{"id":27837025,"url":"https://github.com/MotiaDev/motia-examples","last_synced_at":"2025-05-02T18:04:57.795Z","repository":{"id":275359379,"uuid":"925853480","full_name":"MotiaDev/motia-examples","owner":"MotiaDev","description":"A community maintained list of flow examples built with 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Motia Examples 🚀\n\nWelcome to the official examples repository for [Motia](https://motia.dev/) - the powerful agent development platform that helps you build, visualize, and deploy AI-powered agents with ease.\n\n## What is Motia?\n\nMotia is a modern agent development platform that enables you to:\n\n- **Build versatile agents** - Connect APIs, databases, AI services, and custom logic in a visual interface\n- **Create event-driven architectures** - Build reactive systems that respond to webhooks, scheduled tasks, and internal events\n- **Leverage AI capabilities** - Integrate with LLMs and other AI services to build intelligent agents\n- **Deploy with confidence** - Run your agents reliably in any environment with robust testing and monitoring\n\n## 🗂 Examples\n\n### AI Deep Research Agent\n\nA powerful research assistant that performs comprehensive web research on any topic or question, providing in-depth analysis and reports.\n\n![Finance Agent](examples/ai-deep-research-agent/docs/deep-research1.png)\n\n**Key Features:**\n- Deep Web Research: Searches the web, extracts content, and synthesizes findings\n- Iterative Research Process: Supports multiple research depths for comprehensive exploration\n- API Endpoints: REST API for initiating research and retrieving reports\n- Parallel Processing: Efficiently processes search results and content extraction\n\n**Technologies:** TypeScript, OpenAI, Firecrawl API\n\n[View Example →](examples/ai-deep-research-agent)\n\n### Finance Agent\n\nA powerful event-driven financial analysis workflow built with Motia that combines web search, financial data, and AI analysis to provide comprehensive investment insights.\n\n![Finance Agent](examples/finance-agent/docs/finance-agent.png)\n\n**Key Features:**\n- Real-time Financial Analysis: Combines multiple data sources for comprehensive insights\n- AI-Powered Insights: Leverages OpenAI GPT-4 for intelligent market analysis\n- Web Search Integration: Aggregates latest market news and analysis\n- Financial Data Integration: Real-time stock and company information\n\n**Technologies:** TypeScript, Alpha Vantage API, SerperDev, OpenAI\n\n[View Example →](examples/finance-agent)\n\n### GitHub Integration Agent\n\nA comprehensive agent for automating GitHub issue and pull request management using AI-powered classification and routing.\n\n\u003cdiv style=\"display: flex; gap: 10px;\"\u003e\n  \u003cimg src=\"examples/github-integration-workflow/docs/images/github-pr-management.png\" width=\"49%\" alt=\"GitHub PR Integration Agent\" /\u003e\n  \u003cimg src=\"examples/github-integration-workflow/docs/images/github-issue-management.png\" width=\"49%\" alt=\"GitHub Issue Integration Agent\" /\u003e\n\u003c/div\u003e\n\n**Key Features:**\n- AI-powered issue and PR classification\n- Automatic label assignment based on content\n- Smart reviewer suggestions based on expertise\n- Automatic movement between stages in the development lifecycle\n\n**Technologies:** TypeScript, OpenAI, GitHub API\n\n[View Example →](examples/github-integration-workflow)\n\n### Gmail Account Manager\n\nAn intelligent Gmail agent that monitors, analyzes, and automatically responds to incoming emails.\n\n![Gmail Agent](examples/gmail-workflow/docs/images/gmail-flow.png)\n\n**Key Features:**\n- Email classification and urgency detection\n- Automated responses based on content analysis\n- Smart email organization\n- Daily summaries via Discord\n\n**Technologies:** TypeScript, Python, Google APIs, Discord, Hugging Face\n\n[View Example →](examples/gmail-workflow)\n\n### Trello Task Automation\n\nStreamline development processes with an intelligent task progression agent for Trello boards.\n\n![Trello Agent](examples/trello-flow/docs/images/trello-manager.png)\n\n**Key Features:**\n- Automated card movement between lists\n- Task validation and requirement checking\n- AI-generated task summaries\n- Slack integration for notifications\n\n**Technologies:** TypeScript, Trello API, OpenAI, Slack\n\n[View Example →](examples/trello-flow)\n\n### Retrieval-Augmented Generation (RAG)\n\nA complete RAG agent implementation for building knowledge-based AI applications.\n\n![RAG Agent](examples/rag_example/docs/images/parse-embed-rag.png)\n\n**Key Features:**\n- Web page content extraction and parsing\n- Text chunking and embedding\n- Vector database integration\n- AI-powered question answering\n\n**Technologies:** Python, TypeScript, FAISS, Google's Generative AI\n\n[View Example →](examples/rag_example)\n\n### AI Image Generation and Evaluation\n\nAn agent that generates and evaluates AI images with feedback loops and quality metrics.\n\n\u003cdiv style=\"display: flex; gap: 10px;\"\u003e\n  \u003cimg src=\"examples/vision-example/docs/images/generate-image.png\" width=\"49%\" alt=\"Vision Agent\" /\u003e\n  \u003cimg src=\"examples/vision-example/docs/images/eval-agent.png\" width=\"49%\" alt=\"Evaluation Results\" /\u003e\n\u003c/div\u003e\n\n**Key Features:**\n- Prompt enhancement with AI\n- Image generation with Flux\n- Evaluation of generated images\n- Dataset reports with quality metrics\n\n**Technologies:** TypeScript, Python, Claude, Flux, OpenAI\n\n[View Example →](examples/vision-example)\n\n### PDF RAG Agent using Motia, Docling and Weaviate\n\nAn LLM chat-like question-answering system with RAG (Retrieval-Augmented Generation) to provide accurate answers from PDF documents.\nThe system leverages Docling to parse and intelligently chunk PDF documents, Weaviate as a vector database to store vectorized chunks, and OpenAI for embeddings and text generation.\n\n\u003cdiv style=\"display: flex; gap: 10px;\"\u003e\n  \u003cimg src=\"examples/rag-docling-weaviate-agent/docs/images/workbench.png\" alt=\"PDF RAG Docling Weaviate Agent\" /\u003e\n\u003c/div\u003e\n\n**Key Features:**\n- PDF document processing and chunking\n- Vector storage using Weaviate\n- Docling for PDF parsing and hybrid chunking\n- OpenAI integration for embeddings and text generation\n- Question answering using RAG pattern\n\n**Technologies:** TypeScript, Python, Docling, Weaviate, OpenAI\n\n[View Example →](examples/rag-docling-weaviate-agent)\n\n## 🚀 Getting Started\n\nEach example includes its own README with detailed setup instructions. Generally, you'll need:\n\n1. Clone this repository\n2. Navigate to the example directory\n3. Install dependencies\n4. Configure environment variables\n5. Run the agent with Motia\n\n## 🤝 Contributing\n\nWe welcome contributions! If you've built an interesting agent with Motia, please share it by following our [contribution guidelines](CONTRIBUTING.md).\n\n## 📝 License\n\nThis repository and its contents are licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## 📚 Learn More\n\n- [Motia Documentation](https://motia.dev/docs)\n- [API Reference](https://motia.dev/docs/api)\n- [Tutorial Videos](https://motia.dev/resources)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMotiaDev%2Fmotia-examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FMotiaDev%2Fmotia-examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMotiaDev%2Fmotia-examples/lists"}