笔者最近在测试星火大模型的时候，他们是使用websocket 来建立对话，而且星火大模型开放的测试代码，质量上不咋地（20231030记录），还需要对websocket有一定的了解，才适合自己微调。
安装：
pip install websocket
pip install websocket-client
1 常见的websocket获取数据的方法
参考【python: websocket获取实时数据的几种常见链接方式】常见的两种。
1.1 第一种使用create_connection链接
需要pip install websocket-client (此方法不建议使用，链接不稳定，容易断，并且连接很耗时)
import time
from websocket import create_connection
url = 'wss://i.cg.net/wi/ws'
while True: # 一直链接，直到连接上就退出循环
time.sleep(2)
try:
ws = create_connection(url)
print(ws)
break
except Exception as e:
print('连接异常：', e)
continue
while True: # 连接上，退出第一个循环之后，此循环用于一直获取数据
ws.send('{"event":"subscribe", "channel":"btc_usdt.ticker"}')
response = ws.recv()
print(response)
1.2 第二种：WebSocketApp + run_forever的方式
import websocket
def on_message(ws, message): # 服务器有数据更新时，主动推送过来的数据
print(message)
def on_error(ws, error): # 程序报错时，就会触发on_error事件
print(error)
def on_close(ws):
print("Connection closed ……")
def on_open(ws): # 连接到服务器之后就会触发on_open事件，这里用于send数据
req = '{"event":"subscribe", "channel":"btc_usdt.deep"}'
print(req)
ws.send(req)
if __name__ == "__main__":
websocket.enableTrace(True)
ws = websocket.WebSocketApp("wss://i.cg.net/wi/ws",
on_message=on_message,
on_error=on_error,
on_close=on_close)
ws.on_open = on_open
ws.run_forever(ping_timeout=30)
第二种方式里面，run_forever其实是流式返回内容，大概可以看，流式输出的样例：
{"code":0,"sid":"5ebc0d6833b54909b4a51fbe75a5051a","status":0}
### error: 'content'
{"code":0,"fileRefer":"{\"43816997a7a44a299d0bfb7c360c5838\":[2,0,1]}","sid":"5ebc0d6833b54909b4a51fbe75a5051a","status":99}
### error: 'content'
{"code":0,"content":"橘","sid":"5ebc0d6833b54909b4a51fbe75a5051a","status":1}
橘{"code":0,"content":"子。","sid":"5ebc0d6833b54909b4a51fbe75a5051a","status":1}
子。{"code":0,"content":"","sid":"5ebc0d6833b54909b4a51fbe75a5051a","status":2}
### closed ###
那么run_forever流式输出，正常的内容如何保存呢，进入下一章
2 针对run_forever内容保存
2.1 通过定义global变量来保存内容
参考【将Websocket数据保存到Pandas】
来看一下，文中的案例：
import json
import pandas as pd
import websocket
df = pd.DataFrame(columns=['foreignNotional', 'grossValue', 'homeNotional', 'price', 'side',
'size', 'symbol', 'tickDirection', 'timestamp', 'trdMatchID'])
def on_message(ws, message):
msg = json.loads(message)
print(msg)
global df
# `ignore_index=True` has to be provided, otherwise you'll get
# "Can only append a Series if ignore_index=True or if the Series has a name" errors
df = df.append(msg, ignore_index=True)
def on_error(ws, error):
print(error)
def on_close(ws):
print("### closed ###")
def on_open(ws):
return
if __name__ == "__main__":
ws = websocket.WebSocketApp("wss://www.bitmex.com/realtime?subscribe=trade:XBTUSD",
on_open=on_open, on_message=on_message, on_error=on_error, on_close=on_close)
ws.run_forever()
其中global df是在定义全局变量df，可以在函数中把流式数据拿出来，还是很不错的
2.2 通过CallbackToIterator()来返回
在开源项目中ChuanhuChatGPT，看到了使用的方式spark.py，个人还没有尝试，只是贴在这里。
贴一下这个函数：文章来源：https://www.toymoban.com/news/detail-784636.html
class CallbackToIterator:
def __init__(self):
self.queue = deque()
self.cond = Condition()
self.finished = False
def callback(self, result):
with self.cond:
self.queue.append(result)
self.cond.notify() # Wake up the generator.
def __iter__(self):
return self
def __next__(self):
with self.cond:
# Wait for a value to be added to the queue.
while not self.queue and not self.finished:
self.cond.wait()
if not self.queue:
raise StopIteration()
return self.queue.popleft()
def finish(self):
with self.cond:
self.finished = True
self.cond.notify() # Wake up the generator if it's waiting.
# 主函数截取
def get_answer_stream_iter(self):
wsParam = Ws_Param(self.appid, self.api_key, self.api_secret, self.spark_url)
websocket.enableTrace(False)
wsUrl = wsParam.create_url()
ws = websocket.WebSocketApp(
wsUrl,
on_message=self.on_message,
on_error=self.on_error,
on_close=self.on_close,
on_open=self.on_open,
)
ws.appid = self.appid
ws.domain = self.domain
# Initialize the CallbackToIterator
ws.iterator = CallbackToIterator()
# Start the WebSocket connection in a separate thread
thread.start_new_thread(
ws.run_forever, (), {"sslopt": {"cert_reqs": ssl.CERT_NONE}}
)
# Iterate over the CallbackToIterator instance
answer = ""
total_tokens = 0
for message in ws.iterator:
data = json.loads(message)
code = data["header"]["code"]
if code != 0:
ws.close()
raise Exception(f"请求错误: {code}, {data}")
else:
choices = data["payload"]["choices"]
status = choices["status"]
content = choices["text"][0]["content"]
if "usage" in data["payload"]:
total_tokens = data["payload"]["usage"]["text"]["total_tokens"]
answer += content
if status == 2:
ws.iterator.finish() # Finish the iterator when the status is 2
ws.close()
yield answer, total_tokens
截取了部分代码，这里先是定义ws.iterator = CallbackToIterator()然后通过迭代从for message in ws.iterator:拿出数据，看上去也是可行的文章来源地址https://www.toymoban.com/news/detail-784636.html
到了这里，关于python中使用websocket调用、获取、保存大模型API的文章就介绍完了。如果您还想了解更多内容，请在右上角搜索TOY模板网以前的文章或继续浏览下面的相关文章，希望大家以后多多支持TOY模板网！
