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| # encoding: utf-8 | |
| # @Time : 2023/12/21 | |
| # @Author : Spike | |
| # @Descr : | |
| import json | |
| import re | |
| import os | |
| import time | |
| from request_llms.com_google import GoogleChatInit | |
| from toolbox import get_conf, update_ui, update_ui_lastest_msg, have_any_recent_upload_image_files, trimmed_format_exc | |
| proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY') | |
| timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \ | |
| '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。' | |
| def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, | |
| console_slience=False): | |
| # 检查API_KEY | |
| if get_conf("GEMINI_API_KEY") == "": | |
| raise ValueError(f"请配置 GEMINI_API_KEY。") | |
| genai = GoogleChatInit() | |
| watch_dog_patience = 5 # 看门狗的耐心, 设置5秒即可 | |
| gpt_replying_buffer = '' | |
| stream_response = genai.generate_chat(inputs, llm_kwargs, history, sys_prompt) | |
| for response in stream_response: | |
| results = response.decode() | |
| match = re.search(r'"text":\s*"((?:[^"\\]|\\.)*)"', results, flags=re.DOTALL) | |
| error_match = re.search(r'\"message\":\s*\"(.*?)\"', results, flags=re.DOTALL) | |
| if match: | |
| try: | |
| paraphrase = json.loads('{"text": "%s"}' % match.group(1)) | |
| except: | |
| raise ValueError(f"解析GEMINI消息出错。") | |
| buffer = paraphrase['text'] | |
| gpt_replying_buffer += buffer | |
| if len(observe_window) >= 1: | |
| observe_window[0] = gpt_replying_buffer | |
| if len(observe_window) >= 2: | |
| if (time.time() - observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。") | |
| if error_match: | |
| raise RuntimeError(f'{gpt_replying_buffer} 对话错误') | |
| return gpt_replying_buffer | |
| def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream=True, additional_fn=None): | |
| # 检查API_KEY | |
| if get_conf("GEMINI_API_KEY") == "": | |
| yield from update_ui_lastest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0) | |
| return | |
| # 适配润色区域 | |
| if additional_fn is not None: | |
| from core_functional import handle_core_functionality | |
| inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) | |
| if "vision" in llm_kwargs["llm_model"]: | |
| have_recent_file, image_paths = have_any_recent_upload_image_files(chatbot) | |
| if not have_recent_file: | |
| chatbot.append((inputs, "没有检测到任何近期上传的图像文件，请上传jpg格式的图片，此外，请注意拓展名需要小写")) | |
| yield from update_ui(chatbot=chatbot, history=history, msg="等待图片") # 刷新界面 | |
| return | |
| def make_media_input(inputs, image_paths): | |
| for image_path in image_paths: | |
| inputs = inputs + f'<br/><br/><div align="center"><img src="file={os.path.abspath(image_path)}"></div>' | |
| return inputs | |
| if have_recent_file: | |
| inputs = make_media_input(inputs, image_paths) | |
| chatbot.append((inputs, "")) | |
| yield from update_ui(chatbot=chatbot, history=history) | |
| genai = GoogleChatInit() | |
| retry = 0 | |
| while True: | |
| try: | |
| stream_response = genai.generate_chat(inputs, llm_kwargs, history, system_prompt) | |
| break | |
| except Exception as e: | |
| retry += 1 | |
| chatbot[-1] = ((chatbot[-1][0], trimmed_format_exc())) | |
| yield from update_ui(chatbot=chatbot, history=history, msg="请求失败") # 刷新界面 | |
| return | |
| gpt_replying_buffer = "" | |
| gpt_security_policy = "" | |
| history.extend([inputs, '']) | |
| for response in stream_response: | |
| results = response.decode("utf-8") # 被这个解码给耍了。。 | |
| gpt_security_policy += results | |
| match = re.search(r'"text":\s*"((?:[^"\\]|\\.)*)"', results, flags=re.DOTALL) | |
| error_match = re.search(r'\"message\":\s*\"(.*)\"', results, flags=re.DOTALL) | |
| if match: | |
| try: | |
| paraphrase = json.loads('{"text": "%s"}' % match.group(1)) | |
| except: | |
| raise ValueError(f"解析GEMINI消息出错。") | |
| gpt_replying_buffer += paraphrase['text'] # 使用 json 解析库进行处理 | |
| chatbot[-1] = (inputs, gpt_replying_buffer) | |
| history[-1] = gpt_replying_buffer | |
| yield from update_ui(chatbot=chatbot, history=history) | |
| if error_match: | |
| history = history[-2] # 错误的不纳入对话 | |
| chatbot[-1] = (inputs, gpt_replying_buffer + f"对话错误，请查看message\n\n```\n{error_match.group(1)}\n```") | |
| yield from update_ui(chatbot=chatbot, history=history) | |
| raise RuntimeError('对话错误') | |
| if not gpt_replying_buffer: | |
| history = history[-2] # 错误的不纳入对话 | |
| chatbot[-1] = (inputs, gpt_replying_buffer + f"触发了Google的安全访问策略，没有回答\n\n```\n{gpt_security_policy}\n```") | |
| yield from update_ui(chatbot=chatbot, history=history) | |
| if __name__ == '__main__': | |
| import sys | |
| llm_kwargs = {'llm_model': 'gemini-pro'} | |
| result = predict('Write long a story about a magic backpack.', llm_kwargs, llm_kwargs, []) | |
| for i in result: | |
| print(i) | |