把盞言歡,款款而談,ChatGPT結合釘釘機器人(outgoing回呼)打造人工智能群聊/單聊場景,基于Python3.10-有解無憂

就像黑火藥時代里突然誕生的核彈一樣，OpenAI的ChatGPT語言模型的橫空出世，是人工智能技術發展史上的一個重要里程碑，這是一款無與倫比、超凡絕倫的模型，能夠進行自然語言推理和對話，并且具有出色的語言生成能力，

好吧，本篇的開頭其實是由ChatGPT生成的：

沒辦法，面對這個遠超時代的AI產品，我們能說什么呢？頂禮膜拜？驚為天人？任何言語對于描述ChatGPT來說已經是蒼白無力的，而辭海中的形容詞在面對ChatGPT時也已經鞭長莫及，

一句話：言語不能贊其偉大，

本次我們利用ChatGPT的開放API接入釘釘群聊/單聊機器人，讓釘釘機器人具備進行自然語言推理和對話的能力，所謂化腐朽為神奇，不過如此，

注冊和使用OpenAi的ChatGPT

首先注冊OpenAi平臺：https://beta.openai.com/ ，由于ChatGPT過于火爆，導致很多地區無法正常注冊，這里推薦使用北美地區的代理IP，與此同時，一定要注意，如果之后希望使用后端的API介面方式呼叫ChatGPT，就不要使用谷歌或者微軟的三方賬號進行登錄，否則無法通過郵箱和秘鑰交換OpenAi平臺的access_token，切記，

同時，接受驗證碼手機號也必須是北美地區的手機號，這里推薦一個北美地區的接碼平臺：https://sms.qisms.com/index 非常好用，

注冊成功之后，這里推薦github上開源大神rawandahmad698已經封裝好的開源SDK，避免重復造輪子：https://github.com/rawandahmad698/PyChatGPT

安裝SDK:

pip3 install chatgptpy --upgrade

安裝好之后，撰寫測驗腳本：

chat = Chat(email="OpenAi郵箱", password="OpenAi密碼",proxies="代理地址")  
  
answer = chat.ask("你好")  
  
print(answer)

注意，運行代碼之前，一定要使用代理proxies，并且確保是北美地區的IP地址，

程式回傳：

[OpenAI] Email address: ********  
[OpenAI] Password: *********  
[OpenAI] Using proxy: {'http': 'http://localhost:4780', 'https': 'http://localhost:4780'}  
[OpenAI] Beginning auth process  
[OpenAI][1] Making request to https://chat.openai.com/auth/login  
[OpenAI][1] Request was successful  
[OpenAI][2] Beginning part two  
[OpenAI][2] Grabbing CSRF token from https://chat.openai.com/api/auth/csrf  
[OpenAI][2] Request was successful  
[OpenAI][2] CSRF Token: 1b1357a34e4b0b9a74e999372fe0413ab981c9a72e030a54b3bf172bd6176c5e  
[OpenAI][3] Beginning part three  
[OpenAI][3] Making request to https://chat.openai.com/api/auth/signin/auth0?prompt=login  
[OpenAI][3] Request was successful  
[OpenAI][3] Callback URL: https://auth0.openai.com/authorize?client_id=TdJIcbe16WoTHtN95nyywh5E4yOo6ItG&scope=openid%20email%20profile%20offline_access%20model.request%20model.read%20organization.read&response_type=code&redirect_uri=https%3A%2F%2Fchat.openai.com%2Fapi%2Fauth%2Fcallback%2Fauth0&audience=https%3A%2F%2Fapi.openai.com%2Fv1&prompt=login&state=RJt9U13ATPmlt795xMNohQZcUNOytZNvHoq3JI8HGZ4&code_challenge=Pq97ptna00Ybak2dUmIMhR3eqmXZnZz-Fij7otMMw7U&code_challenge_method=S256  
[OpenAI][4] Making request to https://auth0.openai.com/authorize?client_id=TdJIcbe16WoTHtN95nyywh5E4yOo6ItG&scope=openid%20email%20profile%20offline_access%20model.request%20model.read%20organization.read&response_type=code&redirect_uri=https%3A%2F%2Fchat.openai.com%2Fapi%2Fauth%2Fcallback%2Fauth0&audience=https%3A%2F%2Fapi.openai.com%2Fv1&prompt=login&state=RJt9U13ATPmlt795xMNohQZcUNOytZNvHoq3JI8HGZ4&code_challenge=Pq97ptna00Ybak2dUmIMhR3eqmXZnZz-Fij7otMMw7U&code_challenge_method=S256  
[OpenAI][4] Request was successful  
[OpenAI][4] Current State: hKFo2SA5VzlqUDA0Mkl5TnQtNUpYcGRBU0ZfRkhQVUY1eVpWV6Fur3VuaXZlcnNhbC1sb2dpbqN0aWTZIGMzU0xvbThRUXFxMTczeVg4bF8zRFZnYVNOM2M3Q0RFo2NpZNkgVGRKSWNiZTE2V29USHROOTVueXl3aDVFNHlPbzZJdEc  
[OpenAI][5] Making request to https://auth0.openai.com/u/login/identifier?state=hKFo2SA5VzlqUDA0Mkl5TnQtNUpYcGRBU0ZfRkhQVUY1eVpWV6Fur3VuaXZlcnNhbC1sb2dpbqN0aWTZIGMzU0xvbThRUXFxMTczeVg4bF8zRFZnYVNOM2M3Q0RFo2NpZNkgVGRKSWNiZTE2V29USHROOTVueXl3aDVFNHlPbzZJdEc  
[OpenAI][5] Request was successful  
[OpenAI][5] No captcha detected  
[OpenAI][6] Making request to https://auth0.openai.com/u/login/identifier  
[OpenAI][6] Email found  
[OpenAI][7] Entering password...  
[OpenAI][7] Password was correct  
[OpenAI][7] Old state: hKFo2SA5VzlqUDA0Mkl5TnQtNUpYcGRBU0ZfRkhQVUY1eVpWV6Fur3VuaXZlcnNhbC1sb2dpbqN0aWTZIGMzU0xvbThRUXFxMTczeVg4bF8zRFZnYVNOM2M3Q0RFo2NpZNkgVGRKSWNiZTE2V29USHROOTVueXl3aDVFNHlPbzZJdEc  
[OpenAI][7] New State: c3SLom8QQqq173yX8l_3DVgaSN3c7CDE  
[OpenAI][8] Making request to https://auth0.openai.com/authorize/resume?state=c3SLom8QQqq173yX8l_3DVgaSN3c7CDE  
[OpenAI][8] All good  
[OpenAI][8] Access Token: eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCIsImtpZCI6Ik1UaEVOVUpHTkVNMVFURTRNMEZCTWpkQ05UZzVNRFUxUlRVd1FVSkRNRU13UmtGRVFrRXpSZyJ9.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.PtXKhJqwudNKLIkNRc5OO6T7Tsl8ydZ8WWnCJ3Ax2c40CQibRTiGLDmfvk2gW5pVIkOpKldWYs6Jrd8UVi0Ih9VMDwS9JL6HpZKsoRaIhy6r6l7AW5vMMQN-l0ntCsgefQeGIrwtCTUsIklN8dyZDkRkympC2AzRkayAcFvFckXTHi_J5Fivr5J7We_OM4cGFJEKTLkaSw6MnYku-uYwAKPVEpFsF7fLnUBRQxn5Zz90FhdeLYEg4IUjPWKPp1iMbp_fa9qhwwtKBwogtrIVzq2t8NdUotoNYgoo2uV2xjQWC2m4V4C_xgkSzLj2TTtRJMOYKGH-lHWs2_yRQF0wOg  
[OpenAI][9] Saving access token...  
[OpenAI][8] Saved access token

首次運行程式會通過代理自動登錄OpenAi平臺，并且換取token，最后將token存盤在本地，

隨后回傳ChatGPT的資訊：

?  mydemo git:(master) ? /opt/homebrew/bin/python3.10 "/Users/liuyue/wodfan/work/mydemo/test_chatgpt.py"  
Using proxies: http://localhost:4780  
你好，很高興為你提供幫助，有什么需要我幫忙的嗎？

至此，ChatGPT介面就除錯好了，

配置釘釘Dingding機器人

隨后，我們來配置C端的機器人，注意這里一定要使用支持outgoing回呼的企業機器人，而不是普通的機器人，參考檔案：https://open.dingtalk.com/document/group/enterprise-created-chatbot

創建好企業機器人之后，獲取機器人應用的Key和秘鑰，同時配置好出口IP和介面地址：

所謂出口IP即呼叫釘釘服務合法的ip，訊息接受地址是接受C端資訊的地址，這里我們使用異步非阻塞的Tornado框架來構建接受資訊服務：

import hmac  
import hashlib  
import base64  
import json  
import tornado  
  
from tornado.options import define, options  
define('port', default=8000, help='default port',type=int)  
  
class Robot(tornado.web.RequestHandler):  
  
    async def post(self):  
  
  
        timestamp = self.request.headers.get('timestamp', None)  
  
        sign = self.request.headers.get('sign', None)  
        app_secret = '釘釘機器人秘鑰'  
        app_secret_enc = app_secret.encode('utf-8')  
        string_to_sign = '{}\n{}'.format(timestamp, app_secret)  
        string_to_sign_enc = string_to_sign.encode('utf-8')  
        hmac_code = hmac.new(app_secret_enc, string_to_sign_enc, digestmod=hashlib.sha256).digest()  
        my_sign = base64.b64encode(hmac_code).decode('utf-8')  
        if sign != my_sign:  
            return self.finish({"errcode":1,"msg":"簽名有誤"})  
        data = https://www.cnblogs.com/v3ucn/p/json.loads(self.request.body)  
        text = data['text']["content"]  
        atUsers = data.get("atUsers",None)  
        uid = data.get("senderStaffId",None)  
        return self.finish({"errcode":0,"msg":text})  
  
urlpatterns = [  
    (r"/robot_chat/",Robot),  
]  
  
  
# 創建Tornado實體  
application = tornado.web.Application(urlpatterns,debug=True)  
  
  
if __name__ == "__main__":  
    tornado.options.parse_command_line()  
    application.listen(options.port)  
    tornado.ioloop.IOLoop.instance().start()

這里我們通過Robot異步控制器來接受所有來自釘釘客戶端的資訊，即人類對機器人說的話，需要注意的是，后端服務需要對請求頭中的timestamp和sign進行驗證，以判斷是否是來自釘釘的合法請求，避免其他仿冒釘釘呼叫開發者的HTTPS服務傳送資料，

所以這里一旦簽名有問題，就結束邏輯：



timestamp = self.request.headers.get('timestamp', None)  
  
sign = self.request.headers.get('sign', None)  
app_secret = '釘釘機器人秘鑰'  
app_secret_enc = app_secret.encode('utf-8')  
string_to_sign = '{}\n{}'.format(timestamp, app_secret)  
string_to_sign_enc = string_to_sign.encode('utf-8')  
hmac_code = hmac.new(app_secret_enc, string_to_sign_enc, digestmod=hashlib.sha256).digest()  
my_sign = base64.b64encode(hmac_code).decode('utf-8')  
if sign != my_sign:  
    return self.finish({"errcode":1,"msg":"簽名有誤"})

最后該介面會回傳發信人id（uid）以及具體資訊內容（text），

至此，后端接受服務就配置好了，

下面就是后端推送服務，首先，根據官方檔案：https://open.dingtalk.com/document/orgapp-server/obtain-the-access_token-of-an-internal-app?spm=ding_open_doc.document.0.0.5f255239xgW3zE#topic-2056397

需要獲取釘釘介面的token:

def get_token(self):  
  
        res = requests.post("https://api.dingtalk.com/v1.0/oauth2/accessToken",data=https://www.cnblogs.com/v3ucn/p/json.dumps({"appKey":self._appKey,"appSecret":self._appSecret}),headers={"Content-Type":"application/json"})  
  
        token = res.json()["accessToken"]  
  
        return token

隨后，根據檔案：https://open.dingtalk.com/document/group/chatbots-send-one-on-one-chat-messages-in-batches?spm=ding_open_doc.document.0.0.22e749acXECz5m#topic-2080109

我們來配置單聊推送：

# 單聊  
    def send_message(self,uid,message):  
  
        res = requests.post("https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend",data=https://www.cnblogs.com/v3ucn/p/json.dumps({"robotCode":self._appKey,"userIds":[uid],"msgKey":"sampleText","msgParam":'{"content":"'+message+'"}'}),headers={"Content-Type":"application/json","x-acs-dingtalk-access-token":self._token})  
  
        print(res.text)

具體效果：

接著，繼續根據官方檔案：https://open.dingtalk.com/document/robots/guide-to-user-access-for-intra-enterprise-robot-group-chat

配置群聊推送方法：

# 群聊  
    def send_user(self,uid,message):  
  
        data = https://www.cnblogs.com/v3ucn/p/{"at": {  
            "atUserIds": [  
                uid  
            ]  
        },  
        "text": {  
            "content": message  
        },  
        "msgtype": "text"  
        }  
  
        res = requests.post(self._webhook,data=https://www.cnblogs.com/v3ucn/p/json.dumps(data),headers={"Content-Type":"application/json"})  
  
        print(res.text)

群聊效果：

這里需要注意的是，單聊是通過介面的方式進行推送，而群內聊天是通過webhook方式進行推送，關于webhook，請移玉步至：使用python3.7配置開發釘釘群自定義機器人(2020年新版攻略)

完整代碼：

import requests  
import json  
  
from pychatgpt import Chat  
  
class DingDing:  
  
  
    def __init__(self,appKey=None,appSecret=None) -> None:  
  
        self._appKey = appKey  
  
        self._appSecret = appSecret  
          
        self._token = self.get_token()  
  
        # 機器人webhook地址  
        self._webhook = ""  
  
          
  
  
    def get_token(self):  
  
        res = requests.post("https://api.dingtalk.com/v1.0/oauth2/accessToken",data=https://www.cnblogs.com/v3ucn/p/json.dumps({"appKey":self._appKey,"appSecret":self._appSecret}),headers={"Content-Type":"application/json"})  
  
        token = res.json()["accessToken"]  
  
        return token  
  
    # 單聊  
    def send_message(self,uid,message):  
  
        res = requests.post("https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend",data=https://www.cnblogs.com/v3ucn/p/json.dumps({"robotCode":self._appKey,"userIds":[uid],"msgKey":"sampleText","msgParam":'{"content":"'+message+'"}'}),headers={"Content-Type":"application/json","x-acs-dingtalk-access-token":self._token})  
  
        print(res.text)  
  
    # 群聊  
    def send_user(self,uid,message):  
  
        data = https://www.cnblogs.com/v3ucn/p/{"at": {  
            "atUserIds": [  
                uid  
            ]  
        },  
        "text": {  
            "content": message  
        },  
        "msgtype": "text"  
        }  
  
        res = requests.post(self._webhook,data=https://www.cnblogs.com/v3ucn/p/json.dumps(data),headers={"Content-Type":"application/json"})  
  
        print(res.text)  
  
  
  
  
if __name__ == '__main__':  
  
    dingding = DingDing("appkey","appSecret")  
  
    #chat = Chat(email="OpenAi郵箱", password="OpenAi密碼",proxies="代理地址")  
  
    #answer = chat.ask("你好")  
  
    # 單聊  
    #dingding.send_message('uid',answer)  
  
    # 群聊  
    #dingding.send_user('uid',answer)  
  
    #print(answer)

至此，后端推送服務就配置好了，

結語

最后，奉上Github專案地址，與眾親同饗：https://github.com/zcxey2911/Python_ChatGPT_ForDingding_OpenAi ，毫無疑問，ChatGPT是NLP領域歷史上最偉大的專案，沒有之一，偉大，就是技術層面的極致，你同意嗎？

轉載請註明出處，本文鏈接：https://www.uj5u.com/houduan/539488.html

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