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
Dialogue analysis uses output from:Using proxies to bring NPCs to life with CrewAI Analysis • Simulation 1: A group of software engineers, computer scientists, and computer engineers • Conclusion • Support Analysis Methods • Extracted Features • Split global_conversations.txt • Sentiment, Topic, Vocabulary Diversity, Emotion • Self-Similarity • Notebook Background Previously, I discussed in my … Read more
CrewAI’s architecture goes far beyond static workflows; it supports intelligent, context-aware, and collaborative AI agents. Translated fromHow CrewAI Enables AI Agents as Collaborative Team Members, author Janakiram MSV. In the first part of this series, we introduced CrewAI and mapped its features against key attributes of AI agents. Now, we will take a closer look … Read more
In daily work, writing personal and team weekly reports is a tedious and monotonous task. Fortunately, this scenario is very suitable for leveraging artificial intelligence (AI) technology to simplify the process. Although there are various GPT-based agents available in the market, such as Wenxin Yiyan, iFlytek Spark, and Zhipu Qingyan, which can summarize content provided … Read more
Unlike traditional isolated single-agent systems, CrewAI introduces autonomous AI agents that can work collaboratively. Translated from Developer Guide to the CrewAI Agent Framework for Python, by Janakiram MSV. CrewAI is one of the most popular Python frameworks designed for intelligent multi-agent collaboration—transforming how developers handle complex AI workflows. Unlike traditionally standalone single-agent systems, CrewAI introduces … Read more
Learn from João Moura, the founder and CEO of crewAI, and explore the key components of multi-agent systems: Role Assignment: Assign dedicated roles to agents Memory: Provide agents with short-term, long-term, and shared memory Tools: Allocate pre-built and custom tools to each agent (e.g., tools for web searches) Focus: Decompose tasks, goals, and tools, and … Read more
For beginners in machine learning, the most daunting aspects are the various formulas, concepts, and derivations. Faced with heavy textbooks and complex concepts, one often doesn’t know where to start. I used to struggle with the “Watermelon Book,” and when I saw examples like using watermelon vines to pick watermelons or judging the weather based … Read more
Table of Contents · 1. Introduction ∘ Customer Support Agent ∘ Personal Finance Advisor ∘ Medical Assistant ∘ Learning Companion ∘ Project Management Assistant ∘ Creative Partner ∘ Smart Home Manager ∘ Cybersecurity Assistant · 2. Setting Up the Basics · 3. Understanding CrewAI ∘ 1. AI Agents ∘ 2. Tools ∘ 3. Processes ∘ … Read more
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
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