How vaidhika1105/ai-search-engine works
This is a multi-platform repository discovery and analysis application: users search repositories, inspect details, compare projects, explore trending results, and access recommendations and saved/history features. The frontend search page shown uses mock repository data, while the backend exposes provider-backed discovery and initializes an AI facade for semantic search, query understanding, ranking, recommendations, and summarization. Several backend routes and AI modules are indexed but not excerpted, so their subsystem coverage is shown without asserting unverified calls.
Main entry points: facade.py AI facade · main.py FastAPI application · search.py Search route · App.jsx Route application
Components 22
Web interface
- Route application
frontend/src/App.jsx - Search page
frontend/src/pages/Search.jsx - Mock repositories
frontend/src/data/mockRepositories.js - Explore pages
frontend/src/pages - API client
frontend/src/services/api.js
Backend API
- FastAPI application
backend/app/main.py - Search route
backend/app/routers/search.py - Feature routes
backend/app/routers - SQLite database
backend/app/database.py - History and favorites
backend/app/database_models.py - AI service adapter
backend/app/services/ai_service.py
Repository discovery
- Discovery service
backend/app/services/discovery_service.py - Platform providers
backend/app/services/providers
AI search
- AI facade
ai-search/ai/facade.py - Query understanding
ai-search/ai/query_processor/engine.py - Semantic search
ai-search/ai/semantic_search/search_engine.py - FAISS index
ai-search/ai/semantic_search/faiss_index.py - Result ranking
ai-search/ai/ranking/service.py - Recommendations
ai-search/ai/recommendation/engine.py - Repository summaries
ai-search/ai/summarizer/summarizer.py - Embedding generation
ai-search/ai/embeddings/generator.py
Other components
- User
Connections 21
- User → Route application: uses
frontend/src/App.jsx - Route application → Search page: routes to
frontend/src/App.jsx - Route application → Explore pages: routes to
frontend/src/App.jsx - Search page → Mock repositories: filters
frontend/src/pages/Search.jsx - FastAPI application → Search route: registers
backend/app/main.py - FastAPI application → Feature routes: registers
backend/app/main.py - Search route → Discovery service: queries
backend/app/routers/search.py - Search route → SQLite database: accesses
backend/app/routers/search.py - Search route → History and favorites: uses
backend/app/routers/search.py - Discovery service → Platform providers: dispatches
backend/app/services/discovery_service.py - FastAPI application → SQLite database: creates tables
backend/app/main.py - History and favorites → SQLite database: uses base
backend/app/database_models.py - FastAPI application → AI facade: initializes
backend/app/main.py - AI facade → Query understanding: uses
ai-search/ai/facade.py - AI facade → Semantic search: uses
ai-search/ai/facade.py - AI facade → FAISS index: uses
ai-search/ai/facade.py - AI facade → Result ranking: uses
ai-search/ai/facade.py - AI facade → Recommendations: uses
ai-search/ai/facade.py - AI facade → Repository summaries: uses
ai-search/ai/facade.py - AI facade → Embedding generation: uses
ai-search/ai/facade.py - Semantic search → FAISS index: builds and searches
ai-search/ai/semantic_search/search_engine.py