[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-11":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":9,"totalLinesOfCode":9,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":9,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":9,"rankLanguage":9,"license":9,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":22,"topics":24,"createdAt":9,"pushedAt":9,"updatedAt":30,"readmeContent":31,"aiSummary":32,"trendingCount":16,"starSnapshotCount":16,"syncStatus":33,"lastSyncTime":34,"discoverSource":35},11,"awesome-ai-apps","Arindam200\u002Fawesome-ai-apps","Arindam200","A collection of projects showcasing RAG, agents, workflows, and other AI use cases",null,"https:\u002F\u002Fgithub.com\u002FArindam200\u002Fawesome-ai-apps","Python",12756,1631,112,40,0,152,205,648,456,44.64,false,"main",[25,26,27,28,29],"agents","ai","llm","mcp","hacktoberfest","2026-06-12 02:00:06","![Banner](\u002Fassets\u002Fbanner_new.png)\n\n\u003Cdiv align=\"center\">\n\n# Awesome AI Apps [![Awesome](https:\u002F\u002Fawesome.re\u002Fbadge.svg)](https:\u002F\u002Fawesome.re)\n\n\u003Ca href=\"https:\u002F\u002Ftrendshift.io\u002Frepositories\u002F14662\" target=\"_blank\">\u003Cimg src=\"https:\u002F\u002Ftrendshift.io\u002Fapi\u002Fbadge\u002Frepositories\u002F14662\" alt=\"Arindam200%2Fawesome-ai-apps | Trendshift\" style=\"width: 250px; height: 55px;\" width=\"250\" height=\"55\"\u002F>\u003C\u002Fa>\n\n\u003C\u002Fdiv>\n\nThis repository is a comprehensive collection of **80+ practical examples, tutorials, and recipes** for building powerful LLM-powered applications — including text agents, voice assistants, RAG apps, and MCP-backed tools. These projects serve as a guide for developers working with various AI frameworks and stacks.\n\n## 📋 Table of Contents\n\n- [🎓 Courses](#-courses)\n- [🚀 Featured AI Apps](#-featured-ai-apps)\n  - [🧩 Starter Agents](#-starter-agents)\n  - [🪶 Simple Agents](#-simple-agents)\n  - [🎙️ Voice Agents](#-voice-agents)\n  - [🗂️ MCP Agents](#️-mcp-agents)\n  - [🧠 Memory Agents](#-memory-agents)\n  - [📚 RAG Applications](#-rag-applications)\n  - [🔬 Advanced Agents](#-advanced-agents)\n- [📺 Tutorials & Videos](#-tutorials--videos)\n- [🚀 Getting Started](#getting-started)\n- [🤝 Contributing](#-contributing)\n\n---\n\n\u003Cdiv align=\"center\">\n\n## 💎 Sponsors\n\n\u003Cp align=\"center\">\n  A huge thank you to our sponsors for their generous support!\n\u003C\u002Fp>\n\n\u003Ctable align=\"center\" cellpadding=\"10\" style=\"width:100%; border-collapse:collapse;\">\n  \u003Ctr align=\"center\">\n    \u003Ctd width=\"300\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fbrightdata\" target=\"_blank\" title=\"Visit Bright Data\">\n        \u003Cimg src=\"https:\u002F\u002Fmintlify.s3.us-west-1.amazonaws.com\u002Fbrightdata\u002Flogo\u002Flight.svg\" height=\"35\" style=\"max-width:180px;\" alt=\"Bright Data - Web Data Platform\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">Web Data Platform\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fbrightdata\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"Visit Bright Data website\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n    \u003Ctd width=\"300\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fnebius\" target=\"_blank\" title=\"Visit Nebius Token Factory\">\n        \u003Cimg src=\".\u002Fassets\u002Fnebius.png\" height=\"36\" style=\"max-width:180px;\" alt=\"Nebius Token Factory\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">AI Inference Provider\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fnebius\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"Visit Nebius Token Factory\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n    \u003Ctd width=\"300\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fscrapegraphai\" target=\"_blank\" title=\"Visit ScrapeGraphAI on GitHub\">\n        \u003Cimg src=\"https:\u002F\u002Fraw.githubusercontent.com\u002FScrapeGraphAI\u002FScrapeGraph-AI\u002Fmain\u002Fdocs\u002Fassets\u002Fscrapegraphai_logo.png\" height=\"44\" style=\"max-width:180px;\" alt=\"ScrapeGraphAI - Web Scraping Library\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">AI Web Scraping framework\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fscrapegraphai\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"View ScrapeGraphAI on GitHub\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n  \u003C\u002Ftr>\n  \u003Ctr align=\"center\">\n    \u003Ctd width=\"300\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fmemorilabs\" target=\"_blank\" title=\"Visit Memorilabs\">\n        \u003Cimg src=\"assets\u002Fmemori.png\" height=\"36\" style=\"max-width:180px;\" alt=\"Memori - SQL Native Memory for AI\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">SQL Native Memory for AI\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fmemorilabs\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"Visit Memorilabs website\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n    \u003Ctd width=\"300\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fcopilotkit\" target=\"_blank\" title=\"Visit CopilotKit\">\n        \u003Cimg src=\"assets\u002Fcopilot-kit-logo.svg\" height=\"36\" style=\"max-width:180px;\" alt=\"CopilotKit - Agentic Application Platform\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">Agentic Application Platform\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fcopilotkit\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"Visit CopilotKit website\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n    \u003Ctd width=\"300\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fscalekitt\" target=\"_blank\" title=\"Visit ScaleKit\">\n        \u003Cimg src=\"assets\u002Fscalekit.svg\" height=\"36\" style=\"max-width:180px;\" alt=\"ScaleKit - Auth Stack for AI\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">Auth Stack for AI\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fscalekitt\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"Visit ScaleKit website\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n  \u003C\u002Ftr>\n  \u003Ctr align=\"center\">\n    \u003Ctd width=\"200\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fokahu.ai\" target=\"_blank\" title=\"Visit Okahu\">\n        \u003Cimg src=\"assets\u002Fokahu.png\" height=\"36\" style=\"max-width:180px;\" alt=\"Okahu - AI Platform\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">AI Observability Platform\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fokahu.ai\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"Visit Okahu website\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n    \u003Ctd width=\"200\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fdub.sh\u002FserpApi\" target=\"_blank\" title=\"Visit SerpApi\">\n        \u003Cimg src=\"assets\u002Fserpapi.png\" height=\"36\" style=\"max-width:180px;\" alt=\"SerpApi - Google Search API\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">Google Search API\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fdub.sh\u002FserpApi\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"Visit SerpApi website\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n    \u003Ctd width=\"200\" valign=\"middle\" align=\"center\">\n      \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fagentfield\" target=\"_blank\" title=\"Visit AgentField\">\n        \u003Cimg src=\"assets\u002Fagentfield.png\" height=\"40\" style=\"max-width:180px;\" alt=\"AgentField - Kubernetes for AI Agents\">\n      \u003C\u002Fa>\n      \u003Cbr>\n      \u003Csub>\n        \u003Cspan style=\"white-space:nowrap;\">Kubernetes for AI Agents\u003C\u002Fspan>\n        \u003Cbr>\n        \u003Ca href=\"https:\u002F\u002Fdub.sh\u002Fagentfield\" target=\"_blank\">\n          \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FVisit%20Site-blue?style=flat-square\" alt=\"Visit AgentField website\">\n        \u003C\u002Fa>\n      \u003C\u002Fsub>\n    \u003C\u002Ftd>\n  \u003C\u002Ftr>\n\n   \n\n\u003C\u002Ftable>\n\n### 💎 Become a Sponsor\n\n\u003Cp align=\"center\">\nInterested in sponsoring this project? Feel free to reach out!\n\u003Cbr\u002F>\n\u003Ca href=\"https:\u002F\u002Fdub.sh\u002Farindam-linkedin\" target=\"_blank\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white\" alt=\"LinkedIn\">\n\u003C\u002Fa>\n\u003Ca href=\"mailto:arindammajumder2020@gmail.com\">\n    \u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEmail-D14836?style=for-the-badge&logo=gmail&logoColor=white\" alt=\"Email\">\n\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003C\u002Fdiv>\n\n---\n\n## 🎓 Courses\n\n### AWS Strands Course for Beginners\n\n**Comprehensive hands-on course on building AI agents with AWS Strands SDK:**\n\n- [**AWS Strands Course**](course\u002Faws_strands) - Complete 8-lesson course covering agent fundamentals to production patterns\n  - **Foundation**: Basic agents, session management, structured output\n  - **Integration**: MCP agents, human-in-the-loop patterns\n  - **Multi-Agent**: Orchestrator agents, swarm intelligence, graph workflows\n  - **Production**: Observability, safety guardrails, and best practices\n\n## 🚀 Featured AI Apps\n\n### 🧩 Starter Agents\n\n**Quick-start agents for learning and extending different AI frameworks.** _19 projects_\n\n- [Agno HackerNews Analysis](starter_ai_agents\u002Fagno_starter) - Agno-based agent for trend analysis on HackerNews\n- [OpenAI SDK Starter](starter_ai_agents\u002Fopenai_agents_sdk) - OpenAI Agents SDK with email helper & haiku writer examples\n- [LlamaIndex Task Manager](starter_ai_agents\u002Fllamaindex_starter) - LlamaIndex-powered task assistant\n- [CrewAI Research Crew](starter_ai_agents\u002Fcrewai_starter) - Multi-agent research team example\n- [Letta Starter](starter_ai_agents\u002Fletta_starter) - Stateful agent with persistent long-term memory across sessions\n- [PydanticAI Weather Bot](starter_ai_agents\u002Fpydantic_starter) - Real-time weather information agent\n- [LangChain Starter](starter_ai_agents\u002Flangchain_starter) - LangChain tool-calling agent with `create_tool_calling_agent` + `AgentExecutor`, powered by Nebius\n- [LangGraph Starter](starter_ai_agents\u002Flanggraph_starter) - LangGraph prebuilt ReAct agent (`create_react_agent`) with custom tools, powered by Nebius\n- [AWS Strands Agent Starter](starter_ai_agents\u002Faws_strands_starter) - Weather report agent using AWS Strands SDK\n- [Mastra Starter](starter_ai_agents\u002Fmastra_starter) - TypeScript-first agent with a custom tool powered by Nebius Token Factory\n- [Camel AI Starter](starter_ai_agents\u002Fcamel_ai_starter) - Performance benchmarking tool comparing various AI models\n- [DSPy Starter](starter_ai_agents\u002Fdspy_starter) - DSPy framework for building and optimizing AI systems\n- [Google ADK Starter](starter_ai_agents\u002Fgoogle_adk_starter) - Google Agent Development Kit starter template\n- [Semantic Kernel Starter](starter_ai_agents\u002Fsemantic_kernel_starter) - Microsoft Semantic Kernel `ChatCompletionAgent` with plugin-based tool calling\n- [smolagents Starter](starter_ai_agents\u002Fsmolagents_starter) - Hugging Face smolagents code-first web-search agent\n- [AutoGen Starter](starter_ai_agents\u002Fautogen_starter) - Microsoft AutoGen `AssistantAgent` with a custom tool, powered by Nebius Token Factory\n- [cagent Starter](starter_ai_agents\u002Fcagent_starter) - Open-source customizable multi-agent runtime by Docker\n- [Sayna Voice Agent](starter_ai_agents\u002Fsayna_starter) - Real-time voice infrastructure with multi-provider STT\u002FTTS (Deepgram, ElevenLabs, Azure, Google) and WebSocket streaming\n- [KAOS Starter](starter_ai_agents\u002Fkaos_starter) - Kubernetes-native multi-agent system with MCP tools and in-cluster LLM\n\n### 🪶 Simple Agents\n\n**Straightforward, practical use-cases for everyday AI applications.** _14 projects_\n\n- [Agno AI Examples](simple_ai_agents\u002Fagno_ai_examples) - Simple to multi-agent examples with web search & knowledge base\n- [Finance Agent](simple_ai_agents\u002Ffinance_agent) - Real-time stock & market data tracking agent\n- [Human-in-the-Loop Agent](simple_ai_agents\u002Fhuman_in_the_loop_agent) - HITL actions for safe AI task execution\n- [Newsletter Generator](simple_ai_agents\u002Fnewsletter_agent) - AI-powered newsletter builder with Firecrawl integration\n- [Reasoning Agent](simple_ai_agents\u002Freasoning_agent) - Step-by-step financial reasoning demonstration\n- [Agno UI Example](simple_ai_agents\u002Fagno_ui_agent) - Interactive UI for web & finance agents\n- [Mastra Weather Bot](simple_ai_agents\u002Fmastra_ai_weather_agent) - Weather updates using Mastra AI framework\n- [Calendar Assistant](simple_ai_agents\u002Fcal_scheduling_agent) - Calendar scheduling integration with Cal.com\n- [Smart Scheduler Assistant](simple_ai_agents\u002Femail_to_calendar_scheduler) - AI-powered Gmail reader and Google Calendar manager\n- [Web Automation Agent](simple_ai_agents\u002Fbrowser_agent) - Browser automation agent using Nebius & browser-use\n- [Nebius Chat](simple_ai_agents\u002Fnebius_chat) - Chat interface for Nebius Token Factory\n- [RouteLLM Chat](simple_ai_agents\u002Fllm_router) - Intelligent model routing with RouteLLM (GPT-4o-mini vs Nebius Llama) for cost optimization\n- [Talk to Your DB](simple_ai_agents\u002Ftalk_to_db) - Natural language database queries with GibsonAI & LangChain\n- [Agent Discovery Agent](simple_ai_agents\u002Fagent_discovery_agent) - Find and compare AI agents across NANDA, MCP, Virtuals, A2A, and ERC-8004 registries\n\n### 🎙️ Voice Agents\n\n**Real-time voice assistants and streaming speech pipelines.** _6 projects_\n\n- [Healthcare Voice Contact Center](voice_agents\u002Fhealthcare_contact_center) - Pipecat healthcare contact center with appointment booking, FAQ handling, and supervisor escalation\n- [LiveKit + Gemini Realtime](voice_agents\u002Flivekit_gemini_agents) - LiveKit Agents with Google Gemini Live (`gemini` multimodal realtime) for low-latency voice conversations in a LiveKit room\n- [LiveKit Voice Agent with Web Search](voice_agents\u002Flivekit_web_search_agent) - LiveKit + Gemini realtime voice agent with an Olostep-backed `web_search` tool for fresh, source-cited answers\n- [LiveKit RSVP Confirmation Agent](voice_agents\u002Flivekit_rsvp_agent) - Outbound voice agent that calls attendees, confirms RSVPs, and updates a JSON-backed event database\n- [Pipecat + Sarvam](voice_agents\u002Fpipecat_agent) - Pipecat voice pipeline with Sarvam STT\u002FTTS and OpenAI for chat; WebRTC (browser) or Daily transport via the Pipecat runner\n- [Speed-to-Lead Voice Agent](voice_agents\u002Fspeed_to_lead_agent) - LiveKit-based voice agent that calls inbound leads instantly, routes them to specialists, and logs to a mock CRM\n\n### 🗂️ MCP Agents\n\n**Examples using Model Context Protocol for external tool integration.** _13 projects_\n\n- [Doc-MCP](mcp_ai_agents\u002Fdoc_mcp) - Semantic RAG documentation & Q&A system\n- [LangGraph MCP Agent](mcp_ai_agents\u002Flangchain_langgraph_mcp_agent) - LangChain ReAct agent with Couchbase integration\n- [GitHub MCP Agent](mcp_ai_agents\u002Fgithub_mcp_agent) - Repository insights and analysis via MCP\n- [MCP Starter](mcp_ai_agents\u002Fmcp_starter) - GitHub repository analyzer starter template\n- [Talk to your Docs](mcp_ai_agents\u002Fdocs_qna_agent) - Documentation Q&A agent with MCP\n- [Database MCP Agent](mcp_ai_agents\u002Fdatabase_mcp_agent) - Conversational AI agent for managing GibsonAI database projects and schemas\n- [Hotel Finder Agent](mcp_ai_agents\u002Fhotel_finder_agent) - Hotel search and booking using MCP integration\n- [Custom MCP Server](mcp_ai_agents\u002Fcustom_mcp_server) - Custom MCP server implementation example\n- [Couchbase MCP Server](mcp_ai_agents\u002Fcouchbase_mcp_server) - Couchbase database integration with MCP protocol\n- [ScaleKit Exa MCP Security](mcp_ai_agents\u002Fscalekit-exa-mcp-security) - Security-focused MCP integration with Exa search\n- [Docker E2B MCP Agent](mcp_ai_agents\u002Fe2b_docker_mcp_agent) - Secure AI agent for running agents in sandboxed Docker environments via MCP Gateway\n- [Taskade MCP Agent](mcp_ai_agents\u002Ftaskade_mcp_agent) - AI-powered workspace agent for managing projects, tasks, and workflows via Taskade MCP\n- [Telemetry MCP Okahu](mcp_ai_agents\u002Ftelemetry-mcp-okahu) - Self-healing Text-to-SQL demo using Okahu Cloud traces via hosted MCP\n\n### 🧠 Memory Agents\n\n**Agents with advanced memory capabilities for context retention and personalization.** _12 projects_\n\n- [Agno Memory Agent](memory_agents\u002Fagno_memory_agent) - Agno-based agent with persistent memory capabilities\n- [arXiv Researcher Agent with Memori](memory_agents\u002Farxiv_researcher_agent_with_memori) - Research assistant using OpenAI Agents and GibsonAI Memori\n- [AWS Strands Agent with Memori](memory_agents\u002Faws_strands_agent_with_memori) - AWS Strands agent enhanced with Memori memory system\n- [Blog Writing Agent](memory_agents\u002Fblog_writing_agent) - Personalized blog writing agent with memory for style consistency\n- [Social Media Agent](memory_agents\u002Fsocial_media_agent) - Social media automation agent with memory for brand voice\n- [Job Search Agent](memory_agents\u002Fjob_search_agent) - Job search agent with memory for preference tracking\n- [Brand Reputation Monitor](memory_agents\u002Fbrand_reputation_monitor) - AI-powered brand reputation monitoring with news analysis and sentiment tracking\n- [Product Launch Agent](memory_agents\u002Fproduct_launch_agent) - Competitive intelligence tool for analyzing competitor product launches\n- [AI Consultant Agent](memory_agents\u002Fai_consultant_agent\u002F) - AI-powered consulting agent using **Memori v3** as long-term memory fabric and **ExaAI** for research\n- [Customer Support Voice Agent](memory_agents\u002Fcustomer_support_voice_agent) - Voice-enabled customer support assistant with Memori v3 and Firecrawl for knowledge base management\n- [YouTube Trend Agent](memory_agents\u002Fyoutube_trend_agent) - YouTube channel analysis agent with Memori, Agno, and Exa for trend analysis and video ideas\n- [Study Coach Agent](memory_agents\u002Fstudy_coach_agent) - AI-powered study coach with Memori v3 and LangGraph for multi-step verification of understanding\n\n### 📚 RAG Applications\n\n**Retrieve-augmented generation examples for document understanding and knowledge bases.** _12 projects_\n\n- [Agentic RAG](rag_apps\u002Fagentic_rag) - Agentic RAG implementation with Agno & GPT-5\n- [Agentic RAG with Web Search](rag_apps\u002Fagentic_rag_with_web_search) - Advanced RAG with CrewAI, Qdrant, and Exa for hybrid search capabilities\n- [Resume Optimizer](rag_apps\u002Fresume_optimizer) - AI-powered resume optimization and enhancement tool\n- [LlamaIndex RAG Starter](rag_apps\u002FllamaIndex_starter) - LlamaIndex + Nebius RAG starter template\n- [PDF RAG Analyzer](rag_apps\u002Fpdf_rag_analyser) - Multi-PDF chat and analysis system\n- [Qwen3 RAG Chat](rag_apps\u002Fqwen3_rag) - PDF chatbot interface built with Streamlit\n- [Chat with Code](rag_apps\u002Fchat_with_code) - Conversational code explorer and documentation assistant\n- [Gemma3 OCR](rag_apps\u002Fgemma_ocr\u002F) - OCR-based document and image processor using Gemma3 model\n- [Nvidia Nemotron OCR](rag_apps\u002Fnvidia_ocr\u002F) - OCR-based document and image parsing using Nvidia Nemotron-Nano-V2-12b\n- [Contextual AI RAG](rag_apps\u002Fcontextual_ai_rag) - Enterprise-level RAG with managed datastores and quality evaluation\n- [Advanced RAG with Reranking](rag_apps\u002Fadvanced_rag_with_reranking) - Production-shaped PDF RAG with contextual retrieval, Qdrant hybrid search, reranking, streaming answers, upload ingestion, and clickable citations\n- [Simple RAG](rag_apps\u002Fsimple_rag) - Basic RAG implementation with Nebius for quick starts\n- [WFGY 16 Problem Map LLM Debugger](rag_apps\u002Fwfgy_llm_debugger) - 16-mode map based debugger for LLM and RAG bugs\n\n### 🔬 Advanced Agents\n\n**Complex multi-agent pipelines for production-ready end-to-end workflows.** _18 projects_\n\n- [Nebius AutoResearch](advance_ai_agents\u002Fnebius-autoresearch-autoresearch-mar30) - NYC taxi analytics pipeline optimizer; iterative code search with Nebius Token Factory (real-time or batch inference)\n- [AgentField Financial Research Agent](advance_ai_agents\u002Fagentfield_finance_research_agent) - Financial Research Agent with AgentField\n- [Due Diligence Agent](advance_ai_agents\u002Fdue_diligence_agent) - Multi-agent company due diligence pipeline with AG2 and TinyFish deep web scraping\n- [Deep Researcher](advance_ai_agents\u002Fdeep_researcher_agent) - Multi-stage research agent with Agno & ScrapeGraph AI\n- [Candilyzer](advance_ai_agents\u002Fcandidate_analyser) - Candidate analysis tool for GitHub\u002FLinkedIn profiles\n- [Job Finder](advance_ai_agents\u002Fjob_finder_agent) - LinkedIn job search automation with Bright Data integration\n- [AI Trend Analyzer](advance_ai_agents\u002Ftrend_analyzer_agent) - AI trend mining and analysis with Google ADK\n- [Conference Talk Generator](advance_ai_agents\u002Fconference_talk_abstract_generator) - Automated talk abstract generation with Google ADK & Couchbase\n- [Finance Service Agent](advance_ai_agents\u002Ffinance_service_agent) - FastAPI server for stock data and predictions with Agno\n- [Price Monitoring Agent](advance_ai_agents\u002Fprice_monitoring_agent) - Price monitoring and alerting agent powered by CrewAI, Twilio & Nebius\n- [Startup Idea Validator Agent](advance_ai_agents\u002Fstartup_idea_validator_agent) - Agentic workflow to validate and analyze startup ideas\n- [Meeting Assistant Agent](advance_ai_agents\u002Fmeeting_assistant_agent) - Automated meeting notes and task creation from conversations\n- [AI Hedgefund](advance_ai_agents\u002Fai-hedgefund) - Agentic workflow for comprehensive financial analysis\n- [Smart GTM Agent](advance_ai_agents\u002Fsmart_gtm_agent) - Go-to-market strategy and competitive analysis agent\n- [Conference Agnostic CFP Generator](advance_ai_agents\u002Fconference_agnositc_cfp_generator) - Automated conference proposal generation system\n- [Car Finder Agent](advance_ai_agents\u002Fcar_finder_agent) - AI-powered used car recommendation system with CrewAI and MongoDB\n- [Content Team Agent](advance_ai_agents\u002Fcontent_team_agent) - SEO content optimization workflow with Agno & SerpAPI for Google AI Search ranking\n- [Temporal Agents](advance_ai_agents\u002Ftemporal_agents\u002F) - Examples of Temporal based AI Agents\n\n## 📺 Tutorials & Videos\n\n### 🎓 Course Playlists\n\n- [**AWS Strands Course**](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLMZM1DAlf0Lrc43ZtUXAwYu9DhnqxzRKZ) - Complete 8-lesson course on building AI agents with AWS Strands SDK\n\n### 🔧 Framework Tutorials\n\n- [**Build with MCP**](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLMZM1DAlf0Lolxax4L2HS54Me8gn1gkz4) - Model Context Protocol tutorials and examples\n- [**Build AI Agents**](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PLMZM1DAlf0LqixhAG9BDk4O_FjqnaogK8) - General AI agent development tutorials\n- [**AI Agents, MCP and more...**](https:\u002F\u002Fwww.youtube.com\u002Fplaylist?list=PL2ambAOfYA6-LDz0KpVKu9vJKAqhv0KKI) - Mixed tutorials and project demos\n\n---\n\n\u003Cdiv align=\"center\">\n\n## 📥 Stay Updated with Daily AI Insight!\n\nGet easy-to-follow weekly tutorials and deep dives on AI, LLMs, and agent frameworks. Perfect for developers who want to learn, build, and stay ahead with new tech. Subscribe our Newsletter!\n\n[![Subscribe to our Newsletter](https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F990d1947-337b-4e87-a7e6-e619ec19dee6)](https:\u002F\u002Fmranand.substack.com\u002Fsubscribe)\n\n\u003C\u002Fdiv>\n\n---\n\n## Getting Started\n\n### Prerequisites\n\n- **Python 3.10+** (Python 3.11+ recommended for newer projects)\n- **Git** for cloning the repository\n- **Package Manager**: `pip` or `uv` (recommended for faster installs)\n- **API Keys**: Most projects require API keys (see individual project READMEs)\n\n### Quick Start\n\n1. **Clone the repository**\n\n   ```bash\n   git clone https:\u002F\u002Fgithub.com\u002FArindam200\u002Fawesome-ai-apps.git\n   cd awesome-ai-apps\n   ```\n\n2. **Choose a project** and navigate to its directory\n\n   ```bash\n   cd starter_ai_agents\u002Fagno_starter  # Example: Start with Agno starter\n   ```\n\n3. **Set up environment variables**\n\n   ```bash\n   cp .env.example .env  # Copy example environment file\n   # Edit .env with your API keys\n   ```\n\n4. **Install dependencies**\n\n   ```bash\n   # Using pip\n   pip install -r requirements.txt\n\n   # OR using uv (recommended - faster)\n   uv sync\n   # or\n   uv pip install -e .\n   ```\n\n5. **Run the project**\n\n   ```bash\n   python main.py\n   # or for Streamlit apps\n   streamlit run app.py\n   ```\n\n## 🤝 Contributing\n\nWe welcome contributions from the community! Here's how you can help:\n\n- 🐛 **Report bugs** or suggest improvements via [GitHub Issues](https:\u002F\u002Fgithub.com\u002FArindam200\u002Fawesome-ai-apps\u002Fissues)\n- 💡 **Add new projects** - Submit your own AI agent examples\n- 📝 **Improve documentation** - Help make projects more accessible\n- 🔧 **Fix issues** - Contribute code improvements and bug fixes\n\n**Before contributing:**\n\n- Read our [Contributing Guidelines](CONTRIBUTING.md) for detailed information\n- Check existing issues to avoid duplicates\n- Follow the project structure and naming conventions\n- Ensure your project includes a comprehensive README.md\n\n**Important:** This project follows a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By participating, you agree to abide by its terms.\n\n## 📜 License\n\nThis repository is licensed under the [MIT License](.\u002FLICENSE). Feel free to use and modify the examples for your projects.\n\n## 👥 Core Maintainers\n\nThis project is actively maintained by:\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FArindam200\" title=\"Arindam Majumder\">\n    \u003Cimg src=\"https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F109217591?s=128&v=4\" width=\"72\" height=\"72\" alt=\"Arindam Majumder\" style=\"border-radius: 50%;\" \u002F>\n  \u003C\u002Fa>\n     \n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fshivaylamba\" title=\"Shivay Lamba\">\n    \u003Cimg src=\"https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F19529592?s=128&v=4\" width=\"72\" height=\"72\" alt=\"Shivay Lamba\" style=\"border-radius: 50%;\" \u002F>\n  \u003C\u002Fa>\n     \n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FAstrodevil\" title=\"Astrodevil\">\n    \u003Cimg src=\"https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F73425223?s=128&v=4\" width=\"72\" height=\"72\" alt=\"Astrodevil\" style=\"border-radius: 50%;\" \u002F>\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Csub>\n    \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FArindam200\">Arindam Majumder\u003C\u002Fa>\n     · \n    \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fshivaylamba\">Shivay Lamba\u003C\u002Fa>\n     · \n    \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FAstrodevil\">Astrodevil\u003C\u002Fa>\n  \u003C\u002Fsub>\n\u003C\u002Fp>\n\nFor any questions, suggestions, or contributions, feel free to reach out to the maintainers.\n\n## Thank You for the Support! 🙏\n\n[![Star History Chart](https:\u002F\u002Fapi.star-history.com\u002Fsvg?repos=Arindam200\u002Fawesome-ai-apps&type=Date)](https:\u002F\u002Fwww.star-history.com\u002F#Arindam200\u002Fawesome-ai-apps&Date)\n","awesome-ai-apps 是一个汇集了80多个实用示例、教程和食谱的项目，旨在帮助开发者构建强大的基于大语言模型（LLM）的应用程序。该项目涵盖了文本代理、语音助手、RAG应用以及MCP支持的工具等多种AI用例，所有这些都使用Python编写。它不仅提供了丰富的案例研究，还为不同复杂度的AI应用场景提供了从入门到高级的开发指导。非常适合希望快速上手并深入理解如何将AI技术应用于实际问题解决中的开发者。",2,"2026-06-11 02:30:28","trending"]