文本生成 API

https://api.aiearth.dev/v1
https://api.aiearth.vip/v1

POST /chat/completions

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIO_API_KEY"],
    base_url=os.environ.get("AIO_BASE_URL", "https://api.aiearth.dev/v1"),
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "user", "content": "用三句话介绍人工智能的发展历程。"}
    ],
)

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

curl "https://api.aiearth.dev/v1/chat/completions" \
  -H "Authorization: Bearer $AIO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [
      {
        "role": "user",
        "content": "用三句话介绍人工智能的发展历程。"
      }
    ]
  }'

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://api.aiearth.dev/v1",
)

messages = [
    {"role": "system", "content": "你是一个专业的 Python 编程助手。"},
    {"role": "user", "content": "如何读取 CSV 文件？"},
    {"role": "assistant", "content": "可以使用 pandas 的 read_csv() 函数读取 CSV 文件。"},
    {"role": "user", "content": "如何只读取其中两列？"},
]

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=messages,
)

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

[
  {
    "role": "system",
    "content": "你是一个友好的客服助手。回答要简洁，并先确认用户诉求。"
  },
  {
    "role": "user",
    "content": "我想咨询退款问题。"
  },
  {
    "role": "assistant",
    "content": "可以的。请说明订单状态和退款原因。"
  },
  {
    "role": "user",
    "content": "商品有质量问题。"
  }
]

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIO_API_KEY"],
    base_url="https://api.aiearth.dev/v1",
)

stream = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "user", "content": "写一段 300 字左右的产品介绍。"}
    ],
    stream=True,
)

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

messages = [
    {
        "role": "system",
        "content": """你是一个企业知识库问答助手。
规则：
1. 只根据用户提供的上下文回答。
2. 不确定时明确说明信息不足。
3. 使用项目符号输出关键结论。
4. 不编造链接、价格或政策。"""
    },
    {
        "role": "user",
        "content": "根据下面资料总结售后流程：..."
    },
]

messages = [
    {
        "role": "system",
        "content": "你是一名资深 Python 开发者。优先给出可运行代码，并指出复杂度和边界条件。"
    },
    {
        "role": "user",
        "content": "帮我写一个 CSV 文件去重脚本。"
    },
]

def trim_messages(messages, max_history=10):
    system_messages = [m for m in messages if m["role"] == "system"]
    non_system = [m for m in messages if m["role"] != "system"]
    return system_messages + non_system[-max_history:]

messages = trim_messages(messages)

请写一篇关于人工智能在医疗领域应用的科普文章。

要求：
- 长度：800 到 1000 字
- 受众：普通读者
- 结构：引言、应用场景、案例分析、未来展望
- 语气：专业但易懂
- 避免编造未给出来源的真实案例

import time
from openai import OpenAI, OpenAIError

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://api.aiearth.dev/v1",
)

def chat_with_retry(messages, model="gpt-4o-mini", max_retries=3):
    for attempt in range(max_retries):
        try:
            response = client.chat.completions.create(
                model=model,
                messages=messages,
            )
            return response.choices[0].message.content
        except OpenAIError:
            if attempt == max_retries - 1:
                raise
            time.sleep(2 ** attempt)