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Introduction

LangChain​

LangChain is an application development framework designed to facilitate the integration of language models into various applications. For example, it allows developers to easily integrate GPT models from OpenAI into their projects.

Support for Python and JavaScript​

LangChain is implemented in both Python and JavaScript. This implementation allows developers to build applications using their preferred language while accessing the extensive ecosystem of libraries and tools available for both languages.

Modular Components​

LangChain features a modular design, which allows developers to create and combine various components according to their specific requirements. This modularity enables easy customisation of applications, as well as reusability and sharing of components among different projects.

Examples of components in LangChain include:

  • LLMs and Chat Models, which serve as wrappers around APIs for models that generate text and chat models.
  • Chains, objects that connect components (like LLMs, prompts, etc.) or other chains to fulfill specific tasks.
  • Agents, autonomous entities that utilise a large language model as their reasoning mechanism.
  • Vector Stores, interfaces to vector databases or vector data structures.
  • Document loaders, tools for loading documents in various formats (websites, PDF files) and converting them into other formats, such as text.
  • Embeddings generation, components designed to generate embeddings for specified text.

Use Cases​

LangChain can be utilised in a variety of applications, including:

  • Question-Answer - developers can use LangChain to create question-answering systems, providing users with accurate and contextually relevant responses to their queries. Applications built on LangChain can be employed for real-time support, customer assistance, or knowledge management systems.

  • Classification - LangChain can assist in text classification tasks such as sentiment analysis, spam detection, or document categorisation.

  • Summarisation - LangChain's summarisation capabilities allow developers to build applications that can extract key information and condense various types of content, such as lengthy documents, articles, or customer reviews, into brief summaries.

  • Language Model-Environment Interaction - LangChain enables developers to create applications that interact with their environment through natural language, allowing for tasks such as downloading resources from the Internet or executing commands in the shell.

Installation​

To install LangChain, please follow the instruction provided below:

pip install langchain