Recently, the topic of AI agents has gained immense popularity, with the rapid advancement of reasoning model performance igniting a heightened interest in the application prospects of agents. Although the concept of agents has existed for a long time, supported by the reasoning capabilities of large models, the value expectations of AI agents within business … Read more
• Hello everyone, I am student Xiao Zhang, sharing AI knowledge and practical cases daily. • Welcome to like + follow 👏, continue learning, and continuously output practical content. • +v: jasper_8017 let’s communicate 💬 and improve together 💪. Overview of Articles on Official Account Today we continue to learn the basic content of LangGraph. … Read more
Introduction In the previous article, we introduced the concept of Agentic RAG, emphasizing how it extends traditional retrieval-augmented generation (RAG) frameworks by integrating autonomous agent capabilities. In this issue, we delve deeper into LangGraph, an innovative framework for coordinating logical workflows. LangGraph enables the creation of multi-agent systems with complex reasoning capabilities, making it an … Read more
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
Author:DeanSacoransky and Deniz Askin The Impact of DeepSeek-r1 DeepSeek publicly released the r1 model less than a month ago. Suddenly, everyone can publicly use a powerful reasoning model for application and model development. In this article, we propose a simple intelligent agent workflow that empowers DeepSeek-r1 to perform information retrieval in an intelligent agent manner! … Read more
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
– **Trend Analysis**: Stock price breaks above the 200-day moving average, indicating a strengthening mid-term trend – **Potential Risks**: Debt ratio exceeds the industry average by 30% – **Operation Suggestion**: If it pulls back to the 50-day moving average, consider building positions in batches Through the DeepSeek inference engine, we have comprehensively considered technical trends, … Read more
1. Technical Background and Design Goals Current content generation systems face three common technical challenges: low efficiency in processing multi-source heterogeneous data, insufficient structural coherence in long text generation, and weak collaborative generation capabilities for multimodal content. This research proposes a solution based on the LangGraph framework, aiming to build a modular and scalable intelligent … Read more
Why Do You Need This AI Assistant? Complex Requirement Documents PRD documents can be dozens of pages long, mixing text and images, making it easy to overlook test points when extracting manually. Time-Consuming Test Case Design It requires considering various methods such as equivalence class, boundary value, and exception flows, which can be overwhelming. Difficult … Read more
In LangGraph, <span>State</span> is a core concept used to save and share context information in complex tasks or dialogue systems. Here is a detailed explanation of <span>State</span>: 1.Definition of State <span>State</span> is a shared data structure used in LangGraph to represent the current snapshot of the application. It can be any Python type, but is … Read more