API Developer Manual

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Why Choose LaoZhang API?

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Platform Features

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OpenAI Compatible Mode

• 🤖 OpenAI: gpt-4o, gpt-5-chat-latest, gpt-3.5-turbo, etc.
• 🧠 Anthropic: claude-sonnet-4-20250514, claude-opus-4-1-20250805, etc.
• 💎 Google: gemini-2.5-pro, gemini-2.5-flash, etc.
• 🚀 xAI: grok-4-0709, grok-3, etc.
• 🔍 DeepSeek: deepSeek-r1, deepSeek-v3, etc.
• 🌟 Alibaba: Qwen series models
• 💬 Moonshot: Kimi models, etc.

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Feature Support

• 💬 Chat Completions: Chat Completions interface
• 🖼️ Image Generation: gpt-image-1, flux-kontext-pro, flux-kontext-max, etc.
• 🔊 Audio Processing: Whisper transcription
• 📊 Embeddings: Text vectorization
• ⚡ Function Calling: Function Calling
• 📡 Streaming: Real-time responses
• 🔧 OpenAI Parameters: temperature, top_p, max_tokens, etc.
• 🆕 Responses Endpoint: Latest OpenAI features

• 🔧 Fine-tuning interface
• 📁 Files management interface
• 🏢 Organization management interface
• 💳 Billing management interface

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Easy Model Switching

# Use GPT-4o
response = client.chat.completions.create(
    model="gpt-4o",  # OpenAI model
    messages=[...]
)

# Switch to Claude, everything else stays the same!
response = client.chat.completions.create(
    model="claude-3.5-sonnet",  # Just change model name
    messages=[...]
)

# Switch to Gemini
response = client.chat.completions.create(
    model="gemini-1.5-pro",  # Just change model name
    messages=[...]
)

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Quick Start - Using ChatGPT API in China

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Get API Key (China-Specific)

1. Visit LaoZhang API Console
2. Log in to your account
3. Click “Add” on the token management page to create an API Key
4. Copy the generated API Key for interface calls

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View Request Examples

1. Go to Token Management Page
2. Find the row with the API Key you want to use
3. Click the 🔧wrench icon (tool icon) in the “Actions” column
4. Select “Request Example” from the pop-up menu
5. View complete code examples in the following languages:

• cURL - Command-line testing
• Python (SDK) - Using official OpenAI library
• Python (requests) - Using requests library
• Node.js - JavaScript/TypeScript
• Java - Java application development
• C# - .NET application development
• Go - Go language development
• PHP - Web development
• Ruby - Ruby application development
• And more languages…

• ✅ Complete and runnable: Copy and paste to use
• ✅ Parameter descriptions: Detailed parameter configuration
• ✅ Error handling: Includes exception handling logic
• ✅ Best practices: Follows development standards for each language

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Basic Information

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API Endpoints

• Primary endpoint: https://api.laozhang.ai/v1
• Backup endpoint: https://api-cf.laozhang.ai/v1

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Authentication Method

Authorization: Bearer YOUR_API_KEY

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Request Format

• Content-Type: application/json
• Encoding: UTF-8
• Request Method: POST (for most interfaces)

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Core Interfaces

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1. Chat Completions

POST /v1/chat/completions

{
  "role": "system|user|assistant",
  "content": "Message content"
}

curl -X POST "https://api.laozhang.ai/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-3.5-turbo",
    "messages": [
      {"role": "system", "content": "You are a helpful AI assistant."},
      {"role": "user", "content": "Hello! Please introduce yourself."}
    ],
    "temperature": 0.7,
    "max_tokens": 1000
  }'

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1699000000,
  "model": "gpt-3.5-turbo",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "Hello! How can I help you today?"
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 20,
    "completion_tokens": 10,
    "total_tokens": 30
  }
}

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2. Text Completions

POST /v1/completions

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3. Embeddings

POST /v1/embeddings

curl -X POST "https://api.laozhang.ai/v1/embeddings" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-ada-002",
    "input": "This is a text example that needs to be vectorized"
  }'

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4. Images

POST /v1/images/generations

curl -X POST "https://api.laozhang.ai/v1/images/generations" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-1",
    "prompt": "A cute orange kitten sitting in a sunny garden",
    "n": 1,
    "size": "1024x1024",
    "quality": "hd"
  }'

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5. Audio

POST /v1/audio/transcriptions

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6. Model List

GET /v1/models

{
  "object": "list",
  "data": [
    {
      "id": "gpt-3.5-turbo",
      "object": "model",
      "created": 1677610602,
      "owned_by": "openai"
    },
    {
      "id": "gpt-4o",
      "object": "model",
      "created": 1687882411,
      "owned_by": "openai"
    }
  ]
}

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Streaming Responses

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Enable Streaming Output

{
  "model": "gpt-3.5-turbo",
  "messages": [{"role": "user", "content": "Hello"}],
  "stream": true
}

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Streaming Response Format

data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1699000000,"model":"gpt-3.5-turbo","choices":[{"delta":{"content":"Hello"},"index":0}]}

data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1699000000,"model":"gpt-3.5-turbo","choices":[{"delta":{"content":" there"},"index":0}]}

data: [DONE]

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Handling Streaming Responses

import requests
import json

response = requests.post(
    'https://api.laozhang.ai/v1/chat/completions',
    headers={
        'Authorization': f'Bearer {api_key}',
        'Content-Type': 'application/json'
    },
    json={
        'model': 'gpt-3.5-turbo',
        'messages': [{'role': 'user', 'content': 'Hello'}],
        'stream': True
    },
    stream=True
)

for line in response.iter_lines():
    if line:
        line = line.decode('utf-8')
        if line.startswith('data: '):
            data = line[6:]
            if data != '[DONE]':
                chunk = json.loads(data)
                content = chunk['choices'][0]['delta'].get('content', '')
                print(content, end='')

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Error Handling

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Error Response Format

{
  "error": {
    "message": "Invalid API key provided",
    "type": "invalid_request_error",
    "param": null,
    "code": "invalid_api_key"
  }
}

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Common Error Codes

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Error Handling Example

try:
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": "Hello"}]
    )
except Exception as e:
    if hasattr(e, 'status_code'):
        if e.status_code == 401:
            print("Invalid API key")
        elif e.status_code == 429:
            print("Requests too frequent or insufficient quota")
        elif e.status_code == 500:
            print("Server error, please try again later")
    else:
        print(f"Unknown error: {str(e)}")

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Best Practices

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1. Request Optimization

• Set max_tokens reasonably: Avoid unnecessarily long outputs
• Use temperature: Control output randomness
• Batch processing: Combine multiple requests to reduce call count

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2. Error Retry

import time
import random

def retry_with_backoff(func, max_retries=3):
    for i in range(max_retries):
        try:
            return func()
        except Exception as e:
            if i == max_retries - 1:
                raise e
            wait_time = (2 ** i) + random.uniform(0, 1)
            time.sleep(wait_time)

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3. Security Recommendations

• Protect API keys: Store in environment variables
• Limit permissions: Create different keys for different applications
• Monitor usage: Regularly check API usage logs

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4. Performance Optimization

• Use streaming output: Improve user experience
• Cache responses: Cache results for identical requests
• Concurrency control: Reasonably control concurrent request count

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Rate Limits

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Need Help?

• Visit LaoZhang API Official Site
• Check Supported Models
• Contact technical support: [email protected]