Previously, I have written many articles introducing RAG implemented based on Azure OpenAI. This article introduces the implementation of RAG through Phi-2 and LlamaIndex. LlamaIndex is an open-source framework that effectively builds LLM applications when used in conjunction with Hugging Face Transformers, providing convenient methods for setting up databases and retrievers. The community activity of … Read more
How to manage personal knowledge in the AI era? Quivr gives us a glimpse. Today, we introduce an open-source software for personal knowledge management using AI: Quivr. GitHub link: https://github.com/QuivrHQ/quivr Its cloud-deployed product: https://quivr.app/ Product Slogan 🚀 The official slogan of Quivr is “Your GenAI Second Brain,” emphasizing that this project provides users with a … Read more
Phidata is a framework designed for building AI agents with memory, knowledge, and tools. https://www.phidata.com/ https://github.com/phidatahq/phidata https://docs.phidata.com/introduction Three Aspects of Phidata Enhancing LLM Functionality: Memory: Phidata stores chat history in a database, allowing large language models to support longer conversations, thereby better understanding and tracking the context of dialogues. Knowledge: By storing business-relevant information in … Read more
In the current development frameworks for distributed AI systems, AutoGen led by Microsoft and phiData represent two different technical paths. Architectural Design Philosophy AutoGen adopts an event-driven distributed architecture, achieving decoupling and collaboration of complex tasks through dynamic Agent orchestration. Its core is a decentralized event bus that supports asynchronous message passing and state synchronization … Read more
Introduction on how to use LangGraph to improve RAG. Long press to follow “Python Learning Base”, join the reader group, and share more wonderful content. 1. Introduction LangGraph is the latest member of the LangChain, LangServe, and LangSmith series, aimed at building generative AI applications using LLMs. Remember, all these are independent packages and must … Read more
▼Recently, there have been many live broadcasts,make an appointment to ensure you gain something —1— The Two Core Concepts of LangChain 1、Process-Oriented Architecture Design of Chains：Programs written based on large models that follow predefined steps and rules, which cannot be flexibly adjusted, used for executing tasks like: automatic SQL writing or multi-turn dialogue, etc. 2、Goal-Oriented … Read more
Types of Memory in CrewAI In CrewAI, the memory system enhances the capabilities of AI agents by enabling them to remember, reason, and learn from past interactions. Previous Chapter: The system consists of several key components: • Short-Term Memory: This component temporarily stores recent interactions and outcomes, allowing the agent to recall relevant information during … Read more
In the rapidly evolving field of AI, the ability to provide accurate, context-aware responses to user queries is a game changer. Retrieval-Augmented Generation (RAG) is a powerful paradigm that combines the retrieval of relevant information from external sources with the generative capabilities of large language models (LLMs). However, as queries become increasingly complex and diverse, … Read more
The RAG technology introduces external knowledge retrieval in the AI generation process, evolving from basic document queries to intelligent architectures with multi-modal and Multi-Agent collaborations, allowing AI to provide more accurate and comprehensive answers. Core Components: Embedding Model: Converts text into vector representations. Generation Model: Responsible for the final content generation. Re-ranking Model: Optimizes the … Read more
Roaming RAG, as an innovative RAG technology, can be elaborated on in detail regarding its characteristics and advantages from the following aspects: Working Principle and Process The core of Roaming RAG lies in utilizing the hierarchical structure of documents to enhance the information retrieval capabilities of large language models (LLMs). The specific process includes: Document … Read more