Analysis & Monitoring

MindMirror Micro-Coach

Real-time micro-coaching with OpenAI Realtime API and emotion detection

Intelligent Emotional Guidance

Minimal Node.js WebSocket client for OpenAI Realtime API that provides real-time micro-coaching based on emotional state, focus levels, and task engagement. Sends JSON state updates and validates responses against a strict contract.

Includes three operational modes: OpenAI Realtime WebSocket, offline rule-based engine requiring no API, and DeepSeek integration for normal LLM processing.

Operating Modes

Realtime OpenAI WebSocket
Offline Rule-Based Engine
DeepSeek Normal LLM API
Model gpt-4o-realtime

Core Features

Emotion Detection

Real-time emotion analysis tracking focus, valence, arousal, and dominant emotions for personalized coaching responses.

JSON State Updates

Sends structured JSON state updates as plain text turns including language, focus, valence, arousal, emotion, time on task, and consent status.

Contract Validation

Validates assistant responses against JSON contract (message/follow_up_question/nudge_type/tip/cooldown_sec/content_warnings).

Offline Rule Engine

Deterministic rules engine that mirrors spec trigger logic, returns contract-valid JSON, and requires no API.

System Prompt Loading

Loads MindMirror system prompt from prompts/mindmirror_realtime_coach.txt for session instructions.

Multi-LLM Support

Works with OpenAI Realtime (gpt-4o-realtime-preview-2024-12-17) and DeepSeek API (deepseek-chat) with configurable models.

Technical Specifications

Runtime
Node.js 18+
Realtime Model
gpt-4o-realtime-preview-2024-12-17
Protocol
WebSocket
Offline Engine
Rule-Based (No API)
DeepSeek Model
deepseek-chat
State Format
Structured JSON
Validation
JSON Schema Contract
Authentication
OPENAI_API_KEY / DEEPSEEK_API_KEY

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