Knowledge Base (RAG)

Give your Agents access to documents, FAQs, and data. Agents automatically search the knowledge base to answer questions accurately.

Quick Start

Simple Usage

import { Agent, createKnowledgeBase } from 'praisonai';

// Create knowledge base with your documents
const kb = createKnowledgeBase();
await kb.add({ id: 'faq1', content: 'Our return policy allows returns within 30 days.' });
await kb.add({ id: 'faq2', content: 'Shipping takes 3-5 business days.' });
await kb.add({ id: 'faq3', content: 'Contact support at help@example.com.' });

// Agent uses knowledge base to answer questions
const agent = new Agent({
  name: 'Support Agent',
  instructions: 'Answer customer questions using the knowledge base.',
  knowledgeBase: kb
});

await agent.chat('What is your return policy?');
// Agent searches KB and responds: "Our return policy allows returns within 30 days."

await agent.chat('How long does shipping take?');
// Agent responds: "Shipping takes 3-5 business days."

With Configuration

const kb = createKnowledgeBase({ embeddings: 'openai/text-embedding-3-small' });

const agent = new Agent({
  name: 'Support Agent',
  instructions: 'Answer customer questions using the knowledge base.',
  knowledgeBase: kb,
  verbose: true,
});

Agent with Document Loading

import { Agent, createKnowledgeBase } from 'praisonai';

const kb = createKnowledgeBase();

// Load multiple documents
await kb.addBatch([
  { id: 'product-1', content: 'Product A: $99, wireless headphones with 20hr battery' },
  { id: 'product-2', content: 'Product B: $149, noise-canceling headphones with 30hr battery' },
  { id: 'product-3', content: 'Product C: $199, premium headphones with 40hr battery and ANC' }
]);

const salesAgent = new Agent({
  name: 'Sales Agent',
  instructions: 'Help customers find the right product based on their needs.',
  knowledgeBase: kb
});

await salesAgent.chat('I need headphones with long battery life');
// Agent searches and recommends Product C with 40hr battery

Multi-Agent Shared Knowledge

import { Agent, Agents, createKnowledgeBase } from 'praisonai';

// Shared knowledge base for the team
const companyKB = createKnowledgeBase();
await companyKB.addBatch([
  { id: 'policy-1', content: 'Vacation policy: 20 days PTO per year' },
  { id: 'policy-2', content: 'Remote work: Hybrid model, 3 days in office' },
  { id: 'tech-1', content: 'Tech stack: TypeScript, React, PostgreSQL' }
]);

// HR Agent uses company knowledge
const hrAgent = new Agent({
  name: 'HR Assistant',
  instructions: 'Answer HR and policy questions.',
  knowledgeBase: companyKB
});

// Tech Agent uses same knowledge
const techAgent = new Agent({
  name: 'Tech Assistant',
  instructions: 'Answer technical questions about our stack.',
  knowledgeBase: companyKB
});

await hrAgent.chat('How many vacation days do I get?');
await techAgent.chat('What database do we use?');

Agent with RAG Tool

Give Agent explicit control over knowledge search:

import { Agent, createKnowledgeBase, createTool } from 'praisonai';

const kb = createKnowledgeBase();
await kb.add({ id: 'doc1', content: 'Important company information...' });

// Tool to search knowledge base
const searchKBTool = createTool({
  name: 'search_knowledge',
  description: 'Search the knowledge base for relevant information',
  parameters: {
    type: 'object',
    properties: {
      query: { type: 'string', description: 'Search query' }
    },
    required: ['query']
  },
  execute: async ({ query }) => {
    const results = await kb.search(query, 3);
    return results.map(r => r.document.content).join('\n');
  }
});

const agent = new Agent({
  name: 'Research Agent',
  instructions: 'Use search_knowledge to find information before answering.',
  tools: [searchKBTool]
});

await agent.chat('What do you know about the company?');

Document Operations

// Get document
const doc = kb.get('doc1');

// Delete document
kb.delete('doc1');

// List all documents
const allDocs = kb.list();

// Get count
console.log('Documents:', kb.size);

// Clear all
kb.clear();

Custom Embedding Provider

import { KnowledgeBase, EmbeddingProvider } from 'praisonai';

const customEmbedder: EmbeddingProvider = {
  async embed(text: string): Promise<number[]> {
    // Your embedding logic
    return await callEmbeddingAPI(text);
  },
  async embedBatch(texts: string[]): Promise<number[][]> {
    return Promise.all(texts.map(t => this.embed(t)));
  }
};

const kb = new KnowledgeBase({
  embeddingProvider: customEmbedder,
  similarityThreshold: 0.7,
  maxResults: 5
});

Knowledge Base CLI

CLI knowledge commands

Vector Stores

Scalable document storage

​Quick Start

​Agent with Document Loading

​Multi-Agent Shared Knowledge

​Agent with RAG Tool

​Document Operations

​Custom Embedding Provider

​Related