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import json
import gradio as gr
import openai
import os
import sys
import traceback
# import markdown
my_api_key = "" # 在这里输入你的 API 密钥
initial_prompt = "You are a helpful assistant."
if my_api_key == "":
my_api_key = os.environ.get('my_api_key')
if my_api_key == "empty":
print("Please give a api key!")
sys.exit(1)
if my_api_key == "":
initial_keytxt = None
elif len(str(my_api_key)) == 51:
initial_keytxt = "默认api-key(未验证):" + str(my_api_key[:4] + "..." + my_api_key[-4:])
else:
initial_keytxt = "默认api-key无效,请重新输入"
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(" ", " ")
lines[i] = '<br/>'+line
return "".join(lines)
def get_response(system, context, myKey, raw = False):
openai.api_key = myKey
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[system, *context],
)
openai.api_key = ""
if raw:
return response
else:
statistics = f'本次对话Tokens用量【{response["usage"]["total_tokens"]} / 4096】 ( 提问+上文 {response["usage"]["prompt_tokens"]},回答 {response["usage"]["completion_tokens"]} )'
message = response["choices"][0]["message"]["content"]
message_with_stats = f'{message}\n\n================\n\n{statistics}'
# message_with_stats = markdown.markdown(message_with_stats)
return message, parse_text(message_with_stats)
def predict(chatbot, input_sentence, system, context, myKey):
if len(input_sentence) == 0:
return []
context.append({"role": "user", "content": f"{input_sentence}"})
try:
message, message_with_stats = get_response(system, context, myKey)
except openai.error.AuthenticationError:
chatbot.append((input_sentence, "请求失败,请检查API-key是否正确。"))
return chatbot, context
except openai.error.Timeout:
chatbot.append((input_sentence, "请求超时,请检查网络连接。"))
return chatbot, context
except openai.error.APIConnectionError:
chatbot.append((input_sentence, "连接失败,请检查网络连接。"))
return chatbot, context
except openai.error.RateLimitError:
chatbot.append((input_sentence, "请求过于频繁,请5s后再试。"))
return chatbot, context
except:
chatbot.append((input_sentence, "发生了未知错误Orz"))
return chatbot, context
context.append({"role": "assistant", "content": message})
chatbot.append((input_sentence, message_with_stats))
return chatbot, context
def retry(chatbot, system, context, myKey):
if len(context) == 0:
return [], []
try:
message, message_with_stats = get_response(system, context[:-1], myKey)
except openai.error.AuthenticationError:
chatbot.append(("重试请求", "请求失败,请检查API-key是否正确。"))
return chatbot, context
except openai.error.Timeout:
chatbot.append(("重试请求", "请求超时,请检查网络连接。"))
return chatbot, context
except openai.error.APIConnectionError:
chatbot.append(("重试请求", "连接失败,请检查网络连接。"))
return chatbot, context
except openai.error.RateLimitError:
chatbot.append(("重试请求", "请求过于频繁,请5s后再试。"))
return chatbot, context
except:
chatbot.append(("重试请求", "发生了未知错误Orz"))
return chatbot, context
context[-1] = {"role": "assistant", "content": message}
chatbot[-1] = (context[-2]["content"], message_with_stats)
return chatbot, context
def delete_last_conversation(chatbot, context):
if len(context) == 0:
return [], []
chatbot = chatbot[:-1]
context = context[:-2]
return chatbot, context
def reduce_token(chatbot, system, context, myKey):
context.append({"role": "user", "content": "请帮我总结一下上述对话的内容,实现减少tokens的同时,保证对话的质量。在总结中不要加入这一句话。"})
response = get_response(system, context, myKey, raw=True)
statistics = f'本次对话Tokens用量【{response["usage"]["completion_tokens"]+12+12+8} / 4096】'
optmz_str = parse_text( f'好的,我们之前聊了:{response["choices"][0]["message"]["content"]}\n\n================\n\n{statistics}' )
chatbot.append(("请帮我总结一下上述对话的内容,实现减少tokens的同时,保证对话的质量。", optmz_str))
context = []
context.append({"role": "user", "content": "我们之前聊了什么?"})
context.append({"role": "assistant", "content": f'我们之前聊了:{response["choices"][0]["message"]["content"]}'})
return chatbot, context
def save_chat_history(filepath, system, context):
if filepath == "":
return
history = {"system": system, "context": context}
with open(f"{filepath}.json", "w") as f:
json.dump(history, f)
def load_chat_history(fileobj):
with open(fileobj.name, "r") as f:
history = json.load(f)
context = history["context"]
chathistory = []
for i in range(0, len(context), 2):
chathistory.append((parse_text(context[i]["content"]), parse_text(context[i+1]["content"])))
return chathistory , history["system"], context, history["system"]["content"]
def get_history_names():
with open("history.json", "r") as f:
history = json.load(f)
return list(history.keys())
def reset_state():
return [], []
def update_system(new_system_prompt):
return {"role": "system", "content": new_system_prompt}
def set_apikey(new_api_key, myKey):
old_api_key = myKey
try:
get_response(update_system(initial_prompt), [{"role": "user", "content": "test"}], new_api_key)
except openai.error.AuthenticationError:
return "无效的api-key", myKey
except openai.error.Timeout:
return "请求超时,请检查网络设置", myKey
except openai.error.APIConnectionError:
return "网络错误", myKey
except:
return "发生了未知错误Orz", myKey
encryption_str = "验证成功,api-key已做遮挡处理:" + new_api_key[:4] + "..." + new_api_key[-4:]
return encryption_str, new_api_key
with gr.Blocks() as demo:
keyTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入你的OpenAI API-key...", value=initial_keytxt, label="API Key").style(container=True)
chatbot = gr.Chatbot().style(color_map=("#1D51EE", "#585A5B"))
context = gr.State([])
systemPrompt = gr.State(update_system(initial_prompt))
myKey = gr.State(my_api_key)
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("♻️ 优化Tokens")
newSystemPrompt = gr.Textbox(show_label=True, placeholder=f"在这里输入新的System Prompt...", label="更改 System prompt").style(container=True)
systemPromptDisplay = gr.Textbox(show_label=True, value=initial_prompt, interactive=False, label="目前的 System prompt").style(container=True)
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本地)", 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="保存对话", value="对话历史记录").style(container=True)
with gr.Column(scale=1):
saveBtn = gr.Button("💾 保存对话")
uploadBtn = gr.UploadButton("📂 读取对话", file_count="single", file_types=["json"])
txt.submit(predict, [chatbot, txt, systemPrompt, context, myKey], [chatbot, context], show_progress=True)
txt.submit(lambda :"", None, txt)
submitBtn.click(predict, [chatbot, txt, systemPrompt, context, myKey], [chatbot, context], show_progress=True)
submitBtn.click(lambda :"", None, txt)
emptyBtn.click(reset_state, outputs=[chatbot, context])
newSystemPrompt.submit(update_system, newSystemPrompt, systemPrompt)
newSystemPrompt.submit(lambda x: x, newSystemPrompt, systemPromptDisplay)
newSystemPrompt.submit(lambda :"", None, newSystemPrompt)
retryBtn.click(retry, [chatbot, systemPrompt, context, myKey], [chatbot, context], show_progress=True)
delLastBtn.click(delete_last_conversation, [chatbot, context], [chatbot, context], show_progress=True)
reduceTokenBtn.click(reduce_token, [chatbot, systemPrompt, context, myKey], [chatbot, context], show_progress=True)
keyTxt.submit(set_apikey, [keyTxt, myKey], [keyTxt, myKey], show_progress=True)
uploadBtn.upload(load_chat_history, uploadBtn, [chatbot, systemPrompt, context, systemPromptDisplay], show_progress=True)
saveBtn.click(save_chat_history, [saveFileName, systemPrompt, context], None, show_progress=True)
demo.launch()
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