your-project-directory/
├── .env                                 # API keys
├── organization_names_with_domains.json # Input file
├── company_analysis_results.json        # Output file
└── linkup_enrich.py                     # Enrichment script

import os
import json
import time
import re
from dotenv import load_dotenv
import requests

# Load environment variables
load_dotenv()

# API keys from environment variables
ATTIO_API_KEY = os.getenv('ATTIO_API_KEY')
LINKUP_API_KEY = os.getenv('LINKUP_API_KEY')

if not ATTIO_API_KEY or not LINKUP_API_KEY:
    print("Error: Missing API keys in .env file")
    exit(1)

# File paths and settings
FILE = 'new_companies.json'
MAX_COMPANIES = 50

def load_existing_data():
    """Load file with new companies to enrich"""
    try:
        with open(FILE, 'r') as f:
            return json.load(f)
    except (FileNotFoundError, json.JSONDecodeError):
        print(f"Error: Could not load {FILE}")
        exit(1)

def find_website_url(company_name, company_domain=None):
    if not company_name or not company_name.strip():
        return ""

    url = "https://api.linkup.so/v1/search"
    headers = {
        "Authorization": f"Bearer {LINKUP_API_KEY}",
        "Content-Type": "application/json"
    }

    domain_info = company_domain if company_domain else ""
    payload = {
        "q": f"Based on the name {company_name} and the email domain {domain_info}, find the most likely company website URL. Only return a result if you are 90% sure this is the correct website. If {company_name} seems like a generic company name (e.g. personal, perso, n/a), return nothing. If the domain is a generic domain (e.g. gmail.com, yahoo.com, hotmail.com, icloud.com), do not consider it. Only consider professional email domains. Only return the company domain URL.",
        "depth": "standard",
        "outputType": "sourcedAnswer",
        "includeImages": "false"
    }

    print(f"Sending API request to Linkup for: {company_name}")
    try:
        response = requests.post(url, headers=headers, json=payload)
        print(f"API response status: {response.status_code}")
        response.raise_for_status()

        result = response.json()
        if 'answer' in result:
            url_text = result['answer']
            url_pattern = re.compile(r'https?://\S+')
            url_match = url_pattern.search(url_text)

            if url_match:
                website_url = url_match.group(0)
                return re.sub(r'[.,;:"\')]\s*$', '', website_url)
        return ""

    except Exception as e:
        print(f"Error in API call: {e}")
        return ""

def analyze_icp_fit(company_name, website_url):
    if not website_url:
        return "1"

    url = "https://api.linkup.so/v1/search"
    headers = {
        "Authorization": f"Bearer {LINKUP_API_KEY}",
        "Content-Type": "application/json"
    }
    payload = {
        "q": f"Analyze the website {website_url}. Determine if this company could be an Ideal Customer Profile (ICP) for my company https://www.linkup.so/. For context, we are selling a search API. We target AI companies, Tech Companies, and corporates, as well as consulting and financial firms. Our search API allows companies to enrich applications with real-time web knowledge and business intelligence, at scale. Consider factors like industry and whether they're likely to need API services, and if they might be building software products. Return a rating from 1 to 5, 1 being lowest ICP, 5 being highest ICP. Universities and schools should get a 3.  Only return the rating, nothing else.",
        "depth": "deep",
        "outputType": "sourcedAnswer",
        "includeImages": "false"
    }

    print(f"Sending ICP analysis request to Linkup for: {company_name}")
    try:
        response = requests.post(url, headers=headers, json=payload)
        print(f"ICP API response status: {response.status_code}")
        response.raise_for_status()

        result = response.json()
        if 'answer' in result:
            return result['answer']
        return "1"

    except Exception as e:
        print(f"Error in ICP API call: {e}")
        return "1"

def save_results(results):
    print(f"\nSaving results to {FILE}...")
    try:
        # First try to save to a temporary file
        temp_file = f"{FILE}.tmp"
        with open(temp_file, 'w') as f:
            json.dump(results, f, indent=2)

        # If successful, rename the temp file to the actual file
        if os.path.exists(FILE):
            os.replace(temp_file, FILE)
        else:
            os.rename(temp_file, FILE)

        print(f"Successfully saved {len(results)} results")

        # Verify the save
        with open(FILE, 'r') as f:
            saved_data = json.load(f)
            print(f"Verified save: {len(saved_data)} results in file")

    except Exception as e:
        print(f"Error saving results: {e}")
        # Try to clean up temp file if it exists
        if os.path.exists(temp_file):
            try:
                os.remove(temp_file)
            except:
                pass

def main():
    results = load_existing_data()
    print(f"\nLoaded {len(results)} existing results")

    # Find organizations to process
    to_process = {record_id: (results[record_id]["name"], results[record_id].get("domain"))
                  for record_id in results
                  if not results[record_id].get("website") and
                     results[record_id].get("name") and
                     (not results[record_id].get("icp_analysis") or results[record_id].get("icp_analysis") == "")}

    companies_to_process = dict(list(to_process.items())[:MAX_COMPANIES])

    print(f"\nFound {len(to_process)} organizations to process")
    print(f"Will process {len(companies_to_process)} organizations...")

    processed_count = 0
    websites_found = 0

    for record_id, (org_name, org_domain) in companies_to_process.items():
        print(f"\nProcessing: {org_name}")

        company_result = results[record_id]
        website_url = find_website_url(org_name, org_domain)

        if website_url:
            company_result["website"] = website_url
            websites_found += 1
            print(f"Found: {website_url}")

            time.sleep(2)
            icp_analysis = analyze_icp_fit(org_name, website_url)
            company_result["icp_analysis"] = icp_analysis
            print(f"Updated {org_name} with website: {website_url} and ICP: {icp_analysis}")
        else:
            # Set default ICP analysis to "1" when no website is found
            company_result["icp_analysis"] = "1"
            print(f"Updated {org_name} with default ICP: 1")

        results[record_id] = company_result
        processed_count += 1

        # Save after each company
        save_results(results)
        print(f"Saved results after processing {org_name}")

        if processed_count < len(companies_to_process):
            time.sleep(3)

    websites_with_analysis = sum(1 for r in results.values() if r.get("website") and r.get("icp_analysis"))

    print(f"\nFinal Results:")
    print(f"Processed {processed_count} organizations")
    print(f"Found {websites_found} websites")
    print(f"Total organizations with websites: {sum(1 for r in results.values() if r.get('website'))}")
    print(f"Total organizations with analysis: {websites_with_analysis}")

    # Final save with verification
    save_results(results)

if __name__ == "__main__":
    main()