How maruthi-gunisetty/innovex-nov16 works
SARVAVIDYA is a Streamlit multi-subject learning platform. Learners authenticate, choose a curriculum track, study lessons and take assessments; assessment responses feed mastery tracking and misconception diagnosis, while dashboards and recommendations surface progress and next steps. Faculty have analytics and management views, and the product also includes global search, SARVA AI, rewards, and Avatarverse. The routing and several module dependencies are documented in the source index; unsampled implementations are represented at their exact tree paths, without assuming unshown calls.
Main entry points: app.py Streamlit router · db.py Learning database · assessment.py Assessment · student_dashboard.py Student dashboard
Components 28
Application and access
- Streamlit router
app.py - Authentication view
views/auth.py - Auth service
core/auth_service.py - Navigation
components/navigation.py
Learning experience
- Subjects hub
views/subjects_hub.py - Learning library
views/library.py - Assessment
views/assessment.py - Student dashboard
views/student_dashboard.py - Learning path
views/learning_path.py - Faculty dashboard
views/teacher_dashboard.py
Learning intelligence
- Mastery tracking
core/bkt.py - Misconception diagnosis
core/misconception.py - Recommendations
core/recommender.py - Learning analytics
views/analytics.py
Platform services
- Global search
components/search_view.py - Search service
core/search_service.py - SARVA AI assistant
components/sarva_ai.py - Gemini AI service
core/ai_service.py - Ask AI Why
components/ask_ai_why.py - Rewards engine
core/rewards_engine.py - Rewards view
views/rewards_view.py - Avatarverse
views/avatarverse.py
Content and persistence
- Course manager
core/course_manager.py - Curriculum seed data
database/seed_data.py - Learning database
database/db.py
Other components
- Learner
- Faculty
- Google Gemini
Connections 48
- Learner → Streamlit router: opens platform
README.md - Faculty → Streamlit router: opens platform
README.md - Streamlit router → Authentication view: routes unauthenticated
app.py - Streamlit router → Student dashboard: routes learners
app.py - Streamlit router → Faculty dashboard: routes faculty
app.py - Authentication view → Auth service: uses authentication
views/auth.py - Authentication view → Learning database: reads and writes users
views/auth.py - Streamlit router → Navigation: renders navigation
app.py - Navigation → Global search: renders search
components/navigation.py - Streamlit router → Global search: routes active query
app.py - Global search → Search service: queries results
components/search_view.py - Search service → Learning database: searches learning data
core/search_service.py - Streamlit router → Subjects hub: routes page
app.py - Streamlit router → Learning library: routes page
app.py - Streamlit router → Assessment: routes page
app.py - Streamlit router → Learning path: routes page
app.py - Streamlit router → Learning analytics: routes page
app.py - Subjects hub → Course manager: selects curriculum
views/subjects_hub.py - Subjects hub → Learning database: reads subjects
views/subjects_hub.py - Learning library → Course manager: gets active track
views/library.py - Learning library → Learning database: loads lessons
views/library.py - Assessment → Learning database: records attempts
views/assessment.py - Assessment → Mastery tracking: updates mastery
views/assessment.py - Assessment → Misconception diagnosis: diagnoses distractors
views/assessment.py - Assessment → Recommendations: requests next steps
views/assessment.py - Assessment → Ask AI Why: offers explanations
views/assessment.py - Assessment → Rewards engine: awards learning rewards
views/assessment.py - Student dashboard → Learning database: loads progress
views/student_dashboard.py - Student dashboard → Mastery tracking: summarizes mastery
views/student_dashboard.py - Student dashboard → Misconception diagnosis: summarizes patterns
views/student_dashboard.py - Student dashboard → Recommendations: gets recommendations
views/student_dashboard.py - Student dashboard → Course manager: gets active track
views/student_dashboard.py - Student dashboard → Rewards engine: loads rewards
views/student_dashboard.py - Learning path → Mastery tracking: uses mastery
views/learning_path.py - Learning path → Recommendations: loads recommendations
views/learning_path.py - Learning path → Learning database: reads learning state
views/learning_path.py - Faculty dashboard → Learning database: loads class data
views/teacher_dashboard.py - Faculty dashboard → Mastery tracking: uses mastery
views/teacher_dashboard.py - Faculty dashboard → Misconception diagnosis: reviews diagnoses
views/teacher_dashboard.py - Faculty dashboard → Rewards engine: reviews rewards
views/teacher_dashboard.py - Learning analytics → Learning database: loads metrics
views/analytics.py - Learning analytics → Course manager: uses curriculum
views/analytics.py - SARVA AI assistant → Gemini AI service: requests responses
components/sarva_ai.py - SARVA AI assistant → Learning database: loads learning context
components/sarva_ai.py - Gemini AI service → Google Gemini: calls model
core/ai_service.py - Ask AI Why → Gemini AI service: requests diagnosis explanation
components/ask_ai_why.py - Ask AI Why → Misconception diagnosis: uses diagnosis
components/ask_ai_why.py - Rewards view → Rewards engine: loads rewards
views/rewards_view.py