Using ToolNode for tool calls ToolNode is a LangChain Runnable that takes a graphical state (with a list of messages) as input and outputs a state update using the results of tool calls. It is designed to work out of the box with LangGraph’s pre-built ReAct agent, but it can also work with any StateGraph … Read more
How to Add and Use Subgraphs Subgraphs allow the construction of complex systems with multiple components, each of which is a graph. A common use case for using subgraphs is building multi-agent systems. The main issue when adding subgraphs is how the parent graph and the subgraph communicate, i.e., how they pass state to each … Read more
LangGraph is an innovative Graph Neural Network (GNN) technology designed to address the complex relationship modeling challenges in Natural Language Processing (NLP) tasks. Traditional NLP models often treat text data as linear sequences, overlooking the intricate relationships between entities within the text. In contrast, LangGraph constructs a graph structure to represent the entities and their … 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
“This is the best of times, and the worst of times. But, ultimately, it is a good era.” The intelligent platform introduced today differs from low-code platforms like Coze and Dify, as it is entirely built using Python code. Moreover, during application, there is no need to arrange the collaboration mode among the … Read more
In today’s rapidly evolving technological landscape, artificial intelligence (AI) agents have become key tools for optimizing workflows, improving efficiency, and reducing labor costs. Recently, Google released a white paper on AI Agents, and industry insiders have even directly defined 2025 as the era of Agents. Recently, I tried Crew.ai, an advanced AI agent platform that … 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
Introduction This paper shares the research titled CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation, proposed by Fudan University & ByteDance. It introduces a new paradigm for layout-to-image generation that supports controllable image generation under the MM-DiT framework based on layouts! Pytorch training camp, mastering code implementation in two weeks Comprehensive tutorials on various … Read more
2025: The Year of AI Agents – Building Multi-Agent Systems with CrewAi and Gemini 1.5 As many experts predict, 2025 is gradually becoming the year of agent-based artificial intelligence. This emerging field is poised to redefine the way we interact with technology by introducing highly autonomous systems that can make decisions and execute complex tasks … Read more
Source: I Love Computer Vision This paper shares the work titledCreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation, proposed by Fudan University and ByteDance, introducing a new paradigm for layout-to-image generation that supports controllable image generation under the MM-DiT architecture based on layouts! Paper link: https://arxiv.org/abs/2412.03859 Project homepage: https://creatilayout.github.io Project code: https://github.com/HuiZhang0812/CreatiLayout Project Demo: … Read more