镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 06:26:47 +00:00
将“生成多种图表”插件高级参数更新为二级菜单 (#1839)
* Improve the prompts * Update to new meun form * Bug fix (wrong type of plugin_kwargs)
这个提交包含在：
Menghuan1918
@@ -36,7 +36,7 @@ def get_crazy_functions():
|
||||
from crazy_functions.Latex全文润色 import Latex英文纠错
|
||||
from crazy_functions.Markdown_Translate import Markdown中译英
|
||||
from crazy_functions.虚空终端 import 虚空终端
|
||||
from crazy_functions.生成多种Mermaid图表 import 生成多种Mermaid图表
|
||||
from crazy_functions.生成多种Mermaid图表 import Mermaid_Gen
|
||||
from crazy_functions.PDF_Translate_Wrap import PDF_Tran
|
||||
from crazy_functions.Latex_Function import Latex英文纠错加PDF对比
|
||||
from crazy_functions.Latex_Function import Latex翻译中文并重新编译PDF
|
||||
@@ -84,9 +84,8 @@ def get_crazy_functions():
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"Info" : "基于当前对话或文件生成多种Mermaid图表,图表类型由模型判断",
|
||||
"Function": HotReload(生成多种Mermaid图表),
|
||||
"AdvancedArgs": True,
|
||||
"ArgsReminder": "请输入图类型对应的数字,不输入则为模型自行判断:1-流程图,2-序列图,3-类图,4-饼图,5-甘特图,6-状态图,7-实体关系图,8-象限提示图,9-思维导图",
|
||||
"Function": None,
|
||||
"Class": Mermaid_Gen
|
||||
},
|
||||
"批量总结Word文档": {
|
||||
"Group": "学术",
|
||||
|
||||
@@ -1,8 +1,11 @@
|
||||
from toolbox import CatchException, update_ui, report_exception
|
||||
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||
import datetime
|
||||
from crazy_functions.plugin_template.plugin_class_template import (
|
||||
GptAcademicPluginTemplate,
|
||||
)
|
||||
from crazy_functions.plugin_template.plugin_class_template import ArgProperty
|
||||
|
||||
#以下是每类图表的PROMPT
|
||||
# 以下是每类图表的PROMPT
|
||||
SELECT_PROMPT = """
|
||||
“{subject}”
|
||||
=============
|
||||
@@ -17,22 +20,24 @@ SELECT_PROMPT = """
|
||||
8 象限提示图
|
||||
不需要解释原因，仅需要输出单个不带任何标点符号的数字。
|
||||
"""
|
||||
#没有思维导图!!!测试发现模型始终会优先选择思维导图
|
||||
#流程图
|
||||
# 没有思维导图!!!测试发现模型始终会优先选择思维导图
|
||||
# 流程图
|
||||
PROMPT_1 = """
|
||||
请你给出围绕“{subject}”的逻辑关系图，使用mermaid语法，mermaid语法举例：
|
||||
请你给出围绕“{subject}”的逻辑关系图，使用mermaid语法，注意需要使用双引号将内容括起来。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
graph TD
|
||||
P(编程) --> L1(Python)
|
||||
P(编程) --> L2(C)
|
||||
P(编程) --> L3(C++)
|
||||
P(编程) --> L4(Javascipt)
|
||||
P(编程) --> L5(PHP)
|
||||
P("编程") --> L1("Python")
|
||||
P("编程") --> L2("C")
|
||||
P("编程") --> L3("C++")
|
||||
P("编程") --> L4("Javascipt")
|
||||
P("编程") --> L5("PHP")
|
||||
```
|
||||
"""
|
||||
#序列图
|
||||
# 序列图
|
||||
PROMPT_2 = """
|
||||
请你给出围绕“{subject}”的序列图，使用mermaid语法，mermaid语法举例：
|
||||
请你给出围绕“{subject}”的序列图，使用mermaid语法。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
sequenceDiagram
|
||||
participant A as 用户
|
||||
@@ -43,9 +48,10 @@ sequenceDiagram
|
||||
B->>A: 返回数据
|
||||
```
|
||||
"""
|
||||
#类图
|
||||
# 类图
|
||||
PROMPT_3 = """
|
||||
请你给出围绕“{subject}”的类图，使用mermaid语法，mermaid语法举例：
|
||||
请你给出围绕“{subject}”的类图，使用mermaid语法。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
classDiagram
|
||||
Class01 <|-- AveryLongClass : Cool
|
||||
@@ -63,9 +69,10 @@ classDiagram
|
||||
Class08 <--> C2: Cool label
|
||||
```
|
||||
"""
|
||||
#饼图
|
||||
# 饼图
|
||||
PROMPT_4 = """
|
||||
请你给出围绕“{subject}”的饼图，使用mermaid语法，mermaid语法举例：
|
||||
请你给出围绕“{subject}”的饼图，使用mermaid语法，注意需要使用双引号将内容括起来。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
pie title Pets adopted by volunteers
|
||||
"狗" : 386
|
||||
@@ -73,38 +80,41 @@ pie title Pets adopted by volunteers
|
||||
"兔子" : 15
|
||||
```
|
||||
"""
|
||||
#甘特图
|
||||
# 甘特图
|
||||
PROMPT_5 = """
|
||||
请你给出围绕“{subject}”的甘特图，使用mermaid语法，mermaid语法举例：
|
||||
请你给出围绕“{subject}”的甘特图，使用mermaid语法，注意需要使用双引号将内容括起来。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
gantt
|
||||
title 项目开发流程
|
||||
title "项目开发流程"
|
||||
dateFormat YYYY-MM-DD
|
||||
section 设计
|
||||
需求分析 :done, des1, 2024-01-06,2024-01-08
|
||||
原型设计 :active, des2, 2024-01-09, 3d
|
||||
UI设计 : des3, after des2, 5d
|
||||
section 开发
|
||||
前端开发 :2024-01-20, 10d
|
||||
后端开发 :2024-01-20, 10d
|
||||
section "设计"
|
||||
"需求分析" :done, des1, 2024-01-06,2024-01-08
|
||||
"原型设计" :active, des2, 2024-01-09, 3d
|
||||
"UI设计" : des3, after des2, 5d
|
||||
section "开发"
|
||||
"前端开发" :2024-01-20, 10d
|
||||
"后端开发" :2024-01-20, 10d
|
||||
```
|
||||
"""
|
||||
#状态图
|
||||
# 状态图
|
||||
PROMPT_6 = """
|
||||
请你给出围绕“{subject}”的状态图，使用mermaid语法，mermaid语法举例：
|
||||
请你给出围绕“{subject}”的状态图，使用mermaid语法，注意需要使用双引号将内容括起来。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
stateDiagram-v2
|
||||
[*] --> Still
|
||||
Still --> [*]
|
||||
Still --> Moving
|
||||
Moving --> Still
|
||||
Moving --> Crash
|
||||
Crash --> [*]
|
||||
[*] --> "Still"
|
||||
"Still" --> [*]
|
||||
"Still" --> "Moving"
|
||||
"Moving" --> "Still"
|
||||
"Moving" --> "Crash"
|
||||
"Crash" --> [*]
|
||||
```
|
||||
"""
|
||||
#实体关系图
|
||||
# 实体关系图
|
||||
PROMPT_7 = """
|
||||
请你给出围绕“{subject}”的实体关系图，使用mermaid语法，mermaid语法举例：
|
||||
请你给出围绕“{subject}”的实体关系图，使用mermaid语法。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
erDiagram
|
||||
CUSTOMER ||--o{ ORDER : places
|
||||
@@ -124,118 +134,173 @@ erDiagram
|
||||
}
|
||||
```
|
||||
"""
|
||||
#象限提示图
|
||||
# 象限提示图
|
||||
PROMPT_8 = """
|
||||
请你给出围绕“{subject}”的象限图，使用mermaid语法，mermaid语法举例：
|
||||
请你给出围绕“{subject}”的象限图，使用mermaid语法，注意需要使用双引号将内容括起来。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
graph LR
|
||||
A[Hard skill] --> B(Programming)
|
||||
A[Hard skill] --> C(Design)
|
||||
D[Soft skill] --> E(Coordination)
|
||||
D[Soft skill] --> F(Communication)
|
||||
A["Hard skill"] --> B("Programming")
|
||||
A["Hard skill"] --> C("Design")
|
||||
D["Soft skill"] --> E("Coordination")
|
||||
D["Soft skill"] --> F("Communication")
|
||||
```
|
||||
"""
|
||||
#思维导图
|
||||
# 思维导图
|
||||
PROMPT_9 = """
|
||||
{subject}
|
||||
==========
|
||||
请给出上方内容的思维导图，充分考虑其之间的逻辑，使用mermaid语法，mermaid语法举例：
|
||||
请给出上方内容的思维导图，充分考虑其之间的逻辑，使用mermaid语法，注意需要使用双引号将内容括起来。
|
||||
mermaid语法举例：
|
||||
```mermaid
|
||||
mindmap
|
||||
root((mindmap))
|
||||
Origins
|
||||
Long history
|
||||
("Origins")
|
||||
("Long history")
|
||||
::icon(fa fa-book)
|
||||
Popularisation
|
||||
British popular psychology author Tony Buzan
|
||||
Research
|
||||
On effectiveness<br/>and features
|
||||
On Automatic creation
|
||||
Uses
|
||||
Creative techniques
|
||||
Strategic planning
|
||||
Argument mapping
|
||||
Tools
|
||||
Pen and paper
|
||||
Mermaid
|
||||
("Popularisation")
|
||||
("British popular psychology author Tony Buzan")
|
||||
::icon(fa fa-user)
|
||||
("Research")
|
||||
("On effectiveness<br/>and features")
|
||||
::icon(fa fa-search)
|
||||
("On Automatic creation")
|
||||
::icon(fa fa-robot)
|
||||
("Uses")
|
||||
("Creative techniques")
|
||||
::icon(fa fa-lightbulb-o)
|
||||
("Strategic planning")
|
||||
::icon(fa fa-flag)
|
||||
("Argument mapping")
|
||||
::icon(fa fa-comments)
|
||||
("Tools")
|
||||
("Pen and paper")
|
||||
::icon(fa fa-pencil)
|
||||
("Mermaid")
|
||||
::icon(fa fa-code)
|
||||
```
|
||||
"""
|
||||
|
||||
def 解析历史输入(history,llm_kwargs,file_manifest,chatbot,plugin_kwargs):
|
||||
|
||||
def 解析历史输入(history, llm_kwargs, file_manifest, chatbot, plugin_kwargs):
|
||||
############################## <第 0 步，切割输入> ##################################
|
||||
# 借用PDF切割中的函数对文本进行切割
|
||||
TOKEN_LIMIT_PER_FRAGMENT = 2500
|
||||
txt = str(history).encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
|
||||
from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
|
||||
txt = breakdown_text_to_satisfy_token_limit(txt=txt, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model'])
|
||||
txt = (
|
||||
str(history).encode("utf-8", "ignore").decode()
|
||||
) # avoid reading non-utf8 chars
|
||||
from crazy_functions.pdf_fns.breakdown_txt import (
|
||||
breakdown_text_to_satisfy_token_limit,
|
||||
)
|
||||
|
||||
txt = breakdown_text_to_satisfy_token_limit(
|
||||
txt=txt, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs["llm_model"]
|
||||
)
|
||||
############################## <第 1 步，迭代地历遍整个文章，提取精炼信息> ##################################
|
||||
results = []
|
||||
MAX_WORD_TOTAL = 4096
|
||||
n_txt = len(txt)
|
||||
last_iteration_result = "从以下文本中提取摘要。"
|
||||
if n_txt >= 20: print('文章极长，不能达到预期效果')
|
||||
if n_txt >= 20:
|
||||
print("文章极长，不能达到预期效果")
|
||||
for i in range(n_txt):
|
||||
NUM_OF_WORD = MAX_WORD_TOTAL // n_txt
|
||||
i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words in Chinese: {txt[i]}"
|
||||
i_say_show_user = f"[{i+1}/{n_txt}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {txt[i][:200]} ...."
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user, # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
|
||||
llm_kwargs, chatbot,
|
||||
history=["The main content of the previous section is?", last_iteration_result], # 迭代上一次的结果
|
||||
sys_prompt="Extracts the main content from the text section where it is located for graphing purposes, answer me with Chinese." # 提示
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
i_say,
|
||||
i_say_show_user, # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
|
||||
llm_kwargs,
|
||||
chatbot,
|
||||
history=[
|
||||
"The main content of the previous section is?",
|
||||
last_iteration_result,
|
||||
], # 迭代上一次的结果
|
||||
sys_prompt="Extracts the main content from the text section where it is located for graphing purposes, answer me with Chinese.", # 提示
|
||||
)
|
||||
results.append(gpt_say)
|
||||
last_iteration_result = gpt_say
|
||||
############################## <第 2 步，根据整理的摘要选择图表类型> ##################################
|
||||
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
|
||||
gpt_say = plugin_kwargs.get("advanced_arg", "") #将图表类型参数赋值为插件参数
|
||||
results_txt = '\n'.join(results) #合并摘要
|
||||
if gpt_say not in ['1','2','3','4','5','6','7','8','9']: #如插件参数不正确则使用对话模型判断
|
||||
i_say_show_user = f'接下来将判断适合的图表类型,如连续3次判断失败将会使用流程图进行绘制'; gpt_say = "[Local Message] 收到。" # 用户提示
|
||||
chatbot.append([i_say_show_user, gpt_say]); yield from update_ui(chatbot=chatbot, history=[]) # 更新UI
|
||||
gpt_say = str(plugin_kwargs) # 将图表类型参数赋值为插件参数
|
||||
results_txt = "\n".join(results) # 合并摘要
|
||||
if gpt_say not in [
|
||||
"1",
|
||||
"2",
|
||||
"3",
|
||||
"4",
|
||||
"5",
|
||||
"6",
|
||||
"7",
|
||||
"8",
|
||||
"9",
|
||||
]: # 如插件参数不正确则使用对话模型判断
|
||||
i_say_show_user = (
|
||||
f"接下来将判断适合的图表类型,如连续3次判断失败将会使用流程图进行绘制"
|
||||
)
|
||||
gpt_say = "[Local Message] 收到。" # 用户提示
|
||||
chatbot.append([i_say_show_user, gpt_say])
|
||||
yield from update_ui(chatbot=chatbot, history=[]) # 更新UI
|
||||
i_say = SELECT_PROMPT.format(subject=results_txt)
|
||||
i_say_show_user = f'请判断适合使用的流程图类型,其中数字对应关系为:1-流程图,2-序列图,3-类图,4-饼图,5-甘特图,6-状态图,7-实体关系图,8-象限提示图。由于不管提供文本是什么,模型大概率认为"思维导图"最合适,因此思维导图仅能通过参数调用。'
|
||||
for i in range(3):
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say,
|
||||
inputs_show_user=i_say_show_user,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
|
||||
sys_prompt=""
|
||||
llm_kwargs=llm_kwargs,
|
||||
chatbot=chatbot,
|
||||
history=[],
|
||||
sys_prompt="",
|
||||
)
|
||||
if gpt_say in ['1','2','3','4','5','6','7','8','9']: #判断返回是否正确
|
||||
if gpt_say in [
|
||||
"1",
|
||||
"2",
|
||||
"3",
|
||||
"4",
|
||||
"5",
|
||||
"6",
|
||||
"7",
|
||||
"8",
|
||||
"9",
|
||||
]: # 判断返回是否正确
|
||||
break
|
||||
if gpt_say not in ['1','2','3','4','5','6','7','8','9']:
|
||||
gpt_say = '1'
|
||||
if gpt_say not in ["1", "2", "3", "4", "5", "6", "7", "8", "9"]:
|
||||
gpt_say = "1"
|
||||
############################## <第 3 步，根据选择的图表类型绘制图表> ##################################
|
||||
if gpt_say == '1':
|
||||
if gpt_say == "1":
|
||||
i_say = PROMPT_1.format(subject=results_txt)
|
||||
elif gpt_say == '2':
|
||||
elif gpt_say == "2":
|
||||
i_say = PROMPT_2.format(subject=results_txt)
|
||||
elif gpt_say == '3':
|
||||
elif gpt_say == "3":
|
||||
i_say = PROMPT_3.format(subject=results_txt)
|
||||
elif gpt_say == '4':
|
||||
elif gpt_say == "4":
|
||||
i_say = PROMPT_4.format(subject=results_txt)
|
||||
elif gpt_say == '5':
|
||||
elif gpt_say == "5":
|
||||
i_say = PROMPT_5.format(subject=results_txt)
|
||||
elif gpt_say == '6':
|
||||
elif gpt_say == "6":
|
||||
i_say = PROMPT_6.format(subject=results_txt)
|
||||
elif gpt_say == '7':
|
||||
i_say = PROMPT_7.replace("{subject}", results_txt) #由于实体关系图用到了{}符号
|
||||
elif gpt_say == '8':
|
||||
elif gpt_say == "7":
|
||||
i_say = PROMPT_7.replace("{subject}", results_txt) # 由于实体关系图用到了{}符号
|
||||
elif gpt_say == "8":
|
||||
i_say = PROMPT_8.format(subject=results_txt)
|
||||
elif gpt_say == '9':
|
||||
elif gpt_say == "9":
|
||||
i_say = PROMPT_9.format(subject=results_txt)
|
||||
i_say_show_user = f'请根据判断结果绘制相应的图表。如需绘制思维导图请使用参数调用,同时过大的图表可能需要复制到在线编辑器中进行渲染。'
|
||||
i_say_show_user = f"请根据判断结果绘制相应的图表。如需绘制思维导图请使用参数调用,同时过大的图表可能需要复制到在线编辑器中进行渲染。"
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say,
|
||||
inputs_show_user=i_say_show_user,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
|
||||
sys_prompt=""
|
||||
llm_kwargs=llm_kwargs,
|
||||
chatbot=chatbot,
|
||||
history=[],
|
||||
sys_prompt="",
|
||||
)
|
||||
history.append(gpt_say)
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
|
||||
|
||||
@CatchException
|
||||
def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
def 生成多种Mermaid图表(
|
||||
txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port
|
||||
):
|
||||
"""
|
||||
txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
|
||||
llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行
|
||||
@@ -248,15 +313,21 @@ def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history,
|
||||
import os
|
||||
|
||||
# 基本信息：功能、贡献者
|
||||
chatbot.append([
|
||||
chatbot.append(
|
||||
[
|
||||
"函数插件功能？",
|
||||
"根据当前聊天历史或指定的路径文件(文件内容优先)绘制多种mermaid图表，将会由对话模型首先判断适合的图表类型，随后绘制图表。\
|
||||
\n您也可以使用插件参数指定绘制的图表类型,函数插件贡献者: Menghuan1918"])
|
||||
\n您也可以使用插件参数指定绘制的图表类型,函数插件贡献者: Menghuan1918",
|
||||
]
|
||||
)
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
if os.path.exists(txt): #如输入区无内容则直接解析历史记录
|
||||
if os.path.exists(txt): # 如输入区无内容则直接解析历史记录
|
||||
from crazy_functions.pdf_fns.parse_word import extract_text_from_files
|
||||
file_exist, final_result, page_one, file_manifest, excption = extract_text_from_files(txt, chatbot, history)
|
||||
|
||||
file_exist, final_result, page_one, file_manifest, excption = (
|
||||
extract_text_from_files(txt, chatbot, history)
|
||||
)
|
||||
else:
|
||||
file_exist = False
|
||||
excption = ""
|
||||
@@ -264,33 +335,104 @@ def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history,
|
||||
|
||||
if excption != "":
|
||||
if excption == "word":
|
||||
report_exception(chatbot, history,
|
||||
a = f"解析项目: {txt}",
|
||||
b = f"找到了.doc文件，但是该文件格式不被支持，请先转化为.docx格式。")
|
||||
report_exception(
|
||||
chatbot,
|
||||
history,
|
||||
a=f"解析项目: {txt}",
|
||||
b=f"找到了.doc文件，但是该文件格式不被支持，请先转化为.docx格式。",
|
||||
)
|
||||
|
||||
elif excption == "pdf":
|
||||
report_exception(chatbot, history,
|
||||
a = f"解析项目: {txt}",
|
||||
b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pymupdf```。")
|
||||
report_exception(
|
||||
chatbot,
|
||||
history,
|
||||
a=f"解析项目: {txt}",
|
||||
b=f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pymupdf```。",
|
||||
)
|
||||
|
||||
elif excption == "word_pip":
|
||||
report_exception(chatbot, history,
|
||||
report_exception(
|
||||
chatbot,
|
||||
history,
|
||||
a=f"解析项目: {txt}",
|
||||
b=f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade python-docx pywin32```。")
|
||||
b=f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade python-docx pywin32```。",
|
||||
)
|
||||
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
else:
|
||||
if not file_exist:
|
||||
history.append(txt) #如输入区不是文件则将输入区内容加入历史记录
|
||||
i_say_show_user = f'首先你从历史记录中提取摘要。'; gpt_say = "[Local Message] 收到。" # 用户提示
|
||||
chatbot.append([i_say_show_user, gpt_say]); yield from update_ui(chatbot=chatbot, history=history) # 更新UI
|
||||
yield from 解析历史输入(history,llm_kwargs,file_manifest,chatbot,plugin_kwargs)
|
||||
history.append(txt) # 如输入区不是文件则将输入区内容加入历史记录
|
||||
i_say_show_user = f"首先你从历史记录中提取摘要。"
|
||||
gpt_say = "[Local Message] 收到。" # 用户提示
|
||||
chatbot.append([i_say_show_user, gpt_say])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 更新UI
|
||||
yield from 解析历史输入(
|
||||
history, llm_kwargs, file_manifest, chatbot, plugin_kwargs
|
||||
)
|
||||
else:
|
||||
file_num = len(file_manifest)
|
||||
for i in range(file_num): #依次处理文件
|
||||
i_say_show_user = f"[{i+1}/{file_num}]处理文件{file_manifest[i]}"; gpt_say = "[Local Message] 收到。" # 用户提示
|
||||
chatbot.append([i_say_show_user, gpt_say]); yield from update_ui(chatbot=chatbot, history=history) # 更新UI
|
||||
history = [] #如输入区内容为文件则清空历史记录
|
||||
for i in range(file_num): # 依次处理文件
|
||||
i_say_show_user = f"[{i+1}/{file_num}]处理文件{file_manifest[i]}"
|
||||
gpt_say = "[Local Message] 收到。" # 用户提示
|
||||
chatbot.append([i_say_show_user, gpt_say])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 更新UI
|
||||
history = [] # 如输入区内容为文件则清空历史记录
|
||||
history.append(final_result[i])
|
||||
yield from 解析历史输入(history,llm_kwargs,file_manifest,chatbot,plugin_kwargs)
|
||||
yield from 解析历史输入(
|
||||
history, llm_kwargs, file_manifest, chatbot, plugin_kwargs
|
||||
)
|
||||
|
||||
|
||||
class Mermaid_Gen(GptAcademicPluginTemplate):
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def define_arg_selection_menu(self):
|
||||
gui_definition = {
|
||||
"Type_of_Mermaid": ArgProperty(
|
||||
title="绘制的Mermaid图表类型",
|
||||
options=[
|
||||
"由LLM决定",
|
||||
"流程图",
|
||||
"序列图",
|
||||
"类图",
|
||||
"饼图",
|
||||
"甘特图",
|
||||
"状态图",
|
||||
"实体关系图",
|
||||
"象限提示图",
|
||||
"思维导图",
|
||||
],
|
||||
default_value="由LLM决定",
|
||||
description="选择'由LLM决定'时将由对话模型判断适合的图表类型(不包括思维导图)，选择其他类型时将直接绘制指定的图表类型。",
|
||||
type="dropdown",
|
||||
).model_dump_json(),
|
||||
}
|
||||
return gui_definition
|
||||
|
||||
def execute(
|
||||
txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request
|
||||
):
|
||||
options = [
|
||||
"由LLM决定",
|
||||
"流程图",
|
||||
"序列图",
|
||||
"类图",
|
||||
"饼图",
|
||||
"甘特图",
|
||||
"状态图",
|
||||
"实体关系图",
|
||||
"象限提示图",
|
||||
"思维导图",
|
||||
]
|
||||
plugin_kwargs = options.index(plugin_kwargs['Type_of_Mermaid'])
|
||||
yield from 生成多种Mermaid图表(
|
||||
txt,
|
||||
llm_kwargs,
|
||||
plugin_kwargs,
|
||||
chatbot,
|
||||
history,
|
||||
system_prompt,
|
||||
user_request,
|
||||
)
|
||||
|
||||
在新工单中引用
屏蔽一个用户