1 line
11 KiB
JSON
1 line
11 KiB
JSON
{"repo": "bg2mkj/runara", "files": {"chat.py": {"ab4e11d2694595b02cafa82acb9988f650a7ab89": {"t": 1785745977.7261467, "n": 2268, "h": "4bd90d223c00a779", "c": "from openai import OpenAI\nimport requests\nfrom multiprocessing import Queue\nimport json\n\nclass Chat_Api:\n api_key = ''\n client = OpenAI(api_key=api_key,base_url=\"https://api.deepseek.com\")\n\n\n def __init__(self,set_api_key,data_queue:Queue):\n self.api_key = set_api_key\n self.client.api_key=set_api_key\n self.data_queue = data_queue\n\n def set_ley(self,key:str):\n self.api_key = key\n\n def send_data(self,head:str,data):\n send = (head,data)\n self.data_queue.put(send)\n\n def generate_promots(self,num_of_questions):\n promots = f\"接下来我将给你{num_of_questions}道题目，帮我解答，注意B选项可能错误识别为8。你只需要告诉我答案不需要写解析，你要快速输出。\"+\"输出格式：题干+换行+答案标号和答案内容+换行+解释+换行+换行\"\n return promots\n\n def format_output(self,answer):\n j_answer = json.loads(answer)\n format_output = []\n for e in j_answer:\n format_output.append([e[\"question\"],e[\"type\"],e[\"options\"],e[\"answer\"],e[\"explanation\"]])\n return format_output\n \n def chat_to_ai(self,question):\n messages = [{\"role\": \"user\", \"content\": question}]\n response = self.client.chat.completions.create(model=\"deepseek-reasoner\",messages=messages)\n content = response.choices[0].message.content\n return content\n \n def request_balance(self):\n print(\"asking\")\n url = \"https://api.deepseek.com/user/balance\"\n payload={}\n headers = {\n 'Accept': 'application/json',\n 'Authorization': 'Bearer ' + self.api_key\n }\n try:\n response = requests.request(\"GET\", url, headers=headers, data=payload)\n response_json = json.loads(response.text)\n balance = (response_json[\"balance_infos\"][0][\"total_balance\"])\n except Exception as e:\n print(e)\n return None\n self.send_data(\"balance\",balance)\n return balance\n\n def ask_question(self,questions:str):\n text_question = self.generate_promots(len(questions))\n for q in questions:\n text_question+=q\n print(\"requesting...\")\n answers = self.chat_to_ai(text_question)\n\n return answers\n \n def print_single_answer(self,format_output):\n for e in format_output:\n print(e[0],e[1],e[3])\n \n"}, "bcb4c3078f6410c0afe9ce587dd9584f724026e4": {"t": 1785758442.2789397, "n": 2476, "h": "506e5a718f7f6950", "c": "from openai import OpenAI\nimport requests\nfrom multiprocessing import Queue\nimport json\n\nclass Chat_Api:\n api_key = ''\n client = OpenAI(api_key=api_key,base_url=\"https://api.deepseek.com\")\n\n\n def __init__(self,set_api_key,data_queue:Queue):\n self.api_key = set_api_key\n self.client.api_key=set_api_key\n self.data_queue = data_queue\n\n def set_ley(self,key:str):\n self.api_key = key\n\n def send_data(self,head:str,data):\n send = (head,data)\n self.data_queue.put(send)\n\n def generate_promots(self,num_of_questions):\n promots = f\"接下来我将给你{num_of_questions}道题目，帮我解答，注意B选项可能错误识别为8。你只需要告诉我答案不需要写解析，你要快速输出。\"+\"请按以下 JSON 格式输出： [{ \\\"question\\\": \\\"题目内容\\\", \\\"type\\\": \\\"题目类型（single_choice/multiple_choice/true_false）\\\", \\\"options\\\": {\\\"A\\\": \\\"选项A内容\\\", \\\"B\\\": \\\"选项B内容\\\", ...}, \\\"answer\\\": \\\"正确答案（单选/判断为字符串，多选为数组）\\\", \\\"explanation\\\": \\\"解析\\\" }下一道题....]\"\n return promots\n\n def format_output(self,answer):\n j_answer = json.loads(answer)\n format_output = []\n for e in j_answer:\n format_output.append([e[\"question\"],e[\"type\"],e[\"options\"],e[\"answer\"],e[\"explanation\"]])\n return format_output\n \n def chat_to_ai(self,question):\n messages = [{\"role\": \"user\", \"content\": question}]\n response = self.client.chat.completions.create(model=\"deepseek-reasoner\",messages=messages)\n content = response.choices[0].message.content\n return content\n \n def request_balance(self):\n print(\"asking\")\n url = \"https://api.deepseek.com/user/balance\"\n payload={}\n headers = {\n 'Accept': 'application/json',\n 'Authorization': 'Bearer ' + self.api_key\n }\n try:\n response = requests.request(\"GET\", url, headers=headers, data=payload)\n response_json = json.loads(response.text)\n balance = (response_json[\"balance_infos\"][0][\"total_balance\"])\n except Exception as e:\n print(e)\n return None\n self.send_data(\"balance\",balance)\n return balance\n\n def ask_question(self,questions:str):\n text_question = self.generate_promots(len(questions))\n for q in questions:\n text_question+=q\n print(\"requesting...\")\n answers = self.chat_to_ai(text_question)\n\n return answers\n \n def print_single_answer(self,format_output):\n for e in format_output:\n print(e[0],e[1],e[3])\n \n"}, "232574f62104d1e9709cb7bec7fa6d1da20ee188": {"t": 1785758443.4720829, "n": 2161, "h": "4a7104a41fa3ba66", "c": "from openai import OpenAI\nimport requests\nimport json\n\nclass Chat_Api:\n api_key = ''\n client = OpenAI(api_key=api_key,base_url=\"https://api.deepseek.com\")\n\n\n def __init__(self,set_api_key):\n self.api_key = set_api_key\n self.client.api_key=set_api_key\n\n def generate_promots(self,num_of_questions):\n promots = f\"接下来我将给你{num_of_questions}道题目，帮我解答，注意B选项可能错误识别为8。你只需要告诉我答案不需要写解析，你要快速输出。\"+\"请按以下 JSON 格式输出： [{ \\\"question\\\": \\\"题目内容\\\", \\\"type\\\": \\\"题目类型（single_choice/multiple_choice/true_false）\\\", \\\"options\\\": {\\\"A\\\": \\\"选项A内容\\\", \\\"B\\\": \\\"选项B内容\\\", ...}, \\\"answer\\\": \\\"正确答案（单选/判断为字符串，多选为数组）\\\", \\\"explanation\\\": \\\"解析\\\" }下一道题....]\"\n return promots\n\n def format_output(self,answer):\n j_answer = json.loads(answer)\n format_output = []\n for e in j_answer:\n format_output.append([e[\"question\"],e[\"type\"],e[\"options\"],e[\"answer\"],e[\"explanation\"]])\n return format_output\n \n def chat_to_ai(self,question):\n messages = [{\"role\": \"user\", \"content\": question}]\n response = self.client.chat.completions.create(model=\"deepseek-reasoner\",messages=messages)\n content = response.choices[0].message.content\n return content\n \n def request_balance(self):\n url = \"https://api.deepseek.com/user/balance\"\n payload={}\n headers = {\n 'Accept': 'application/json',\n 'Authorization': 'Bearer ' + self.api_key\n }\n try:\n response = requests.request(\"GET\", url, headers=headers, data=payload)\n response_json = json.loads(response.text)\n balance = (response_json[\"balance_infos\"][0][\"total_balance\"])\n except Exception as e:\n print(e)\n return None\n return balance\n\n def ask_question(self,questions:str):\n text_question = self.generate_promots(len(questions))\n for q in questions:\n text_question+=q\n print(\"requesting...\")\n answers = self.chat_to_ai(text_question)\n return answers\n \n def print_single_answer(self,format_output):\n for e in format_output:\n print(e[0],e[1],e[3])\n \n"}, "6ca977661c6f8ea2ffe2ec617537ec85a0553f8b": {"t": 1785758446.2226412, "n": 1527, "h": "ad0b4d38855a8bb8", "c": "from openai import OpenAI\nimport requests\nimport json\n\nclass Chat_Api:\n api_key = ''\n client = OpenAI(api_key=api_key,base_url=\"https://api.deepseek.com\")\n\n\n def __init__(self,set_api_key):\n self.api_key = set_api_key\n self.client.api_key=set_api_key\n \n def generate_promots(self,num_of_questions):\n promots = f\"接下来我将给你{num_of_questions}道题目，帮我解答，注意B选项可能错误识别为8。:\"\n return promots\n\n\n def chat_to_ai(self,question):\n messages = [{\"role\": \"user\", \"content\": question}]\n response = self.client.chat.completions.create(model=\"deepseek-reasoner\",messages=messages)\n content = response.choices[0].message.content\n return content\n \n def request_balance(self):\n url = \"https://api.deepseek.com/user/balance\"\n payload={}\n headers = {\n 'Accept': 'application/json',\n 'Authorization': 'Bearer ' + self.api_key\n }\n try:\n response = requests.request(\"GET\", url, headers=headers, data=payload)\n response_json = json.loads(response.text)\n balance = (response_json[\"balance_infos\"][0][\"total_balance\"])\n except Exception as e:\n print(e)\n return None\n return balance\n\n def ask_question(self,questions):\n text_question = self.generate_promots(len(questions))\n for q in questions:\n text_question+=q\n print(\"requesting...\")\n answers = self.chat_to_ai(text_question)\n return answers\n \n \n\n"}, "142880c879ae2533f3aac9cca1ddc14efbf00380": {"t": 1785758447.868417, "n": 1194, "h": "2bf24f0f952ff3e8", "c": "from openai import OpenAI\nimport requests\nimport json\n\nclass Chat_Api:\n api_key = ''\n client = OpenAI(api_key=api_key,base_url=\"https://api.deepseek.com\")\n def __init__(self,set_api_key):\n self.api_key = set_api_key\n self.client.api_key=set_api_key\n \n def chat_to_ai(self,question):\n messages = [{\"role\": \"user\", \"content\": question}]\n response = self.client.chat.completions.create(model=\"deepseek-reasoner\",messages=messages)\n content = response.choices[0].message.content\n return content\n \n def request_balance(self):\n url = \"https://api.deepseek.com/user/balance\"\n payload={}\n headers = {\n 'Accept': 'application/json',\n 'Authorization': 'Bearer ' + self.api_key\n }\n try:\n response = requests.request(\"GET\", url, headers=headers, data=payload)\n response_json = json.loads(response.text)\n balance = (response_json[\"balance_infos\"][0][\"total_balance\"])\n except Exception as e:\n print(e)\n return None\n return balance\n\nchat_api = Chat_Api(\"sk-4dd7b73b63a149518ffd105c7a464634\")\nprint(chat_api.request_balance())\n"}}}} |