def dpskr1bj(self, event=None):  # deepseek-r1
        def deepseekr1_th():
            getmyques = self.stext.get(1.0, "end") # -------bd  # import wenxin_api  # 可以通过"pip install wenxin-api"命令安装  # pip install --upgrade wenxin-api # https://wenxin.baidu.com/wenxin/docs#2l6tgx5rc   # runingpb()
            url = "https://api.siliconflow.cn/v1/chat/completions"
            payload = {
                "model": "deepseek-ai/DeepSeek-R1",
                "messages": [
                    {
                        "role": "user",
                        "content": getmyques
                    }
                ],
                "stream": False, #如果已设置，则令牌在可用时将作为服务器发送事件返回。流以数据终止：[完成]
                "max_tokens": 4096,#要生成的最大令牌数。
                "temperature": 1,#0.7 确定响应中的随机程度。
                "top_p": 0.7,#指定模型输出的多样性。与温度相似，但更精确。
                "top_k": 50,#从前k个令牌中采样。有助于加快生成过程，并可以提高生成文本的质量。
                "frequency_penalty": 0,#0.5 通过惩罚已经频繁使用的单词来降低模型行中重复单词的可能性。
                "n": 1,
                "response_format": {"type": "text"},

            }
            headers = {
                "Authorization": "Bearer sk-kjuqzpegevynpfofkfueyptglajkvlaxpmvoiefnglakban",
                "Content-Type": "application/json"
            }

            response = requests.request("POST", url, json=payload, headers=headers)

            # print(response.text)
            wendadpskr1 = response.json()['choices'][0]['message']['content']
            print(wendadpskr1)


            # print(wendadpsk)
            with open('dpskr1logb.txt', "a", encoding='UTF-8') as out_fadv:
                out_fadv.write(wendadpskr1)
        # deepseek_th()
            time.sleep(3)
            with open('dpskr1logb.txt', "r", encoding='UTF-8') as out_fadv2:
            # with open('dpsklogb.txt', "rt", encoding='UTF-8') as out_fadv2:
                wxhdadv = out_fadv2.read()
            self.totext.delete(1.0, 'end')
            self.totext.insert(1.0, wxhdadv)
            time.sleep(3)
            os.remove('dpskr1logb.txt')

        self.totext.delete(1.0, 'end')
        self.totext.insert(1.0, 'deepseek-r1-siliconflow下载答案中，耐心等待......')
        t2wxdsr1 = Thread(target=deepseekr1_th)
        t2wxdsr1.start()

deepseek api r1

"stream": False, #如果已设置，则令牌在可用时将作为服务器发送事件返回。流以数据终止：[完成]pan.baidu.com/s/1ZGB1MwL51L_bDkuqBhQuYQ?pwd=1029
                "max_tokens": 4096,#要生成的最大令牌数。
                "temperature": 1,#0.7 确定响应中的随机程度。
                "top_p": 0.7,#指定模型输出的多样性。与温度相似，但更精确。
                "top_k": 50,#从前k个令牌中采样。有助于加快生成过程，并可以提高生成文本的质量。
                "frequency_penalty": 0,#0.5 通过惩罚已经频繁使用的单词来降低模型行中重复单词的可能性。
                "n": 1,

    def dpskdeepseek3(self, event=None):  # deepseek v3
        def deepseek_th():
            getmyques = self.stext.get(1.0, "end") # -------bd  # import wenxin_api  # 可以通过"pip install wenxin-api"命令安装  # pip install --upgrade wenxin-api # https://wenxin.baidu.com/wenxin/docs#2l6tgx5rc   # runingpb()
            url = "https://api.deepseek.com/chat/completions" #v3
            # url = "https://api.deepseek.com/beta" #r1
            # https://api-docs.deepseek.com/zh-cn/api/create-chat-completion
            # https://platform.deepseek.com/usage
            payload = json.dumps({
                "messages": [
                    {
                        "content": getmyques,
                        "role": "system",
                        "prefix": True
                    }

                ],
                "model": "deepseek-chat",
                "frequency_penalty": 0,
                "max_tokens": 4096,  # 2048
                "presence_penalty": 0,
                "response_format": {
                    "type": "text"
                },
                "stop": None,
                "stream": False,
                "stream_options": None,
                "temperature": 1,
                "top_p": 1,
                "tools": None,
                "tool_choice": "none",
                "logprobs": False,
                "top_logprobs": None
            })
            headers = {
                'Content-Type': 'application/json',
                'Accept': 'application/json',
                'Authorization': 'Bearer sk-0b6ca63e126d411aaf7ffa7947aa5b1'
            }
            response = requests.request("POST", url, headers=headers, data=payload)
            print(response.text)
            wendadpsk = response.json()['choices'][0]['message']['content']
            # print(wendadpsk)
            with open('dpsklogb.txt', "a", encoding='UTF-8') as out_fadv:
                out_fadv.write(wendadpsk)
        # deepseek_th()
            time.sleep(3)
            with open('dpsklogb.txt', "r", encoding='UTF-8') as out_fadv2:
            # with open('dpsklogb.txt', "rt", encoding='UTF-8') as out_fadv2:
                wxhdadv = out_fadv2.read()
            self.totext.delete(1.0, 'end')
            self.totext.insert(1.0, wxhdadv)
            time.sleep(2)
            os.remove('dpsklogb.txt')

        self.totext.delete(1.0, 'end')
        self.totext.insert(1.0, 'deepseek-v3-下载答案中，耐心等待......')
        t2wxds = Thread(target=deepseek_th)
        t2wxds.start()

deepseek api v3