Tag: LangChain

Learn to build and deploy advanced AI applications using prompt engineering and agentic AI workflows, focusing on practical, …

Learn to build a Retrieval-Augmented Generation (RAG) system from scratch, covering document chunking, generating embeddings, and utilizing …

Unpack the core components of an Agentic AI system: the LLM brain, crucial memory, external tools, and intelligent planning mechanisms. …

Learn how to orchestrate complex AI agents using popular frameworks like LangChain and LlamaIndex, integrating LLMs, tools, and memory for …

Extend your AI agents' capabilities by integrating custom tools and external APIs to access real-time data and perform actions beyond their …

Explore persistent agent memory, distinguishing between short-term context and long-term knowledge bases for robust, production-ready AI …

Dive into advanced design patterns for building robust, scalable, and reliable AI agents ready for production environments.

Dive into LangGraph to build dynamic, stateful AI agent workflows. Learn about state machines, graph nodes, and edges for complex agent …

Learn how to implement distributed tracing for AI systems, covering OpenTelemetry setup, instrumenting LLM calls, and tracking critical …

Learn to build a simple Retrieval Augmented Generation (RAG) agent that leverages vector memory and conversational history to provide …

Explore agentic retrieval, a paradigm where LLMs act as intelligent agents to plan and execute complex information retrieval tasks, going …

Get hands-on building your first autonomous AI agent using Python and LangChain. Learn to integrate LLMs, tools, and memory to create a …