Duplicate from yizhangliu/chatGPT

Co-authored-by: yizhangliu <yizhangliu@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+title: ChatGPT
+emoji: 📊
+colorFrom: blue
+colorTo: blue
+sdk: gradio
+sdk_version: 3.12.0
+app_file: app.py
+pinned: false
+duplicated_from: yizhangliu/chatGPT
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import os, sys, json
+os.system("pip install gradio==3.19.1")
+import openai
+import gradio as gr
+
+from loguru import logger
+import paddlehub as hub
+import random
+from encoder import get_encoder
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+from utils import get_tmt_client, getTextTrans_tmt
+tmt_client = get_tmt_client()
+
+def getTextTrans(text, source='zh', target='en'):
+    def is_chinese(string):
+        for ch in string:
+            if u'\u4e00' <= ch <= u'\u9fff':
+                return True
+        return False
+        
+    if not is_chinese(text) and target == 'en': 
+        return text
+       
+    try:
+        text_translation = getTextTrans_tmt(tmt_client, text, source, target)
+        return text_translation
+    except Exception as e:
+        return text 
+
+start_work = """async() => {
+    function isMobile() {
+        try {
+            document.createEvent("TouchEvent"); return true;
+        } catch(e) {
+            return false; 
+        }
+    }
+	function getClientHeight()
+	{
+	  var clientHeight=0;
+	  if(document.body.clientHeight&&document.documentElement.clientHeight) {
+		var clientHeight = (document.body.clientHeight<document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight;
+	  } else {
+		var clientHeight = (document.body.clientHeight>document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight;
+	  }
+	  return clientHeight;
+	}
+ 
+    function setNativeValue(element, value) {
+      const valueSetter = Object.getOwnPropertyDescriptor(element.__proto__, 'value').set;
+      const prototype = Object.getPrototypeOf(element);
+      const prototypeValueSetter = Object.getOwnPropertyDescriptor(prototype, 'value').set;
+      
+      if (valueSetter && valueSetter !== prototypeValueSetter) {
+            prototypeValueSetter.call(element, value);
+      } else {
+            valueSetter.call(element, value);
+      }
+      element.dispatchEvent(new Event('input', { bubbles: true }));
+    }
+   function get_clear_innerHTML(innerHTML) {
+        innerHTML = innerHTML.replace(/<p>|<\\/p>|\\n/g, '');
+        regexp = /\\★☆(.*?)\\☆★/;
+        match = innerHTML.match(regexp);
+        if (match) {
+            innerHTML = match[1];
+        } 
+        return innerHTML;
+    }    
+    function save_conversation(chatbot) {        
+        var conversations = new Array();
+        var conversations_clear = new Array();
+        for (var i = 0; i < chatbot.children.length; i++) {
+            testid_icon = '☟:'; //'user'
+            if (chatbot.children[i].dataset['testid'] == 'bot') {
+                testid_icon = '☝:'; //'bot'
+            }            
+            innerHTML = chatbot.children[i].innerHTML;
+            conversations.push(testid_icon + innerHTML);
+            if (innerHTML.indexOf("<img") == -1 && innerHTML.indexOf("null_") == -1) {              
+                conversations_clear.push(testid_icon + get_clear_innerHTML(innerHTML));
+            }
+        }
+        var json_str = JSON.stringify(conversations);
+        setNativeValue(window['chat_his'], JSON.stringify(conversations_clear));
+        localStorage.setItem('chatgpt_conversations', json_str);
+    }
+    function img_click(img) {
+        this_width = parseInt(img.style.width) + 20;
+        if (this_width > 100) {
+            this_width = 20;
+        }
+        img.style.width = this_width + "%";
+        img.style.height = img.offsetWidth + 'px'; 
+    }
+    function load_conversation(chatbot) {
+        var json_str = localStorage.getItem('chatgpt_conversations');
+        if (json_str) {
+            var conversations_clear = new Array();
+            conversations = JSON.parse(json_str);
+            for (var i = 0; i < conversations.length; i++) {
+                innerHTML = conversations[i];
+                if (innerHTML.indexOf("☝:") == -1) {
+                    className = "message user svelte-134zwfa";
+                    bgcolor = "#16a34a"; 
+                    testid = "user";
+                    testid_icon = '☟:'; //'user'
+                } else {
+                    className = "message bot svelte-134zwfa";
+                    bgcolor = "#2563eb";  
+                    testid = "bot";
+                    testid_icon = '☝:'; //'bot'
+                }
+                var new_div = document.createElement("div");
+                new_div.className = className;
+                new_div.style.backgroundColor = bgcolor;
+                new_div.dataset.testid = testid;
+                if (innerHTML.indexOf("data:image/jpeg") >= 0) { 
+                    new_div.style.width = "20%"; 
+                    new_div.style.padding = "0.2rem"; 
+                    new_div.onclick = function(e) {
+                        img_click(this);
+                    }
+                    setTimeout(function(){
+                        new_div.style.height = new_div.offsetWidth + 'px'; 
+                        new_div.children[0].setAttribute('style', 'max-width: none; width:100%');
+                    }, 10);                    
+                }   
+                innerHTML = innerHTML.replace("☝:", "");
+                innerHTML = innerHTML.replace("☟:", "");                             
+                new_div.innerHTML = innerHTML;
+                if (innerHTML.indexOf("null_") != -1) {
+                    new_div.style.display = 'none';
+                }                
+                chatbot.appendChild(new_div);
+                
+                if (innerHTML.indexOf("<img") == -1 && innerHTML.indexOf("null_") == -1) {
+                    conversations_clear.push(testid_icon + get_clear_innerHTML(innerHTML));
+                }                
+            }
+            setNativeValue(window['chat_his'], JSON.stringify(conversations_clear));
+            setTimeout(function(){
+                window['chat_bot1'].children[1].scrollTop = window['chat_bot1'].children[1].scrollHeight;
+            }, 500);             
+        }
+    }
+    var gradioEl = document.querySelector('body > gradio-app').shadowRoot;
+    if (!gradioEl) {
+        gradioEl = document.querySelector('body > gradio-app');
+    }
+    
+    if (typeof window['gradioEl'] === 'undefined') {
+        window['gradioEl'] = gradioEl;
+       
+        const page1 = window['gradioEl'].querySelectorAll('#page_1')[0];
+        const page2 = window['gradioEl'].querySelectorAll('#page_2')[0]; 
+    
+        page1.style.display = "none";
+        page2.style.display = "block";
+        window['div_count'] = 0;
+        window['chat_radio_0'] = window['gradioEl'].querySelectorAll('#chat_radio')[0].querySelectorAll('input[name=radio-chat_radio]')[0];
+        window['chat_radio_1'] = window['gradioEl'].querySelectorAll('#chat_radio')[0].querySelectorAll('input[name=radio-chat_radio]')[1];        
+        window['chat_bot'] = window['gradioEl'].querySelectorAll('#chat_bot')[0];
+        window['chat_bot1'] = window['gradioEl'].querySelectorAll('#chat_bot1')[0];  
+        window['my_prompt'] = window['gradioEl'].querySelectorAll('#my_prompt')[0].querySelectorAll('textarea')[0];
+        window['my_prompt_en'] = window['gradioEl'].querySelectorAll('#my_prompt_en')[0].querySelectorAll('textarea')[0];
+        window['chat_his'] = window['gradioEl'].querySelectorAll('#chat_history')[0].querySelectorAll('textarea')[0];
+        chat_row = window['gradioEl'].querySelectorAll('#chat_row')[0]; 
+        prompt_row = window['gradioEl'].querySelectorAll('#prompt_row')[0]; 
+        window['chat_bot1'].children[1].children[0].textContent = '';
+        
+        clientHeight = getClientHeight();
+        if (isMobile()) {
+            output_htmls = window['gradioEl'].querySelectorAll('.output-html');
+            for (var i = 0; i < output_htmls.length; i++) {
+               output_htmls[i].style.display = "none";
+            }
+            new_height = (clientHeight - 250) + 'px';
+        } else {
+            new_height = (clientHeight - 350) + 'px';
+        }
+        chat_row.style.height = new_height;
+        window['chat_bot'].style.height = new_height;
+        window['chat_bot'].children[1].style.height = new_height;
+        window['chat_bot1'].style.height = new_height;
+        window['chat_bot1'].children[1].style.height = new_height;
+        window['chat_bot1'].children[0].style.top = (parseInt(window['chat_bot1'].style.height)-window['chat_bot1'].children[0].offsetHeight-2) + 'px';
+        prompt_row.children[0].style.flex = 'auto';
+        prompt_row.children[0].style.width = '100%';
+        window['gradioEl'].querySelectorAll('#chat_radio')[0].style.flex = 'auto';
+        window['gradioEl'].querySelectorAll('#chat_radio')[0].style.width = '100%';        
+        prompt_row.children[0].setAttribute('style','flex-direction: inherit; flex: 1 1 auto; width: 100%;border-color: green;border-width: 1px !important;')
+        window['chat_bot1'].children[1].setAttribute('style', 'border-bottom-right-radius:0;top:unset;bottom:0;padding-left:0.1rem');
+        window['gradioEl'].querySelectorAll('#btns_row')[0].children[0].setAttribute('style', 'min-width: min(10px, 100%); flex-grow: 1');
+        window['gradioEl'].querySelectorAll('#btns_row')[0].children[1].setAttribute('style', 'min-width: min(10px, 100%); flex-grow: 1');
+        
+        load_conversation(window['chat_bot1'].children[1].children[0]);
+        window['chat_bot1'].children[1].scrollTop = window['chat_bot1'].children[1].scrollHeight;
+        
+        window['gradioEl'].querySelectorAll('#clear-btn')[0].onclick = function(e){
+            if (confirm('Clear all outputs?')==true) {
+                for (var i = window['chat_bot'].children[1].children[0].children.length-1; i >= 0; i--) {
+                    window['chat_bot'].children[1].children[0].removeChild(window['chat_bot'].children[1].children[0].children[i]); 
+                }
+                for (var i = window['chat_bot1'].children[1].children[0].children.length-1; i >= 0; i--) {
+                    window['chat_bot1'].children[1].children[0].removeChild(window['chat_bot1'].children[1].children[0].children[i]); 
+                }                
+                window['div_count'] = 0;
+                save_conversation(window['chat_bot1'].children[1].children[0]);
+            }
+        }
+ 
+        function set_buttons(action) {
+            window['submit-btn'].disabled = action;
+            window['clear-btn'].disabled = action;
+            window['chat_radio_0'].disabled = action;
+            window['chat_radio_1'].disabled = action; 
+            btn_color = 'color:#000';
+            if (action) {
+                btn_color = 'color:#ccc';
+            }
+            window['submit-btn'].setAttribute('style', btn_color);
+            window['clear-btn'].setAttribute('style', btn_color);
+            window['chat_radio_0'].setAttribute('style', btn_color);
+            window['chat_radio_1'].setAttribute('style', btn_color);             
+        }  
+        window['prevPrompt'] = '';
+        window['doCheckPrompt'] = 0;
+        window['prevImgSrc'] = '';
+        window['checkChange'] = function checkChange() {
+            try {
+                if (window['chat_radio_0'].checked) {
+                    dot_flashing = window['chat_bot'].children[1].children[0].querySelectorAll('.dot-flashing');
+                    if (window['chat_bot'].children[1].children[0].children.length > window['div_count'] && dot_flashing.length == 0) {
+                        new_len = window['chat_bot'].children[1].children[0].children.length - window['div_count'];
+                        for (var i = 0; i < new_len; i++) { 
+                            new_div = window['chat_bot'].children[1].children[0].children[window['div_count'] + i].cloneNode(true);
+                            window['chat_bot1'].children[1].children[0].appendChild(new_div);
+                        }
+                        window['div_count'] = window['chat_bot'].children[1].children[0].children.length;
+                        window['chat_bot1'].children[1].scrollTop = window['chat_bot1'].children[1].scrollHeight;
+                        save_conversation(window['chat_bot1'].children[1].children[0]);
+                    }
+                    if (window['chat_bot'].children[0].children.length > 1) {
+                        set_buttons(true);
+                        window['chat_bot1'].children[0].textContent = window['chat_bot'].children[0].children[1].textContent;
+                    } else {
+                        set_buttons(false);
+                        window['chat_bot1'].children[0].textContent = '';
+                    }
+                } else {
+                    img_index = 0;
+                    draw_prompt_en = window['my_prompt_en'].value;
+                    if (window['doCheckPrompt'] == 0 && window['prevPrompt'] != draw_prompt_en) {
+                            console.log('_____draw_prompt_en___[' + draw_prompt_en + ']_');
+                            window['doCheckPrompt'] = 1;
+                            window['prevPrompt'] = draw_prompt_en;
+ 
+                            tabitems = window['gradioEl'].querySelectorAll('.tabitem');
+                            for (var i = 0; i < tabitems.length; i++) {   
+                                inputText = tabitems[i].children[0].children[1].children[0].querySelectorAll('input')[0];
+                                setNativeValue(inputText, draw_prompt_en);
+                            }                            
+                            setTimeout(function() {
+                                window['draw_prompt'] = window['my_prompt'].value; 
+                                btns = window['gradioEl'].querySelectorAll('button');
+                                for (var i = 0; i < btns.length; i++) {
+                                    if (['Generate image','Run'].includes(btns[i].innerText)) {
+                                        btns[i].click();                
+                                    }
+                                }
+                                window['doCheckPrompt'] = 0;
+                            }, 10);                   
+                    }
+                    tabitems = window['gradioEl'].querySelectorAll('.tabitem');
+                    imgs = tabitems[img_index].children[0].children[1].children[1].querySelectorAll("img");
+                    if (imgs.length > 0) {
+                        if (window['prevImgSrc'] !== imgs[0].src) {
+                            var user_div = document.createElement("div");
+                            user_div.className = "message user svelte-134zwfa";
+                            user_div.style.backgroundColor = "#16a34a"; 
+                            user_div.dataset.testid = 'user';
+                            user_div.innerHTML = "<p>作画: " + window['draw_prompt'] + "</p><img></img>";
+                            window['chat_bot1'].children[1].children[0].appendChild(user_div);
+                            var bot_div = document.createElement("div");
+                            bot_div.className = "message bot svelte-134zwfa";
+                            bot_div.style.backgroundColor = "#2563eb"; 
+                            bot_div.style.width = "20%"; 
+                            bot_div.dataset.testid = 'bot';
+                            bot_div.onclick = function(e){
+                                img_click(this);
+                            }
+                            setTimeout(function(){
+                                bot_div.style.height = bot_div.offsetWidth + 'px'; 
+                                bot_div.children[0].setAttribute('style', 'max-width:none; width:100%');
+                            }, 10);                             
+                            bot_div.style.padding = "0.2rem"; 
+                            bot_div.appendChild(imgs[0].cloneNode(true));
+                            window['chat_bot1'].children[1].children[0].appendChild(bot_div);
+                            
+                            window['chat_bot1'].children[1].scrollTop = window['chat_bot1'].children[1].scrollHeight;
+                            window['prevImgSrc'] = imgs[0].src;
+                            save_conversation(window['chat_bot1'].children[1].children[0]);
+                        }
+                    }
+                    if (tabitems[img_index].children[0].children[1].children[1].children[0].children.length > 1) {
+                        tips = tabitems[img_index].children[0].children[1].children[1].children[0].textContent;
+                        if (tips.indexOf("Error") == -1) {
+                            set_buttons(true);
+                        } else {
+                            set_buttons(false);
+                        }
+                        window['chat_bot1'].children[0].textContent = '作画中 ' + tips;
+                    } else {
+                        set_buttons(false);
+                        window['chat_bot1'].children[0].textContent = '';
+                    } 
+                }
+              
+            } catch(e) {
+            }        
+        }
+        window['checkChange_interval'] = window.setInterval("window.checkChange()", 500);         
+    }
+   
+    return false;
+}"""
+
+space_ids = {
+            "spaces/stabilityai/stable-diffusion":"Stable Diffusion 2.1",
+            # "spaces/runwayml/stable-diffusion-v1-5":"Stable Diffusion 1.5",
+            # "spaces/stabilityai/stable-diffusion-1":"Stable Diffusion 1.0",
+            }
+
+tab_actions = []
+tab_titles = []
+
+for space_id in space_ids.keys():
+    print(space_id, space_ids[space_id])
+    try:
+        tab = gr.Interface.load(space_id)
+        tab_actions.append(tab)
+        tab_titles.append(space_ids[space_id])
+    except Exception as e:
+        logger.info(f"load_fail__{space_id}_{e}")
+        
+token_encoder = get_encoder()
+total_tokens = 4096
+max_output_tokens = 1024
+max_input_tokens = total_tokens - max_output_tokens
+
+def set_openai_api_key(api_key):
+    if api_key and api_key.startswith("sk-") and len(api_key) > 50:
+        openai.api_key = api_key
+
+def get_response_from_openai(input, chat_history, model_radio):
+    error_1 = 'You exceeded your current quota, please check your plan and billing details.'
+    def openai_create(input_list, model_radio):
+        try:
+            # print(f'input_list={input_list}')
+            input_list_len = len(input_list)
+            out_prompt = ''
+            messages = []
+            if model_radio == 'GPT-3.0':
+                out_prompt = 'AI:'
+            for i in range(input_list_len):
+                input = input_list[input_list_len-i-1].replace("<br>", '\n\n')
+                if input.startswith("Openai said:"):
+                    input = "☝:"
+    
+                if input.startswith("☝:"):
+                    if model_radio == 'GPT-3.0':
+                        out_prompt = input.replace("☝:", "AI:") + '\n' + out_prompt
+                    else:
+                        out_prompt = input.replace("☝:", "") + out_prompt
+                        messages.insert(0, {"role": "assistant", "content": input.replace("☝:", "")})
+                elif input.startswith("☟:"):
+                    if model_radio == 'GPT-3.0':
+                        out_prompt = input.replace("☟:", "Human:") + '\n' + out_prompt
+                    else:
+                        out_prompt = input.replace("☟:", "") + out_prompt
+                        messages.insert(0, {"role": "user", "content": input.replace("☟:", "")})
+                tokens = token_encoder.encode(out_prompt)
+                if len(tokens) > max_input_tokens: 
+                    break
+                
+            if model_radio == 'GPT-3.0':
+                # print(out_prompt)
+                response = openai.Completion.create(
+                    model="text-davinci-003",
+                    prompt=out_prompt,
+                    temperature=0.7,
+                    max_tokens=max_output_tokens,
+                    top_p=1,
+                    frequency_penalty=0,
+                    presence_penalty=0,
+                    stop=[" Human:", " AI:"]
+                )
+                # print(f'response_3.0__:{response}')
+                ret = response.choices[0].text
+            else:
+                # print(messages)
+                response = openai.ChatCompletion.create(
+                    model="gpt-3.5-turbo",
+                    messages=messages,
+                    temperature=0.7,
+                    max_tokens=max_output_tokens,
+                    top_p=1,
+                    frequency_penalty=0,
+                    presence_penalty=0,
+                    stop=[" Human:", " AI:"]
+                )                            
+                # print(f'response_3.5__:{response}')                
+                ret = response.choices[0].message['content']
+            if ret.startswith("\n\n"):
+                ret = ret.replace("\n\n", '') 
+            ret = ret.replace('\n', '<br>')  
+            if ret == '':
+                ret = f"Openai said: I'm too tired."   
+            return ret, response.usage                           
+        except Exception as e:
+            logger.info(f"openai_create_error__{e}")
+            ret = f"Openai said: {e} Perhaps enter your OpenAI API key."
+            return ret, {"completion_tokens": -1, "prompt_tokens": -1, "total_tokens": -1}
+    
+    # logger.info(f'chat_history = {chat_history}')
+    chat_history_list = []
+    chat_history = chat_history.replace("<p>", "").replace("</p>", "")
+    if chat_history != '':        
+        chat_history_list = json.loads(chat_history)
+    chat_history_list.append(f'☟:{input}')
+        
+    output, response_usage = openai_create(chat_history_list, model_radio)
+    logger.info(f'response_usage={response_usage}')
+    return output
+    
+def chat(input0, input1, chat_radio, model_radio, all_chat_history, chat_history):
+    all_chat = []
+    if all_chat_history != '':
+        all_chat = json.loads(all_chat_history)
+
+    if len(input0) == 0:
+        return all_chat, json.dumps(all_chat), input0, input1
+            
+    if chat_radio == "Talk to chatGPT":
+        response = get_response_from_openai(input0, chat_history, model_radio)
+        all_chat.append((input0, response))
+        return all_chat, json.dumps(all_chat), '', input1
+    else:
+        prompt_en = getTextTrans(input0, source='zh', target='en') + f',{random.randint(0,sys.maxsize)}'
+        return all_chat, json.dumps(all_chat), input0, prompt_en
+        
+def chat_radio_change(chat_radio):
+    if chat_radio == "Talk to chatGPT":
+        return gr.Radio.update(visible=True), gr.Text.update(visible=True)
+    else:
+        return gr.Radio.update(visible=False), gr.Text.update(visible=False)
+
+with gr.Blocks(title='Talk to chatGPT') as demo:    
+    with gr.Row(elem_id="page_0", visible=False) as page_0:
+        gr.HTML("<p>You can duplicating this space and use your own session token: <a style='display:inline-block' href='https://huggingface.co/spaces/yizhangliu/chatGPT?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p>")
+    with gr.Group(elem_id="page_1", visible=True) as page_1:
+        with gr.Box():            
+            with gr.Row():
+                start_button = gr.Button("Let's talk to chatGPT!", elem_id="start-btn", visible=True) 
+                start_button.click(fn=None, inputs=[], outputs=[], _js=start_work)
+                
+    with gr.Row(elem_id="page_2", visible=False) as page_2:        
+        with gr.Row(elem_id="chat_row"):
+            chatbot = gr.Chatbot(elem_id="chat_bot", visible=False).style(color_map=("green", "blue"))
+            chatbot1 = gr.Chatbot(elem_id="chat_bot1").style(color_map=("green", "blue"))
+        with gr.Row(elem_id="prompt_row"):
+            prompt_input0 = gr.Textbox(lines=2, label="input", elem_id="my_prompt", show_label=True)
+            prompt_input1 = gr.Textbox(lines=4, label="prompt", elem_id="my_prompt_en", visible=False)
+            chat_history = gr.Textbox(lines=4, label="chat_history", elem_id="chat_history", visible=False)
+            all_chat_history = gr.Textbox(lines=4, label="会话上下文：", elem_id="all_chat_history", visible=False)
+
+            chat_radio = gr.Radio(["Talk to chatGPT", "Text to Image"], elem_id="chat_radio",value="Talk to chatGPT", show_label=False, visible=True)
+            model_radio = gr.Radio(["GPT-3.0", "GPT-3.5"], elem_id="model_radio", value="GPT-3.5", 
+                                label='GPT model: ', show_label=True,interactive=True, visible=True) 
+            openai_api_key_textbox = gr.Textbox(placeholder="Paste your OpenAI API key (sk-...) and hit Enter",
+                                    show_label=False, lines=1, type='password')
+        with gr.Row(elem_id="btns_row"):
+            with gr.Column(id="submit_col"):
+                submit_btn = gr.Button(value = "submit",elem_id="submit-btn").style(
+                        margin=True,
+                        rounded=(True, True, True, True),
+                        width=100
+                    )
+            with gr.Column(id="clear_col"):
+                clear_btn = gr.Button(value = "clear outputs", elem_id="clear-btn").style(
+                        margin=True,
+                        rounded=(True, True, True, True),
+                        width=100
+                    )
+            submit_btn.click(fn=chat, 
+                             inputs=[prompt_input0, prompt_input1, chat_radio, model_radio, all_chat_history, chat_history], 
+                             outputs=[chatbot, all_chat_history, prompt_input0, prompt_input1],
+                            )
+        with gr.Row(elem_id='tab_img', visible=False).style(height=5):
+           tab_img = gr.TabbedInterface(tab_actions, tab_titles)  
+
+        openai_api_key_textbox.change(set_openai_api_key,
+                                      inputs=[openai_api_key_textbox],
+                                      outputs=[])
+        openai_api_key_textbox.submit(set_openai_api_key,
+                                      inputs=[openai_api_key_textbox],
+                                      outputs=[])
+        chat_radio.change(fn=chat_radio_change, 
+                        inputs=[chat_radio], 
+                        outputs=[model_radio, openai_api_key_textbox],
+                        ) 
+
+demo.launch(debug = True)

baidu_translate/module.py

@@ -0,0 +1,106 @@
+import argparse
+import random, os
+from hashlib import md5
+from typing import Optional
+
+import requests
+
+import paddlehub as hub
+from paddlehub.module.module import moduleinfo
+from paddlehub.module.module import runnable
+from paddlehub.module.module import serving
+
+
+def make_md5(s, encoding='utf-8'):
+    return md5(s.encode(encoding)).hexdigest()
+
+
+@moduleinfo(name="baidu_translate",
+            version="1.0.0",
+            type="text/machine_translation",
+            summary="",
+            author="baidu-nlp",
+            author_email="paddle-dev@baidu.com")
+class BaiduTranslate:
+
+    def __init__(self, appid=None, appkey=None):
+        """
+      :param appid: appid for requesting Baidu translation service.
+      :param appkey: appkey for requesting Baidu translation service.
+      """
+        appid = os.environ.get('baidu_translate_appid')
+        appkey = os.environ.get('baidu_translate_appkey')
+        # Set your own appid/appkey.
+        if appid is None:
+            self.appid = ''
+        else:
+            self.appid = appid
+        if appkey is None:
+            self.appkey = ''
+        else:
+            self.appkey = appkey
+        self.url = 'http://api.fanyi.baidu.com/api/trans/vip/translate'
+
+    def translate(self, query: str, from_lang: Optional[str] = "en", to_lang: Optional[int] = "zh"):
+        """
+        Create image by text prompts using ErnieVilG model.
+
+        :param query: Text to be translated.
+        :param from_lang: Source language.
+        :param to_lang: Dst language.
+
+        Return translated string.
+        """
+        # Generate salt and sign
+        salt = random.randint(32768, 65536)
+        sign = make_md5(self.appid + query + str(salt) + self.appkey)
+
+        # Build request
+        headers = {'Content-Type': 'application/x-www-form-urlencoded'}
+        payload = {'appid': self.appid, 'q': query, 'from': from_lang, 'to': to_lang, 'salt': salt, 'sign': sign}
+
+        # Send request
+        try:
+            r = requests.post(self.url, params=payload, headers=headers)
+            result = r.json()
+        except Exception as e:
+            error_msg = str(e)
+            raise RuntimeError(error_msg)
+        if 'error_code' in result:
+            raise RuntimeError(result['error_msg'])
+        return result['trans_result'][0]['dst']
+
+    @runnable
+    def run_cmd(self, argvs):
+        """
+        Run as a command.
+        """
+        self.parser = argparse.ArgumentParser(description="Run the {} module.".format(self.name),
+                                              prog='hub run {}'.format(self.name),
+                                              usage='%(prog)s',
+                                              add_help=True)
+        self.arg_input_group = self.parser.add_argument_group(title="Input options", description="Input data. Required")
+        self.add_module_input_arg()
+        args = self.parser.parse_args(argvs)
+        if args.appid is not None and args.appkey is not None:
+            self.appid = args.appid
+            self.appkey = args.appkey
+        result = self.translate(args.query, args.from_lang, args.to_lang)
+        return result
+
+    @serving
+    def serving_method(self, query, from_lang, to_lang):
+        """
+        Run as a service.
+        """
+        return self.translate(query, from_lang, to_lang)
+
+    def add_module_input_arg(self):
+        """
+        Add the command input options.
+        """
+        self.arg_input_group.add_argument('--query', type=str)
+        self.arg_input_group.add_argument('--from_lang', type=str, default='en', help="源语言")
+        self.arg_input_group.add_argument('--to_lang', type=str, default='zh', help="目标语言")
+        self.arg_input_group.add_argument('--appid', type=str, default=None, help="注册得到的个人appid")
+        self.arg_input_group.add_argument('--appkey', type=str, default=None, help="注册得到的个人appkey")

encoder.py

@@ -0,0 +1,120 @@
+# This file includes code which was modified from https://github.com/openai/gpt-2
+
+import tensorflow as tf
+import os
+import json
+import regex as re
+from functools import lru_cache
+import requests
+import boto3
+import pdb
+
+
+@lru_cache()
+def bytes_to_unicode():
+
+    bs = (
+        list(range(ord("!"), ord("~") + 1))
+        + list(range(ord("¡"), ord("¬") + 1))
+        + list(range(ord("®"), ord("ÿ") + 1))
+    )
+    cs = bs[:]
+    n = 0
+    for b in range(2 ** 8):
+        if b not in bs:
+            bs.append(b)
+            cs.append(2 ** 8 + n)
+            n += 1
+    cs = [chr(n) for n in cs]
+    return dict(zip(bs, cs))
+
+
+def get_pairs(word):
+    pairs = set()
+    prev_char = word[0]
+    for char in word[1:]:
+        pairs.add((prev_char, char))
+        prev_char = char
+    return pairs
+
+
+class Encoder:
+    def __init__(self, encoder, bpe_merges, errors="replace"):
+        self.encoder = encoder
+        self.decoder = {v: k for k, v in self.encoder.items()}
+        self.errors = errors
+        self.byte_encoder = bytes_to_unicode()
+        self.byte_decoder = {v: k for k, v in self.byte_encoder.items()}
+        self.bpe_ranks = dict(zip(bpe_merges, range(len(bpe_merges))))
+        self.cache = {}
+        self.pat = re.compile(
+            r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""
+        )
+
+    def bpe(self, token):
+        if token in self.cache:
+            return self.cache[token]
+        word = tuple(token)
+
+        pairs = get_pairs(word)
+
+        if not pairs:
+            return token
+
+        while True:
+            bigram = min(pairs, key=lambda pair: self.bpe_ranks.get(pair, float("inf")))
+            if bigram not in self.bpe_ranks:
+                break
+            first, second = bigram
+            new_word = []
+            i = 0
+            while i < len(word):
+                try:
+                    j = word.index(first, i)
+                    new_word.extend(word[i:j])
+                    i = j
+                except:
+                    new_word.extend(word[i:])
+                    break
+
+                if word[i] == first and i < len(word) - 1 and word[i + 1] == second:
+                    new_word.append(first + second)
+                    i += 2
+                else:
+                    new_word.append(word[i])
+                    i += 1
+            new_word = tuple(new_word)
+            word = new_word
+            if len(word) == 1:
+                break
+            else:
+                pairs = get_pairs(word)
+
+        word = " ".join(word)
+        self.cache[token] = word
+        return word
+
+    def encode(self, text):
+        bpe_tokens = []
+        for token in re.findall(self.pat, text):
+            token = "".join(self.byte_encoder[b] for b in token.encode("utf-8"))
+
+            bpe_tokens.extend(self.encoder[bpe_token] for bpe_token in self.bpe(token).split(" "))
+        return bpe_tokens
+
+    def decode(self, tokens):
+        text = "".join([self.decoder[token] for token in tokens])
+        text = bytearray([self.byte_decoder[c] for c in text]).decode("utf-8", errors=self.errors)
+        return text
+
+
+def get_encoder():
+    with open("encoder.json", "r") as f:
+        encoder = json.load(f)
+    with open("vocab.bpe", "r", encoding="utf-8") as f:
+        bpe_data = f.read()
+    bpe_merges = [tuple(merge_str.split()) for merge_str in bpe_data.split("\n")[1:-1]]
+    return Encoder(encoder=encoder, bpe_merges=bpe_merges)
+
+# encoder = get_encoder()
+# print('encoded is ', encoder.encode('hello 👋 world 🌍 This is a long string to test whether or not the emoji issue was fixed!'))

requirements.txt

@@ -0,0 +1,11 @@
+openai
+loguru
+paddlepaddle==2.3.2
+paddlehub
+# transformers
+# torch
+tensorflow
+regex
+boto3
+gradio==3.19.1
+tencentcloud-sdk-python

utils.py

@@ -0,0 +1,54 @@
+import json, os
+from tencentcloud.common import credential
+from tencentcloud.common.profile.client_profile import ClientProfile
+from tencentcloud.common.profile.http_profile import HttpProfile
+from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
+from tencentcloud.tmt.v20180321 import tmt_client, models
+
+def get_tmt_client():
+    try:
+        # 实例化一个认证对象，入参需要传入腾讯云账户 SecretId 和 SecretKey，此处还需注意密钥对的保密
+        # 代码泄露可能会导致 SecretId 和 SecretKey 泄露，并威胁账号下所有资源的安全性。以下代码示例仅供参考，建议采用更安全的方式来使用密钥，请参见：https://cloud.tencent.com/document/product/1278/85305
+        # 密钥可前往官网控制台 https://console.cloud.tencent.com/cam/capi 进行获取
+        SecretId = os.environ.get("TENCENTCLOUD_SECRET_ID")
+        SecretKey = os.environ.get("TENCENTCLOUD_SECRET_KEY")    
+        cred = credential.Credential(SecretId, SecretKey)
+        # 实例化一个http选项，可选的，没有特殊需求可以跳过
+        httpProfile = HttpProfile()
+        httpProfile.endpoint = "tmt.tencentcloudapi.com"
+
+        # 实例化一个client选项，可选的，没有特殊需求可以跳过
+        clientProfile = ClientProfile()
+        clientProfile.httpProfile = httpProfile
+        # 实例化要请求产品的client对象,clientProfile是可选的
+        client = tmt_client.TmtClient(cred, "ap-shanghai", clientProfile)
+        print(f'client_{client}')
+        return client
+    except TencentCloudSDKException as err:
+        print(f'client_err_{err}')
+        return None
+
+def getTextTrans_tmt(tmt_client, text, source='zh', target='en'):
+    def is_chinese(string):
+        for ch in string:
+            if u'\u4e00' <= ch <= u'\u9fff':
+                return True
+        return False
+
+    if tmt_client is None:
+        return text
+    if not is_chinese(text) and target == 'en': 
+        return text
+    try:
+        req = models.TextTranslateRequest()
+        params = {
+            "SourceText": text,
+            "Source": source,
+            "Target": target,
+            "ProjectId": 0
+        }   
+        req.from_json_string(json.dumps(params))
+        resp = tmt_client.TextTranslate(req)
+        return resp.TargetText
+    except Exception as e:
+        return text