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STARLPrep Backend

Backend service for STARLPrep.AI, a mode-based interview coaching copilot that produces structured STARL answers and follow-up practice.

What it does

  • Mode detection: Quick Polish vs Guided Build vs Follow-up Simulator
  • Generates: Fit check, STARL answer, scoring rubric, follow-up questions, and improvement plan
  • Guardrail: avoids fabricated metrics; recommends labeled proxies when numbers are unknown

Tech

  • Node.js + Express
  • LLM API (configured via env vars)
  • Prompt orchestration via promptSpec.js

Endpoints

  • GET /health — service status
  • POST /chat — accepts { sessionId, messages } and returns { type, reply }

Local setup

  1. npm install
  2. Create .env with your API key
  3. npm start

Roadmap (reliability + product hardening)

  • Session persistence (Redis/Supabase)
  • Structured outputs (schema-validated)
  • Evaluation harness (quality/cost/latency/safety)

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