add private conf

README.md

@@ -2,7 +2,42 @@
 
 **如果喜欢这个项目，请给它一个Star**
 
-## 使用docker
+- 支持GPT输出的markdown表格
+<div align="center">
+<img src="demo2.jpg" width="500" >
+</div>
+
+- 如果输出包含公式，会同时以tex形式和渲染形式显示，方便复制和阅读
+<div align="center">
+<img src="demo.jpg" width="500" >
+</div>
+
+- 所有按钮都通过读取functional.py动态生成，可随意加自定义功能，解放粘贴板
+<div align="center">
+<img src="公式.gif" width="700" >
+</div>
+
+- 代码的显示自然也不在话下 https://www.bilibili.com/video/BV1F24y147PD/
+<div align="center">
+<img src="润色.gif" width="700" >
+</div>
+
+## 直接运行 (Windows or Linux)
+
+```
+# 下载项目
+git clone https://github.com/binary-husky/chatgpt_academic.git
+cd chatgpt_academic
+# 配置 海外Proxy 和 OpenAI API KEY
+config.py
+# 安装依赖
+python -m pip install -r requirements.txt
+# 运行
+python main.py
+```
+
+
+## 使用docker (Linux)
 
 ``` sh
 # 下载项目
@@ -17,6 +52,25 @@ docker run --rm -it --net=host gpt-academic
 
 ```
 
+
+## 自定义新的便捷按钮
+打开functional.py，只需看一眼就知道怎么弄了
+例如
+```
+"英译中": {
+    "Prefix": "请翻译成中文：\n\n",
+    "Button": None,
+    "Suffix": "",
+},
+```
+
+## 配置代理
+
+在```config.py```中修改端口与代理软件对应
+![image](https://user-images.githubusercontent.com/96192199/226571294-37a47cd9-4d40-4c16-97a2-d360845406f7.png)
+![image](https://user-images.githubusercontent.com/96192199/226838985-e5c95956-69c2-4c23-a4dd-cd7944eeb451.png)
+
+
 ## 参考项目
 ```
 https://github.com/Python-Markdown/markdown

check_proxy.py

@@ -0,0 +1,26 @@
+
+"""
+我：用python的requests库查询本机ip地址所在地
+ChatGPT:
+"""
+def check_proxy(proxies):
+    import requests
+    proxies_https = proxies['https'] if proxies is not None else '无'
+    try:
+        response = requests.get("https://ipapi.co/json/", proxies=proxies, timeout=4)
+        data = response.json()
+        print(f'查询代理的地理位置，返回的结果是{data}')
+        country = data['country_name']
+        result = f"代理配置 {proxies_https}, 代理所在地：{country}"
+        print(result)
+        return result
+    except:
+        result = f"代理配置 {proxies_https}, 代理所在地查询超时，代理可能无效"
+        print(result)
+        return result
+
+
+if __name__ == '__main__':
+    try: from config_private import proxies # 放自己的秘密如API和代理网址 os.path.exists('config_private.py')
+    except: from config import proxies
+    check_proxy(proxies)

config.py

@@ -1,11 +1,23 @@
-# my_api_key = "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"
+# API_KEY = "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" 此key无效
 API_KEY = "sk-此处填API秘钥"
 API_URL = "https://api.openai.com/v1/chat/completions"
 
+# 改为True应用代理
 USE_PROXY = False
 if USE_PROXY:
+    # 代理网络的地址，打开你的科学上网软件查看代理的协议(socks5/http)、地址(localhost)和端口(11284)
     proxies = { "http": "socks5h://localhost:11284", "https": "socks5h://localhost:11284", } 
     print('网络代理状态：运行。')
 else:
     proxies = None
     print('网络代理状态：未配置。无代理状态下很可能无法访问。')
+
+# 发送请求到OpenAI后，等待多久判定为超时
+TIMEOUT_SECONDS = 20
+
+# 网页的端口, -1代表随机端口
+WEB_PORT = -1
+
+# 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"

functional.py

@@ -10,19 +10,16 @@ def get_functionals():
         "英语学术润色": {
             "Prefix": "Below is a paragraph from an academic paper. Polish the writing to meet the academic style, \
 improve the spelling, grammar, clarity, concision and overall readability. When neccessary, rewrite the whole sentence. \
-Furthermore, list all modification and explain the reasons to do so in markdown table.\n\n",
+Furthermore, list all modification and explain the reasons to do so in markdown table.\n\n",    # 前言
-            "Button": None,
+            "Suffix": "",   # 后语
-            "Suffix": "",
+            "Color": "stop",    # 按钮颜色
-            "Color": "stop",
         },
         "中文学术润色": {
             "Prefix": "作为一名中文学术论文写作改进助理，你的任务是改进所提供文本的拼写、语法、清晰、简洁和整体可读性，同时分解长句，减少重复，并提供改进建议。请只提供文本的更正版本，避免包括解释。请编辑以下文本：\n\n",
-            "Button": None,
             "Suffix": "",
         },
         "查找语法错误": {
             "Prefix": "Below is a paragraph from an academic paper. Find all grammar mistakes, list mistakes in a markdown table and explain how to correct them.\n\n",
-            "Button": None,
             "Suffix": "",
         },
         "中英互译": {
@@ -37,28 +34,23 @@ When providing translations, please use Chinese to explain each sentence’s ten
 For phrases or individual words that require translation, provide the source (dictionary) for each one.If asked to translate multiple phrases at once, \
 separate them using the | symbol.Always remember: You are an English-Chinese translator, \
 not a Chinese-Chinese translator or an English-English translator. Below is the text you need to translate: \n\n",
-            "Button": None,
             "Suffix": "",
             "Color": "stop",
         },
         "中译英": {
             "Prefix": "Please translate following sentence to English: \n\n",
-            "Button": None,
             "Suffix": "",
         },
         "学术中译英": {
             "Prefix": "Please translate following sentence to English with academic writing, and provide some related authoritative examples: \n\n",
-            "Button": None,
             "Suffix": "",
         },
         "英译中": {
             "Prefix": "请翻译成中文：\n\n",
-            "Button": None,
             "Suffix": "",
         },
         "解释代码": {
             "Prefix": "请解释以下代码：\n```\n",
-            "Button": None,
             "Suffix": "\n```\n",
             "Color": "stop",
         },

main.py

@@ -4,6 +4,9 @@ import markdown, mdtex2html
 from predict import predict
 from show_math import convert as convert_math
 
+try: from config_private import proxies, WEB_PORT # 放自己的秘密如API和代理网址 os.path.exists('config_private.py')
+except: from config import proxies, WEB_PORT
+
 def find_free_port():
     import socket
     from contextlib import closing
@@ -11,16 +14,16 @@ def find_free_port():
         s.bind(('', 0))
         s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
         return s.getsockname()[1]
-    
+
-PORT = find_free_port()
+PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
 
 initial_prompt = "Serve me as a writing and programming assistant."
 title_html = """<h1 align="center">ChatGPT 学术优化</h1>"""
 
 import logging
 os.makedirs('gpt_log', exist_ok=True)
-logging.basicConfig(filename='gpt_log/predict.log', level=logging.INFO)
+logging.basicConfig(filename='gpt_log/chat_secrets.log', level=logging.INFO, encoding='utf-8')
-
+print('所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log，请注意自我隐私保护哦！')
 
 from functional import get_functionals
 functional = get_functionals()
@@ -46,9 +49,6 @@ def markdown_convertion(txt):
     else:
         return markdown.markdown(txt,extensions=['fenced_code','tables'])
 
-# math_config = {'mdx_math': {'enable_dollar_delimiter': True}}
-# markdown.markdown(txt, extensions=['fenced_code', 'tables', 'mdx_math'], extension_configs=math_config)
-
 
 def format_io(self,y):
     if y is None:
@@ -84,8 +84,8 @@ with gr.Blocks() as demo:
                 for k in functional:
                     variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
                     functional[k]["Button"] = gr.Button(k, variant=variant)
-
+            from check_proxy import check_proxy
-            statusDisplay = gr.Markdown("status: ready")
+            statusDisplay = gr.Markdown(f"{check_proxy(proxies)}")
             systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt).style(container=True)
             #inputs, top_p, temperature, top_k, repetition_penalty
             with gr.Accordion("arguments", open=False):

predict.py

@@ -4,23 +4,11 @@ import logging
 import traceback
 import requests
 import importlib
-import os
 
-if os.path.exists('config_private.py'):
+try: from config_private import proxies, API_URL, API_KEY, TIMEOUT_SECONDS # 放自己的秘密如API和代理网址 os.path.exists('config_private.py')
-    # 放自己的秘密如API和代理网址
+except: from config import proxies, API_URL, API_KEY, TIMEOUT_SECONDS
-    from config_private import proxies, API_URL, API_KEY
-else:
-    from config import proxies, API_URL, API_KEY
-
-
-
-def compose_system(system_prompt):
-    return {"role": "system", "content": system_prompt}
-
-
-def compose_user(user_input):
-    return {"role": "user", "content": user_input}
 
+timeout_bot_msg = 'Request timeout, network error. please check proxy settings in config.py.'
 
 def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', retry=False, 
             stream = True, additional_fn=None):
@@ -35,7 +23,7 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
         raw_input = inputs
         logging.info(f'[raw_input] {raw_input}')
         chatbot.append((inputs, ""))
-        yield chatbot, history, "Waiting"
+        yield chatbot, history, "等待响应"
 
     headers = {
         "Content-Type": "application/json",
@@ -46,29 +34,32 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
 
     print(f"chat_counter - {chat_counter}")
 
-    messages = [compose_system(system_prompt)]
+    messages = [{"role": "system", "content": system_prompt}]
     if chat_counter:
         for index in range(0, 2*chat_counter, 2):
-            d1 = {}
+            what_i_have_asked = {}
-            d1["role"] = "user"
+            what_i_have_asked["role"] = "user"
-            d1["content"] = history[index]
+            what_i_have_asked["content"] = history[index]
-            d2 = {}
+            what_gpt_answer = {}
-            d2["role"] = "assistant"
+            what_gpt_answer["role"] = "assistant"
-            d2["content"] = history[index+1]
+            what_gpt_answer["content"] = history[index+1]
-            if d1["content"] != "":
+            if what_i_have_asked["content"] != "":
-                if d2["content"] != "" or retry:
+                if not (what_gpt_answer["content"] != "" or retry): continue
-                    messages.append(d1)
+                if what_gpt_answer["content"] == timeout_bot_msg: continue
-                    messages.append(d2)
+                messages.append(what_i_have_asked)
+                messages.append(what_gpt_answer)
             else:
-                messages[-1]['content'] = d2['content']
+                messages[-1]['content'] = what_gpt_answer['content']
+
     if retry and chat_counter:
         messages.pop()
     else:
-        temp3 = {}
+        what_i_ask_now = {}
-        temp3["role"] = "user"
+        what_i_ask_now["role"] = "user"
-        temp3["content"] = inputs
+        what_i_ask_now["content"] = inputs
-        messages.append(temp3)
+        messages.append(what_i_ask_now)
         chat_counter += 1
+
     # messages
     payload = {
         "model": "gpt-3.5-turbo",
@@ -87,10 +78,10 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
     try:
         # make a POST request to the API endpoint using the requests.post method, passing in stream=True
         response = requests.post(API_URL, headers=headers, proxies=proxies,
-                                json=payload, stream=True, timeout=15)
+                                json=payload, stream=True, timeout=TIMEOUT_SECONDS)
     except:
-        chatbot[-1] = ((chatbot[-1][0], 'Requests Timeout, Network Error.'))
+        chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg))
-        yield chatbot, history, "Requests Timeout"
+        yield chatbot, history, "请求超时"
         raise TimeoutError
 
     token_counter = 0
@@ -101,8 +92,6 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
         stream_response =  response.iter_lines()
         while True:
             chunk = next(stream_response)
-            # print(chunk)
-            
             if chunk == b'data: [DONE]':
                 break
 
@@ -119,16 +108,21 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
                         break
                 except Exception as e:
                     traceback.print_exc()
+                    print(chunk.decode())
 
-                chunkjson = json.loads(chunk.decode()[6:])
+                try:
-                status_text = f"id: {chunkjson['id']}, finish_reason: {chunkjson['choices'][0]['finish_reason']}"
+                    chunkjson = json.loads(chunk.decode()[6:])
-                partial_words = partial_words + \
+                    status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}"
-                    json.loads(chunk.decode()[6:])[
+                    partial_words = partial_words + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
-                        'choices'][0]["delta"]["content"]
+                    if token_counter == 0:
-                if token_counter == 0:
+                        history.append(" " + partial_words)
-                    history.append(" " + partial_words)
+                    else:
-                else:
+                        history[-1] = partial_words
-                    history[-1] = partial_words
+                    chatbot[-1] = (history[-2], history[-1])
-                chatbot[-1] = (history[-2], history[-1])
+                    token_counter += 1
-                token_counter += 1
+                    yield chatbot, history, status_text
-                yield chatbot, history, status_text
+
+                except Exception as e:
+                    traceback.print_exc()
+                    print(chunk.decode())
+                    yield chatbot, history, "Json解析不合常规"