🤖 LangChain

What Is LangChain?

LangChain is a framework for building LLM-powered applications.

It helps you:

• Connect models to data sources
• Orchestrate multi-step workflows
• Integrate tools and APIs

Think of it as an abstraction layer over raw model calls, adding structure, memory, and reasoning so your app becomes a system, not just a single prompt.

Core Architectural Ideas

LangChain centers on:

• Models: LLMs, chat models, embeddings
• Prompts: templates, variables, formatting
• Memory: state across turns
• Chains: sequences of calls
• Agents: LLMs that choose tools

These primitives combine to create complex, modular applications while keeping each part testable and replaceable.

Models and Chat Models

LangChain wraps many providers: OpenAI, Anthropic, local models, etc.

• LLM models: text-in → text-out
• Chat models: message-in → message-out with roles

Benefits:

• Unified interface across vendors
• Easy switching/tuning
• Standardized callbacks, tracing

You focus on behavior, not vendor-specific SDKs.

Prompts as First-Class Objects

Prompting is not ad hoc text; in LangChain it is structured:

• Templates with variables
• Partial variables and reuse
• Chat prompts combining system, user, tool messages

This encourages parameterization, versioning, and testing, instead of editing long strings scattered through code.