Searching a Knowledge Base

curl --location 'https://api.orq.ai/v2/knowledge/KNOWLEDGE_BASE_ID/search' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer $ORQ_API_KEY' \
--data '{
    "query": "What are the benefits of machine learning?"
}'

from orq_ai_sdk import Orq
import os

client = Orq(api_key=os.getenv("ORQ_API_KEY"))

results = client.knowledge.search(
    knowledge_id="KNOWLEDGE_BASE_ID",
    query="What are the benefits of machine learning?"
)

import { Orq } from '@orq-ai/node';

const orq = new Orq({
  apiKey: process.env.ORQ_API_KEY,
});

const results = await orq.knowledge.search({
  knowledgeId: 'KNOWLEDGE_BASE_ID',
  query: 'What are the benefits of machine learning?'
});

{
  "matches": [
    {
      "id": "01K2XYMZB25NC01T4BKWARQG5M",
      "text": "Machine learning algorithms excel at identifying complex patterns within vast datasets, enabling computers to make predictions and decisions without explicit programming. From recommendation systems that suggest your next favorite movie to autonomous vehicles navigating city streets, ML transforms raw data into actionable insights. Deep neural networks mimic brain structures, while ensemble methods combine multiple models for enhanced accuracy and robustness across diverse applications."
    },
    {
      "id": "01K2XYMZB25NC01T4BKWARQG5V",
      "text": "The neural network's gradient descent algorithm struggled to converge during training, prompting Sarah to adjust the learning rate from 0.01 to 0.001. Her convolutional layers were overfitting on the image classification dataset, so she implemented dropout regularization and data augmentation techniques. After 50 epochs, the validation accuracy plateaued at 87%, suggesting she needed more diverse training samples or perhaps a deeper architecture with residual connections to break through the performance barrier."
    }
... 
}

{
    "page_id": "page_x1i2j3",
    "edition": 2020,
}

{
    "color": "blue",
    "is_premium_info": true
}

curl --location 'http://api.orq.ai/v2/knowledge/01J58RKRX4AWMSBMJVPYY1N2CG/search' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer $ORQ_API_KEY' \
--data '{
    "query": "What we the top editions of science fiction books",
    "filter_by": {
        "edition": {
            "gte": 2020
        }
    },
    "search_options":{
        "include_metadata": true,
        "include_vectors": true,
        "include_scores": true
    }
}'

from orq_ai_sdk import Orq
import os

client = Orq(api_key=os.getenv("ORQ_API_KEY"))

client.knowledge.search(
    knowledge_id="unique_knowledge_id",
    query={"edition": {"$gte": 2020}},
    search_options={
        "include_metadata": True,
        "include_vectors": True,
        "include_scores": True,
    },
)

import { Orq } from '@orq-ai/node';

const orq = new Orq({
  apiKey: 'ORQ_API_KEY',
});

orq.knowledge.search({
  knowledgeId: 'unique_knowledge_id',
  query: { edition: { $gte: 2020 } },
  searchOptions: {
    includeMetadata: true,
    includeVectors: true,
    includeScores: true,
  },
});