AI, LLM: LangChain

Introduction | 🦜️🔗 Langchain

LangChain is a framework for developing applications powered by language models. It enables applications that:

• Are context-aware: connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response in, etc.)
  
  
• Reason: rely on a language model to reason (about how to answer based on provided context, what actions to take, etc.)

The main value props of LangChain are:Components: abstractions for working with language models, along with a collection of implementations for each abstraction. Components are modular and easy-to-use, whether you are using the rest of the LangChain framework or not
Off-the-shelf chains: a structured assembly of components for accomplishing specific higher-level tasks

Off-the-shelf chains make it easy to get started. For complex applications, components make it easy to customize existing chains and build new ones.

Learn LangChain, Pinecone & OpenAI: Build Next-Gen LLM Apps | Udemy Business

LangChain- Develop LLM powered applications with LangChain | Udemy Business

langchain-ai/langchain: ⚡ Building applications with LLMs through composability ⚡ @GitHub

(Python/Jupyter)