from openai import OpenAI
from datetime import datetime
# 初始化 阶跃星辰 Client
STEPFUN_KEY = "YOUR_STEP_API_KEY"
client = OpenAI(
base_url="https://api.stepfun.com/v1",
api_key=STEPFUN_KEY
)
# 定义数据结构
class Chat:
id: str
user_id: str
class Message:
chat_id: str
role : str # 可选值 system, user,assistant,tool
content: str # 用户输入的信息 / 大模型返回的信息
created_at: datetime
# 从数据库中提取数据
# messages_from_db = orm.order_by ("created_at","asc").first (5)
messages_from_db = [
{
"chat_id":"chat_1",
"role":"system",
"content":"你是阶跃星辰大模型助手",
"created_at": "2024-01-01 10:01:00"
},
{
"chat_id":"chat_1",
"role":"user",
"content":"今天天气怎么样？",
"created_at": "2024-01-01 10:02:00"
},
{
"chat_id":"chat_1",
"role":"assistant",
"content":"对不起，我不能回答你关于天气的问题。",
"created_at": "2024-01-01 10:03:00"
},
{
"chat_id":"chat_1",
"role":"user",
"content":"那你告诉我北京适合去旅游么？",
"created_at": "2024-01-01 10:04:00"
}
]
def clean_msg(msg):
del msg["chat_id"]
del msg["created_at"]
return msg
messages_for_chat = [clean_msg (item) for item in messages_from_db]
# 调用补全接口进行补全
stream = client.chat.completions.create(
model="step-5-preview",
messages=messages_for_chat,
stream=True,
)
# 对流式返回的内容进行打印 / 渲染输出
for chunk in stream:
if chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end="")
