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A production-ready, enterprise-grade chatbot platform built with MongoDB, Express, React (Vite), and Node.js.

Multi-Provider Support: OpenAI GPT-4 & Google Gemini integration
Streaming Responses: Real-time AI responses with Server-Sent Events (SSE)
Smart Context Management: Maintains conversation history and context
Cost Tracking: Monitor AI usage and token consumption
Retry Logic: Automatic retry with exponential backoff for reliability
Timeout Handling: 30-second timeout protection with graceful fallbacks
AI-to-Operator Handoff: Seamless transition from AI to human operator
Real-Time Dashboard: Live operator interface with active conversations
Priority Queue System: 4-level priority (low/normal/high/urgent)
Auto-Assignment: 6 intelligent strategies (Longest Wait, Lowest Workload, Round Robin, Skill-Based, Hybrid, Random)
Queue Position Tracking: Real-time position updates with estimated wait times for users
Session Tracking: Performance metrics per operator
Internal Notes & Tags: Conversation management tools
Status Management: Online/Away/Busy/Offline operator states
Transfer Capability: Move conversations between operators
Queue Analytics: Wait time, resolution time, satisfaction metrics
Admin Queue Configuration: Configurable assignment strategies with testing capabilities
One-Line Integration: Simple <script> tag embedding
Fully Customizable: Colors, logo, position, branding
Pre-Chat Forms: Collect user information before chat starts
Domain Security: Whitelist-based CORS protection
Mobile Responsive: Works seamlessly on all devices
Sound Notifications: Optional audio alerts
Minimized/Maximized States: User-friendly interface
Public Token Auth: No user login required for visitors
Hierarchical Action Buttons: WhatsApp-like service navigation system
3 Display Styles: Buttons, List, or Cards for action buttons
Unlimited Nesting Depth: Service → Sub-Service → Content hierarchy
Click Analytics: Track user navigation patterns through action buttons
Powered By Branding: Configurable "Powered by" link with theming
Security Alerts: Visual warnings for policy violations (strike system)
Operator Request Cooldown: 10-second cooldown to prevent spam
Keyword Detection: Automatic operator detection (e.g., "operator", "canlı destek")
Document Upload: Support for PDF, DOCX, DOC (with warning), TXT, MD formats
Enhanced PDF Extraction: Quality assessment, better text cleaning, detailed error messages
Improved DOCX Processing: Better structure preservation, table handling, extraction warnings
Smart Text Cleaning: RAG-optimized cleaning that preserves meaningful structure
Validation & Error Handling: File integrity checks, helpful error messages, quality metrics
3 Chunking Strategies: Recursive, Fixed-size, Semantic
Multi-Provider Embeddings: Gemini (free/multilingual), OpenAI (cloud/paid), HuggingFace (local)
Provider Switching: Zero-code switching via admin panel configuration
6 HuggingFace Models: all-MiniLM-L6-v2, all-mpnet-base-v2, BGE variants
Hybrid Search: Vector similarity + keyword BM25 search
Semantic Retrieval: Context-aware document search with RAG
Real-Time Streaming: RAG context integrated with streaming responses
Document Management: Upload, view, reindex, delete operations
Usage Analytics: Track retrieval effectiveness with quality scores
MinIO Storage: Scalable object storage backend
UTF-8 Support: Full multi-byte character handling (Azerbaijani, Turkish, etc.)
Query Rewrite Layer: AI-powered query optimization before vector search
Automatic typo correction and normalization
Query expansion with synonyms
Separate AI model (gpt-4o-mini) to avoid impacting main responses
Smart caching to reduce API calls and costs
Reranking Layer: Cross-encoder reranking for improved accuracy
Fetch more candidates (topN), rerank to best matches (topK)
Configurable truncate length (500-5000 chars) for context optimization
LLM-based scoring with relevance explanations
Answer Validation Layer: Verify AI responses against source documents
Hallucination detection with PASS/FAIL/UNCERTAIN verdicts
Automatic regeneration on validation failure
Confidence scoring with detailed reasoning
Metadata Filtering: Filter documents by tags, categories, dates
Widget-specific document access control
Dynamic filter building from query context
Legal Text Preservation: Special handling for legal documents
Preserve article boundaries (Maddə, Bənd, Hissə, Fəsil)
Configurable heading patterns for different document types
Query Normalization: Multi-language text preprocessing
Azerbaijani/Turkish special character handling
Automatic language detection
Search variant generation for better matching
RAG Caching: Intelligent caching for cost optimization
Configurable TTL (60-3600 seconds)
Cache statistics and manual clear functionality
Separate caches for query rewrite and reranking
Smart Model Selection: Use cheaper models (gpt-4o-mini) for RAG processing
Caching System: Reduce duplicate API calls with configurable TTL caching
Truncation Control: Limit context size to reduce token usage
Confidence-Based Processing: Only apply expensive RAG layers when needed
Free Embeddings: Gemini embedding models with zero cost
Fallback Providers: Automatic failover to backup AI providers
Token Monitoring: Real-time tracking of API usage and costs
Admin Dashboard: Visual cost analytics and efficiency metrics