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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
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")
count = 0
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]}">'
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(" ", " ")
if not line.startswith("<br/>"):
lines[i] = '<br/>'+line
return "".join(lines)
def predict(inputs, top_p, temperature, openai_api_key, chatbot=[], history=[], system_prompt=initial_prompt, retry=False, summary=False): # repetition_penalty, top_k
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 data in chatbot:
temp1 = {}
temp1["role"] = "user"
temp1["content"] = data[0]
temp2 = {}
temp2["role"] = "assistant"
temp2["content"] = data[1]
if temp1["content"] != "":
messages.append(temp1)
messages.append(temp2)
else:
messages[-1]['content'] = temp2['content']
if retry and chat_counter:
messages.pop()
elif summary:
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。"))
history = ["我们刚刚聊了什么?"]
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": True,
"presence_penalty": 0,
"frequency_penalty": 0,
}
if not summary:
history.append(inputs)
print(f"payload is - {payload}")
# 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)
#response = requests.post(API_URL, headers=headers, json=payload, stream=True)
token_counter = 0
partial_words = ""
counter = 0
chatbot.append((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:
chatbot.pop()
chatbot.append((history[-1], f"☹️发生了错误\n返回值:{response.text}\n异常:{e}"))
history.pop()
yield chatbot, history
break
#print(json.loads(chunk.decode()[6:])['choices'][0]["delta"] ["content"])
partial_words = partial_words + \
json.loads(chunk.decode()[6:])[
'choices'][0]["delta"]["content"]
if token_counter == 0:
history.append(" " + partial_words)
else:
history[-1] = parse_text(partial_words)
chatbot[-1] = (history[-2], history[-1])
# chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ] # convert to tuples of list
token_counter += 1
# resembles {chatbot: chat, state: history}
yield chatbot, history
def delete_last_conversation(chatbot, history):
if chat_counter > 0:
chat_counter -= 1
chatbot.pop()
history.pop()
history.pop()
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}
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)
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 = [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):
lines = []
with open(os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8") as csvfile:
reader = csv.reader(csvfile)
lines = list(reader)
lines = lines[1:]
return {row[0]:row[1] for row in lines}, gr.Dropdown.update(choices=[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) 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>
"""
with gr.Blocks() as demo:
gr.HTML(title)
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").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")
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=[], 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])
txt.submit(reset_textbox, [], [txt])
submitBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot,
history, systemPromptTxt], [chatbot, history], 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], 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], 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(server_name = "0.0.0.0", 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
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