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Multi-Agent Orchestrator

Comprehend Filter Agent

The ComprehendFilterAgent is an agent class in the Multi-Agent Orchestrator System that uses Amazon Comprehend to analyze and filter content based on sentiment, Personally Identifiable Information (PII), and toxicity.

It can be used as a standalone agent within the Multi-Agent Orchestrator or as part of a chain in the ChainAgent.

When used in a ChainAgent configuration, it’s particularly effective as the first agent in the list. In this setup, it can check the user input against all configured filters, and if the content passes these checks, it will forward the original user input to the next agent in the chain. This allows for a robust content moderation system that can be seamlessly integrated into more complex processing pipelines, ensuring that only appropriate content is processed by subsequent agents.

Key Features

  • Content analysis using Amazon Comprehend
  • Configurable checks for sentiment, PII, and toxicity
  • Customizable thresholds for sentiment and toxicity
  • Support for multiple languages
  • Ability to add custom content checks

Creating a Comprehend Filter Agent

Python Package

If you haven’t already installed the AWS-related dependencies, make sure to install them:

Terminal window
pip install "multi-agent-orchestrator[aws]"

Basic Example

To create a new ComprehendFilterAgent with default settings:

import { ComprehendFilterAgent, ComprehendFilterAgentOptions } from 'multi-agent-orchestrator';


const agent = new ComprehendFilterAgent({
  name: 'ContentModerator',
  description: 'Analyzes and filters content using Amazon Comprehend'
});

Advanced Example

For more complex use cases, you can create a ComprehendFilterAgent with custom settings:

import { ComprehendFilterAgent, ComprehendFilterAgentOptions } from 'multi-agent-orchestrator';


const options: ComprehendFilterAgentOptions = {
  name: 'AdvancedContentModerator',
  description: 'Advanced content moderation with custom settings',
  region: 'us-west-2',
  enableSentimentCheck: true,
  enablePiiCheck: true,
  enableToxicityCheck: true,
  sentimentThreshold: 0.8,
  toxicityThreshold: 0.6,
  allowPii: false,
  languageCode: 'en'
};


const agent = new ComprehendFilterAgent(options);

Integrating Comprehend Filter Agent

To integrate the ComprehendFilterAgent into your orchestrator:

import { MultiAgentOrchestrator } from "multi-agent-orchestrator";


const orchestrator = new MultiAgentOrchestrator();
orchestrator.addAgent(agent);

Adding Custom Checks

This example demonstrates how to add a Custom Check to the ComprehendFilterAgent:

import { ComprehendFilterAgent, ComprehendFilterAgentOptions } from 'multi-agent-orchestrator';


const filterAgent = new ComprehendFilterAgent({
  name: 'AdvancedContentFilter',
  description: 'Advanced content filter with custom checks'
});


// Add a custom check for specific keywords
filterAgent.addCustomCheck(async (text: string) => {
  const keywords = ['banned', 'inappropriate', 'offensive'];
  for (const keyword of keywords) {
    if (text.toLowerCase().includes(keyword)) {
      return `Banned keyword detected: ${keyword}`;
    }
  }
  return null;
});


const orchestrator = new MultiAgentOrchestrator();
orchestrator.addAgent(filterAgent);


const response = await orchestrator.routeRequest(
  "This message contains a banned word.",
  "user789",
  "session101"
);


if (response) {
  console.log("Content passed all checks");
} else {
  console.log("Content was flagged by the filter");
}

Dynamic Language Detection and Handling

The ComprehendFilterAgent offers flexible language handling capabilities. You can specify the language either at initialization or dynamically during invocation. Additionally, it supports automatic language detection, allowing it to adapt to content in various languages without manual specification.

This example demonstrates dynamic language detection and handling:

import { MultiAgentOrchestrator, ComprehendFilterAgent } from 'multi-agent-orchestrator';
import { ComprehendClient, DetectDominantLanguageCommand } from "@aws-sdk/client-comprehend";


const filterAgent = new ComprehendFilterAgent({
  name: 'MultilingualContentFilter',
  description: 'Filters content in multiple languages'
});


const orchestrator = new MultiAgentOrchestrator();
orchestrator.addAgent(filterAgent);


async function detectLanguage(text: string): Promise<string> {
  const comprehendClient = new ComprehendClient({ region: "us-east-1" });
  const command = new DetectDominantLanguageCommand({ Text: text });
  const response = await comprehendClient.send(command);
  return response.Languages[0].LanguageCode;
}


let detectedLanguage: string | null = null;


async function processUserInput(userInput: string, userId: string, sessionId: string): Promise<void> {
  if (!detectedLanguage) {
    detectedLanguage = await detectLanguage(userInput);
    console.log(`Detected language: ${detectedLanguage}`);
  }


  try {
    const response = await orchestrator.routeRequest(
      userInput,
      userId,
      sessionId,
      { languageCode: detectedLanguage }
    );


    console.log("Processed response:", response);
  } catch (error) {
    console.error("Error:", error);
  }
}


// Example usage
processUserInput("Hello, world!", "user123", "session456");
// Subsequent calls will use the same detected language
processUserInput("How are you?", "user123", "session456");

Usage with ChainAgent

This example demonstrates how to use the ComprehendFilterAgent as part of a ChainAgent configuration:

import { MultiAgentOrchestrator, ChainAgent, ComprehendFilterAgent, BedrockLLMAgent } from 'multi-agent-orchestrator';


// Create a ComprehendFilterAgent
const filterAgent = new ComprehendFilterAgent({
  name: 'ContentFilter',
  description: 'Filters inappropriate content',
  enableSentimentCheck: true,
  enablePiiCheck: true,
  enableToxicityCheck: true,
  sentimentThreshold: 0.7,
  toxicityThreshold: 0.6
});


// Create a BedrockLLMAgent (or any other agent you want to use after filtering)
const llmAgent = new BedrockLLMAgent({
  name: 'LLMProcessor',
  description: 'Processes filtered content using a language model',
  streaming: true
});


// Create a ChainAgent that combines the filter and LLM agents
const chainAgent = new ChainAgent({
  name: 'FilteredLLMChain',
  description: 'Chain that filters content before processing with LLM',
  agents: [filterAgent, llmAgent]
});


// Add the chain agent to the orchestrator
const orchestrator = new MultiAgentOrchestrator();
orchestrator.addAgent(chainAgent);


// Use the chain
const response = await orchestrator.routeRequest(
  "Process this message after ensuring it's appropriate.",
  "user123",
  "session456"
);


if (response) {
  console.log("Message processed successfully:", response);
} else {
  console.log("Message was filtered out due to inappropriate content");
}

Configuration Options

The ComprehendFilterAgent supports the following configuration options:

  • enableSentimentCheck: Enable sentiment analysis (default: true)
  • enablePiiCheck: Enable PII detection (default: true)
  • enableToxicityCheck: Enable toxicity detection (default: true)
  • sentimentThreshold: Threshold for negative sentiment (default: 0.7)
  • toxicityThreshold: Threshold for toxic content (default: 0.7)
  • allowPii: Allow PII in content (default: false)
  • languageCode: ISO 639-1 language code for analysis (default: ‘en’)

Supported Languages

The ComprehendFilterAgent supports the following languages:

‘en’ (English), ‘es’ (Spanish), ‘fr’ (French), ‘de’ (German), ‘it’ (Italian), ‘pt’ (Portuguese), ‘ar’ (Arabic), ‘hi’ (Hindi), ‘ja’ (Japanese), ‘ko’ (Korean), ‘zh’ (Chinese Simplified), ‘zh-TW’ (Chinese Traditional)

By leveraging the ComprehendFilterAgent, you can implement robust content moderation in your Multi-Agent Orchestrator system, ensuring safe and appropriate interactions while leveraging the power of Amazon Comprehend for advanced content analysis.