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Introduction

Our agents framework provides a robust infrastructure for creating and managing multiple AI agents. It enables seamless collaboration between agents to tackle complex tasks, dynamically adapting to user inputs and changing conditions.

Core Components

Our agentic AI framework comprises of several core components:

Component Description
Orchestrator Central hub for task assignment, execution, and monitoring. Manages agent interactions and refines workflows dynamically.
Agent An autonomous unit programmed to perform tasks, make decisions, and communicate with other agents.
Task A specific assignment completed by an agent, providing all necessary details like description, tools, and responsibilities.
Crew A collaborative group of agents working together to achieve a set of tasks. Crews define strategies for task execution and agent collaboration.
Process Implementations Frameworks for agent collaboration. This includes sequential tasks that are executed in an orderly progression, or hierarchical tasks are managed via a structured chain of command
Large Language Models (LLMs) Backbone of intelligent agents, enabling capabilities like natural language understanding and reasoning. Includes models like GPT, Claude, Mistral, Gemini, and Llama that are Optimized for complex workflows.
Tool A skill or function agents use to perform actions, that includes capabilities like search, computer use, data extraction, file uploading and advanced interactions.
Agent Registry A structured catalog organizing agents by domain, task type, and functionality, allowing users to deploy agents seamlessly.
Frontend Interface Drag-and-drop visual workflow builder and real-time dashboards for monitoring, debugging, and optimizing agent performance.

System Architecture Overview

Our architecture is built around a decentralized network of specialized agents that work both independently and collaboratively. These agents communicate through defined pathways, managed by an orchestrator that ensures tasks are distributed and executed efficiently.

Orchestration

The orchestrator plays a pivotal role in managing workflows. It interprets user queries, breaks them down into actionable tasks, and assigns these tasks to the appropriate agents. The orchestrator ensures that tasks are distributed efficiently, optimizing workflow execution and ensuring timely completion.

The orchestrator ensures that tasks are distributed efficiently, optimizing workflow execution and ensuring timely completion.

Orchestration Process

Task execution is automated through dynamic selection of the best agents, tools, and workflows for the job. The system handles dependencies, monitors progress, and troubleshoots issues in real time. The following process is how this works:

  1. Query Interpretation: The orchestrator parses the natural language query to understand the user's intent and extract relevant entities.
  2. Task Breakdown: The query is decomposed into smaller, manageable tasks that can be assigned to individual agents.
  3. Task Assignment: Tasks are allocated to the appropriate agents based on their specialization and current workload.
  4. Monitoring and Adjustment: The orchestrator monitors task execution, making adjustments as necessary to handle delays or errors.

Orchestrator Features

  • Intelligent Routing: Utilizes AI to determine the most efficient agent for each task.
  • Dynamic Scaling: Adjusts the number of active agents based on task volume and complexity.
  • Failure Recovery: Implements strategies to recover from agent failures, ensuring workflow continuity.
  • Performance Optimization: Continuously analyzes workflow performance to identify and eliminate bottlenecks.

Key Features

Here are a few features related to our agentic AI framework.

Feature Description
Decentralized Agents Each agent operates autonomously while collaborating to achieve complex tasks.
Orchestrator Acts as the central command center, managing task distribution and workflow coordination.
Communication Edges Enable seamless data exchange and coordination between agents.
Logging & Monitoring Ensure transparency, performance tracking, and issue resolution.
Dynamic Workflows Build complex workflows with drag-and-drop tools.
Agent Collaboration Enable sequential, parallel, or hierarchical execution of tasks.
Customizable Framework Integrate third-party apps and tools, such as Slack, AWS, or Google Workspace.
Real-Time Debugging Visualize and troubleshoot workflows using interactive flowcharts.
Model-Agnostic Design Supports various models, including OpenAI, Claude, Llama, and Mistral.
Private Deployments Operate securely in local environments with privacy-preserving configurations.

Domain Specific Agent Registry

The registry offers a catalog of prebuilt agents optimized for specific domains, such as coding, data analysis, and natural language processing. This allows users to quickly integrate tailored solutions into their workflows without extensive setup. Within the use cases folder, we share a few examples of agents within the registry.