"Ernie Bot API Guide 2026: Baidu AI API for Developers"

import requests

def get_ernie_access_token(api_key: str, secret_key: str) -> str:
    """Get OAuth access token for Ernie Bot API."""
    url = f"https://aip.baidubce.com/oauth/2.0/token"
    params = {
        "grant_type": "client_credentials",
        "client_id": api_key,
        "client_secret": secret_key
    }
    response = requests.post(url, params=params)
    return response.json()["access_token"]

def chat_with_ernie(
    message: str,
    api_key: str,
    secret_key: str,
    model: str = "ernie-4.0-turbo-8k"
) -> str:
    """Send a message to Ernie Bot."""
    
    access_token = get_ernie_access_token(api_key, secret_key)
    
    url = f"https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/{model}"
    
    headers = {"Content-Type": "application/json"}
    params = {"access_token": access_token}
    
    payload = {
        "messages": [
            {"role": "user", "content": message}
        ]
    }
    
    response = requests.post(url, headers=headers, params=params, json=payload)
    data = response.json()
    
    return data["result"]

# Usage
answer = chat_with_ernie(
    "请解释一下人工智能在医疗诊断中的应用",
    api_key="your-api-key",
    secret_key="your-secret-key"
)
print(answer)

def multi_turn_chat(
    conversation_history: list,
    new_message: str,
    api_key: str,
    secret_key: str
) -> tuple[str, list]:
    """Multi-turn conversation with Ernie."""
    
    access_token = get_ernie_access_token(api_key, secret_key)
    
    # Add new user message
    conversation_history.append({
        "role": "user",
        "content": new_message
    })
    
    url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k"
    
    payload = {
        "messages": conversation_history,
        "system": "你是一个专业的AI助手，回答要准确、简洁。"
    }
    
    response = requests.post(
        url,
        params={"access_token": access_token},
        json=payload
    )
    
    reply = response.json()["result"]
    
    # Add assistant reply to history
    conversation_history.append({
        "role": "assistant",
        "content": reply
    })
    
    return reply, conversation_history

# Usage
history = []
reply, history = multi_turn_chat(history, "什么是Transformer架构？", api_key, secret_key)
print(f"Ernie: {reply}")

reply, history = multi_turn_chat(history, "它的主要优势是什么？", api_key, secret_key)
print(f"Ernie: {reply}")

from openai import OpenAI

client = OpenAI(
    api_key="your-crazyrouter-key",
    base_url="https://crazyrouter.com/v1"
)

# Access Ernie via OpenAI-compatible format
response = client.chat.completions.create(
    model="ernie-4.0-turbo",
    messages=[
        {
            "role": "system",
            "content": "你是一个专业的助手，请用准确的中文回答问题。"
        },
        {
            "role": "user",
            "content": "解释一下大数据在零售行业的应用案例"
        }
    ],
    max_tokens=1024
)

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

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.CRAZYROUTER_API_KEY,
  baseURL: 'https://crazyrouter.com/v1',
});

async function ernieChatbot(userMessage, systemPrompt = '你是一个专业助手') {
  const response = await client.chat.completions.create({
    model: 'ernie-4.0-turbo',
    messages: [
      { role: 'system', content: systemPrompt },
      { role: 'user', content: userMessage }
    ],
    max_tokens: 2048,
    temperature: 0.7,
  });
  
  return response.choices[0].message.content;
}

// Usage
const answer = await ernieChatbot('帮我写一段商品介绍文案，产品是智能手表');
console.log(answer);

CUSTOMER_SERVICE_PROMPT = """你是XX公司的客服助手。
- 用礼貌、专业的中文回答
- 遇到无法解决的问题，引导用户联系人工客服
- 不要编造信息，如果不确定，请说"让我帮您查询一下"
- 回答要简洁，不超过200字"""

def handle_customer_query(query: str) -> str:
    return chat_with_ernie_sdk(query, system_prompt=CUSTOMER_SERVICE_PROMPT)

def summarize_chinese_doc(document: str, summary_length: str = "medium") -> str:
    length_map = {
        "short": "请用3句话总结",
        "medium": "请用100-200字总结",
        "long": "请用要点形式详细总结，分为主要观点和关键细节"
    }
    
    prompt = f"{length_map[summary_length]}以下文档的核心内容：\n\n{document}"
    
    response = client.chat.completions.create(
        model="ernie-4.0-turbo",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.3
    )
    
    return response.choices[0].message.content