\n- Slack (via Slack App API)\n- SMS/MMS (via Telnyx API)\n- Email (via SendGrid API)\n- WhatsApp Business API (webhook-based)\n- Additional platforms via webhook integrations\n\n## Core Features\n\n1. **Personality Learning** - Analyzes conversation patterns to understand group dynamics\n2. **Contextual Engagement** - Provides relevant, witty responses based on conversation context\n3. **Multi-Platform Support** - Unified backend with platform-specific adapters\n4. **Admin Dashboard** - Web-based monitoring and configuration interface\n5. **Self-Monitoring** - Automated system health and performance tracking\n\n## Development Status\n\n🚧 **In Development** - Initial architecture and core components being implemented\n\n## Quick Start\n\n1. Set up environment variables in `.env`\n2. Deploy to Val Town\n3. Configure platform webhooks\n4. Access admin dashboard at deployed URL\n\n## Documentation\n\nSee `/docs/` directory for detailed specifications and design documents.",[],[428],{"_104":436,"_95":437,"_152":438,"_154":-5,"_155":138,"_156":439,"_158":159,"_106":440,"_100":430,"_161":355,"_163":441,"_164":22,"_165":-5,"_166":442,"_98":443},"3a906568-8eaf-11f0-9db0-0224a6c84d84","main.ts","e0b97664-8eaa-11f0-b609-0224a6c84d84",27,["D",1757554370129],"/**\n * YapTrap Main Entry Point\n * Redirects to the backend HTTP handler\n */\n\n// Import and re-export the backend handler\nexport { default } from 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