LangChain Overview | RAG_Prompt Engg, Fine Tuning using Langchain | Scodeen Global

LangChain Overview — From Concepts to Production-Ready Workflows

RAG ,Prompt engineering , Fine tuning using Langchain -Production level code discussion

Description: In this video, we break down LangChain from the ground up and show how to take it from a cool prototype to reliable, production-grade systems. You’ll learn the core building blocks, how they fit together, and the patterns that actually hold up in real-world apps.

What we cover:

What LangChain is and when to use it
Core primitives: Models, Prompts, Tools, Chains, Agents, Runnables
Structured outputs and schemas (Pydantic / JSONMode)
Tools and retrieval: Retrievers, VectorStores, RAG pipelines
Observability and tracing (LangSmith) for debugging and evals
Production patterns: deterministic prompts, retries, timeouts, fallbacks
Memory strategies (conversation vs. retrieval vs. summaries)
Caching, batching, streaming, and concurrency
Guardrails, validation, and safety checks
Deployment tips: environments, secrets, versioning, and cost controls
Testing: unit tests for chains, offline fixtures, golden outputs
Common pitfalls and how to avoid them

Видео LangChain Overview | RAG_Prompt Engg, Fine Tuning using Langchain | Scodeen Global канала SCODEEN GLOBAL