How praveenamurugesan-tech/aithera--the-prompt-playground-for-every-learning-style works
AIthera is a personalized educational-prompt platform: learners submit a topic and preferences, the backend coordinates a multi-model council, then returns a synthesized prompt and learning support. The graph includes the documented generation stages and the frontend’s major learning features. Some backend pipeline links follow the README’s architecture description; unsampled implementation details are not inferred beyond that documentation.
Main entry points: App.tsx Web application · router.py Prompt endpoints · api.ts API client · live_council.py Council orchestration
Components 27
Learner experience
- Web application
frontend/src/App.tsx - Prompt workspace
frontend/src/pages/prompt/PromptPage.tsx - Generated result
frontend/src/pages/result/ResultPage.tsx - Learning features
frontend/src/pages/recommendations/RecommendationPage.tsx - Chat experience
frontend/src/pages/chat/ChatPage.tsx - Voice tools
frontend/src/pages/voice/VoicePage.tsx - Image upload
frontend/src/pages/upload/UploadPage.tsx - API client
frontend/src/services/api.ts
API and identity
- FastAPI app
src/main.py - Authentication
src/auth/router.py - Prompt endpoints
src/prompts/router.py - Prompt records
src/prompts/crud.py
Prompt generation
- AI service
src/services/ai_service.py - Learning styles
src/learning/style_engine.py - Council orchestration
src/council/live_council.py - Provider registry
src/providers/provider_registry.py - Model providers
src/providers - Response normalization
src/council/response_normalizer.py - Consensus builder
src/consensus/consensus_builder.py - Prompt scoring
src/scoring/prompt_scorer.py - Pedagogical rationale
src/explanation/explanation_generator.py
Learning support
- Recommendations API
src/recommendations/router.py - Learning recommendations
src/services/recommendation_generator.py - Prompt suggestions
src/optimizer/recommendation_engine.py
Other components
- Learner
- AI model services
- Application database
src/database/connection.py
Connections 32
- Learner → Web application: uses
- Web application → Prompt workspace: routes to
- Web application → Generated result: routes to
- Web application → Learning features: routes to
- Web application → Chat experience: routes to
- Web application → Voice tools: routes to
- Web application → Image upload: routes to
- Prompt workspace → API client: requests API
- Generated result → API client: requests API
- Learning features → API client: requests API
- Chat experience → API client: requests API
- Image upload → API client: requests API
- API client → FastAPI app: sends HTTP
- FastAPI app → Authentication: mounts router
- FastAPI app → Prompt endpoints: mounts router
- FastAPI app → Recommendations API: mounts router
- Prompt endpoints → Prompt records: reads and writes
- Prompt endpoints → AI service: generates prompt
- AI service → Council orchestration: executes council
- Council orchestration → Learning styles: applies style
- Council orchestration → Provider registry: selects providers
- Provider registry → Model providers: dispatches requests
- Model providers → AI model services: queries models
- Council orchestration → Response normalization: normalizes replies
- Council orchestration → Consensus builder: builds consensus
- Prompt endpoints → Prompt scoring: scores prompt
- Prompt endpoints → Pedagogical rationale: generates rationale
- Prompt endpoints → Application database: persists request
- Recommendations API → Prompt records: loads history
- Recommendations API → Learning recommendations: generates dashboard
- Learning recommendations → AI model services: queries Gemini
- AI service → Prompt suggestions: generates suggestions