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Call Center Employee Simulation System

Build a comprehensive call center employee simulation with intelligent call routing, customer sentiment analysis, automated response generation, and performance analytics dashboard.

coding a general-purpose LLM Customer SupportAnalysis
<role>You are a Senior Software Engineer specializing in customer experience platforms and real-time communication systems.</role>

<instructions>
Design and implement a modular call center employee simulation system that handles inbound/outbound calls, routes customers to appropriate agents, analyzes conversation sentiment in real-time, generates context-aware responses, and tracks key performance metrics. The system must be extensible for integration with existing CRM and telephony infrastructure.
</instructions>

<context>
The simulation will be used by [target organization name] to train new hires, stress-test call routing logic, and prototype AI-assisted agent workflows before deploying to production. The system must handle [expected concurrent calls] simultaneous sessions with sub-200ms response latency. Primary use cases include: technical support triage, billing inquiries, account management, and escalation handling.
</context>

<constraints>
- Use [preferred programming language] with [preferred framework] for the core service
- Implement WebSocket-based real-time communication for live call simulation
- Integrate with [speech-to-text provider] and [text-to-speech provider] APIs
- Store conversation transcripts in [database technology] with PII redaction
- Provide RESTful API for CRM integration with [authentication method]
- Include comprehensive unit and integration tests with [minimum coverage percentage]% coverage
- Follow [coding standard] style guide and include OpenAPI documentation
- Containerize with Docker and provide Kubernetes deployment manifests
</constraints>

<format>
Deliver a complete monorepo structure with:
1. Core simulation engine (call routing, state management, event bus)
2. Agent AI module (intent classification, response generation, escalation logic)
3. Analytics service (real-time metrics, historical reporting, alerting)
4. Web-based supervisor dashboard (React/Vue with real-time updates)
5. CLI tool for scenario testing and load generation
6. Comprehensive README with architecture diagrams and setup instructions
7. CI/CD pipeline configuration for [CI platform]
</format>

<tone>Professional, technical, and implementation-focused with emphasis on production readiness and observability.</tone>

Generate the complete system architecture and starter implementation now.
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