curl -X POST "https://api.floreal.aiv1/public/documents/upload-from-url" \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://example.com/john-doe-cv.pdf",
    "documentName": "John Doe - Software Engineer",
    "documentDate": "11-2025"
  }'

{
  "documentId": "789e4567-e89b-12d3-a456-426614174000",
  "status": "uploading",
  "message": "Document fetched from URL and processing started",
  "estimatedProcessingTime": "30-60 seconds"
}

curl -X POST "https://api.floreal.aiv1/public/documents/upload-direct?documentName=John%20Doe&documentDate=11-2025" \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/pdf" \
  --data-binary @resume.pdf

# Step 1: Get presigned URL
curl -X POST "https://api.floreal.aiv1/public/documents/upload-presigned" \
  -H "X-API-Key: YOUR_API_KEY" \
  -d '{"fileName":"resume.pdf","contentType":"application/pdf","fileSize":245760}'

# Step 2: Upload to S3
curl -X PUT "PRESIGNED_URL" \
  -H "Content-Type: application/pdf" \
  --data-binary @resume.pdf

# Step 3: Finalize
curl -X POST "https://api.floreal.aiv1/public/documents/upload-presigned-finalize" \
  -H "X-API-Key: YOUR_API_KEY" \
  -d '{"uploadId":"...","documentName":"John Doe","documentDate":"11-2025"}'

async function waitForCompletion(documentId) {
  for (let i = 0; i < 18; i++) {
    // 90 seconds max
    const res = await fetch(
      `https://api.floreal.aiv1/public/documents/${documentId}`,
      { headers: { "X-API-Key": "YOUR_API_KEY" } }
    );
    const data = await res.json();

    if (data.status === "completed") {
      console.log("✅ Processing complete!");
      return data;
    }

    if (data.status === "failed") {
      throw new Error(data.error?.message);
    }

    console.log(`⏳ Status: ${data.status}`);
    await new Promise((r) => setTimeout(r, 5000)); // Wait 5s
  }
  throw new Error("Timeout");
}

const result = await waitForCompletion("789e4567-...");
console.log("Contact:", result.contact);
console.log("Profile:", result.profile);

import time
import requests

def wait_for_completion(document_id):
    for i in range(18):  # 90 seconds max
        response = requests.get(
            f'https://api.floreal.aiv1/public/documents/{document_id}',
            headers={'X-API-Key': 'YOUR_API_KEY'}
        )
        data = response.json()

        if data['status'] == 'completed':
            print('✅ Processing complete!')
            return data

        if data['status'] == 'failed':
            raise Exception(data.get('error', {}).get('message'))

        print(f"⏳ Status: {data['status']}")
        time.sleep(5)

    raise Exception('Timeout')

result = wait_for_completion('789e4567-...')
print('Contact:', result['contact'])
print('Profile:', result['profile'])

# Poll manually every 5 seconds
curl "https://api.floreal.aiv1/public/documents/789e4567-..." \
  -H "X-API-Key: YOUR_API_KEY"

const BASE_URL = "https://api.floreal.ai";
const API_KEY = "YOUR_API_KEY";

// 1. Upload CV
async function uploadCV(url, name) {
  const response = await fetch(
    `${BASE_URL}/v1/public/documents/upload-from-url`,
    {
      method: "POST",
      headers: {
        "X-API-Key": API_KEY,
        "Content-Type": "application/json",
      },
      body: JSON.stringify({
        url: url,
        documentName: name,
        documentDate: "11-2025",
      }),
    }
  );

  const { documentId } = await response.json();
  console.log("✅ Upload started:", documentId);

  // Wait for processing
  return await waitForProcessing(documentId);
}

// 2. Wait for processing
async function waitForProcessing(documentId) {
  for (let i = 0; i < 18; i++) {
    const response = await fetch(
      `${BASE_URL}/v1/public/documents/${documentId}`,
      {
        headers: { "X-API-Key": API_KEY },
      }
    );

    const data = await response.json();

    if (data.status === "completed") {
      console.log("✅ Processing complete!");
      return data;
    }

    if (data.status === "failed") {
      throw new Error(`Failed: ${data.error?.message}`);
    }

    console.log(`⏳ ${data.status}...`);
    await new Promise((r) => setTimeout(r, 5000));
  }
  throw new Error("Timeout");
}

// 3. Search for candidates
async function searchCandidates(query) {
  // Start search
  const searchResponse = await fetch(`${BASE_URL}/v1/public/searches/dense`, {
    method: "POST",
    headers: {
      "X-API-Key": API_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({ query, top_k: 20 }),
  });

  const { searchId } = await searchResponse.json();
  console.log("🔍 Search started:", searchId);

  // Wait for completion
  for (let i = 0; i < 20; i++) {
    const statusResponse = await fetch(
      `${BASE_URL}/v1/public/searches/${searchId}`,
      {
        headers: { "X-API-Key": API_KEY },
      }
    );

    const status = await statusResponse.json();

    if (status.status === "completed") {
      // Get results
      const resultsResponse = await fetch(
        `${BASE_URL}/v1/public/searches/${searchId}/results`,
        {
          headers: { "X-API-Key": API_KEY },
        }
      );

      const results = await resultsResponse.json();
      console.log(`✅ Found ${results.totalResults} candidates`);
      return results;
    }

    if (status.status === "failed") {
      throw new Error(`Search failed: ${status.error}`);
    }

    await new Promise((r) => setTimeout(r, 3000));
  }
  throw new Error("Search timeout");
}

// Usage
async function main() {
  // Upload CVs
  const cv1 = await uploadCV(
    "https://example.com/john-doe.pdf",
    "John Doe - Software Engineer"
  );
  console.log("Contact:", cv1.contact);
  console.log("Profile:", cv1.profile);

  // Search
  const results = await searchCandidates("experienced Python developer");
  results.results.forEach((candidate) => {
    console.log(`${candidate.contact.fullName} - Score: ${candidate.score}`);
  });
}

main();

import requests
import time

BASE_URL = 'https://api.floreal.ai'
API_KEY = 'YOUR_API_KEY'

def upload_cv(url, name):
    """Upload CV and wait for processing"""
    # Start upload
    response = requests.post(
        f'{BASE_URL}/v1/public/documents/upload-from-url',
        headers={
            'X-API-Key': API_KEY,
            'Content-Type': 'application/json'
        },
        json={
            'url': url,
            'documentName': name,
            'documentDate': '11-2025'
        }
    )

    document_id = response.json()['documentId']
    print(f'✅ Upload started: {document_id}')

    # Wait for processing
    for i in range(18):
        status_response = requests.get(
            f'{BASE_URL}/v1/public/documents/{document_id}',
            headers={'X-API-Key': API_KEY}
        )

        data = status_response.json()

        if data['status'] == 'completed':
            print('✅ Processing complete!')
            return data

        if data['status'] == 'failed':
            raise Exception(f"Failed: {data.get('error', {}).get('message')}")

        print(f"⏳ {data['status']}...")
        time.sleep(5)

    raise Exception('Timeout')

def search_candidates(query):
    """Search for candidates"""
    # Start search
    search_response = requests.post(
        f'{BASE_URL}/v1/public/searches/dense',
        headers={
            'X-API-Key': API_KEY,
            'Content-Type': 'application/json'
        },
        json={'query': query, 'top_k': 20}
    )

    search_id = search_response.json()['searchId']
    print(f'🔍 Search started: {search_id}')

    # Wait for completion
    for i in range(20):
        status_response = requests.get(
            f'{BASE_URL}/v1/public/searches/{search_id}',
            headers={'X-API-Key': API_KEY}
        )

        status = status_response.json()

        if status['status'] == 'completed':
            # Get results
            results_response = requests.get(
                f'{BASE_URL}/v1/public/searches/{search_id}/results',
                headers={'X-API-Key': API_KEY}
            )

            results = results_response.json()
            print(f"✅ Found {results['totalResults']} candidates")
            return results

        if status['status'] == 'failed':
            raise Exception(f"Search failed: {status.get('error')}")

        time.sleep(3)

    raise Exception('Search timeout')

# Usage
if __name__ == '__main__':
    # Upload CV
    cv = upload_cv(
        'https://example.com/john-doe.pdf',
        'John Doe - Software Engineer'
    )
    print('Contact:', cv['contact'])
    print('Profile:', cv['profile'])

    # Search
    results = search_candidates('experienced Python developer')
    for candidate in results['results']:
        print(f"{candidate['contact']['fullName']} - Score: {candidate['score']}")