Anything LLM

Practical Programming with Local Large Models (20): Implementing RAG with LangGraph and Agents (4)

by
Practical Programming with Local Large Models (20): Implementing RAG with LangGraph and Agents (4)

In the previous article, we practiced a [RAG (Retrieval Augmented Generation) system implemented with `langgraph`]. This article will build upon that by adding an automatic chat history logging feature. Additionally, we will use an `Agent` to achieve almost the same functionality. Let’s explore the differences between implementing the `RAG system` using `langgraph` and `Agent`. – … Read more

DeepSeek & LangGraph: Evaluating Reasoning Models in Agent Applications

by
DeepSeek & LangGraph: Evaluating Reasoning Models in Agent Applications

Click the blue text above to follow us DeepSeek has gained popularity, especially against the OpenAI o1’s R1 model, whose lower prompt threshold and deep reasoning capabilities have accelerated the adoption of AI applications. However, compared to the enthusiasm on the personal application side, we need a more objective and scientific focus on its productivity … Read more

Understanding LangChain’s New Tool: LangGraph

by
Understanding LangChain's New Tool: LangGraph

▼Recently, there have been many live broadcasts,make an appointment to ensure you gain something Today’s live broadcast:《Building Agent Industrial Applications with RAG and GPTs Practical Implementation》 —1— LangGraph Technical Architecture Interpretation LangGraph is a tool for building stateful and multi-role Agent applications. It is not a new framework independent of Langchain, but rather an extension … Read more

What Is LangGraph and Its Applications in Agent Frameworks

by
What Is LangGraph and Its Applications in Agent Frameworks

1. What Is LangGraph Why Use LangGraph? Developing agents using frameworks like langchain involves significant development effort, lacks flexibility, and incurs high modification costs. Reducing development effort while increasing the flexibility of agents is a key point for promoting agents. LangGraph supports production-grade agents and is trusted by companies like Linkedin, Uber, Klarna, and GitLab. … Read more

LangGraph Practical Series Part 2: Extending Multi-Agent Applications with Tools

by
LangGraph Practical Series Part 2: Extending Multi-Agent Applications with Tools

In Part 1, “LangGraph Practical Series Part 1: Creating Stateful Multi-Agent Applications“, I added short-term memory to the chatbot, allowing it to retain context during conversations. In this section, I will take it a step further by introducing tools into our chatbot. Tools allow the chatbot to retrieve real-time data from external sources, making it … Read more

Getting Started with LangGraph: Building a Basic Chatbot

by
Getting Started with LangGraph: Building a Basic Chatbot

LangGraph is not a new framework independent of LangChain, but rather an extension library built on top of LLM and LangChain, enabling seamless collaboration with existing chains in LangChain. LangGraph can coordinate multiple Chains, Agents, Tools, etc., to collaboratively perform Q&A tasks that depend on external tools and databases with feedback. We will first create … Read more

Building a Dynamic Order Management System with LangGraph

by
Building a Dynamic Order Management System with LangGraph

In this extremely detailed Tutorial, we will explore LangGraph — a powerful library for coordinating complex multi-step workflows, suitable for large language models (LLMs) — and apply it to a common e-commerce problem: deciding whether to place or cancel an order based on user queries. By the end of this blog, you will understand how … Read more

Creating Your Own AI Team with CrewAI

by
Creating Your Own AI Team with CrewAI

Introduction to CrewAI CrewAI is a cutting-edge framework for coordinating autonomous AI agents. CrewAI allows you to create AI teams, where each agent has specific roles, tools, and goals, working together to accomplish complex tasks. Think of it as assembling your dream team—each member (agent) brings unique skills and expertise, collaborating seamlessly to achieve your … Read more

CrewAI: A Multi-Agent Framework Combining Diverse Strengths

by
CrewAI: A Multi-Agent Framework Combining Diverse Strengths

In previous articles, such as “Exploring LLM Application Development (26) – Prompt (Architecture Patterns of Agent Frameworks like AutoGPT, AutoGen, etc.)”, I introduced several multi-agent frameworks like AutoGen and ChatDev. Recently, a promising framework has emerged in the industry – CrewAI, which stands on the shoulders of frameworks like AutoGen, aiming for practical deployment. It … Read more

Reducing LLM Hallucinations with the Agentic Approach: In-Depth Analysis and Practice

by
Reducing LLM Hallucinations with the Agentic Approach: In-Depth Analysis and Practice

Click the “blue words” to follow us In the field of artificial intelligence, especially in the application of large language models (LLMs), the phenomenon of hallucination has always been a key issue affecting the reliability and accuracy of the models. Hallucination (How to Eliminate Hallucinations in Large Language Models (LLMs)) refers to the text generated … Read more