Spaces:
Sleeping
Sleeping
Tuchuanhuhuhu
commited on
Commit
·
4333f18
1
Parent(s):
022b9a0
大幅度改进代码质量
Browse files- ChuanhuChatbot.py +31 -21
- presets.py +10 -0
- utils.py +125 -111
ChuanhuChatbot.py
CHANGED
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@@ -8,9 +8,6 @@ from presets import *
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my_api_key = "" # 在这里输入你的 API 密钥
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HIDE_MY_KEY = False # 如果你想在UI中隐藏你的 API 密钥,将此值设置为 True
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-
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gr.Chatbot.postprocess = postprocess
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#if we are running in Docker
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if os.environ.get('dockerrun') == 'yes':
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@@ -42,12 +39,17 @@ else:
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if username != "" and password != "":
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authflag = True
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with gr.Blocks(css=customCSS) as demo:
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gr.HTML(title)
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-
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-
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chatbot = gr.Chatbot() # .style(color_map=("#1D51EE", "#585A5B"))
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history = gr.State([])
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promptTemplates = gr.State(load_template(get_template_names(plain=True)[0], mode=2))
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TRUECOMSTANT = gr.State(True)
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FALSECONSTANT = gr.State(False)
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@@ -55,16 +57,16 @@ with gr.Blocks(css=customCSS) as demo:
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with gr.Row():
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with gr.Column(scale=12):
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-
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container=False)
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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("🗑️
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reduceTokenBtn = gr.Button("♻️ 总结对话")
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-
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systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入System Prompt...",
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label="System prompt", value=initial_prompt).style(container=True)
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with gr.Accordion(label="加载Prompt模板", open=False):
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@@ -105,26 +107,34 @@ with gr.Blocks(css=customCSS) as demo:
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gr.Markdown(description)
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submitBtn.click(predict, [
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-
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emptyBtn.click(reset_state, outputs=[chatbot, history])
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saveHistoryBtn.click(save_chat_history, [
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saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)
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saveHistoryBtn.click(get_history_names, None, [historyFileSelectDropdown])
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historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
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historyReadBtn.click(load_chat_history, [historyFileSelectDropdown, systemPromptTxt, history, chatbot], [saveFileName, systemPromptTxt, history, chatbot], show_progress=True)
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templateRefreshBtn.click(get_template_names, None, [templateFileSelectDropdown])
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templaeFileReadBtn.click(load_template, [templateFileSelectDropdown], [promptTemplates, templateSelectDropdown], show_progress=True)
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templateApplyBtn.click(get_template_content, [promptTemplates, templateSelectDropdown, systemPromptTxt], [systemPromptTxt], show_progress=True)
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print("川虎的温馨提示:访问 http://localhost:7860 查看界面")
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my_api_key = "" # 在这里输入你的 API 密钥
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#if we are running in Docker
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if os.environ.get('dockerrun') == 'yes':
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if username != "" and password != "":
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authflag = True
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+
gr.Chatbot.postprocess = postprocess
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+
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with gr.Blocks(css=customCSS) as demo:
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gr.HTML(title)
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with gr.Row():
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keyTxt = gr.Textbox(show_label=False, placeholder=f"在这里输入你的OpenAI API-key...",
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value=my_api_key, type="password", visible=not HIDE_MY_KEY).style(container=True)
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use_streaming_checkbox = gr.Checkbox(label="实时传输回答", value=True, visible=enable_streaming_option)
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chatbot = gr.Chatbot() # .style(color_map=("#1D51EE", "#585A5B"))
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history = gr.State([])
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token_count = gr.State([])
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promptTemplates = gr.State(load_template(get_template_names(plain=True)[0], mode=2))
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TRUECOMSTANT = gr.State(True)
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FALSECONSTANT = gr.State(False)
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with gr.Row():
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with gr.Column(scale=12):
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user_input = gr.Textbox(show_label=False, placeholder="在这里输入").style(
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container=False)
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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("🗑️ 删除最近一条对话")
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reduceTokenBtn = gr.Button("♻️ 总结对话")
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status_display = gr.Markdown("status: ready")
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systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入System Prompt...",
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label="System prompt", value=initial_prompt).style(container=True)
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with gr.Accordion(label="加载Prompt模板", open=False):
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gr.Markdown(description)
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user_input.submit(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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user_input.submit(reset_textbox, [], [user_input])
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submitBtn.click(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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submitBtn.click(reset_textbox, [], [user_input])
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emptyBtn.click(reset_state, outputs=[chatbot, history, token_count, status_display], show_progress=True)
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retryBtn.click(retry, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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delLastBtn.click(delete_last_conversation, [chatbot, history, token_count, use_streaming_checkbox], [
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chatbot, history, token_count, status_display], show_progress=True)
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reduceTokenBtn.click(reduce_token_size, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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saveHistoryBtn.click(save_chat_history, [
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saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)
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saveHistoryBtn.click(get_history_names, None, [historyFileSelectDropdown])
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historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
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historyReadBtn.click(load_chat_history, [historyFileSelectDropdown, systemPromptTxt, history, chatbot], [saveFileName, systemPromptTxt, history, chatbot], show_progress=True)
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templateRefreshBtn.click(get_template_names, None, [templateFileSelectDropdown])
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templaeFileReadBtn.click(load_template, [templateFileSelectDropdown], [promptTemplates, templateSelectDropdown], show_progress=True)
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templateApplyBtn.click(get_template_content, [promptTemplates, templateSelectDropdown, systemPromptTxt], [systemPromptTxt], show_progress=True)
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print("川虎的温馨提示:访问 http://localhost:7860 查看界面")
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presets.py
CHANGED
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@@ -29,3 +29,13 @@ pre code {
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box-shadow: inset 0px 8px 16px hsla(0, 0%, 0%, .2)
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}
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"""
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box-shadow: inset 0px 8px 16px hsla(0, 0%, 0%, .2)
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}
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"""
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standard_error_msg = "☹️发生了错误:" # 错误信息的标准前缀
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error_retrieve_prompt = "连接超时,无法获取对话。请检查网络连接,或者API-Key是否有效。" # 获取对话时发生错误
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summarize_prompt = "请总结以上对话,不超过100字。" # 总结对话时的 prompt
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max_token_streaming = 3000 # 流式对话时的最大 token 数
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timeout_streaming = 5 # 流式对话时的超时时间
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max_token_all = 3500 # 非流式对话时的最大 token 数
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timeout_all = 200 # 非流式对话时的超时时间
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enable_streaming_option = False # 是否启用选择选择是否实时显示回答的勾选框
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HIDE_MY_KEY = False # 如果你想在UI中隐藏你的 API 密钥,将此值设置为 True
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utils.py
CHANGED
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@@ -14,6 +14,7 @@ import requests
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import csv
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import mdtex2html
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from pypinyin import lazy_pinyin
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if TYPE_CHECKING:
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from typing import TypedDict
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lines = text.split("\n")
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lines = [line for line in lines if line != ""]
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count = 0
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firstline = False
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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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text = "".join(lines)
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return text
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def
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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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print(f"chat_counter - {chat_counter}")
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messages = []
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if chat_counter:
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for index in range(0, 2*chat_counter, 2):
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temp1 = {}
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temp1["role"] = "user"
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temp1["content"] = history[index]
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temp2 = {}
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temp2["role"] = "assistant"
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temp2["content"] = history[index+1]
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if temp1["content"] != "":
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if temp2["content"] != "" or retry:
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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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if retry_on_crash:
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messages = messages[-6:]
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messages.pop()
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elif summary:
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history = [*[i["content"] for i in messages[-2:]], "我们刚刚聊了什么?"]
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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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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 = [compose_system(system_prompt), *messages]
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# messages
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payload = {
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"model": "gpt-3.5-turbo",
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"messages":
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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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"presence_penalty": 0,
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"frequency_penalty": 0,
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}
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history.append(inputs)
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else:
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try:
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response =
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except:
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yield history, chatbot, f"获取请求失败,请检查网络连接。"
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return
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chatbot.append((parse_text(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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history.append("")
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yield next(predict(inputs, top_p, temperature, openai_api_key, chatbot, history, system_prompt, retry, summary=False, retry_on_crash=True, stream=False))
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else:
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msg = "☹️发生了错误:生成失败,请检查网络"
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print(msg)
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history.append(inputs, "")
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chatbot.append(inputs, msg)
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yield chatbot, history, "status: ERROR"
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break
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status_text = f"id: {chunkjson['id']}, finish_reason: {chunkjson['choices'][0]['finish_reason']}"
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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] = (parse_text(
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token_counter += 1
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yield
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else:
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try:
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responsejson = json.loads(response.text)
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content = responsejson["choices"][0]["message"]["content"]
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history.append(content)
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chatbot.append((parse_text(history[-2]), parse_text(content)))
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status_text = "精简完成"
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except:
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chatbot.append((parse_text(history[-1]), "☹️发生了错误,请检查网络连接或者稍后再试。"))
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status_text = "status: ERROR"
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yield chatbot, history, status_text
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try:
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chatbot.pop()
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history.pop()
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history.pop()
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chatbot.pop()
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def save_chat_history(filename, system, history, chatbot):
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if filename == "":
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return original_system_prompt
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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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import csv
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import mdtex2html
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from pypinyin import lazy_pinyin
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from presets import *
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if TYPE_CHECKING:
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from typing import TypedDict
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lines = text.split("\n")
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lines = [line for line in lines if line != ""]
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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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text = "".join(lines)
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return text
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def construct_text(role, text):
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return {"role": role, "content": text}
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def construct_user(text):
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return construct_text("user", text)
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def construct_system(text):
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return construct_text("system", text)
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def construct_assistant(text):
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return construct_text("assistant", text)
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def construct_token_message(token, stream=False):
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extra = "【仅包含回答的计数】 " if stream else ""
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return f"{extra}Token 计数: {token}"
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def get_response(openai_api_key, system_prompt, history, temperature, top_p, stream):
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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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history = [construct_system(system_prompt), *history]
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| 106 |
payload = {
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"model": "gpt-3.5-turbo",
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"messages": history, # [{"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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"presence_penalty": 0,
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"frequency_penalty": 0,
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}
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if stream:
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timeout = timeout_streaming
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else:
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| 119 |
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timeout = timeout_all
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| 120 |
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response = requests.post(API_URL, headers=headers, json=payload, stream=True, timeout=timeout)
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| 121 |
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return response
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| 123 |
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def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, previous_token_count, top_p, temperature):
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| 124 |
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def get_return_value():
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| 125 |
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return chatbot, history, status_text, [*previous_token_count, token_counter]
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| 126 |
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token_counter = 0
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| 127 |
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partial_words = ""
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| 128 |
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counter = 0
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| 129 |
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status_text = "OK"
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| 130 |
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history.append(construct_user(inputs))
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| 131 |
try:
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| 132 |
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response = get_response(openai_api_key, system_prompt, history, temperature, top_p, True)
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| 133 |
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except requests.exceptions.ConnectTimeout:
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| 134 |
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status_text = standard_error_msg + error_retrieve_prompt
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| 135 |
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yield get_return_value()
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| 136 |
return
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| 138 |
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chatbot.append((parse_text(inputs), ""))
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| 139 |
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yield get_return_value()
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| 140 |
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| 141 |
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for chunk in response.iter_lines():
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| 142 |
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if counter == 0:
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| 143 |
counter += 1
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| 144 |
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continue
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| 145 |
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counter += 1
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| 146 |
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# check whether each line is non-empty
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| 147 |
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if chunk:
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| 148 |
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chunk = chunk.decode()
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| 149 |
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chunklength = len(chunk)
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| 150 |
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chunk = json.loads(chunk[6:])
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| 151 |
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# decode each line as response data is in bytes
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| 152 |
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if chunklength > 6 and "delta" in chunk['choices'][0]:
|
| 153 |
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finish_reason = chunk['choices'][0]['finish_reason']
|
| 154 |
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status_text = construct_token_message(sum(previous_token_count)+token_counter, stream=True)
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| 155 |
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if finish_reason == "stop":
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| 156 |
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yield get_return_value()
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| 157 |
break
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| 158 |
+
partial_words = partial_words + chunk['choices'][0]["delta"]["content"]
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| 159 |
if token_counter == 0:
|
| 160 |
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history.append(construct_assistant(" " + partial_words))
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| 161 |
else:
|
| 162 |
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history[-1] = construct_assistant(partial_words)
|
| 163 |
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chatbot[-1] = (parse_text(inputs), parse_text(partial_words))
|
| 164 |
token_counter += 1
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| 165 |
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yield get_return_value()
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| 166 |
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| 167 |
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| 168 |
+
def predict_all(openai_api_key, system_prompt, history, inputs, chatbot, previous_token_count, top_p, temperature):
|
| 169 |
+
history.append(construct_user(inputs))
|
| 170 |
try:
|
| 171 |
+
response = get_response(openai_api_key, system_prompt, history, temperature, top_p, False)
|
| 172 |
+
except requests.exceptions.ConnectTimeout:
|
| 173 |
+
status_text = standard_error_msg + error_retrieve_prompt
|
| 174 |
+
return chatbot, history, status_text, previous_token_count
|
| 175 |
+
response = json.loads(response.text)
|
| 176 |
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content = response["choices"][0]["message"]["content"]
|
| 177 |
+
history.append(construct_assistant(content))
|
| 178 |
+
chatbot.append((parse_text(inputs), parse_text(content)))
|
| 179 |
+
total_token_count = response["usage"]["total_tokens"]
|
| 180 |
+
previous_token_count.append(total_token_count - sum(previous_token_count))
|
| 181 |
+
status_text = construct_token_message(total_token_count)
|
| 182 |
+
return chatbot, history, status_text, previous_token_count
|
| 183 |
+
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| 184 |
+
|
| 185 |
+
def predict(openai_api_key, system_prompt, history, inputs, chatbot, token_count, top_p, temperature, stream=False, should_check_token_count = True): # repetition_penalty, top_k
|
| 186 |
+
if stream:
|
| 187 |
+
iter = stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, token_count, top_p, temperature)
|
| 188 |
+
for chatbot, history, status_text, token_count in iter:
|
| 189 |
+
yield chatbot, history, status_text, token_count
|
| 190 |
+
else:
|
| 191 |
+
chatbot, history, status_text, token_count = predict_all(openai_api_key, system_prompt, history, inputs, chatbot, token_count, top_p, temperature)
|
| 192 |
+
yield chatbot, history, status_text, token_count
|
| 193 |
+
if stream:
|
| 194 |
+
max_token = max_token_streaming
|
| 195 |
+
else:
|
| 196 |
+
max_token = max_token_all
|
| 197 |
+
if sum(token_count) > max_token and should_check_token_count:
|
| 198 |
+
iter = reduce_token_size(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, hidden=True)
|
| 199 |
+
for chatbot, history, status_text, token_count in iter:
|
| 200 |
+
status_text = f"Token 达到上限,已自动降低Token计数至 {status_text}"
|
| 201 |
+
yield chatbot, history, status_text, token_count
|
| 202 |
+
|
| 203 |
+
|
| 204 |
+
def retry(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False):
|
| 205 |
+
if len(history) == 0:
|
| 206 |
+
yield chatbot, history, f"{standard_error_msg}上下文是空的", token_count
|
| 207 |
+
return
|
| 208 |
+
history.pop()
|
| 209 |
+
inputs = history.pop()["content"]
|
| 210 |
+
token_count.pop()
|
| 211 |
+
iter = predict(openai_api_key, system_prompt, history, inputs, chatbot, token_count, top_p, temperature, stream=stream)
|
| 212 |
+
for x in iter:
|
| 213 |
+
yield x
|
| 214 |
+
|
| 215 |
+
|
| 216 |
+
def reduce_token_size(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, hidden=False):
|
| 217 |
+
iter = predict(openai_api_key, system_prompt, history, summarize_prompt, chatbot, token_count, top_p, temperature, stream=stream, should_check_token_count=False)
|
| 218 |
+
for chatbot, history, status_text, previous_token_count in iter:
|
| 219 |
+
history = history[-2:]
|
| 220 |
+
token_count = previous_token_count[-1:]
|
| 221 |
+
if hidden:
|
| 222 |
chatbot.pop()
|
| 223 |
+
yield chatbot, history, construct_token_message(sum(token_count), stream=stream), token_count
|
| 224 |
+
|
| 225 |
+
|
| 226 |
+
def delete_last_conversation(chatbot, history, previous_token_count, streaming):
|
| 227 |
+
if len(chatbot) > 0 and standard_error_msg in chatbot[-1][1]:
|
| 228 |
+
chatbot.pop()
|
| 229 |
+
return chatbot, history
|
| 230 |
+
if len(history) > 0:
|
| 231 |
history.pop()
|
| 232 |
history.pop()
|
| 233 |
+
if len(chatbot) > 0:
|
| 234 |
chatbot.pop()
|
| 235 |
+
if len(previous_token_count) > 0:
|
| 236 |
+
previous_token_count.pop()
|
| 237 |
+
return chatbot, history, previous_token_count, construct_token_message(sum(previous_token_count), streaming)
|
| 238 |
+
|
| 239 |
|
| 240 |
def save_chat_history(filename, system, history, chatbot):
|
| 241 |
if filename == "":
|
|
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|
| 312 |
return original_system_prompt
|
| 313 |
|
| 314 |
def reset_state():
|
| 315 |
+
return [], [], [], construct_token_message(0)
|
| 316 |
|
| 317 |
def compose_system(system_prompt):
|
| 318 |
return {"role": "system", "content": system_prompt}
|