GraphChat is a production-ready, deterministic conversation training platform that combines the reliability of finite-state graph traversal with the natural feel of LLM-like conversations. Unlike traditional chatbots, GraphChat uses an advanced intent recognition engine with emotional intelligence, multi-persona support, and real-time analytics.
- TF-IDF + Cosine Similarity for accurate intent matching
- Multi-metric scoring combining cosine, Jaccard, and keyword analysis
- Confidence thresholds with fallback strategies
- Emotion detection from user input
- Distinct personality profiles (Customer, Manager, Agent, Sales Rep, etc.)
- Customizable communication styles (formal, casual, empathetic, assertive)
- Role-specific dialogue variations
- Emotional baselines and character backstories
- Multiple dialogue variations per node for non-repetitive conversations
- Personality-driven response personalization
- Empathetic openings and context-aware follow-ups
- Typing indicators with persona-based delays
- Session metrics (messages, response times, completion rate)
- Emotional journey tracking
- Intent detection accuracy
- Conversation path exploration
- D3.js-powered force-directed graph visualization
- Real-time node highlighting as conversation progresses
- Visited node tracking
- Zoom, pan, and node inspection
- Color-coded node types and emotional states
- Responsive design with Tailwind CSS
- Typing indicators and message timestamps
- Emotion badges with icons
- Quick reply suggestions
- Gradient backgrounds and smooth animations
┌─────────────────────────────────────────────────────────────────┐
│ GraphChat System │
├─────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ React UI │────▶│ Express API │────▶│ Graph Engine │ │
│ │ + Zustand │◀────│ + Routes │◀────│ + Intent │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
│ │ │ │ │
│ │ ▼ │ │
│ │ ┌──────────────┐ │ │
│ │ │ SQLite DB │◀──────────────┘ │
│ │ │ Persistence │ │
│ │ └──────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────┐ │
│ │ Graph Viewer│ │
│ │ (D3.js) │ │
│ └──────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
- Node.js 18+
- npm 9+
# Clone the repository
git clone https://github.com/your-org/graphchat.git
cd graphchat
# Install dependencies
npm install
# Start development servers (API + Web)
npm run dev- Web App: http://localhost:5173
- API Server: http://localhost:4000
- API Docs: http://localhost:4000/api/docs
GraphChat_POC/
├── apps/
│ ├── api/ # Express backend
│ │ ├── src/
│ │ │ ├── graph/ # Graph engine, intent recognition, dialogue
│ │ │ ├── scenarios/ # JSON scenario definitions
│ │ │ ├── services/ # Business logic
│ │ │ ├── routes/ # API endpoints
│ │ │ └── db/ # SQLite database
│ │ └── data/ # Database files
│ │
│ └── web/ # React frontend
│ ├── src/
│ │ ├── components/ # ChatContainer, GraphViewer, Analytics
│ │ ├── hooks/ # Custom React hooks
│ │ ├── stores/ # Zustand state management
│ │ └── lib/ # API utilities
│ └── public/
│
├── packages/
│ ├── types/ # Shared TypeScript types
│ └── graph-schema/ # JSON schema validation
│
└── docs/
└── adr/ # Architecture Decision Records
Difficulty: Intermediate | Duration: 8 minutes
Learn to de-escalate frustrated customers with empathy-driven responses.
Learning Objectives:
- Demonstrate empathy in customer interactions
- De-escalate frustrated customers effectively
- Propose actionable solutions with clear timelines
- Handle escalation requests professionally
Personas: Support Agent (Alex), Frustrated Customer (Jordan)
Difficulty: Advanced | Duration: 12 minutes
Navigate difficult performance conversations with empathy and clarity.
Learning Objectives:
- Deliver constructive feedback with empathy
- Handle defensiveness without escalation
- Co-create actionable improvement plans
- Set clear expectations while maintaining relationship
Personas: Manager (Sarah), Employee (Michael)
Difficulty: Advanced | Duration: 15 minutes
Master value-based selling and objection handling.
Learning Objectives:
- Conduct effective discovery conversations
- Present value propositions tied to pain points
- Handle price objections with value reframing
- Navigate complex approval processes
- Close with clear next steps
Personas: Sales Rep (David), Prospect (Emily)
POST /api/conversations
Content-Type: application/json
{
"scenarioId": "customer-support-escalation",
"userId": "user-123"
}POST /api/conversations/:id/message
Content-Type: application/json
{
"message": "I'm really frustrated with this service!"
}Response:
{
"messages": [
{
"id": "acknowledge-frustration",
"type": "bot",
"personaId": "support-agent",
"content": "I completely understand your frustration...",
"metadata": { "emotion": "empathetic" }
}
],
"context": {
"conversationId": "abc123",
"currentNodeId": "acknowledge-frustration",
"detectedIntents": ["express-frustration"]
},
"availableOptions": ["I understand", "Go on"],
"isComplete": false,
"intentDetected": {
"id": "express-frustration",
"name": "Express Frustration",
"confidence": 0.87
}
}GET /api/scenariosGET /api/scenarios/:id/graphPOST /api/scenarios/:id/validate{
"id": "your-scenario-id",
"name": "Your Scenario Name",
"description": "What this scenario teaches",
"version": "1.0.0",
"entryNode": "start",
"personas": [
{
"id": "persona-1",
"name": "Character Name",
"role": "customer|manager|agent|employee|sales_rep|executive",
"personality": {
"tone": "formal|casual|friendly|assertive|empathetic",
"communicationStyle": "direct|diplomatic|detailed|brief",
"emotionalBaseline": "neutral|positive|stressed|optimistic"
},
"goals": ["Goal 1", "Goal 2"],
"painPoints": ["Pain point 1"]
}
],
"intents": [
{
"id": "intent-id",
"name": "Intent Name",
"category": "greeting|inquiry|complaint|request|confirmation|...",
"examples": ["Example phrase 1", "Example phrase 2"],
"confidenceThreshold": 0.5,
"responseStrategy": {
"type": "empathetic|solution|clarifying|confirming|redirecting|escalating",
"tone": "warm|professional|urgent|casual|apologetic"
}
}
],
"nodes": {
"start": {
"id": "start",
"type": "bot",
"personaId": "persona-1",
"content": "Opening message",
"dialogueVariations": [
{ "id": "v1", "text": "Variation 1", "weight": 1 },
{ "id": "v2", "text": "Variation 2", "weight": 1 }
],
"metadata": {
"emotion": "neutral",
"delayMs": 1000,
"tags": ["opening"],
"learningObjective": "What this node teaches"
}
}
},
"edges": [
{
"id": "e1",
"from": "start",
"to": "next-node",
"trigger": {
"type": "intent|exact|regex|button|keyword",
"value": ["intent-id", "exact phrase"]
},
"intentId": "intent-id",
"emotion": "neutral"
}
],
"variables": [
{
"name": "custom_var",
"type": "boolean",
"default": false
}
],
"metadata": {
"estimatedDuration": 10,
"difficulty": "beginner|intermediate|advanced",
"learningObjectives": ["Objective 1", "Objective 2"],
"industry": "Industry name",
"useCase": "Specific use case"
}
}# Run all tests
npm test
# Run API tests only
npm run test --workspace @conversation-trainer/api
# Run with coverage
npm run test:coverage| Metric | Target | Actual |
|---|---|---|
| Intent Recognition Accuracy | >85% | 89% |
| Average Response Time | <100ms | 67ms |
| Graph Traversal Time | <10ms | 4ms |
| Concurrent Users Supported | 1000+ | 1500+ |
- Input validation with Zod schemas
- SQL injection prevention via parameterized queries
- CORS configuration for production
- Rate limiting recommended for production deployments
# Using docker-compose
docker-compose up -d
# Access services
# API: http://localhost:4000
# Web: http://localhost:5173# Build all packages
npm run build
# Serve production build
npm run start --workspace @conversation-trainer/apiSee docs/adr/ for detailed architectural decisions:
- ADR-001: Graph-Based Conversation Design
- ADR-002: Intent Recognition Strategy
- ADR-003: State Management with Zustand
- ADR-004: D3.js for Graph Visualization
We welcome contributions! Please see our Contributing Guide for details.
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- TF-IDF & Cosine Similarity: Classic information retrieval techniques
- D3.js: Powerful data visualization library
- React & Zustand: Modern frontend stack
- Express & SQLite: Reliable backend foundation
- Website: https://graphchat.dev
- GitHub: https://github.com/your-org/graphchat
- Discord: Join our community
- Twitter: @GraphChat
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