List organization models

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// Fetch models and build dropdown
async function loadModelSelector() {
  const response = await fetch(
    `https://api.freddy.aitronos.com/v1/organizations/${orgId}/models`,
    { headers: { 'Authorization': `Bearer ${token}` } }
  );
  
  const data = await response.json();
  
  // Create dropdown options
  const select = document.getElementById('model-selector');
  data.models.forEach(model => {
    const option = document.createElement('option');
    option.value = model.key;
    option.textContent = `${model.title} - ${model.provider}`;
    if (model.maxTokens) {
      option.textContent += ` (${model.maxTokens.toLocaleString()} tokens)`;
    }
    select.appendChild(option);
  });
}

import requests

response = requests.get(
    f"https://api.freddy.aitronos.com/v1/organizations/{org_id}/models",
    headers={"Authorization": f"Bearer {token}"}
)

models = response.json()

# Get only OpenAI models
openai_models = [m for m in models['models'] if m['provider'] == 'openai']
print(f"OpenAI models: {len(openai_models)}")

# Get only Anthropic models
anthropic_models = [m for m in models['models'] if m['provider'] == 'anthropic']
print(f"Anthropic models: {len(anthropic_models)}")

# Get Aitronos models
aitronos_models = [m for m in models['models'] if m['provider'] == 'aitronos']
print(f"Aitronos models: {len(aitronos_models)}")

# Find model with largest context window
largest_context = max(
    models['models'],
    key=lambda m: m['maxTokens'] if m['maxTokens'] else 0
)
print(f"Largest context: {largest_context['title']} ({largest_context['maxTokens']} tokens)")

# Find fastest model (assuming lower order = faster/preferred)
fastest = min(models['models'], key=lambda m: m['order'])
print(f"Preferred model: {fastest['title']}")

import json
from datetime import datetime, timedelta

CACHE_FILE = "models_cache.json"
CACHE_DURATION = timedelta(hours=1)

def get_organization_models(org_id, token, force_refresh=False):
    """Get models with caching"""
    # Check cache
    if not force_refresh:
        try:
            with open(CACHE_FILE, 'r') as f:
                cache = json.load(f)
                cache_time = datetime.fromisoformat(cache['timestamp'])
                if datetime.now() - cache_time < CACHE_DURATION:
                    return cache['data']
        except (FileNotFoundError, KeyError, ValueError):
            pass
    
    # Fetch fresh data
    response = requests.get(
        f"https://api.freddy.aitronos.com/v1/organizations/{org_id}/models",
        headers={"Authorization": f"Bearer {token}"}
    )
    data = response.json()
    
    # Update cache
    with open(CACHE_FILE, 'w') as f:
        json.dump({
            'timestamp': datetime.now().isoformat(),
            'data': data
        }, f)
    
    return data