Filters

curl -X POST https://api.brainus.lk/api/v1/dev/query \
  -H "X-API-Key: $BRAINUS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Explain quadratic equations",
    "store_id": "default",
    "filters": {
      "grade": "11"
    }
  }'

# Using Python with actual API
import requests

response = requests.post(
    "https://api.brainus.lk/api/v1/dev/query",
    headers={"X-API-Key": "your_api_key"},
    json={
        "query": "Explain quadratic equations",
        "store_id": "default",
        "filters": {
            "grade": "11"
        }
    }
)

const response = await fetch('https://api.brainus.lk/api/v1/dev/query', {
  method: 'POST',
  headers: {
    'X-API-Key': 'your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    query: 'Explain quadratic equations',
    store_id: 'default',
    filters: {
      grade: '11'
    }
  })
});

import os
import asyncio
from brainus_ai import BrainusAI

async def main():
    async with BrainusAI() as client:
        response = await client.query(
            query="Explain the water cycle",
            store_id="default",
            filters={
                "grade": "9",  # Single string, not array
                "subject": "science",  # Single string, not array
                "language": "english"
            }
        )

        print(f"Answer: {response.answer}\n")

        if response.citations:
            print(f"Found {len(response.citations)} relevant sources:")
            for i, citation in enumerate(response.citations, 1):
                # Accessing metadata dict if available
                grade = citation.metadata.get('grade', 'N/A') if citation.metadata else 'N/A'
                subject = citation.metadata.get('subject', 'N/A') if citation.metadata else 'N/A'

                print(f"\n{i}. {citation.document_name}")
                if citation.pages:
                    print(f"   Pages: {', '.join(map(str, citation.pages))}")
                print(f"   Grade: {grade}")
                print(f"   Subject: {subject}")
                if citation.chunk_text:
                    print(f"   Snippet: {citation.chunk_text[:100]}...")

if __name__ == "__main__":
    asyncio.run(main())

import { BrainusAI } from '@brainus/ai';

const client = new BrainusAI(); // reads BRAINUS_API_KEY from environment

async function main() {
  const response = await client.query({
    query: 'Explain the water cycle',
    storeId: 'default',
    filters: {
      grade: '9',
      subject: 'Science',
      language: 'english'
    }
  });

  console.log(`Answer: ${response.answer}\n`);

  if (response.hasCitations) {
    console.log(`Found ${response.citations.length} relevant sources:`);
    response.citations.forEach((citation, i) => {
      const grade = citation.metadata?.grade || 'N/A';
      const subject = citation.metadata?.subject || 'N/A';

      console.log(`\n${i + 1}. ${citation.documentName}`);
      if (citation.pages.length > 0) {
        console.log(`   Pages: ${citation.pages.join(", ")}`);
      }
      console.log(`   Grade: ${grade}`);
      console.log(`   Subject: ${subject}`);
      if (citation.chunkText) {
        console.log(`   Snippet: ${citation.chunkText.substring(0, 100)}...`);
      }
    });
  }
}

main();