星火认知大模型API接入Python教程,中文回答效果非常友好

申请

地址大概是这个:

https://console.xfyun.cn/app/myapp

自己创建一个应用:
星火认知大模型API接入Python教程,中文回答效果非常友好_第1张图片
进入控制台:
星火认知大模型API接入Python教程,中文回答效果非常友好_第2张图片
注意:我已经申请好了,如果你需要使用,需要提交一个申请,一般第二天通过。

Python接入完整示例

我们可以看到右侧有三个参数:APPID、APISecret、APIKey,填入下方代码的main中即可:

import _thread as thread
import base64
import datetime
import hashlib
import hmac
import json
from urllib.parse import urlparse
import ssl
from datetime import datetime
from time import mktime
from urllib.parse import urlencode
from wsgiref.handlers import format_date_time
# websocket-client
import websocket

class Ws_Param(object):
    # 初始化
    def __init__(self, APPID, APIKey, APISecret, gpt_url):
        self.APPID = APPID
        self.APIKey = APIKey
        self.APISecret = APISecret
        self.host = urlparse(gpt_url).netloc
        self.path = urlparse(gpt_url).path
        self.gpt_url = gpt_url

    # 生成url
    def create_url(self):
        # 生成RFC1123格式的时间戳
        now = datetime.now()
        date = format_date_time(mktime(now.timetuple()))

        # 拼接字符串
        signature_origin = "host: " + self.host + "\n"
        signature_origin += "date: " + date + "\n"
        signature_origin += "GET " + self.path + " HTTP/1.1"

        # 进行hmac-sha256进行加密
        signature_sha = hmac.new(self.APISecret.encode('utf-8'), signature_origin.encode('utf-8'),
                                 digestmod=hashlib.sha256).digest()

        signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding='utf-8')

        authorization_origin = f'api_key="{self.APIKey}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha_base64}"'

        authorization = base64.b64encode(authorization_origin.encode('utf-8')).decode(encoding='utf-8')

        # 将请求的鉴权参数组合为字典
        v = {
            "authorization": authorization,
            "date": date,
            "host": self.host
        }
        # 拼接鉴权参数,生成url
        url = self.gpt_url + '?' + urlencode(v)
        # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释,比对相同参数时生成的url与自己代码生成的url是否一致
        return url


# 收到websocket错误的处理
def on_error(ws, error):
    print("### error:", error)


# 收到websocket关闭的处理
def on_close(ws, status_code, reason):
    print("")




# 收到websocket连接建立的处理
def on_open(ws):
    thread.start_new_thread(run, (ws,))


def run(ws, *args):
    data = json.dumps(gen_params(appid=ws.appid, question=ws.question))
    ws.send(data)


# 收到websocket消息的处理
def on_message(ws, message):
    # print(message)
    data = json.loads(message)
    code = data['header']['code']
    if code != 0:
        print(f'请求错误: {code}, {data}')
        ws.close()
    else:
        choices = data["payload"]["choices"]
        status = choices["status"]
        content = choices["text"][0]["content"]
        print(content, end='')
        if status == 2:
            ws.close()


def gen_params(appid, question):
    """
    通过appid和用户的提问来生成请参数
    """
    data = {
        "header": {
            "app_id": appid,
            "uid": "1234"
        },
        "parameter": {
            "chat": {
                "domain": "general",
                "random_threshold": 0.5,
                "max_tokens": 2048,
                "auditing": "default"
            }
        },
        "payload": {
            "message": {
                "text": [
                    {"role": "user", "content": question}
                ]
            }
        }
    }
    return data


def main(appid, api_key, api_secret, gpt_url, question):
    wsParam = Ws_Param(appid, api_key, api_secret, gpt_url)
    websocket.enableTrace(False)
    wsUrl = wsParam.create_url()
    ws = websocket.WebSocketApp(wsUrl, on_message=on_message, on_error=on_error, on_close=on_close, on_open=on_open)
    ws.appid = appid
    ws.question = question
    ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE})


if __name__ == "__main__":
    # 测试时候在此处正确填写相关信息即可运行
    main(appid="",
         api_secret="",
         api_key="",
         gpt_url="ws://spark-api.xf-yun.com/v1.1/chat",
         question="鲁迅和周树人是同一个人吗?")

运行如下:
在这里插入图片描述
似乎看起来跟GPT4.0回答差不多?总体效果还很好

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