How mpesic84/awesome-llm-apps works
Awesome LLM Apps is a curated collection of independently runnable AI application examples, not a single integrated service. Users choose an app, provide a prompt or source material, and receive a generated answer, plan, or media artifact. The graph highlights documented RAG, agent-team, MCP, podcast, and model-routing examples. Sampled source supports only selected runtime connections; other README capabilities are represented at their enclosing paths without inferred wiring.
Main entry points: query_router.py Math answer routing · beifong News podcast app · ai_blog_search/app.py Blog search · ai_travel_planner_mcp_agent_team/app.py Travel planner
Components 27
App collection
- RAG examples
rag_tutorials - Agent examples
advanced_ai_agents - MCP examples
mcp_ai_agents - Voice examples
voice_ai_agents - Memory tutorials
advanced_llm_apps
RAG apps
- Blog search
rag_tutorials/ai_blog_search/app.py - Web ingestion
rag_tutorials/ai_blog_search/app.py - Retrieval workflow
rag_tutorials/ai_blog_search/app.py - Vector store
rag_tutorials/ai_blog_search/app.py - Math answer routing
rag_tutorials/agentic_rag_math_agent/rag/query_router.py - Math knowledge base
rag_tutorials/agentic_rag_math_agent/rag/query_router.py
Agent teams
- Travel planner
mcp_ai_agents/ai_travel_planner_mcp_agent_team/app.py - Travel specialists
mcp_ai_agents/ai_travel_planner_mcp_agent_team/app.py - Domain agent teams
advanced_ai_agents/multi_agent_apps/agent_teams
Media agents
- News podcast app
advanced_ai_agents/multi_agent_apps/ai_news_and_podcast_agents/beifong - Podcast agents
advanced_ai_agents/multi_agent_apps/ai_news_and_podcast_agents/beifong/agents - Audio generation
advanced_ai_agents/multi_agent_apps/ai_news_and_podcast_agents/beifong/utils/tts_engine_selector.py - Podcast sessions
advanced_ai_agents/multi_agent_apps/ai_news_and_podcast_agents/beifong/services/internal_session_service.py
External services
- Model routing chat
advanced_llm_apps/cursor_ai_experiments/llm_router_app/llm_router.py - Browser MCP agent
mcp_ai_agents/browser_mcp_agent/main.py - MCP tools
mcp_ai_agents/ai_travel_planner_mcp_agent_team/app.py - Qdrant
- Web sources
- Model services
- Browser service
- Speech services
Other components
- App user
Connections 24
- App user → Blog search: asks questions
- App user → Math answer routing: asks math
- App user → Travel planner: requests trip
- App user → News podcast app: requests podcast
- App user → Model routing chat: sends prompt
- App user → Browser MCP agent: gives command
- Blog search → Web ingestion: adds sources
- Web ingestion → Vector store: stores chunks
- Retrieval workflow → Vector store: retrieves chunks
- Blog search → Retrieval workflow: runs query
- Web ingestion → Web sources: loads pages
- Math answer routing → Math knowledge base: retrieves answer
- Math answer routing → Model services: generates explanation
- Math answer routing → Web sources: searches fallback
- Travel planner → Travel specialists: runs team
- Travel planner → MCP tools: attaches tools
- Travel specialists → MCP tools: invoke tools
- MCP tools → Model services: queries services
- News podcast app → Podcast agents: coordinates
- News podcast app → Audio generation: requests audio
- Audio generation → Speech services: generates speech
- News podcast app → Podcast sessions: stores session
- Model routing chat → Model services: routes prompts
- Browser MCP agent → Browser service: controls browser