AI Agents

Intelligent AI agents that can understand, reason, and act autonomously. Learn about agent architecture, design patterns, and implementation strategies.

Agent Intelligence

AI agents combine natural language understanding, reasoning capabilities, and autonomous action to solve complex problems and automate workflows.

Natural Language Processing

Reasoning & Decision Making

Autonomous Action

AI Agent Architecture

AI agents in Vistara are built with a modular architecture that enables flexibility, scalability, and intelligent behavior.

Agent Architecture Overview

Core Agent Components

Natural Language Processing

Text Understanding: Parse and comprehend user input
Intent Recognition: Identify user goals and objectives
Entity Extraction: Extract relevant information from input
Context Management: Maintain conversation context and history

Knowledge Base

Domain Knowledge: Specialized knowledge for specific domains
Learning Capabilities: Continuous learning and knowledge updates
Memory Management: Short-term and long-term memory systems
Knowledge Graph: Structured representation of information

Reasoning Engine

Logical Reasoning: Apply logical rules and constraints
Pattern Recognition: Identify patterns in data and behavior
Inference Engine: Make conclusions from available information
Uncertainty Handling: Deal with incomplete or uncertain information

Decision Maker

Goal Orientation: Work towards specific objectives
Priority Management: Handle multiple competing goals
Risk Assessment: Evaluate potential risks and benefits
Adaptive Behavior: Adjust behavior based on outcomes

Agent Lifecycle

Complete Agent Lifecycle

Agent States and Transitions

Creation Phase

Agent Design: Define agent capabilities and behavior
Architecture Selection: Choose appropriate agent architecture
Resource Planning: Plan computational and memory requirements
Security Design: Implement security and isolation measures

Training Phase

Data Preparation: Gather and prepare training data
Model Training: Train AI models and algorithms
Validation: Validate agent behavior and performance
Optimization: Optimize for efficiency and accuracy

Deployment Phase

Environment Setup: Prepare deployment environment
Resource Allocation: Allocate necessary system resources
Integration: Integrate with external systems and APIs
Testing: Comprehensive testing and validation

Running Phase

Request Processing: Handle user requests and queries
Task Execution: Execute assigned tasks and workflows
Performance Monitoring: Monitor agent performance and health
Continuous Learning: Learn from interactions and outcomes

Agent Types and Specializations

Market Intelligence Agents

Capabilities

Data Collection: Gather data from multiple sources
Market Analysis: Analyze market trends and patterns
Competitive Intelligence: Monitor competitor activities
Predictive Modeling: Forecast market movements

Use Cases

Investment Analysis: Analyze investment opportunities
Market Research: Conduct market research and surveys
Trend Monitoring: Track industry trends and developments
Risk Assessment: Assess market risks and opportunities

Code Generation Agents

Capabilities

Code Understanding: Understand code requirements and context
Language Support: Support multiple programming languages
Best Practices: Apply coding best practices and standards
Testing: Generate tests and validation code

Use Cases

Rapid Prototyping: Quickly prototype new features
Code Review: Review and improve existing code
Documentation: Generate code documentation
Refactoring: Refactor and optimize code

Workflow Automation Agents

Capabilities

Process Mapping: Understand and map business processes
Automation Logic: Design automation workflows
Integration: Integrate with external systems
Monitoring: Monitor workflow execution and performance

Use Cases

Business Process Automation: Automate repetitive business processes
Data Processing: Automate data processing and transformation
Customer Service: Automate customer service workflows
Quality Assurance: Automate testing and quality checks

Agent Configuration

Agent Configuration Schema

// agent.config.js
module.exports = {
  agent: {
    name: 'Market Intelligence Agent',
    type: 'market-intelligence',
    version: '1.0.0',
    description: 'AI agent for market analysis and intelligence'
  },
  
  capabilities: {
    dataCollection: true,
    marketAnalysis: true,
    trendDetection: true,
    reporting: true
  },
  
  models: {
    language: 'gpt-4',
    reasoning: 'custom-reasoning-engine',
    memory: 'vector-database'
  },
  
  resources: {
    memory: '1GB',
    cpu: '0.5 cores',
    storage: '10GB',
    network: '100Mbps'
  },
  
  security: {
    isolation: true,
    encryption: true,
    accessControl: true,
    auditLogging: true
  },
  
  monitoring: {
    metrics: ['response_time', 'accuracy', 'throughput'],
    alerting: true,
    logging: 'structured'
  }
}

Environment Variables

# Agent Configuration
AGENT_NAME=market-intelligence-agent
AGENT_TYPE=market-intelligence
AGENT_VERSION=1.0.0
 
# Model Configuration
AGENT_LANGUAGE_MODEL=gpt-4
AGENT_REASONING_ENGINE=custom
AGENT_MEMORY_DATABASE=vector
 
# Resource Limits
AGENT_MEMORY_LIMIT=1GB
AGENT_CPU_LIMIT=0.5
AGENT_STORAGE_LIMIT=10GB
 
# Security Settings
AGENT_ENABLE_ISOLATION=true
AGENT_ENABLE_ENCRYPTION=true
AGENT_ENABLE_AUDIT=true

Agent Performance & Monitoring

Performance Metrics

Response Time: Time to process and respond to requests
Accuracy: Quality and correctness of agent responses
Throughput: Number of requests processed per unit time
Resource Usage: CPU, memory, and storage utilization

Monitoring Tools

# Agent status
npm run status:agents
 
# Performance monitoring
npm run monitor:agents
 
# Resource usage
npm run metrics:agents
 
# Health checks
npm run health:agents
 
# Logs
npm run logs:agents

Getting Started

Deploy Your First Agent

# Clone agent templates
git clone https://github.com/vistara-labs/agent-templates.git
cd agent-templates
 
# Choose agent type
cd market-intelligence
 
# Install dependencies
npm install
 
# Configure agent
cp config.example.js config.js
# Edit config.js with your settings
 
# Deploy agent
npm run deploy

Agent Development

# Start development mode
npm run dev
 
# Test agent
npm run test
 
# Build agent
npm run build
 
# Deploy agent
npm run deploy

Learn More

Zara Platform →: Understanding Zara's platform architecture
Workflows →: Workflow engine architecture
Vistara OS →: Core operating system layer
Quick Start →: Get up and running with AI agents

Ready to Build AI Agents?

Start building intelligent AI agents that can understand, reason, and act autonomously.

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