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| import json | |
| import gradio as gr | |
| # import openai | |
| import os | |
| import sys | |
| import traceback | |
| import requests | |
| # import markdown | |
| import csv | |
| my_api_key = "" # 在这里输入你的 API 密钥 | |
| HIDE_MY_KEY = False # 如果你想在UI中隐藏你的 API 密钥，将此值设置为 True | |
| initial_prompt = "You are a helpful assistant." | |
| API_URL = "https://api.openai.com/v1/chat/completions" | |
| HISTORY_DIR = "history" | |
| TEMPLATES_DIR = "templates" | |
| #if we are running in Docker | |
| if os.environ.get('dockerrun') == 'yes': | |
| dockerflag = True | |
| else: | |
| dockerflag = False | |
| if dockerflag: | |
| my_api_key = os.environ.get('my_api_key') | |
| if my_api_key == "empty": | |
| print("Please give a api key!") | |
| sys.exit(1) | |
| #auth | |
| username = os.environ.get('USERNAME') | |
| password = os.environ.get('PASSWORD') | |
| if isinstance(username, type(None)) or isinstance(password, type(None)): | |
| authflag = False | |
| else: | |
| authflag = True | |
| def parse_text(text): | |
| lines = text.split("\n") | |
| lines = [line for line in lines if line != ""] | |
| count = 0 | |
| firstline = False | |
| for i, line in enumerate(lines): | |
| if "```" in line: | |
| count += 1 | |
| items = line.split('`') | |
| if count % 2 == 1: | |
| lines[i] = f'<pre><code class="{items[-1]}">' | |
| firstline = True | |
| else: | |
| lines[i] = f'</code></pre>' | |
| else: | |
| if i > 0: | |
| if count % 2 == 1: | |
| line = line.replace("`", "\`") | |
| line = line.replace("\"", "`\"`") | |
| line = line.replace("\'", "`\'`") | |
| # line = line.replace("&", "&") | |
| line = line.replace("<", "<") | |
| line = line.replace(">", ">") | |
| line = line.replace(" ", " ") | |
| line = line.replace("*", "*") | |
| line = line.replace("_", "_") | |
| line = line.replace("-", "-") | |
| line = line.replace(".", ".") | |
| line = line.replace("!", "!") | |
| line = line.replace("(", "(") | |
| line = line.replace(")", ")") | |
| line = line.replace("$", "$") | |
| lines[i] = "<br>"+line | |
| text = "".join(lines) | |
| return text | |
| def predict(inputs, top_p, temperature, openai_api_key, chatbot=[], history=[], system_prompt=initial_prompt, retry=False, summary=False, summary_on_crash = False, stream = True): # repetition_penalty, top_k | |
| if summary: | |
| stream = False | |
| headers = { | |
| "Content-Type": "application/json", | |
| "Authorization": f"Bearer {openai_api_key}" | |
| } | |
| chat_counter = len(history) // 2 | |
| print(f"chat_counter - {chat_counter}") | |
| messages = [compose_system(system_prompt)] | |
| if chat_counter: | |
| for index in range(0, 2*chat_counter, 2): | |
| temp1 = {} | |
| temp1["role"] = "user" | |
| temp1["content"] = history[index] | |
| temp2 = {} | |
| temp2["role"] = "assistant" | |
| temp2["content"] = history[index+1] | |
| if temp1["content"] != "": | |
| if temp2["content"] != "" or retry: | |
| messages.append(temp1) | |
| messages.append(temp2) | |
| else: | |
| messages[-1]['content'] = temp2['content'] | |
| if retry and chat_counter: | |
| messages.pop() | |
| elif summary: | |
| history = [*[i["content"] for i in messages[-2:]], "我们刚刚聊了什么？"] | |
| messages.append(compose_user( | |
| "请帮我总结一下上述对话的内容，实现减少字数的同时，保证对话的质量。在总结中不要加入这一句话。")) | |
| else: | |
| temp3 = {} | |
| temp3["role"] = "user" | |
| temp3["content"] = inputs | |
| messages.append(temp3) | |
| chat_counter += 1 | |
| # messages | |
| payload = { | |
| "model": "gpt-3.5-turbo", | |
| "messages": messages, # [{"role": "user", "content": f"{inputs}"}], | |
| "temperature": temperature, # 1.0, | |
| "top_p": top_p, # 1.0, | |
| "n": 1, | |
| "stream": stream, | |
| "presence_penalty": 0, | |
| "frequency_penalty": 0, | |
| } | |
| if not summary: | |
| history.append(inputs) | |
| else: | |
| print("精简中...") | |
| # make a POST request to the API endpoint using the requests.post method, passing in stream=True | |
| response = requests.post(API_URL, headers=headers, | |
| json=payload, stream=True) | |
| token_counter = 0 | |
| partial_words = "" | |
| counter = 0 | |
| if stream: | |
| chatbot.append((parse_text(history[-1]), "")) | |
| for chunk in response.iter_lines(): | |
| if counter == 0: | |
| counter += 1 | |
| continue | |
| counter += 1 | |
| # check whether each line is non-empty | |
| if chunk: | |
| # decode each line as response data is in bytes | |
| try: | |
| if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0: | |
| break | |
| except Exception as e: | |
| traceback.print_exc() | |
| print("Context 过长，正在尝试精简……") | |
| chatbot.pop() | |
| chatbot, history, status_text = next(predict(inputs, top_p, temperature, openai_api_key, chatbot, history, system_prompt, retry, summary=True, summary_on_crash=True, stream=False)) | |
| yield chatbot, history, status_text | |
| if not "ERROR" in status_text: | |
| print("精简完成，正在尝试重新生成……") | |
| yield next(predict(inputs, top_p, temperature, openai_api_key, chatbot, history, system_prompt, retry, summary=False, summary_on_crash=True, stream=False)) | |
| else: | |
| print("精简出错了，可能是网络原因。") | |
| break | |
| chunkjson = json.loads(chunk.decode()[6:]) | |
| status_text = f"id: {chunkjson['id']}, 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 | |
| chatbot[-1] = (parse_text(history[-2]), parse_text(history[-1])) | |
| token_counter += 1 | |
| yield chatbot, history, status_text | |
| else: | |
| try: | |
| responsejson = json.loads(response.text) | |
| content = responsejson["choices"][0]["message"]["content"] | |
| history.append(content) | |
| chatbot.append((parse_text(history[-2]), parse_text(content))) | |
| status_text = "精简完成" | |
| except: | |
| chatbot.append((parse_text(history[-1]), "☹️发生了错误，请检查网络连接或者稍后再试。")) | |
| status_text = "status: ERROR" | |
| yield chatbot, history, status_text | |
| def delete_last_conversation(chatbot, history): | |
| if "☹️发生了错误" in chatbot[-1][1]: | |
| chatbot.pop() | |
| print(history) | |
| return chatbot, history | |
| history.pop() | |
| history.pop() | |
| print(history) | |
| return chatbot, history | |
| def save_chat_history(filename, system, history, chatbot): | |
| if filename == "": | |
| return | |
| if not filename.endswith(".json"): | |
| filename += ".json" | |
| os.makedirs(HISTORY_DIR, exist_ok=True) | |
| json_s = {"system": system, "history": history, "chatbot": chatbot} | |
| print(json_s) | |
| with open(os.path.join(HISTORY_DIR, filename), "w") as f: | |
| json.dump(json_s, f) | |
| def load_chat_history(filename): | |
| with open(os.path.join(HISTORY_DIR, filename), "r") as f: | |
| json_s = json.load(f) | |
| print(json_s) | |
| return filename, json_s["system"], json_s["history"], json_s["chatbot"] | |
| def get_file_names(dir, plain=False, filetype=".json"): | |
| # find all json files in the current directory and return their names | |
| try: | |
| files = sorted([f for f in os.listdir(dir) if f.endswith(filetype)]) | |
| except FileNotFoundError: | |
| files = [] | |
| if plain: | |
| return files | |
| else: | |
| return gr.Dropdown.update(choices=files) | |
| def get_history_names(plain=False): | |
| return get_file_names(HISTORY_DIR, plain) | |
| def load_template(filename, plain=False): | |
| lines = [] | |
| with open(os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8") as csvfile: | |
| reader = csv.reader(csvfile) | |
| lines = list(reader) | |
| lines = lines[1:] | |
| if plain: | |
| return sorted([row[0] for row in lines]) | |
| else: | |
| return {row[0]:row[1] for row in lines}, gr.Dropdown.update(choices=sorted([row[0] for row in lines])) | |
| def get_template_names(plain=False): | |
| return get_file_names(TEMPLATES_DIR, plain, filetype=".csv") | |
| def reset_state(): | |
| return [], [] | |
| def compose_system(system_prompt): | |
| return {"role": "system", "content": system_prompt} | |
| def compose_user(user_input): | |
| return {"role": "user", "content": user_input} | |
| def reset_textbox(): | |
| return gr.update(value='') | |
| title = """<h1 align="center">川虎ChatGPT 🚀</h1>""" | |
| description = """<div align=center> | |
| 由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536) 和 [明昭MZhao](https://space.bilibili.com/24807452)开发 | |
| 访问川虎ChatGPT的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本 | |
| 此App使用 `gpt-3.5-turbo` 大语言模型 | |
| </div> | |
| """ | |
| customCSS = """ | |
| code { | |
| display: inline; | |
| white-space: break-spaces; | |
| border-radius: 6px; | |
| margin: 0 2px 0 2px; | |
| padding: .2em .4em .1em .4em; | |
| background-color: rgba(175,184,193,0.2); | |
| } | |
| pre { | |
| display: block; | |
| white-space: pre; | |
| background-color: hsla(0, 0%, 0%, 72%); | |
| border: solid 5px var(--color-border-primary) !important; | |
| border-radius: 8px; | |
| padding: 0 1.2rem 1.2rem; | |
| margin-top: 1em !important; | |
| color: #FFF; | |
| box-shadow: inset 0px 8px 16px hsla(0, 0%, 0%, .2) | |
| } | |
| pre code, pre code code { | |
| background-color: transparent !important; | |
| margin: 0; | |
| padding: 0; | |
| } | |
| """ | |
| with gr.Blocks(css=customCSS) as demo: | |
| gr.HTML(title) | |
| gr.HTML('''<center><a href="https://huggingface.co/spaces/JohnSmith9982/ChuanhuChatGPT?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="复制 Space"></a>强烈建议点击上面的按钮复制一份这个Space，在你自己的Space里运行，响应更迅速、也更安全👆</center>''') | |
| keyTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入你的OpenAI API-key...", | |
| value=my_api_key, label="API Key", type="password", visible=not HIDE_MY_KEY).style(container=True) | |
| chatbot = gr.Chatbot() # .style(color_map=("#1D51EE", "#585A5B")) | |
| history = gr.State([]) | |
| promptTemplates = gr.State({}) | |
| TRUECOMSTANT = gr.State(True) | |
| FALSECONSTANT = gr.State(False) | |
| topic = gr.State("未命名对话历史记录") | |
| with gr.Row(): | |
| with gr.Column(scale=12): | |
| txt = gr.Textbox(show_label=False, placeholder="在这里输入").style( | |
| container=False) | |
| with gr.Column(min_width=50, scale=1): | |
| submitBtn = gr.Button("🚀", variant="primary") | |
| with gr.Row(): | |
| emptyBtn = gr.Button("🧹 新的对话") | |
| retryBtn = gr.Button("🔄 重新生成") | |
| delLastBtn = gr.Button("🗑️ 删除上条对话") | |
| reduceTokenBtn = gr.Button("♻️ 总结对话") | |
| statusDisplay = gr.Markdown("status: ready") | |
| systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入System Prompt...", | |
| label="System prompt", value=initial_prompt).style(container=True) | |
| with gr.Accordion(label="加载Prompt模板", open=False): | |
| with gr.Column(): | |
| with gr.Row(): | |
| with gr.Column(scale=6): | |
| templateFileSelectDropdown = gr.Dropdown(label="选择Prompt模板集合文件（.csv）", choices=get_template_names(plain=True), multiselect=False) | |
| with gr.Column(scale=1): | |
| templateRefreshBtn = gr.Button("🔄 刷新") | |
| templaeFileReadBtn = gr.Button("📂 读入模板") | |
| with gr.Row(): | |
| with gr.Column(scale=6): | |
| templateSelectDropdown = gr.Dropdown(label="从Prompt模板中加载", choices=load_template(get_template_names(plain=True)[0], plain=True), multiselect=False) | |
| with gr.Column(scale=1): | |
| templateApplyBtn = gr.Button("⬇️ 应用") | |
| with gr.Accordion(label="保存/加载对话历史记录(在文本框中输入文件名，点击“保存对话”按钮，历史记录文件会被存储到Python文件旁边)", open=False): | |
| with gr.Column(): | |
| with gr.Row(): | |
| with gr.Column(scale=6): | |
| saveFileName = gr.Textbox( | |
| show_label=True, placeholder=f"在这里输入保存的文件名...", label="设置保存文件名", value="对话历史记录").style(container=True) | |
| with gr.Column(scale=1): | |
| saveBtn = gr.Button("💾 保存对话") | |
| with gr.Row(): | |
| with gr.Column(scale=6): | |
| historyFileSelectDropdown = gr.Dropdown(label="从列表中加载对话", choices=get_history_names(plain=True), multiselect=False) | |
| with gr.Column(scale=1): | |
| historyRefreshBtn = gr.Button("🔄 刷新") | |
| historyReadBtn = gr.Button("📂 读入对话") | |
| #inputs, top_p, temperature, top_k, repetition_penalty | |
| with gr.Accordion("参数", open=False): | |
| top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.05, | |
| interactive=True, label="Top-p (nucleus sampling)",) | |
| temperature = gr.Slider(minimum=-0, maximum=5.0, value=1.0, | |
| step=0.1, interactive=True, label="Temperature",) | |
| #top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",) | |
| #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", ) | |
| gr.Markdown(description) | |
| txt.submit(predict, [txt, top_p, temperature, keyTxt, | |
| chatbot, history, systemPromptTxt], [chatbot, history, statusDisplay]) | |
| txt.submit(reset_textbox, [], [txt]) | |
| submitBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot, | |
| history, systemPromptTxt], [chatbot, history, statusDisplay], show_progress=True) | |
| submitBtn.click(reset_textbox, [], [txt]) | |
| emptyBtn.click(reset_state, outputs=[chatbot, history]) | |
| retryBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot, history, | |
| systemPromptTxt, TRUECOMSTANT], [chatbot, history, statusDisplay], show_progress=True) | |
| delLastBtn.click(delete_last_conversation, [chatbot, history], [ | |
| chatbot, history], show_progress=True) | |
| reduceTokenBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot, history, | |
| systemPromptTxt, FALSECONSTANT, TRUECOMSTANT], [chatbot, history, statusDisplay], show_progress=True) | |
| saveBtn.click(save_chat_history, [ | |
| saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True) | |
| saveBtn.click(get_history_names, None, [historyFileSelectDropdown]) | |
| historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown]) | |
| historyReadBtn.click(load_chat_history, [historyFileSelectDropdown], [saveFileName, systemPromptTxt, history, chatbot], show_progress=True) | |
| templateRefreshBtn.click(get_template_names, None, [templateFileSelectDropdown]) | |
| templaeFileReadBtn.click(load_template, [templateFileSelectDropdown], [promptTemplates, templateSelectDropdown], show_progress=True) | |
| templateApplyBtn.click(lambda x, y: x[y], [promptTemplates, templateSelectDropdown], [systemPromptTxt], show_progress=True) | |
| print("川虎的温馨提示：访问 http://localhost:7860 查看界面") | |
| # 默认开启本地服务器，默认可以直接从IP访问，默认不创建公开分享链接 | |
| demo.title = "川虎ChatGPT 🚀" | |
| #if running in Docker | |
| if dockerflag: | |
| if authflag: | |
| demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=(username, password)) | |
| else: | |
| demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False) | |
| #if not running in Docker | |
| else: | |
| demo.queue().launch(share=False) # 改为 share=True 可以创建公开分享链接 | |
| #demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False) # 可自定义端口 | |
| #demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=("在这里填写用户名", "在这里填写密码")) # 可设置用户名与密码 | |
| #demo.queue().launch(auth=("在这里填写用户名", "在这里填写密码")) # 适合Nginx反向代理 | |