This sample showcases a multi-agent system, involving a supervisor, a researcher, and a coder working in coordination to tackle complex tasks.
Here, a multi-agent system breaks down complex tasks into discreet steps, routing them to specialized agents. Each agent operates independently and can be deployed as a separate process. The system includes a planner, researcher, and coder agent.
The RAG Sample project demonstrates the implementation of a Retrieval-Augmented Generation (RAG) system using UiPath Context Grounding.
This example shows how to retrieve relevant documents for a query, using the UiPath Context Grounding vectorstore. It also integrates this into a Langchain retrieval chain for response formulation.
This sample shows how to create an agent using LangGraph with multiple tool servers via the MCP (Model Context Protocol) standard.
This sample demonstrates the creation of an agent using LangGraph, which connects to a remote MCP (Model Context Protocol) Server.
This sample shows how to build a LangGraph agent that connects to a remote UiPath MCP server using OAuth authentication through an external UiPath application for dynamic access token management.
This sample demonstrates automatic classification of support tickets into categories. It includes a human approval step via UiPath Action Center.