From 44b40ff726f95a068829f227cff88edc3f8fb6a1 Mon Sep 17 00:00:00 2001 From: Your Name Date: Fri, 24 Mar 2023 13:12:25 +0800 Subject: [PATCH] update --- colorful.py | 91 ++++++++++++++++++++++ config.py | 3 + functional_crazy.py | 39 ++++------ main.py | 2 +- predict.py | 182 ++++++++++++++++---------------------------- 5 files changed, 176 insertions(+), 141 deletions(-) create mode 100644 colorful.py diff --git a/colorful.py b/colorful.py new file mode 100644 index 0000000..d90972b --- /dev/null +++ b/colorful.py @@ -0,0 +1,91 @@ +import platform +from sys import stdout + +if platform.system()=="Linux": + pass +else: + from colorama import init + init() + +# Do you like the elegance of Chinese characters? +def print红(*kw,**kargs): + print("\033[0;31m",*kw,"\033[0m",**kargs) +def print绿(*kw,**kargs): + print("\033[0;32m",*kw,"\033[0m",**kargs) +def print黄(*kw,**kargs): + print("\033[0;33m",*kw,"\033[0m",**kargs) +def print蓝(*kw,**kargs): + print("\033[0;34m",*kw,"\033[0m",**kargs) +def print紫(*kw,**kargs): + print("\033[0;35m",*kw,"\033[0m",**kargs) +def print靛(*kw,**kargs): + print("\033[0;36m",*kw,"\033[0m",**kargs) + +def print亮红(*kw,**kargs): + print("\033[1;31m",*kw,"\033[0m",**kargs) +def print亮绿(*kw,**kargs): + print("\033[1;32m",*kw,"\033[0m",**kargs) +def print亮黄(*kw,**kargs): + print("\033[1;33m",*kw,"\033[0m",**kargs) +def print亮蓝(*kw,**kargs): + print("\033[1;34m",*kw,"\033[0m",**kargs) +def print亮紫(*kw,**kargs): + print("\033[1;35m",*kw,"\033[0m",**kargs) +def print亮靛(*kw,**kargs): + print("\033[1;36m",*kw,"\033[0m",**kargs) + + + +def print亮红(*kw,**kargs): + print("\033[1;31m",*kw,"\033[0m",**kargs) +def print亮绿(*kw,**kargs): + print("\033[1;32m",*kw,"\033[0m",**kargs) +def print亮黄(*kw,**kargs): + print("\033[1;33m",*kw,"\033[0m",**kargs) +def print亮蓝(*kw,**kargs): + print("\033[1;34m",*kw,"\033[0m",**kargs) +def print亮紫(*kw,**kargs): + print("\033[1;35m",*kw,"\033[0m",**kargs) +def print亮靛(*kw,**kargs): + print("\033[1;36m",*kw,"\033[0m",**kargs) + +print_red = print红 +print_green = print绿 +print_yellow = print黄 +print_blue = print蓝 +print_purple = print紫 +print_indigo = print靛 + +print_bold_red = print亮红 +print_bold_green = print亮绿 +print_bold_yellow = print亮黄 +print_bold_blue = print亮蓝 +print_bold_purple = print亮紫 +print_bold_indigo = print亮靛 + +if not stdout.isatty(): + # redirection, avoid a fucked up log file + print红 = print + print绿 = print + print黄 = print + print蓝 = print + print紫 = print + print靛 = print + print亮红 = print + print亮绿 = print + print亮黄 = print + print亮蓝 = print + print亮紫 = print + print亮靛 = print + print_red = print + print_green = print + print_yellow = print + print_blue = print + print_purple = print + print_indigo = print + print_bold_red = print + print_bold_green = print + print_bold_yellow = print + print_bold_blue = print + print_bold_purple = print + print_bold_indigo = print \ No newline at end of file diff --git a/config.py b/config.py index a894068..aa85bc0 100644 --- a/config.py +++ b/config.py @@ -21,6 +21,9 @@ WEB_PORT = -1 # 如果OpenAI不响应（网络卡顿、代理失败、KEY失效），重试的次数限制 MAX_RETRY = 2 +# 选择的OpenAI模型是（gpt4现在只对申请成功的人开放） +LLM_MODEL = "gpt-3.5-turbo" + # 检查一下是不是忘了改config if API_KEY == "sk-此处填API秘钥": assert False, "请在config文件中修改API密钥, 添加海外代理之后再运行" \ No newline at end of file diff --git a/functional_crazy.py b/functional_crazy.py index 8b641d9..0dd993d 100644 --- a/functional_crazy.py +++ b/functional_crazy.py @@ -1,26 +1,18 @@ -# """ -# 'primary' for main call-to-action, -# 'secondary' for a more subdued style, -# 'stop' for a stop button. -# """ - +from predict import predict_no_ui fast_debug = False -def 自我程序解构简单案例(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT): - import time - from predict import predict_no_ui_no_history +def 高阶功能模板函数(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT): for i in range(5): i_say = f'我给出一个数字，你给出该数字的平方。我给出数字：{i}' - gpt_say = predict_no_ui_no_history(inputs=i_say, top_p=top_p, temperature=temperature) + gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature) chatbot.append((i_say, gpt_say)) history.append(i_say) history.append(gpt_say) yield chatbot, history, '正常' - time.sleep(10) + def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT): import time, glob, os - from predict import predict_no_ui file_manifest = [f for f in glob.glob('*.py')] for index, fp in enumerate(file_manifest): @@ -30,7 +22,7 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx 前言 = "接下来请你分析自己的程序构成，别紧张，" if index==0 else "" i_say = 前言 + f'请对下面的程序文件做一个概述文件名是{fp}，文件代码是 ```{file_content}```' i_say_show_user = 前言 + f'[{index}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {os.path.abspath(fp)}' - chatbot.append((i_say_show_user, "[local] waiting gpt response.")) + chatbot.append((i_say_show_user, "[waiting gpt response]")) yield chatbot, history, '正常' if not fast_debug: @@ -43,7 +35,7 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx time.sleep(2) i_say = f'根据以上你自己的分析，对程序的整体功能和构架做出概括。然后用一张markdown表格整理每个文件的功能（包括{file_manifest}）。' - chatbot.append((i_say, "[local] waiting gpt response.")) + chatbot.append((i_say, "[waiting gpt response]")) yield chatbot, history, '正常' if not fast_debug: @@ -64,7 +56,6 @@ def report_execption(chatbot, history, a, b): def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt): import time, glob, os - from predict import predict_no_ui print('begin analysis on:', file_manifest) for index, fp in enumerate(file_manifest): with open(fp, 'r', encoding='utf-8') as f: @@ -73,7 +64,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, 前言 = "接下来请你逐文件分析下面的工程" if index==0 else "" i_say = 前言 + f'请对下面的程序文件做一个概述文件名是{os.path.relpath(fp, project_folder)}，文件代码是 ```{file_content}```' i_say_show_user = 前言 + f'[{index}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {os.path.abspath(fp)}' - chatbot.append((i_say_show_user, "[local] waiting gpt response.")) + chatbot.append((i_say_show_user, "[waiting gpt response]")) print('[1] yield chatbot, history') yield chatbot, history, '正常' @@ -98,7 +89,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)]) i_say = f'根据以上你自己的分析，对程序的整体功能和构架做出概括。然后用一张markdown表格整理每个文件的功能（包括{all_file}）。' - chatbot.append((i_say, "[local] waiting gpt response.")) + chatbot.append((i_say, "[waiting gpt response]")) yield chatbot, history, '正常' if not fast_debug: @@ -159,22 +150,22 @@ def 解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, s def get_crazy_functionals(): return { - "程序解构简单案例": { - "Color": "stop", # 按钮颜色 - "Function": 自我程序解构简单案例 - }, - "请解析并解构此项目本身": { + "[实验功能] 请解析并解构此项目本身": { "Color": "stop", # 按钮颜色 "Function": 解析项目本身 }, - "解析一整个Python项目（输入栏给定项目完整目录）": { + "[实验功能] 解析一整个Python项目（输入栏给定项目完整目录）": { "Color": "stop", # 按钮颜色 "Function": 解析一个Python项目 }, - "解析一整个C++项目的头文件（输入栏给定项目完整目录）": { + "[实验功能] 解析一整个C++项目的头文件（输入栏给定项目完整目录）": { "Color": "stop", # 按钮颜色 "Function": 解析一个C项目的头文件 }, + "[实验功能] 高阶功能模板函数": { + "Color": "stop", # 按钮颜色 + "Function": 高阶功能模板函数 + }, } diff --git a/main.py b/main.py index 219fd1a..8af31a8 100644 --- a/main.py +++ b/main.py @@ -106,7 +106,7 @@ with gr.Blocks() as demo: # submitBtn.click(reset_textbox, [], [txt]) for k in functional: functional[k]["Button"].click(predict, - [txt, top_p, temperature, chatbot, history, systemPromptTxt, FALSE, TRUE, gr.State(k)], [chatbot, history, statusDisplay], show_progress=True) + [txt, top_p, temperature, chatbot, history, systemPromptTxt, TRUE, gr.State(k)], [chatbot, history, statusDisplay], show_progress=True) for k in crazy_functional: crazy_functional[k]["Button"].click(crazy_functional[k]["Function"], [txt, top_p, temperature, chatbot, history, systemPromptTxt, gr.State(PORT)], [chatbot, history, statusDisplay]) diff --git a/predict.py b/predict.py index 8a18710..7554ace 100644 --- a/predict.py +++ b/predict.py @@ -6,11 +6,12 @@ import logging import traceback import requests import importlib +from colorful import * # config_private.py放自己的秘密如API和代理网址 # 读取时首先看是否存在私密的config_private配置文件（不受git管控），如果有，则覆盖原config文件 -try: from config_private import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY -except: from config import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY +try: from config_private import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY, LLM_MODEL +except: from config import proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY, LLM_MODEL timeout_bot_msg = '[local] Request timeout, network error. please check proxy settings in config.py.' @@ -23,51 +24,12 @@ def get_full_error(chunk, stream_response): return chunk def predict_no_ui(inputs, top_p, temperature, history=[]): - messages = [{"role": "system", "content": ""}] - - # - chat_counter = len(history) // 2 - if chat_counter > 0: - for index in range(0, 2*chat_counter, 2): - what_i_have_asked = {} - what_i_have_asked["role"] = "user" - what_i_have_asked["content"] = history[index] - what_gpt_answer = {} - what_gpt_answer["role"] = "assistant" - what_gpt_answer["content"] = history[index+1] - if what_i_have_asked["content"] != "": - messages.append(what_i_have_asked) - messages.append(what_gpt_answer) - else: - messages[-1]['content'] = what_gpt_answer['content'] - - what_i_ask_now = {} - what_i_ask_now["role"] = "user" - what_i_ask_now["content"] = inputs - messages.append(what_i_ask_now) - - # messages - payload = { - "model": "gpt-3.5-turbo", - # "model": "gpt-4", - "messages": messages, - "temperature": temperature, # 1.0, - "top_p": top_p, # 1.0, - "n": 1, - "stream": False, - "presence_penalty": 0, - "frequency_penalty": 0, - } - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {API_KEY}" - } + headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt="", stream=False) retry = 0 while True: try: - # make a POST request to the API endpoint using the requests.post method, passing in stream=True + # make a POST request to the API endpoint, stream=False response = requests.post(API_URL, headers=headers, proxies=proxies, json=payload, stream=False, timeout=TIMEOUT_SECONDS*2); break except TimeoutError as e: @@ -84,9 +46,7 @@ def predict_no_ui(inputs, top_p, temperature, history=[]): raise ConnectionAbortedError("Json解析不合常规，可能是文本过长" + response.text) - - -def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', retry=False, +def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None): if additional_fn is not None: @@ -101,60 +61,13 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='' chatbot.append((inputs, "")) yield chatbot, history, "等待响应" - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {API_KEY}" - } - - chat_counter = len(history) // 2 - - print(f"chat_counter - {chat_counter}") - - messages = [{"role": "system", "content": system_prompt}] - if chat_counter: - for index in range(0, 2*chat_counter, 2): - what_i_have_asked = {} - what_i_have_asked["role"] = "user" - what_i_have_asked["content"] = history[index] - what_gpt_answer = {} - what_gpt_answer["role"] = "assistant" - what_gpt_answer["content"] = history[index+1] - if what_i_have_asked["content"] != "": - if not (what_gpt_answer["content"] != "" or retry): continue - if what_gpt_answer["content"] == timeout_bot_msg: continue - messages.append(what_i_have_asked) - messages.append(what_gpt_answer) - else: - messages[-1]['content'] = what_gpt_answer['content'] - - if retry and chat_counter: - messages.pop() - else: - what_i_ask_now = {} - what_i_ask_now["role"] = "user" - what_i_ask_now["content"] = inputs - messages.append(what_i_ask_now) - chat_counter += 1 - - # messages - payload = { - "model": "gpt-3.5-turbo", - # "model": "gpt-4", - "messages": messages, - "temperature": temperature, # 1.0, - "top_p": top_p, # 1.0, - "n": 1, - "stream": stream, - "presence_penalty": 0, - "frequency_penalty": 0, - } - - history.append(inputs) + headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt, stream) + history.append(inputs); history.append(" ") retry = 0 while True: try: - # make a POST request to the API endpoint using the requests.post method, passing in stream=True + # make a POST request to the API endpoint, stream=True response = requests.post(API_URL, headers=headers, proxies=proxies, json=payload, stream=True, timeout=TIMEOUT_SECONDS);break except: @@ -164,37 +77,30 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='' yield chatbot, history, "请求超时"+retry_msg if retry > MAX_RETRY: raise TimeoutError - token_counter = 0 - partial_words = "" - - counter = 0 + gpt_replying_buffer = "" + + is_head_of_the_stream = True if stream: stream_response = response.iter_lines() while True: chunk = next(stream_response) - if chunk == b'data: [DONE]': - break - - if counter == 0: - counter += 1 - continue - counter += 1 - # check whether each line is non-empty + # print(chunk.decode()[6:]) + if is_head_of_the_stream: + is_head_of_the_stream = False; continue + if chunk: - # decode each line as response data is in bytes try: if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0: - logging.info(f'[response] {chatbot[-1][-1]}') + # 判定为数据流的结束，gpt_replying_buffer也写完了 + logging.info(f'[response] {gpt_replying_buffer}') break + # 处理数据流的主体 chunkjson = json.loads(chunk.decode()[6:]) status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}" - partial_words = partial_words + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"] - if token_counter == 0: - history.append(" " + partial_words) - else: - history[-1] = partial_words + # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出 + gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"] + history[-1] = gpt_replying_buffer chatbot[-1] = (history[-2], history[-1]) - token_counter += 1 yield chatbot, history, status_text except Exception as e: @@ -207,4 +113,48 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='' yield chatbot, history, "Json解析不合常规，很可能是文本过长" + error_msg return +def generate_payload(inputs, top_p, temperature, history, system_prompt, stream): + headers = { + "Content-Type": "application/json", + "Authorization": f"Bearer {API_KEY}" + } + + conversation_cnt = len(history) // 2 + + messages = [{"role": "system", "content": system_prompt}] + if conversation_cnt: + for index in range(0, 2*conversation_cnt, 2): + what_i_have_asked = {} + what_i_have_asked["role"] = "user" + what_i_have_asked["content"] = history[index] + what_gpt_answer = {} + what_gpt_answer["role"] = "assistant" + what_gpt_answer["content"] = history[index+1] + if what_i_have_asked["content"] != "": + if what_gpt_answer["content"] == "": continue + if what_gpt_answer["content"] == timeout_bot_msg: continue + messages.append(what_i_have_asked) + messages.append(what_gpt_answer) + else: + messages[-1]['content'] = what_gpt_answer['content'] + + what_i_ask_now = {} + what_i_ask_now["role"] = "user" + what_i_ask_now["content"] = inputs + messages.append(what_i_ask_now) + + payload = { + "model": LLM_MODEL, + "messages": messages, + "temperature": temperature, # 1.0, + "top_p": top_p, # 1.0, + "n": 1, + "stream": stream, + "presence_penalty": 0, + "frequency_penalty": 0, + } + + print(f" {LLM_MODEL} : {conversation_cnt} : {inputs}") + return headers,payload +