Configuration

Configure Orka AI defaults, adapters, memory, observability, and prompt management.

Full Configuration

Here's a complete example showing all available configuration options:

Import Methods

Standard import:

import { createOrka, OpenAIAdapter, PineconeAdapter } from 'orkajs';

Tree-shakeable import (recommended for production):

import { createOrka } from 'orkajs/core';
import { OpenAIAdapter, PineconeAdapter } from 'orkajs/adapters/openai';
// Or 
//import { PineconeAdapter } from 'orkajs/adapters/pinecone';

import { createOrka, OpenAIAdapter, PineconeAdapter } from 'orkajs';
 
const orka = createOrka({
  // Required: LLM provider
  llm: new OpenAIAdapter({
    apiKey: process.env.OPENAI_API_KEY!,
    model: 'gpt-4o-mini',
    embeddingModel: 'text-embedding-3-small',
  }),
 
  // Required: Vector database
  vectorDB: new PineconeAdapter({
    apiKey: process.env.PINECONE_API_KEY!,
    indexHost: 'https://your-index.svc.pinecone.io',
  }),
 
  // Optional: Default parameters
  defaults: {
    chunkSize: 1000,
    chunkOverlap: 200,
    topK: 5,
    temperature: 0.7,
    maxTokens: 1024,
  },
 
  // Optional: Memory configuration
  memory: {
    maxMessages: 50,
    strategy: 'sliding_window',
  },
 
  // Optional: Observability
  observability: {
    logLevel: 'info',
    hooks: [{
      onTraceEnd: (trace) => console.log(`Done: ${trace.totalLatencyMs}ms`),
    }],
  },
});

1. LLM Provider (Required)

The LLM adapter handles text generation and embeddings. Orka AI supports multiple providers:

OpenAI

GPT-4, GPT-4o, GPT-3.5-turbo

import { OpenAIAdapter } from 'orkajs';
 
llm: new OpenAIAdapter({
  apiKey: process.env.OPENAI_API_KEY!,
  model: 'gpt-4o-mini',
  embeddingModel: 'text-embedding-3-small',
})

→ Get API Key

Anthropic

Claude 3.5 Sonnet, Claude 3 Opus

import { AnthropicAdapter } from 'orkajs';
 
llm: new AnthropicAdapter({
  apiKey: process.env.ANTHROPIC_API_KEY!,
  model: 'claude-3-5-sonnet-20241022',
})

→ Get API Key

Mistral AI

Mistral Large, Mistral Medium

import { MistralAdapter } from 'orkajs';
 
llm: new MistralAdapter({
  apiKey: process.env.MISTRAL_API_KEY!,
  model: 'mistral-large-latest',
})

→ Get API Key

Ollama

Local models (Llama 3.2, Mistral, etc.)

import { OllamaAdapter } from 'orkajs';
 
llm: new OllamaAdapter({
  baseURL: 'http://localhost:11434',
  model: 'llama3.2',
})

→ Download Ollama

2. Vector Database (Required)

The vector database stores document embeddings for semantic search. Choose based on your deployment needs:

MemoryVectorAdapter

Best for: Development, testing, prototyping

import { MemoryVectorAdapter } from 'orkajs';
 
vectorDB: new MemoryVectorAdapter()

⚠️ Data is lost on restart

PineconeAdapter

Best for: Production, cloud-native, scalable

import { PineconeAdapter } from 'orkajs';
 
vectorDB: new PineconeAdapter({
  apiKey: process.env.PINECONE_API_KEY!,
  indexHost: 'https://your-index.svc.pinecone.io',
})

→ Get Started with Pinecone

QdrantAdapter

Best for: Self-hosted, on-premise, Docker

import { QdrantAdapter } from 'orkajs';
 
vectorDB: new QdrantAdapter({
  url: 'http://localhost:6333',
  apiKey: process.env.QDRANT_API_KEY,
})

→ Qdrant Documentation

ChromaAdapter

Best for: Local development, embedded use

import { ChromaAdapter } from 'orkajs';
 
vectorDB: new ChromaAdapter({
  url: 'http://localhost:8000',
})

→ Chroma Documentation

3. Default Parameters (Optional)

Set default values for chunking, retrieval, and generation. These can be overridden per-call.

4. Memory Configuration (Optional)

Configure conversation memory to maintain context across multiple interactions. The sliding_window strategy keeps the most recent messages.

5. Observability (Optional)

Monitor your application with logging and trace hooks. Use hooks to integrate with external monitoring tools like DataDog, New Relic, or custom analytics.

Configuration Reference

Property	Type	Default	Description
chunkSize	`number`	1000	Characters per chunk
chunkOverlap	`number`	200	Overlap between chunks
topK	`number`	5	Results for RAG queries
temperature	`number`	0.7	LLM creativity (0-1)
maxTokens	`number`	1024	Max tokens per response

💡 Pro Tip

All default values can be overridden per-call. For example, orka.ask({ topK: 10 }) overrides the default topK for that specific query.