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Symptom Description

When calling the API, you receive the following error messages:
{
  "error": {
    "message": "Insufficient balance",
    "type": "insufficient_balance",
    "code": "insufficient_balance"
  }
}
Or similar prompts:
  • “Account balance is insufficient”
  • “Please recharge”
  • “Balance insufficient, unable to complete request”

Cause Analysis

1. Balance Depleted

Account balance has been completely used up and needs recharge.

2. Insufficient Balance

Account has remaining balance, but insufficient for current request:
  • Request token count is too large
  • Selected model is expensive
  • Single request exceeds budget

3. Frozen Balance

Part of balance is frozen and unavailable:
  • Pending transactions
  • Risk control freezing
  • System reservation

4. Billing Method Mismatch

Using wrong billing method token:
  • Pay-per-use token calling usage-based billing models
  • Usage-based billing token calling pay-per-use models

Solutions

Immediate Solutions

1

Check Account Balance

  1. Log in to Laozhang API Console
  2. Check dashboard balance display
  3. View detailed transaction history
2

Recharge Account

  1. Click “Recharge” button in console
  2. Select recharge amount
  3. Complete payment process
  4. Wait for account balance update (usually instant)
3

Verify Recharge Success

  1. Refresh console page
  2. Check if balance has updated
  3. Retry API call

Emergency Alternatives

If urgent need to continue using:
  1. Switch to Lighter Model
    # Original: Using expensive model
    model = "gpt-4-turbo"
    
    # Alternative: Switch to economical model
    model = "gpt-3.5-turbo"
    
  2. Reduce Request Parameters
    # Reduce max_tokens
    response = client.chat.completions.create(
        model="gpt-4-turbo",
        max_tokens=500,  # Reduce from 2000 to 500
        messages=[...]
    )
    
  3. Use Backup Account
    • Switch to alternative API key
    • Switch to different service provider

Preventive Measures

1. Set Low Balance Alert

In console set alert threshold:
  • Recommended setting: 20% of usual daily usage
  • Alert methods: Email, SMS, webhook
  • Check frequency: Daily automatic check

2. Enable Auto-recharge

Configure auto-recharge rules:
Trigger condition: Balance < $10
Recharge amount: $50
Payment method: Credit card auto-deduct

3. Budget Management

Set usage budget:
  • Daily limit: Prevent unusual high usage in single day
  • Monthly limit: Control overall cost
  • Model-specific limit: Limit expensive model usage

4. Monitor Usage

Regularly check usage:
Weekly tasks:
- Check balance trend
- Analyze usage distribution
- Identify unusual usage
- Optimize cost structure

5. Choose Appropriate Billing Method

Choose based on usage pattern:
Usage PatternRecommended MethodReason
Stable, high-frequencyUsage-based billingLower unit price
Occasional usePay-per-useNo waste
Image/Video generationPay-per-useClear pricing
Chat applicationsUsage-based billingMore economical

Balance Management Best Practices

Budget Allocation

Reasonably allocate budgets:
Total monthly budget: $100

Allocation plan:
- Production environment: $60 (60%)
- Development testing: $20 (20%)
- Emergency reserve: $20 (20%)

Cost Optimization

Reduce unnecessary expenses:
  1. Model Selection Optimization
    # Simple tasks use economical models
    if task_complexity == "simple":
        model = "gpt-3.5-turbo"
    else:
        model = "gpt-4-turbo"
    
  2. Enable Caching
    # Cache common requests
    from functools import lru_cache
    
    @lru_cache(maxsize=100)
    def get_completion(prompt):
        return client.chat.completions.create(...)
    
  3. Batch Processing
    # Batch process requests to reduce overhead
    results = []
    for batch in chunks(requests, batch_size=10):
        results.extend(process_batch(batch))
    

Usage Tracking

Record and analyze usage:
import logging

# Log each API call
logging.info(f"API call: model={model}, tokens={tokens}, cost=${cost}")

# Regularly generate usage reports
def generate_usage_report():
    """Generate weekly usage report"""
    total_cost = sum(costs)
    total_requests = len(costs)
    avg_cost = total_cost / total_requests
    
    print(f"Total cost this week: ${total_cost}")
    print(f"Total requests: {total_requests}")
    print(f"Average cost per request: ${avg_cost}")

Common Questions

Recharge arrival time:
  • Online payment (credit card, PayPal): Usually instant
  • Bank transfer: 1-3 business days
  • Cryptocurrency: Wait for blockchain confirmation, about 10-30 minutes
If delayed:
  1. Check payment status
  2. Confirm correct account information
  3. Contact customer support
Refund policy:
  • Balance can be refunded without violations
  • Refund processing time: 3-7 business days
  • May deduct processing fees (typically 3%-5%)
Refund process:
  1. Submit refund request in console
  2. Provide payment proof
  3. Wait for review
  4. Receive refund
Estimation methods:
  1. Token Count Estimation
    • English: ~1 word = 1.3 tokens
    • Chinese: ~1 character = 2 tokens
  2. Use Official Pricing Calculator Visit Pricing Page for calculation
  3. Reference Historical Usage View usage in console
Example calculation:
Request: 1000 token prompt
Response: 2000 token completion
Model: gpt-4-turbo ($10/M tokens)

Cost = (1000 + 2000) / 1,000,000 * $10 = $0.03
Prevention measures:
  1. Set Rate Limits
    from ratelimit import limits, sleep_and_retry
    
    @sleep_and_retry
    @limits(calls=10, period=60)  # Limit 10 requests per minute
    def call_api():
        return client.chat.completions.create(...)
    
  2. Implement Request Validation
    def validate_request(prompt):
        token_count = estimate_tokens(prompt)
        if token_count > 10000:
            raise ValueError("Request too large")
    
  3. Enable Budget Alerts Set daily/weekly/monthly budget alerts
  4. Code Review Regularly review API call code to prevent loops or repeated calls
Free Tier Policy:Laozhang API currently does not offer free tier, but provides:
  • New user discount: First recharge gets 10% bonus
  • Volume discount: Large recharge gets higher discounts
  • Promotional activities: Occasional promotional offers
Cost Reduction Recommendations:
  1. Use economical models (GPT-3.5 Turbo)
  2. Optimize prompt length
  3. Enable result caching
  4. Batch process requests

Emergency Contact

If you cannot resolve the issue through above methods, please contact us through:
  • Online Support: Click chat icon in console
  • Email Support: [email protected]
  • Work Hours: Monday to Friday 9:00-18:00 (UTC+8)
  • Emergency Contact: For production environment issues, specify “Emergency” in email subject
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