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Zero-shot React Agent\n  - Conversational Agent\n  - Self-ask Agent\n  - Plan-and-Execute Agent\n  - ReAct Agent\n- Creating custom tools for agents\n- Implementing a multi-tool agent\n\n## Tutorial 5: Advanced Agent Techniques\n- Debugging and optimizing agent performance\n- Using the JSON Toolkit with agents\n- Integrating Pydantic for structured inputs and outputs\n- Building complex workflows with agents\n\n## Tutorial 6: Memory Systems in LangChain\n- Types of memory in LangChain\n- Implementing conversation memory\n- Creating a chatbot with long-term memory\n- Advanced memory techniques\n\n## Tutorial 7: Introduction to LangGraph\n- What is LangGraph and how does it differ from LangChain?\n- Basic concepts: Nodes, Edges, and Graphs\n- Setting up LangGraph\n- Creating your first LangGraph flow\n\n## Tutorial 8: Building Complex Flows with LangGraph\n- Designing multi-step workflows\n- Handling state and transitions\n- Implementing conditional logic in flows\n- Error handling and fallback strategies\n\n## Tutorial 9: Combining LangChain and LangGraph\n- Integrating LangChain components into LangGraph flows\n- Building a conversational AI system with both libraries\n- Optimizing performance in complex applications\n- Case study: A task planning and execution system\n\n## Tutorial 10: Real-world Applications\n- Building a content moderation system\n- Implementing a language translation service\n- Creating an automated customer support chatbot\n- Developing a text-based game with AI-driven narrative\n\n## Tutorial 11: Working with Structured Data\n- Introduction to Pydantic for data modeling\n- Creating structured inputs and outputs with Pydantic\n- Using the JSON Toolkit for complex data manipulation\n- Integrating structured data with LangChain and LangGraph\n\n## Tutorial 12: Advanced LangChain Techniques\n- Custom chain development\n- Prompt templating and management\n- Implementing retrieval-augmented generation (RAG)\n- Fine-tuning language models for specific tasks\n\n## Tutorial 13: Best Practices and Advanced Topics\n- Performance optimization techniques\n- Handling rate limits and API costs\n- Security considerations\n- Deploying LangChain and LangGraph applications\n- Monitoring and logging in production\n\n\n### Useful Repositories\n- #### LangChain\n  - https://github.com/langchain-ai/langchain\n  - https://github.com/kyrolabs/awesome-langchain\n- #### LangGraph \n  - https://github.com/NirDiamant/GenAI_Agents\n  - https://github.com/langchain-ai/langgraph\n  - https://github.com/langchain-ai/langgraph-example/tree/main\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdooml%2Flangchain-langgraph-tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdooml%2Flangchain-langgraph-tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdooml%2Flangchain-langgraph-tutorial/lists"}