curl -X POST https://api.rhizomeai.com/api/search \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "query_text": "FDA approval process",
    "top_k": 10,
    "offset": 0
  }'

import requests

response = requests.post(
    "https://api.rhizomeai.com/api/search",
    headers={
        "Content-Type": "application/json",
        "x-api-key": "YOUR_API_KEY"
    },
    json={
        "query_text": "FDA approval process",
        "top_k": 10,
        "offset": 0
    }
)

data = response.json()
print(f"Found {data['total']} results")
for result in data["results"]:
    print(f"- {result['name']} (page {result['page_num']})")

const response = await fetch("https://api.rhizomeai.com/api/search", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-api-key": "YOUR_API_KEY",
  },
  body: JSON.stringify({
    query_text: "FDA approval process",
    top_k: 10,
    offset: 0,
  }),
});

const data = await response.json();
console.log(`Found ${data.total} results`);

{
  "results": [
    {
      "id": "nda/2017/208264Orig1s000ChemR.pdf 3 42",
      "doc_id": "nda/2017/208264Orig1s000ChemR.pdf",
      "dataset": "fda_drug",
      "page_num": 42,
      "score": 15.57,
      "name": "TEPADINA THIOTEPA",
      "url": "https://www.accessdata.fda.gov/drugsatfda_docs/nda/2017/208264Orig1s000ChemR.pdf",
      "company": "ADIENNE SA",
      "year_decision": 2017,
      "text": "QUALITY ASSESSMENT | post approval + Formulation...",
      "highlight": "<b>Process</b> parameters * Scale/equipment * Site Leachables..."
    }
  ],
  "total": 17319
}