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LangChain
Since 2022Framework for building LLM-powered applications
Framework for building LLM-powered applications — chains, agents, RAG pipelines, and tool integration.
Overview
LangChain is my orchestration layer for AI applications. I build RAG pipelines chaining document loaders, text splitters, embeddings, and vector stores. Agents with tool-use for autonomous workflows. Memory management for conversational AI. Production monitoring with LangSmith.
Use Cases
- RAG pipelines
- AI agents
- conversational AI with memory
- document processing
- multi-model orchestration
Advantages
- Comprehensive AI toolchain
- supports all major LLMs
- vector store integrations
- agent framework
- LangSmith monitoring
Considerations
- Abstraction overhead
- breaking API changes
- can be overly complex for simple tasks
- documentation gaps