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| from collections.abc import Callable, Iterable, Mapping | |
| from typing import Any | |
| from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc | |
| from toolbox import promote_file_to_downloadzone, get_log_folder | |
| from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive | |
| from .crazy_utils import input_clipping, try_install_deps | |
| from multiprocessing import Process, Pipe | |
| import os | |
| import time | |
| templete = """ | |
| ```python | |
| import ... # Put dependencies here, e.g. import numpy as np | |
| class TerminalFunction(object): # Do not change the name of the class, The name of the class must be `TerminalFunction` | |
| def run(self, path): # The name of the function must be `run`, it takes only a positional argument. | |
| # rewrite the function you have just written here | |
| ... | |
| return generated_file_path | |
| ``` | |
| """ | |
| def inspect_dependency(chatbot, history): | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| return True | |
| def get_code_block(reply): | |
| import re | |
| pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks | |
| matches = re.findall(pattern, reply) # find all code blocks in text | |
| if len(matches) == 1: | |
| return matches[0].strip('python') # code block | |
| for match in matches: | |
| if 'class TerminalFunction' in match: | |
| return match.strip('python') # code block | |
| raise RuntimeError("GPT is not generating proper code.") | |
| def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history): | |
| # 输入 | |
| prompt_compose = [ | |
| f'Your job:\n' | |
| f'1. write a single Python function, which takes a path of a `{file_type}` file as the only argument and returns a `string` containing the result of analysis or the path of generated files. \n', | |
| f"2. You should write this function to perform following task: " + txt + "\n", | |
| f"3. Wrap the output python function with markdown codeblock." | |
| ] | |
| i_say = "".join(prompt_compose) | |
| demo = [] | |
| # 第一步 | |
| gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( | |
| inputs=i_say, inputs_show_user=i_say, | |
| llm_kwargs=llm_kwargs, chatbot=chatbot, history=demo, | |
| sys_prompt= r"You are a programmer." | |
| ) | |
| history.extend([i_say, gpt_say]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新 | |
| # 第二步 | |
| prompt_compose = [ | |
| "If previous stage is successful, rewrite the function you have just written to satisfy following templete: \n", | |
| templete | |
| ] | |
| i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable templete. " | |
| gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( | |
| inputs=i_say, inputs_show_user=inputs_show_user, | |
| llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, | |
| sys_prompt= r"You are a programmer." | |
| ) | |
| code_to_return = gpt_say | |
| history.extend([i_say, gpt_say]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新 | |
| # # 第三步 | |
| # i_say = "Please list to packages to install to run the code above. Then show me how to use `try_install_deps` function to install them." | |
| # i_say += 'For instance. `try_install_deps(["opencv-python", "scipy", "numpy"])`' | |
| # installation_advance = yield from request_gpt_model_in_new_thread_with_ui_alive( | |
| # inputs=i_say, inputs_show_user=inputs_show_user, | |
| # llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, | |
| # sys_prompt= r"You are a programmer." | |
| # ) | |
| # # # 第三步 | |
| # i_say = "Show me how to use `pip` to install packages to run the code above. " | |
| # i_say += 'For instance. `pip install -r opencv-python scipy numpy`' | |
| # installation_advance = yield from request_gpt_model_in_new_thread_with_ui_alive( | |
| # inputs=i_say, inputs_show_user=i_say, | |
| # llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, | |
| # sys_prompt= r"You are a programmer." | |
| # ) | |
| installation_advance = "" | |
| return code_to_return, installation_advance, txt, file_type, llm_kwargs, chatbot, history | |
| def make_module(code): | |
| module_file = 'gpt_fn_' + gen_time_str().replace('-','_') | |
| with open(f'{get_log_folder()}/{module_file}.py', 'w', encoding='utf8') as f: | |
| f.write(code) | |
| def get_class_name(class_string): | |
| import re | |
| # Use regex to extract the class name | |
| class_name = re.search(r'class (\w+)\(', class_string).group(1) | |
| return class_name | |
| class_name = get_class_name(code) | |
| return f"{get_log_folder().replace('/', '.')}.{module_file}->{class_name}" | |
| def init_module_instance(module): | |
| import importlib | |
| module_, class_ = module.split('->') | |
| init_f = getattr(importlib.import_module(module_), class_) | |
| return init_f() | |
| def for_immediate_show_off_when_possible(file_type, fp, chatbot): | |
| if file_type in ['png', 'jpg']: | |
| image_path = os.path.abspath(fp) | |
| chatbot.append(['这是一张图片, 展示如下:', | |
| f'本地文件地址: <br/>`{image_path}`<br/>'+ | |
| f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>' | |
| ]) | |
| return chatbot | |
| def subprocess_worker(instance, file_path, return_dict): | |
| return_dict['result'] = instance.run(file_path) | |
| def have_any_recent_upload_files(chatbot): | |
| _5min = 5 * 60 | |
| if not chatbot: return False # chatbot is None | |
| most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None) | |
| if not most_recent_uploaded: return False # most_recent_uploaded is None | |
| if time.time() - most_recent_uploaded["time"] < _5min: return True # most_recent_uploaded is new | |
| else: return False # most_recent_uploaded is too old | |
| def get_recent_file_prompt_support(chatbot): | |
| most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None) | |
| path = most_recent_uploaded['path'] | |
| return path | |
| def 虚空终端CodeInterpreter(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): | |
| """ | |
| txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径 | |
| llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行 | |
| plugin_kwargs 插件模型的参数，暂时没有用武之地 | |
| chatbot 聊天显示框的句柄，用于显示给用户 | |
| history 聊天历史，前情提要 | |
| system_prompt 给gpt的静默提醒 | |
| web_port 当前软件运行的端口号 | |
| """ | |
| raise NotImplementedError | |
| # 清空历史，以免输入溢出 | |
| history = []; clear_file_downloadzone(chatbot) | |
| # 基本信息：功能、贡献者 | |
| chatbot.append([ | |
| "函数插件功能？", | |
| "CodeInterpreter开源版, 此插件处于开发阶段, 建议暂时不要使用, 插件初始化中 ..." | |
| ]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| if have_any_recent_upload_files(chatbot): | |
| file_path = get_recent_file_prompt_support(chatbot) | |
| else: | |
| chatbot.append(["文件检索", "没有发现任何近期上传的文件。"]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| # 读取文件 | |
| if ("recently_uploaded_files" in plugin_kwargs) and (plugin_kwargs["recently_uploaded_files"] == ""): plugin_kwargs.pop("recently_uploaded_files") | |
| recently_uploaded_files = plugin_kwargs.get("recently_uploaded_files", None) | |
| file_path = recently_uploaded_files[-1] | |
| file_type = file_path.split('.')[-1] | |
| # 粗心检查 | |
| if is_the_upload_folder(txt): | |
| chatbot.append([ | |
| "...", | |
| f"请在输入框内填写需求，然后再次点击该插件（文件路径 {file_path} 已经被记忆）" | |
| ]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| return | |
| # 开始干正事 | |
| for j in range(5): # 最多重试5次 | |
| try: | |
| code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \ | |
| yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history) | |
| code = get_code_block(code) | |
| res = make_module(code) | |
| instance = init_module_instance(res) | |
| break | |
| except Exception as e: | |
| chatbot.append([f"第{j}次代码生成尝试，失败了", f"错误追踪\n```\n{trimmed_format_exc()}\n```\n"]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| # 代码生成结束, 开始执行 | |
| try: | |
| import multiprocessing | |
| manager = multiprocessing.Manager() | |
| return_dict = manager.dict() | |
| p = multiprocessing.Process(target=subprocess_worker, args=(instance, file_path, return_dict)) | |
| # only has 10 seconds to run | |
| p.start(); p.join(timeout=10) | |
| if p.is_alive(): p.terminate(); p.join() | |
| p.close() | |
| res = return_dict['result'] | |
| # res = instance.run(file_path) | |
| except Exception as e: | |
| chatbot.append(["执行失败了", f"错误追踪\n```\n{trimmed_format_exc()}\n```\n"]) | |
| # chatbot.append(["如果是缺乏依赖，请参考以下建议", installation_advance]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 | |
| return | |
| # 顺利完成，收尾 | |
| res = str(res) | |
| if os.path.exists(res): | |
| chatbot.append(["执行成功了，结果是一个有效文件", "结果：" + res]) | |
| new_file_path = promote_file_to_downloadzone(res, chatbot=chatbot) | |
| chatbot = for_immediate_show_off_when_possible(file_type, new_file_path, chatbot) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新 | |
| else: | |
| chatbot.append(["执行成功了，结果是一个字符串", "结果：" + res]) | |
| yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新 | |
| """ | |
| 测试： | |
| 裁剪图像，保留下半部分 | |
| 交换图像的蓝色通道和红色通道 | |
| 将图像转为灰度图像 | |
| 将csv文件转excel表格 | |
| """ |