This repo covers main components of langchain and showcases basic use of them for understanding purposes. This repo covers important concepts like integrating chat models and LLMs in langchain, making efficient chatbots with streaming , history maintenance, cache, tool calling, output parsing, etc. More components will be added soon. The components details are as follows:

• ChatModel: A conversational model that enables interaction with users, processing natural language input to generate relevant responses.

• Document Loader: A utility that loads documents from various sources (files, databases, URLs) into a format suitable for text processing or embedding.

• Output Parser: A tool that extracts structured data from the output generated by a language model, making it easier to interpret and use.

• Text Splitter: Breaks large texts into smaller chunks based on length, sentences, or paragraphs, optimizing them for token-limited models or chunk-based processing.

These components work together to enhance the flexibility and functionality of language models in Langchain.