Search knowledge base

curl --request POST \
  --url https://api.orq.ai/v2/knowledge/{knowledge_id}/search \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "query": "<string>",
  "top_k": 50,
  "threshold": 0.5,
  "search_type": "hybrid_search",
  "filter_by": {},
  "search_options": {
    "include_vectors": true,
    "include_metadata": true,
    "include_scores": true
  }
}
'

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    query: '<string>',
    top_k: 50,
    threshold: 0.5,
    search_type: 'hybrid_search',
    filter_by: {},
    search_options: {include_vectors: true, include_metadata: true, include_scores: true}
  })
};

fetch('https://api.orq.ai/v2/knowledge/{knowledge_id}/search', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

import requests

url = "https://api.orq.ai/v2/knowledge/{knowledge_id}/search"

payload = {
    "query": "<string>",
    "top_k": 50,
    "threshold": 0.5,
    "search_type": "hybrid_search",
    "filter_by": {},
    "search_options": {
        "include_vectors": True,
        "include_metadata": True,
        "include_scores": True
    }
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

{
  "matches": [
    {
      "id": "<string>",
      "text": "<string>",
      "vector": [
        123
      ],
      "metadata": {},
      "scores": {
        "rerank_score": 123,
        "search_score": 123
      }
    }
  ]
}