Spaces:
Sleeping
Sleeping
Chuan Hu
commited on
重大更新:支持像官方网页那样实时传输了;改进的保存/加载机制
Browse files- ChuanhuChatbot.py +182 -169
ChuanhuChatbot.py
CHANGED
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@@ -1,14 +1,15 @@
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import json
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import gradio as gr
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import openai
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import os
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import sys
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import traceback
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my_api_key = "" # 在这里输入你的 API 密钥
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initial_prompt = "You are a helpful assistant."
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if my_api_key == "":
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my_api_key = os.environ.get('my_api_key')
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@@ -16,17 +17,11 @@ if my_api_key == "empty":
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print("Please give a api key!")
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sys.exit(1)
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if my_api_key == "":
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initial_keytxt = None
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elif len(str(my_api_key)) == 51:
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initial_keytxt = "默认api-key(未验证):" + str(my_api_key[:4] + "..." + my_api_key[-4:])
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else:
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initial_keytxt = "默认api-key无效,请重新输入"
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def parse_text(text):
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lines = text.split("\n")
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count = 0
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for i,line in enumerate(lines):
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if "```" in line:
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count += 1
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items = line.split('`')
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@@ -46,190 +41,208 @@ def parse_text(text):
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lines[i] = '<br/>'+line
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return "".join(lines)
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def
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return chatbot,
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def
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if len(context) == 0:
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return [], []
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chatbot = chatbot[:-1]
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context = context[:-2]
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return chatbot, context
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def reduce_token(chatbot, system, context, myKey):
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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。"})
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response = get_response(system, context, myKey, raw=True)
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statistics = f'本次对话Tokens用量【{response["usage"]["completion_tokens"]+12+12+8} / 4096】'
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optmz_str = parse_text( f'好的,我们之前聊了:{response["choices"][0]["message"]["content"]}\n\n================\n\n{statistics}' )
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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))
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context = []
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context.append({"role": "user", "content": "我们之前聊了什么?"})
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context.append({"role": "assistant", "content": f'我们之前聊了:{response["choices"][0]["message"]["content"]}'})
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return chatbot, context
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def save_chat_history(filepath, system, context):
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if filepath == "":
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return
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def load_chat_history(fileobj):
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with open(fileobj.name, "r") as f:
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history = json.load(f)
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context = history["context"]
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chathistory = []
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for i in range(0, len(context), 2):
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chathistory.append((parse_text(context[i]["content"]), parse_text(context[i+1]["content"])))
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return chathistory , history["system"], context, history["system"]["content"]
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def
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with open(
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return
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def reset_state():
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return [], []
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return "请求超时,请检查网络设置", myKey
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except openai.error.APIConnectionError:
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return "网络错误", myKey
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except:
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return "发生了未知错误Orz", myKey
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encryption_str = "验证成功,api-key已做遮挡处理:" + new_api_key[:4] + "..." + new_api_key[-4:]
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return encryption_str, new_api_key
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with gr.Blocks() as demo:
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keyTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入你的OpenAI API-key...",
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topic = gr.State("未命名对话历史记录")
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with gr.Row():
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with gr.Column(scale=12):
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txt = gr.Textbox(show_label=False, placeholder="在这里输入").style(
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with gr.Column(min_width=50, scale=1):
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submitBtn = gr.Button("🚀", variant="primary")
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with gr.Row():
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emptyBtn = gr.Button("🧹 新的对话")
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retryBtn = gr.Button("🔄 重新生成")
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delLastBtn = gr.Button("🗑️ 删除上条对话")
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reduceTokenBtn = gr.Button("♻️
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with gr.Accordion(label="保存/加载对话历史记录(
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with gr.Column():
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with gr.Row():
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with gr.Column(scale=6):
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saveFileName = gr.Textbox(
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with gr.Column(scale=1):
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saveBtn = gr.Button("💾 保存对话")
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import json
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import gradio as gr
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import os
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import sys
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import traceback
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import requests
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my_api_key = "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" # 在这里输入你的 API 密钥
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initial_prompt = "You are a helpful assistant."
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API_URL = "https://api.openai.com/v1/chat/completions"
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if my_api_key == "":
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my_api_key = os.environ.get('my_api_key')
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print("Please give a api key!")
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sys.exit(1)
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def parse_text(text):
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lines = text.split("\n")
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count = 0
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for i, line in enumerate(lines):
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if "```" in line:
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count += 1
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items = line.split('`')
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lines[i] = '<br/>'+line
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return "".join(lines)
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def predict(inputs, top_p, temperature, openai_api_key, chatbot=[], history=[], system_prompt=initial_prompt, retry=False, summary=False): # repetition_penalty, top_k
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {openai_api_key}"
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}
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chat_counter = len(history) // 2
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print(f"chat_counter - {chat_counter}")
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messages = [compose_system(system_prompt)]
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if chat_counter:
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for data in chatbot:
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temp1 = {}
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temp1["role"] = "user"
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temp1["content"] = data[0]
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temp2 = {}
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temp2["role"] = "assistant"
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temp2["content"] = data[1]
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if temp1["content"] != "":
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messages.append(temp1)
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messages.append(temp2)
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else:
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messages[-1]['content'] = temp2['content']
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if retry and chat_counter:
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messages.pop()
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elif summary and chat_counter:
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messages.append(compose_user(
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"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。"))
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history = ["我们刚刚聊了什么?"]
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else:
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temp3 = {}
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temp3["role"] = "user"
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temp3["content"] = inputs
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messages.append(temp3)
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chat_counter += 1
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# messages
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payload = {
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"model": "gpt-3.5-turbo",
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"messages": messages, # [{"role": "user", "content": f"{inputs}"}],
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"temperature": temperature, # 1.0,
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"top_p": top_p, # 1.0,
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"n": 1,
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"stream": True,
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"presence_penalty": 0,
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"frequency_penalty": 0,
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}
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if not summary:
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history.append(inputs)
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print(f"payload is - {payload}")
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# make a POST request to the API endpoint using the requests.post method, passing in stream=True
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response = requests.post(API_URL, headers=headers,
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json=payload, stream=True)
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#response = requests.post(API_URL, headers=headers, json=payload, stream=True)
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token_counter = 0
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partial_words = ""
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counter = 0
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chatbot.append((history[-1], ""))
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for chunk in response.iter_lines():
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if counter == 0:
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counter += 1
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continue
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counter += 1
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# check whether each line is non-empty
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if chunk:
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# decode each line as response data is in bytes
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if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
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break
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#print(json.loads(chunk.decode()[6:])['choices'][0]["delta"] ["content"])
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partial_words = partial_words + \
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json.loads(chunk.decode()[6:])[
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'choices'][0]["delta"]["content"]
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if token_counter == 0:
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history.append(" " + partial_words)
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else:
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history[-1] = partial_words
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chatbot[-1] = (history[-2], history[-1])
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# chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ] # convert to tuples of list
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token_counter += 1
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# resembles {chatbot: chat, state: history}
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yield chatbot, history
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def delete_last_conversation(chatbot, history):
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if chat_counter > 0:
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chat_counter -= 1
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chatbot.pop()
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history.pop()
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history.pop()
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return chatbot, history
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def save_chat_history(filepath, system, history, chatbot):
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if filepath == "":
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return
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if not filepath.endswith(".json"):
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filepath += ".json"
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json_s = {"system": system, "history": history, "chatbot": chatbot}
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with open(filepath, "w") as f:
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json.dump(json_s, f)
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def load_chat_history(filename):
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with open(filename, "r") as f:
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json_s = json.load(f)
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return filename, json_s["system"], json_s["history"], json_s["chatbot"]
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def get_history_names(plain=False):
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# find all json files in the current directory and return their names
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files = [f for f in os.listdir() if f.endswith(".json")]
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if plain:
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return files
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else:
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return gr.Dropdown.update(choices=files)
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def reset_state():
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return [], []
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def compose_system(system_prompt):
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return {"role": "system", "content": system_prompt}
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def compose_user(user_input):
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return {"role": "user", "content": user_input}
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def reset_textbox():
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return gr.update(value='')
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with gr.Blocks() as demo:
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keyTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入你的OpenAI API-key...",
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value=my_api_key, label="API Key", type="password").style(container=True)
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chatbot = gr.Chatbot() # .style(color_map=("#1D51EE", "#585A5B"))
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| 185 |
+
history = gr.State([])
|
| 186 |
+
TRUECOMSTANT = gr.State(True)
|
| 187 |
+
FALSECONSTANT = gr.State(False)
|
| 188 |
topic = gr.State("未命名对话历史记录")
|
| 189 |
|
| 190 |
with gr.Row():
|
| 191 |
with gr.Column(scale=12):
|
| 192 |
+
txt = gr.Textbox(show_label=False, placeholder="在这里输入").style(
|
| 193 |
+
container=False)
|
| 194 |
with gr.Column(min_width=50, scale=1):
|
| 195 |
submitBtn = gr.Button("🚀", variant="primary")
|
| 196 |
with gr.Row():
|
| 197 |
emptyBtn = gr.Button("🧹 新的对话")
|
| 198 |
retryBtn = gr.Button("🔄 重新生成")
|
| 199 |
delLastBtn = gr.Button("🗑️ 删除上条对话")
|
| 200 |
+
reduceTokenBtn = gr.Button("♻️ 总结对话")
|
| 201 |
+
systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入System Prompt...",
|
| 202 |
+
label="System prompt", value=initial_prompt).style(container=True)
|
| 203 |
+
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):
|
| 204 |
with gr.Column():
|
| 205 |
with gr.Row():
|
| 206 |
with gr.Column(scale=6):
|
| 207 |
+
saveFileName = gr.Textbox(
|
| 208 |
+
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)
|
| 209 |
with gr.Column(scale=1):
|
| 210 |
saveBtn = gr.Button("💾 保存对话")
|
| 211 |
+
with gr.Row():
|
| 212 |
+
with gr.Column(scale=6):
|
| 213 |
+
uploadDropdown = gr.Dropdown(label="从列表中加载对话", choices=get_history_names(plain=True), multiselect=False)
|
| 214 |
+
with gr.Column(scale=1):
|
| 215 |
+
refreshBtn = gr.Button("🔄 刷新")
|
| 216 |
+
uploadBtn = gr.Button("📂 读取对话")
|
| 217 |
+
#inputs, top_p, temperature, top_k, repetition_penalty
|
| 218 |
+
with gr.Accordion("参数", open=False):
|
| 219 |
+
top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.05,
|
| 220 |
+
interactive=True, label="Top-p (nucleus sampling)",)
|
| 221 |
+
temperature = gr.Slider(minimum=-0, maximum=5.0, value=1.0,
|
| 222 |
+
step=0.1, interactive=True, label="Temperature",)
|
| 223 |
+
#top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",)
|
| 224 |
+
#repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", )
|
| 225 |
+
|
| 226 |
+
txt.submit(predict, [txt, top_p, temperature, keyTxt,
|
| 227 |
+
chatbot, history, systemPromptTxt], [chatbot, history])
|
| 228 |
+
txt.submit(reset_textbox, [], [txt])
|
| 229 |
+
submitBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot,
|
| 230 |
+
history, systemPromptTxt], [chatbot, history], show_progress=True)
|
| 231 |
+
submitBtn.click(reset_textbox, [], [txt])
|
| 232 |
+
emptyBtn.click(reset_state, outputs=[chatbot, history])
|
| 233 |
+
retryBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot, history,
|
| 234 |
+
systemPromptTxt, TRUECOMSTANT], [chatbot, history], show_progress=True)
|
| 235 |
+
delLastBtn.click(delete_last_conversation, [chatbot, history], [
|
| 236 |
+
chatbot, history], show_progress=True)
|
| 237 |
+
reduceTokenBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot, history,
|
| 238 |
+
systemPromptTxt, FALSECONSTANT, TRUECOMSTANT], [chatbot, history], show_progress=True)
|
| 239 |
+
saveBtn.click(save_chat_history, [
|
| 240 |
+
saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)
|
| 241 |
+
saveBtn.click(get_history_names, None, [uploadDropdown])
|
| 242 |
+
refreshBtn.click(get_history_names, None, [uploadDropdown])
|
| 243 |
+
# uploadBtn.upload(load_chat_history, uploadBtn, [
|
| 244 |
+
# saveFileName, systemPromptTxt, history, chatbot], show_progress=True)
|
| 245 |
+
uploadBtn.click(load_chat_history, [uploadDropdown], [saveFileName, systemPromptTxt, history, chatbot], show_progress=True)
|
| 246 |
+
|
| 247 |
+
|
| 248 |
+
demo.queue().launch(debug=True)
|