Agents Overview

Agents are the core AI entities in PLai Framework. Each agent is a specialized AI assistant that can chat with users, use tools, access datasources, and execute complex workflows.

What are Agents?

Agents in PLai Framework are intelligent AI assistants that can:

Chat & Interact

Engage in natural language conversations with users

Use Tools

Execute actions through connected tools and APIs

Access Data

Query datasources and knowledge bases

Process Requests

Handle batch operations and complex workflows

Agent Features

Core Capabilities

Every agent in PLai Framework includes:

Natural Language Processing: Powered by advanced LLMs
Tool Integration: Connect to 6+ different tool types
Memory & Context: Maintain conversation history and context
Customizable Personality: Define behavior through system instructions
Multi-Modal Support: Handle text, images, and other media types

Advanced Features

Analytics
Answer Filters
Guardrails

Real-time conversation analytics
Performance metrics and insights
Custom reporting and filtering
Progress tracking for batch operations

Agent Configuration

Basic Settings

Each agent has fundamental configuration options:

Identity & Behavior

Name: Human-readable agent identifier
Description: Purpose and capabilities summary
System Instructions (Prompt): Core personality and behavior guidelines
Avatar: Visual representation for chat interfaces

Model Configuration

LLM Provider: OpenAI, Anthropic, Google, Groq, Together AI, OpenRouter, etc.
Model Selection: GPT-4, Claude, Gemini, Llama, and other models
Temperature: Response creativity and randomness
Max Tokens: Response length limitations
RouteLLM: Smart model routing for cost optimization
Streaming: Enable real-time response streaming for interactive conversations
Language Detection: Automatically detect and respond in the user’s language from the first question
Structured Output: Define JSON schemas for consistent, structured responses

Capabilities

Tools: Available actions and integrations
Datasources: Knowledge bases and data access
File Upload: Document processing capabilities
Voice Input: Audio conversation support

Advanced Model Configuration

Response Streaming

Enable real-time response streaming to provide progressive, interactive conversations with your users.

Overview
Use Cases
Compatibility

What is Streaming?Streaming allows the agent to send responses progressively as they’re generated, rather than waiting for the complete response. This creates a more interactive and responsive user experience.Benefits:

Improved user experience with instant feedback
Reduced perceived latency
Better for long-form responses
Real-time interaction feeling

Language Detection

Automatically detect and adapt to your user’s language based on their first question.

Overview
Use Cases
Compatibility

How it Works:When enabled, the agent analyzes the user’s first message to detect the language being used. The agent then automatically responds in the same language throughout the conversation.Benefits:

Seamless multi-language support
No manual language configuration needed
Improved global user experience
Automatic language consistency

Structured Output

Define JSON schemas to enforce consistent, parseable response formats.

Overview
Requirements
Use Cases
Examples

What is Structured Output?Structured Output allows you to define a JSON schema that the agent must follow in its responses. This ensures consistent, predictable, and easily parseable outputs.Benefits:

Guaranteed response format
Easy integration with external systems
Automatic validation
Consistent data extraction

Contact Information Extraction:

{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Full name of the person"
    },
    "email": {
      "type": "string",
      "format": "email"
    },
    "phone": {
      "type": "string"
    }
  },
  "required": ["name", "email"],
  "additionalProperties": false
}

Product Analysis:

{
  "type": "object",
  "properties": {
    "product_name": { "type": "string" },
    "sentiment": {
      "type": "string",
      "enum": ["positive", "negative", "neutral"]
    },
    "key_features": {
      "type": "array",
      "items": { "type": "string" }
    },
    "price_range": {
      "type": "object",
      "properties": {
        "min": { "type": "number" },
        "max": { "type": "number" },
        "currency": { "type": "string" }
      }
    }
  },
  "required": ["product_name", "sentiment"]
}

Agent Types & Use Cases

Customer Support Agents

Purpose: Handle customer inquiries and support tickets
Tools: 
  - Knowledge Base Search
  - Ticket System API
  - Email Integration
Features:
  - Escalation to human agents
  - Sentiment analysis
  - Multi-language support

Data Analysis Agents

Purpose: Process and analyze data from various sources
Tools:
  - Database Connections
  - Code Interpreter
  - Visualization Tools
Features:
  - Automated reporting
  - Data insights generation
  - Chart and graph creation

Content Creation Agents

Purpose: Generate and edit content across formats
Tools:
  - Web Search (Perplexity AI)
  - Document Processing
  - Image Generation
Features:
  - Multi-format output
  - Fact-checking
  - Style consistency

Research Agents

Purpose: Gather and synthesize information from multiple sources
Tools:
  - Web Scraping
  - Academic Databases
  - Document Analysis
Features:
  - Source verification
  - Citation management
  - Summary generation

RouteLLM Integration

RouteLLM automatically routes requests to the most appropriate model based on complexity and cost.

RouteLLM Benefits

Cost Optimization: Use cheaper models for simple tasks
Performance: Route complex queries to advanced models
Automatic: No manual configuration required
Transparent: Full visibility into routing decisions

Getting Started

Ready to create your first agent?

Navigate to Agents

Go to the Agents section in your project dashboard

Click Create Agent

Use the ”+” button or “Create Agent” button

Configure Basic Settings

Set name, description, and system instructions

Select Model

Choose your preferred LLM provider and model

Add Tools (Optional)

Connect tools to extend agent capabilities

Test & Deploy

Test your agent in chat and activate when ready

Next Steps

Create Your First Agent

Step-by-step agent creation guide

Agent Settings

Configure advanced agent features

Analytics

Monitor and analyze agent performance

First Agent Tutorial

Complete walkthrough with examples

Common Questions

How many agents can I create?

The number of agents depends on your subscription plan. Free plans typically allow 3 agents, while premium plans offer unlimited agents.

Can agents communicate with each other?

Currently, agents operate independently. Multi-agent workflows are on our roadmap for future releases.

What happens to conversation history?

Conversation history is stored securely and can be accessed through the analytics dashboard. Data retention policies vary by plan.

Can I export agent configurations?

Yes, agent configurations can be exported as JSON files for backup or migration purposes.

Getting Started

🤖 Agents

🔧 Tools

🗄️ Datasources

📋 Batches

📋 Experiments

📊 Monitor

Advanced

Agents Overview

Agents Overview

What are Agents?

Chat & Interact

Use Tools

Access Data

Process Requests

Agent Features

Core Capabilities

Advanced Features

Agent Configuration

Basic Settings

Advanced Model Configuration

Response Streaming

Language Detection

Structured Output

Agent Types & Use Cases

Customer Support Agents

Data Analysis Agents

Content Creation Agents

Research Agents

RouteLLM Integration

RouteLLM Benefits

Getting Started

Next Steps

Create Your First Agent

Agent Settings

Analytics

First Agent Tutorial

Common Questions

Getting Started

🤖 Agents

🔧 Tools

🗄️ Datasources

📋 Batches

📋 Experiments

📊 Monitor

Advanced

​Agents Overview

​What are Agents?

Chat & Interact

Use Tools

Access Data

Process Requests

​Agent Features

​Core Capabilities

​Advanced Features

​Agent Configuration

​Basic Settings

​Advanced Model Configuration

​Response Streaming

​Language Detection

​Structured Output

​Agent Types & Use Cases

​Customer Support Agents

​Data Analysis Agents

​Content Creation Agents

​Research Agents

​RouteLLM Integration

​RouteLLM Benefits

​Getting Started

​Next Steps

Create Your First Agent

Agent Settings

Analytics

First Agent Tutorial

​Common Questions

Agents Overview

What are Agents?

Agent Features

Core Capabilities

Advanced Features

Agent Configuration

Basic Settings

Advanced Model Configuration

Response Streaming

Language Detection

Structured Output

Agent Types & Use Cases

Customer Support Agents

Data Analysis Agents

Content Creation Agents

Research Agents

RouteLLM Integration

RouteLLM Benefits

Getting Started

Next Steps

Common Questions