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Introduction

The Svahnar Agentic Framework is a powerful framework designed to empower not only developers but also anyone to create intelligent, intentional, and effective computational systems. The framework enables you to deploy Agentic AI, which are systems that can think, learn, and act independently to achieve defined goals and purposes.

With the Svahnar Agentic AI Framework, you can:

  • Integrate with various tools (Knowledge Repositories support coming in the next release).
  • Define specific behaviors and intentions for AI agents.
  • Connect to leading Foundation Models, Agents and Guardrails.

Whether you're building automated workflows, decision-making systems, or state-of-the-art intelligent agents, the Svahnar Framework simplifies the process of designing, deploying, and scaling Agentic AI solutions.

What Is Agentic AI?​

Agentic AI refers to computational systems that operate with a level of autonomy, intelligence, and purpose. Unlike traditional AI systems that simply process inputs and respond with outputs based on predefined rules, Agentic AI is designed to:

  • Perceive its environment, tools, knowledge repositories, and external contexts by gathering and processing data, extracting meaningful features, and identifying relevant entities.
  • Reason through orchestration. Using Agentic Network, it interprets tasks, develops intelligent solutions, and coordinates with other agents for specific functionalities such as content creation, analysis, and personalized recommendations.
  • Act intentionally to achieve specific objectives by executing tasks based on crafted plans. Through integration with external tools and APIs, Agentic AI can ensure accurate, goal-driven operations while leveraging built-in guardrails to maintain control and correctness.
  • Learn dynamically from data over time by incorporating interaction feedback into its models, enabling it to adapt, optimize performance, and enhance decision-making efficacy.

AI Agent

This makes Agentic AI particularly useful for use cases where independent decision-making, dynamic workflows, or autonomous control systems are required.

YAML Configuration for Svahnar Agentic Network​

The Svahnar Agentic AI Framework offers a convenient way to create agentic networks using YAML configuration files and SVAHNAR Console. YAML (Yet Another Markup Language) provides a human-readable way to define the structure, data, and behaviors of your Agentic AI network. Creating an Agentic AI system using YAML ensures simplicity, clarity, and flexibility.

Starting Your YAML Configuration​

Every YAML configuration file for creating a Svahnar Agentic Network must include the top-level key:

create_vertical_agent_network:

This top-level key serves as the starting point for defining every aspect of the Agentic AI network. Within this key, you will organize all the critical components required to configure and operate the agentic network effectively, including:

  • Defining agent function
  • Connecting to Foundation models
  • Data and tools integration
  • Orchestration of Agent interactions

The YAML-based approach enables you to craft fully customized Agentic AI frameworks with ease. By nesting configurations under the create_vertical_agent_network key, you ensure that all components are logically structured and easy to manage.