# LangChain

This product is a full-stack application that leverages LLM (Large Language Models) and LangChain technology, combined with LangGraph, to retrieve and analyze stock data and news. It uses ChromaDB as a vector database to support semantic search and data visualization, providing users with deep insights into the stock market. It is primarily aimed at investors, financial analysts, and data scientists, helping them quickly acquire and analyze stock-related information to support decision-making. The product is currently open-source and free, making it suitable for users who need to efficiently process financial data and news.

Brainstormers is an application built on LangChain and Streamlit, designed to enhance your brainstorming experience by providing a structured and optimized chain inspired by effective brainstorming techniques from the real world. Unlike traditional direct usage of ChatGPT, this application allows for a structured brainstorming approach, guiding you to comprehensively explore ideas and maximize the benefits of LLM-driven brainstorming. The application offers various brainstorming techniques, including mind mapping, reverse brainstorming, role storming, SCAMPER, Six Thinking Hats, and Starbursting, enabling users to examine problems from different perspectives and spark innovative solutions.

IncarnaMind is an open-source project aimed at enabling conversational interactions with personal documents (PDF, TXT) using large language models (LLMs) such as GPT, Claude, and local open-source LLMs. The project enhances query efficiency and improves the accuracy of LLMs through a sliding window chunking mechanism and integrated retrievers. It supports multi-document conversational Q&A, overcoming the limitations of single-document interaction while being compatible with various file formats and LLM models.

Retrieval-Augmented Generation (RAG) is a cutting-edge technique that enhances the capabilities of generative models by integrating external knowledge sources, leading to higher quality and reliability in generated content. LangChain is a powerful framework designed specifically for building and deploying robust language model applications. This tutorial series offers a comprehensive, step-by-step guide to help you implement RAG using LangChain. It starts with an introduction to the fundamental RAG process and gradually delves into areas like query transformation, document embedding, routing mechanisms, query construction, indexing strategies, retrieval techniques, and the generation stage. Ultimately, it integrates all these concepts into a practical scenario, showcasing the power and flexibility of RAG.

CrewAI is an open-source library for developers designed to build and coordinate AI agent teams for tackling complex tasks. Built on the LangChain framework, it seamlessly integrates various AI tools to empower your agents to accomplish specific work goals. You can assemble different agents, tasks, and tools like building blocks to create AI agent systems tailored to your needs.