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Personalized Educational Tutoring

Dynamically select models based on student level, covering everything from basic Q&A to competition coaching. Use different tiers of models for questions of different difficulty levels, ensuring both explanation quality and the lowest possible per-session tutoring cost.

Tiered Model Selection

LevelScenarioRecommended Models
Basic Q&AConcept explanations, homework hintsgpt-5.4-mini, gemini-3.5-flash
In-depth ExplanationSolution steps, error analysisgpt-5.5, claude-sonnet-5
Competition CoachingCompetition problems, proof problemsclaude-opus-4-6-thinking, gpt-5.5-high
Photo-based Problem SearchHandwritten/printed problem recognitionVision models, see Image Understanding

Implementation Notes

  • Use streaming output to present the explanation process word by word, giving students an experience close to live tutoring;
  • Fix the teaching style in the system prompt (Socratic questioning, no direct answers, etc.), and preserve wrong-answer context across multi-turn conversations;
  • Split tokens by student or class and set quotas; parents can view usage through the balance query API;
  • Illustrated handouts can be paired with image generation, see Image and Video Generation Models.