AdvancedLangChainEnglish15 pages
LangChain – Building LLM Applications
Explore Transformer Architecture through clear and well-structured handwritten notes. Understand self-attention, multi-head attention, transformer blocks and tensor shapes with step-by-step explanations and visual diagrams. Ideal for Deep Learning students, LLM developers and aspiring AI Engineers.
What you will learn
- ✓Understand LangChain architecture and core components.
- ✓Integrate chat models and configure model parameters.
- ✓Create reusable prompt templates and manage context.
- ✓Build LLM workflows using LCEL and Runnables.
- ✓Generate structured outputs using parsers and Pydantic.
- ✓Load, clean and split documents for retrieval.
- ✓Build RAG pipelines using retrievers and vector stores.
- ✓Integrate external tools and APIs with LLM applications.
- ✓Understand AI agents, middleware and human approval.
- ✓Build stateful workflows using LangGraph.
- ✓Understand checkpointing, conversation state and memory.
- ✓Implement streaming, asynchronous and batch execution.
- ✓Handle API timeouts, retries and reliability issues.
- ✓Test, evaluate and trace LLM applications.
- ✓Apply security and deployment best practices.
- ✓Prepare for LangChain and LLM engineering interviews.
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Licence
Total₹129
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Details
- Pages
- 15
- Category
- LangChain and LangGraph
- Subject
- LangChain
- Format
- PDF (watermarked)