[Service Name] API

📋 Service Overview

Service Name: [API Service Name]
Provider: Provider Name
API Endpoint: https://api.example.com/v1 (if has placeholders) or https://api.example.com/v1 (if fixed URL)
Service Type: [Completely Free/Limited Free/Trial Credits]
Registration Requirements: [Whether registration/credit card/identity verification required]

✅ Service Description

[Service Name] API is [service form description, such as: developer API interface, RESTful API service, etc.] provided by [Provider Name].

Main Features

• [Feature 1]: [Detailed explanation]
• [Feature 2]: [Detailed explanation]
• [Feature 3]: [Detailed explanation]
• [Feature 4]: [Detailed explanation]

🎁 Available Models

Free/Trial Models List

Model Detailed Description

[Model 1]

• Context Window: [Specific value]
• Main Purpose: [Explanation]
• Advantages: [Explanation]

[Model 2]

• Context Window: [Specific value]
• Main Purpose: [Explanation]
• Advantages: [Explanation]

🔢 Quotas and Limitations

Free Tier Limitations

⚠️ Important Limitations

1. [Limitation 1]: [Detailed explanation]
2. [Limitation 2]: [Detailed explanation]
3. [Limitation 3]: [Detailed explanation]

Quota Reset Time

• Daily Quota: [Reset time, e.g., UTC 0:00]
• Per-minute Quota: [Reset rules]
• Trial Credits: [Validity period and expiration rules]

💰 Pricing Information

Free/Trial

• Free Quota: [Explanation]
• Trial Credits: [Amount and validity period]
• Acquisition Method: [Explanation]

Paid Pricing (if applicable)

🚀 How to Use

Prerequisites

1. Register Account

If registration process is explained in Provider document, link to it:

• Please register an account first

If it’s API-specific registration process, explain in detail.

2. Get API Key

Detailed steps (if same for all users):

Step 1: Login to Developer Platform

1. Visit Developer Platform
2. Login with your account

Step 2: Create API Key

1. [Detailed operation]
2. [Detailed operation]
3. Important: Copy and securely save your API key

Step 3: [Optional step, like topping up or binding credit card]

1. [Detailed operation]
2. [Detailed operation]

💻 Code Examples

Python Example

Install Dependencies:

pip install openai  # or other SDK

Basic Usage:

from openai import OpenAI

# Initialize client (please replace with your API key)
client = OpenAI(
    base_url="https://api.example.com/v1",
    api_key="YOUR_API_KEY"
)

# Send request
response = client.chat.completions.create(
    model="model-name",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello, please introduce yourself."}
    ],
    max_tokens=1000,
    temperature=0.7
)

# Print response
print(response.choices[0].message.content)

# View Token usage
print(f"\nTokens used: {response.usage.total_tokens}")

Streaming Output Example:

# Streaming output (suitable for real-time display)
stream = client.chat.completions.create(
    model="model-name",
    messages=[
        {"role": "user", "content": "Write a poem about AI"}
    ],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

cURL Example

Basic Request:

curl https://api.example.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "model-name",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello, please introduce yourself."
      }
    ],
    "max_tokens": 1000,
    "temperature": 0.7
  }'

Streaming Output:

curl https://api.example.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "model-name",
    "messages": [{"role": "user", "content": "Hello"}],
    "stream": true
  }'

Node.js Example (Optional)

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://api.example.com/v1',
  apiKey: 'YOUR_API_KEY',
});

async function main() {
  const completion = await client.chat.completions.create({
    model: 'model-name',
    messages: [
      { role: 'system', content: 'You are a helpful assistant.' },
      { role: 'user', content: 'Hello, please introduce yourself.' }
    ],
    max_tokens: 1000,
    temperature: 0.7,
  });

  console.log(completion.choices[0].message.content);
  console.log(`\nTokens used: ${completion.usage.total_tokens}`);
}

main();

🌟 Core Advantages

Technical Advantages

1. [Advantage 1]:

   • [Detailed explanation]
   • [Data support]

2. [Advantage 2]:

   • [Detailed explanation]
   • [Data support]

3. [Advantage 3]:

   • [Detailed explanation]
   • [Data support]

Comparison with Other APIs

💡 Practical Suggestions

✅ Recommended Practices

1. [Suggestion 1]:

   • [Detailed explanation]
   • [Code example]

2. [Suggestion 2]:

   • [Detailed explanation]
   • [Code example]

3. [Suggestion 3]:

   • [Detailed explanation]

🎯 Best Practices

Make Full Use of Free Quota:

• [Suggestion 1]
• [Suggestion 2]
• [Suggestion 3]

Optimize Token Usage:

• [Suggestion 1]
• [Suggestion 2]
• [Suggestion 3]

Error Handling:

import time
from openai import OpenAI, RateLimitError, APIError

client = OpenAI(
    base_url="https://api.example.com/v1",
    api_key="YOUR_API_KEY"
)

def call_api_with_retry(messages, max_retries=3):
    """API call with retry mechanism"""
    for attempt in range(max_retries):
        try:
            response = client.chat.completions.create(
                model="model-name",
                messages=messages
            )
            return response
        except RateLimitError:
            print(f"Rate limit reached, waiting and retrying... ({attempt + 1}/{max_retries})")
            time.sleep(2 ** attempt)  # Exponential backoff
        except APIError as e:
            print(f"API error: {e}")
            if attempt == max_retries - 1:
                raise
    
    return None

⚠️ Precautions

1. [Precaution 1]: [Explanation]
2. [Precaution 2]: [Explanation]
3. [Precaution 3]: [Explanation]

🎯 Practical Application Cases

Case 1: [Application Scenario Name]

Scenario Description: [Description]

# Complete code example
def example_case_1():
    """[Function description]"""
    client = OpenAI(
        base_url="https://api.example.com/v1",
        api_key="YOUR_API_KEY"
    )
    
    # Implementation code
    response = client.chat.completions.create(
        model="model-name",
        messages=[
            {"role": "user", "content": "Example question"}
        ]
    )
    
    return response.choices[0].message.content

# Usage example
result = example_case_1()
print(result)

Case 2: [Application Scenario Name]

Scenario Description: [Description]

# Code example

🔧 Common Questions

Q: [Question 1]
A: [Answer]

Q: [Question 2]
A: [Answer]

Q: [Question 3]
A: [Answer]

Q: [Question 4]
A: [Answer]

Q: [Question 5]
A: [Answer]

🔗 Related Resources

• API Endpoint: https://api.example.com/v1
• Developer Platform: https://platform.example.com
• API Documentation: https://docs.example.com
• Provider Homepage: Link to Provider document
• Corresponding Chatbot Service: Link to Chatbot document (if available)
• SDK Repository: [GitHub link]
• Example Code: [GitHub link]
• API Status: [Status page link]

📝 Changelog

• [Year-Month]: [API updates, new models, quota changes]
• [Year-Month]: [API updates, new models, quota changes]
• [Year-Month]: [API updates, new models, quota changes]

Service Provider: [Provider Name]