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Welcome to Python for Generative AI — your step-by-step learning series to build real-world Generative AI applications using Python. In this video, you’ll learn how to split large JSON data efficiently for use in LLMs (Large Language Models). We’ll explore how the Recursive JSON Splitter in LangChain helps handle complex, nested JSON structures, control chunk sizes, and prepare clean, structured data for model ingestion. This session covers: ✅ Why JSON splitting is important for AI workflows ✅ How Recursive JSON Splitter works in LangChain ✅ Practical implementation in Python using API data ✅ Different ways to output JSON chunks, documents, and text By the end, you’ll know how to prepare large API responses or JSON datasets for use in your Generative AI pipelines. Watch the Full Playlist: LangChain Tutorial: From Python to GenAI! → https://youtube.com/playlist?list=PLkt9npIo1sXSKgNrdaF6RjlV-69NSsDLZ&si=dpcM71YqE3jiIchL Connect with Me: LinkedIn Profile : https://www.linkedin.com/in/punyakeerthi-bl-864382aa Email: punya8147@gmail.com 💡 If you found this helpful: 👍 Like the video 💬 Comment your questions or ideas 🔔 Subscribe to the channel for more videos on Generative AI, LangChain, and Python projects #PythonForGenerativeAI #GenerativeAI #LangChain #JSONSplitter #AIinPython #LLM #LangChainTutorial #AIDataProcessing #MachineLearning #ArtificialIntelligence #OpenAI #DataEngineering #DeepLearning #AIProjects #LLMTutorial #AIProgramming #PythonCoding #TechEducation #DataScience #APIDevelopment #PythonAutomation #AIWorkflow #LearnAI #AICoding #PythonTutorial #CodeWithPython #LangChainForAI #punyakeerthibl #pkaitechworld