News from the AI & ML world
DeeperML
@www.marktechpost.com
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The development of AI agents capable of performing human tasks on computers is gaining momentum, with a particular focus on multi-agent communication systems. Several research labs and companies are actively exploring this area, aiming to build agents that can effectively coordinate and collaborate. A key aspect of this research involves establishing robust communication protocols that enable seamless interaction between multiple AI agents. Recent articles highlight the progress being made in constructing code using these multi-agent communication systems, paving the way for more sophisticated and autonomous AI applications.
Mistral AI recently released its Agents API, providing public access through La Plateforme for developers to create autonomous agents. This API allows agents to plan tasks, utilize external tools, and maintain long-term context. The interface comes equipped with connectors for Python execution, web search, Flux 1.1 image generation, and a document library. The Agents API supports the mistral-medium-latest and mistral-large-latest models, allowing agents to delegate subtasks to each other via the Model Context Protocol, creating coordinated workflows across multiple services.
A tutorial was recently released which provides a coding guide to building scalable multi-agent communication systems using the Agent Communication Protocol (ACP). This guide implements ACP by building a flexible messaging system in Python, leveraging Google's Gemini API for natural language processing. The tutorial details the installation and configuration of the google-generativeai library, introduces core abstractions, message types, performatives, and the ACPMessage data class for standardizing inter-agent communication. Through ACPAgent and ACPMessageBroker classes, the guide demonstrates how to create, send, route, and process structured messages among multiple autonomous agents, also showing how to implement querying, requesting actions, broadcasting information, maintaining conversation threads, acknowledgments, and error handling.
References :
Mistral AI recently released its Agents API, providing public access through La Plateforme for developers to create autonomous agents. This API allows agents to plan tasks, utilize external tools, and maintain long-term context. The interface comes equipped with connectors for Python execution, web search, Flux 1.1 image generation, and a document library. The Agents API supports the mistral-medium-latest and mistral-large-latest models, allowing agents to delegate subtasks to each other via the Model Context Protocol, creating coordinated workflows across multiple services.
A tutorial was recently released which provides a coding guide to building scalable multi-agent communication systems using the Agent Communication Protocol (ACP). This guide implements ACP by building a flexible messaging system in Python, leveraging Google's Gemini API for natural language processing. The tutorial details the installation and configuration of the google-generativeai library, introduces core abstractions, message types, performatives, and the ACPMessage data class for standardizing inter-agent communication. Through ACPAgent and ACPMessageBroker classes, the guide demonstrates how to create, send, route, and process structured messages among multiple autonomous agents, also showing how to implement querying, requesting actions, broadcasting information, maintaining conversation threads, acknowledgments, and error handling.
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References :
- Communications of the ACM: The Rise of the AI-Enabled Agentic Internet
- www.marktechpost.com: A Coding Guide to Building a Scalable Multi-Agent Communication Systems Using Agent Communication Protocol (ACP)
- Stack Overflow Blog: Article discussing integration of AI agents.
- Orases: The Roadmap to Successful AI Agent Implementation
- Analytics Vidhya: 8 Things to Keep in Mind while Building AI Agents
Classification:
- HashTags: #AIAgents #AgenticAI #MultimodalModels
- Company: AI Labs
- Target: Enterprises
- Product: AI Agents
- Feature: Agent Communication
- Type: AI
- Severity: Informative