Large Language Models Application

This repository showcases the application of large language models (LLMs) in various tasks. The project is organized into different modules and packages to facilitate learning and experimentation.

📚 Langchain

The Langchain directory contains scripts and resources related to the Langchain framework. Langchain is a powerful tool for building and managing complex language model workflows.

🕹️LangGraph

• Enable the development, debugging, and maintenance of AI agents.
• Integrate agentic search capabilities to enhance agent knowledge and performance.

📚 Ollama

The Ollama framework, which focuses on running with large language models.

• https://github.com/ollama/ollama/tree/main
• python library: https://github.com/ollama/ollama-python

🖥️ UI

Chainlit

Chainlit is an open-source Python package to build production ready Conversational AI.

• https://docs.chainlit.io/get-started/overview

📚 Deep Research

• Deep Research can conduct multi-step investigations, reference multiple sources, and produce structured reports.

🛠️ MCP

• The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
• https://github.com/modelcontextprotocol

Other Repository

The GPT4All runs large language models (LLMs) privately on everyday desktops & laptops.

• https://github.com/nomic-ai/gpt4all