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RAG#

  • in RAG, Swarm
  • 5 min read

Knowledgeable Agents with FalkorDB Graph RAG

FalkorDB Web

TL;DR: * We introduce a new ability for AG2 agents, Graph RAG with FalkorDB, providing the power of knowledge graphs * Structured outputs, using OpenAI models, provide strict adherence to data models to improve reliability and agentic flows * Nested chats are now available with a Swarm

FalkorDB Graph RAG

Typically, RAG uses vector databases, which store information as embeddings, mathematical representations of data points. When a query is received, it's also converted into an embedding, and the vector database retrieves the most similar embeddings based on distance metrics.

Graph-based RAG, on the other hand, leverages graph databases, which represent knowledge as a network of interconnected entities and relationships. When a query is received, Graph RAG traverses the graph to find relevant information based on the query's structure and semantics.

  • in RAG
  • 5 min read

EcoAssistant - Using LLM Assistants More Accurately and Affordably

system

TL;DR: * Introducing the EcoAssistant, which is designed to solve user queries more accurately and affordably. * We show how to let the LLM assistant agent leverage external API to solve user query. * We show how to reduce the cost of using GPT models via Assistant Hierarchy. * We show how to leverage the idea of Retrieval-augmented Generation (RAG) to improve the success rate via Solution Demonstration.

EcoAssistant

In this blog, we introduce the EcoAssistant, a system built upon AutoGen with the goal of solving user queries more accurately and affordably.

  • in RAG
  • 8 min read

Retrieval-Augmented Generation (RAG) Applications with AutoGen

Last update: August 14, 2024; AutoGen version: v0.2.35

RAG Architecture

TL;DR: * We introduce RetrieveUserProxyAgent, RAG agents of AutoGen that allows retrieval-augmented generation, and its basic usage. * We showcase customizations of RAG agents, such as customizing the embedding function, the text split function and vector database. * We also showcase two advanced usage of RAG agents, integrating with group chat and building a Chat application with Gradio.