CH01 LangChain Getting Started

LangChain Refers to a framework that allows you to develop a variety of applications using a language model. This framework allows language models to perform the following functions:

• Context-aware features: LangChain connects language models with various context sources. This includes prompt directives, a handful of examples, and content based on responses. This allows language models to generate more accurate and relevant answers based on the information provided.

• The ability to infer: In addition, the language model can provide any answer based on the context given, or deduce for yourself what action to take. This means that the language model can go beyond simply reproducing information, analyzing a given situation and presenting an appropriate solution.

Using LangChain based on the features mentioned earlier Search enhancement generation (RAG) application production , Structured data analysis , chatbot You can make your back.

install

The recommended Python version 3.11 Version.

Installation with pip

tbd

Configuration

This framework consists of several parts.

• LangChain Library : Python and JavaScript library. Includes the interface and integration of various components, the default runtime that combines these components into chains and agents, and the implementation of ready-to-use chains and agents.

• LangChain template : A collection of reference architectures that make it easy to deploy a variety of tasks.

• LangServe : This is the library for distributing LangChain chains as REST APIs.

• LangSmith : A developer platform that allows you to debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain.

• LangGraph : Libraries to build multi-actor applications capable of staying with LLM, built on top of LangChain and designed for use with LangChain. Adds the ability to adjust multiple chains (or actors) in a circular way at multiple computational stages to the LangChain expression language.

Ease of development ✨

Assembly and integration of components 🔧

• LangChain provides assembleable tools and integration for working with language models.

• Components are modularly designed and easy to use. This allows developers to freely utilize the LangChain framework.

Ready-to-use chain 🚀

• Provides a built-in combination of high-level components to perform high-level tasks.

• These chains simplify and speed up the development process.

Main module 📌

Model I/O

• Includes prompt management, optimization, and general interface with LLM and utilities for working.

Search

• Focusing on 'creating data enhancement', this module is responsible for getting the data needed during the generation phase from an external data source.

Agent

• Includes the process of determining what action the language model will take, implementing that action, observing, and repeating if necessary.

With LangChain, you can start developing language model-based applications more easily, customize features to suit your needs, and integrate with various data sources to handle complex tasks.