app:
description: 随机根据知识点出题
icon: 🤖
icon_background: '#FFEAD5'
icon_type: emoji
mode: advanced-chat
name: 大模型面试题出题小助手
use_icon_as_answer_icon: false
dependencies:
- current_identifier: null
type: marketplace
value:
marketplace_plugin_unique_identifier: langgenius/tongyi:0.2.1@0924de1d15a8a35b0cc64ff396c68d5edddcfbc495a1e52ea57e8648434eff4b
version: null
- current_identifier: null
type: marketplace
value:
marketplace_plugin_unique_identifier: langgenius/mimo:0.0.8@18947da24866d0e1e84558ae7dcc96d491f8d9f96c982f1704945e24a65c0362
version: null
kind: app
version: 0.6.0
workflow:
conversation_variables:
- description: 会话轮数
id: afb2b370-6e77-4e12-a1fc-c02d70fa33ae
name: conversation_num
selector:
- conversation
- conversation_num
value: 1
value_type: integer
- description: 面试题的答案
id: 8c2fa1a6-5ae6-4338-a5f1-f0fb898127ca
name: answer
selector:
- conversation
- answer
value: ''
value_type: string
- description: 面试题
id: b6826fd7-2d3a-4fab-bb62-9f1fe2dc9b65
name: question
selector:
- conversation
- question
value: ''
value_type: string
- description: ''
id: 9800d4f3-75c1-488d-9d73-7ec58cad9914
name: content
selector:
- conversation
- content
value:
answer: null
question: null
value_type: object
environment_variables: []
features:
file_upload:
allowed_file_extensions:
- .JPG
- .JPEG
- .PNG
- .GIF
- .WEBP
- .SVG
allowed_file_types:
- image
allowed_file_upload_methods:
- local_file
- remote_url
enabled: false
fileUploadConfig:
attachment_image_file_size_limit: 2
audio_file_size_limit: 50
batch_count_limit: 5
file_size_limit: 15
file_upload_limit: 20
image_file_batch_limit: 10
image_file_size_limit: 10
single_chunk_attachment_limit: 10
video_file_size_limit: 100
workflow_file_upload_limit: 10
image:
enabled: false
number_limits: 3
transfer_methods:
- local_file
- remote_url
number_limits: 3
opening_statement: ''
retriever_resource:
enabled: true
sensitive_word_avoidance:
enabled: false
speech_to_text:
enabled: false
suggested_questions: []
suggested_questions_after_answer:
enabled: false
text_to_speech:
enabled: false
language: ''
voice: ''
graph:
edges:
- data:
isInIteration: false
isInLoop: false
sourceType: knowledge-retrieval
targetType: llm
id: 1782024938772-source-llm-target
source: '1782024938772'
sourceHandle: source
target: llm
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
isInLoop: false
sourceType: code
targetType: assigner
id: 1782027966563-source-1782028348393-target
source: '1782027966563'
sourceHandle: source
target: '1782028348393'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
isInLoop: false
sourceType: assigner
targetType: answer
id: 1782028348393-source-answer-target
source: '1782028348393'
sourceHandle: source
target: answer
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
isInLoop: false
sourceType: start
targetType: if-else
id: 1782024904545-source-1782029544547-target
source: '1782024904545'
sourceHandle: source
target: '1782029544547'
targetHandle: target
type: custom
zIndex: 0
- data:
isInLoop: false
sourceType: if-else
targetType: knowledge-retrieval
id: 1782029544547-true-1782024938772-target
source: '1782029544547'
sourceHandle: 'true'
target: '1782024938772'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
isInLoop: false
sourceType: if-else
targetType: llm
id: 1782029544547-b75dc3ef-d981-4734-be2b-87763df75140-1782029621885-target
source: '1782029544547'
sourceHandle: b75dc3ef-d981-4734-be2b-87763df75140
target: '1782029621885'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
isInLoop: false
sourceType: llm
targetType: answer
id: 1782029621885-source-1782029787536-target
source: '1782029621885'
sourceHandle: source
target: '1782029787536'
targetHandle: target
type: custom
zIndex: 0
- data:
isInLoop: false
sourceType: llm
targetType: code
id: llm-source-1782027966563-target
source: llm
sourceHandle: source
target: '1782027966563'
targetHandle: target
type: custom
zIndex: 0
nodes:
- data:
selected: false
title: 用户输入
type: start
variables: []
height: 72
id: '1782024904545'
position:
x: 80
y: 282
positionAbsolute:
x: 80
y: 282
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 242
- data:
context:
enabled: true
variable_selector:
- '1782024938772'
- result
model:
completion_params:
temperature: 0.7
mode: chat
name: mimo-v2.5-pro
provider: langgenius/mimo/mimo
prompt_template:
- id: ca8d7571-8aa0-481a-b9d6-b8e75e86c92e
role: system
text: "你是一个精通AI大模型相关知识的面试官，现在根据知识库检索出来的面试题目和答案以及用户的问题，你需要进行整合，润色和优化，如果知识库中检索的结果为空，直接输出:暂无此相关知识点面试题。\n\
如果检索出多道题目，只需要输出一道题目即可。\n最终优化后的效果可以参考示例\n示例: \n题目: 如何解决过拟合问题\n\n答案: 解释过拟合：模型在训练集表现好，在真实数据表现不好，即模型的泛化能⼒不够。从另外⼀个⽅⾯来讲，\
\ 模型在达到经验损失最⼩的时候，模型复杂度较⾼，结构⻛险没有达到最优。"
- id: eb8682ab-922f-4b2e-b13a-b7cfea7a2b88
role: user
text: '{{#sys.query#}}{{#context#}}'
reasoning_format: separated
selected: false
structured_output_enabled: true
title: LLM
type: llm
vision:
enabled: false
height: 87
id: llm
position:
x: 980
y: 282
positionAbsolute:
x: 980
y: 282
selected: true
sourcePosition: right
targetPosition: left
type: custom
width: 241
- data:
answer: '题目: {{#1782027966563.question#}}
请回答.'
selected: false
title: 出题
type: answer
variables: []
height: 118
id: answer
position:
x: 2074.6992100318203
y: 282
positionAbsolute:
x: 2074.6992100318203
y: 282
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 241
- data:
dataset_ids:
- w5unqxdanURz3x/2iC5FPnk8ln2Aqwc/+upRI1FjbTmiWqaxsJ2GeBEO/saNlpkN
multiple_retrieval_config:
reranking_enable: false
reranking_mode: reranking_model
reranking_model:
model: qwen3-rerank
provider: langgenius/tongyi/tongyi
top_k: 4
query_attachment_selector: []
query_variable_selector:
- '1782024904545'
- sys.query
retrieval_mode: multiple
selected: false
title: 面试题查询
type: knowledge-retrieval
height: 89
id: '1782024938772'
position:
x: 680
y: 282
positionAbsolute:
x: 680
y: 282
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 241
- data:
code: "import re\n\ndef main(model_output: str) -> dict:\n \"\"\"\n \
\ 从模型输出中提取题目和答案\n \"\"\"\n # 定义正则表达式匹配\"题目：\"和\"答案：\"\n question_pattern\
\ = r\"题目[：:]\\s*(.+?)(?=\\n\\n答案[：:]|\\n答案[：:]|$)\"\n answer_pattern\
\ = r\"答案[：:]\\s*(.+)$\"\n \n # 提取题目\n question_match = re.search(question_pattern,\
\ model_output, re.DOTALL)\n question = question_match.group(1).strip()\
\ if question_match else \"\"\n \n # 提取答案\n answer_match = re.search(answer_pattern,\
\ model_output, re.DOTALL)\n answer = answer_match.group(1).strip() if\
\ answer_match else \"\"\n \n # 返回结果对象\n return {\n \"question\"\
: question,\n \"answer\": answer\n }\n"
code_language: python3
outputs:
answer:
children: null
type: string
question:
children: null
type: string
selected: false
title: 代码执行
type: code
variables:
- value_selector:
- llm
- text
value_type: string
variable: model_output
height: 51
id: '1782027966563'
position:
x: 1327.6658205922001
y: 282
positionAbsolute:
x: 1327.6658205922001
y: 282
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 241
- data:
items:
- input_type: variable
operation: over-write
value:
- '1782027966563'
- question
variable_selector:
- conversation
- question
- input_type: variable
operation: over-write
value:
- '1782027966563'
- answer
variable_selector:
- conversation
- answer
- input_type: constant
operation: +=
value: 1
variable_selector:
- conversation
- conversation_num
selected: false
title: 变量赋值
type: assigner
version: '2'
height: 135
id: '1782028348393'
position:
x: 1666.7215646620994
y: 282
positionAbsolute:
x: 1666.7215646620994
y: 282
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 241
- data:
cases:
- case_id: 'true'
conditions:
- comparison_operator: '='
id: 7becd8d1-658c-4be6-a2b5-098892e90c46
value: '1'
varType: number
variable_selector:
- conversation
- conversation_num
id: 'true'
logical_operator: and
- case_id: b75dc3ef-d981-4734-be2b-87763df75140
conditions:
- comparison_operator: '='
id: f9bd5bd2-7363-4806-827a-29fc404271a3
value: '2'
varType: number
variable_selector:
- conversation
- conversation_num
logical_operator: and
selected: false
title: 条件分支
type: if-else
height: 171
id: '1782029544547'
position:
x: 380
y: 282
positionAbsolute:
x: 380
y: 282
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 241
- data:
context:
enabled: false
variable_selector: []
model:
completion_params:
temperature: 0.7
mode: chat
name: mimo-v2.5-pro
provider: langgenius/mimo/mimo
prompt_template:
- id: 922fc7ff-91a8-46c0-92b9-491db7495812
role: system
text: '你是一个专业技术面试官，针对面试题和用户的回答以及正确的答案，给用户本次的回答进行评估，评估分成两部分，一个是打分，满分10分，第一个部分是需要进行回答点评，输出示例参考一下:
示例:
分数: 3 分
评价: 回答太简单，基础知识不牢固，不予录用。'
- id: 3bc9d5b2-b448-4e77-89e5-b77cc26c4243
role: user
text: '{{#sys.query#}}{{#conversation.question#}}{{#conversation.answer#}}'
reasoning_format: separated
selected: false
structured_output_enabled: true
title: 评估用户的回答
type: llm
vision:
enabled: false
height: 87
id: '1782029621885'
position:
x: 680
y: 410
positionAbsolute:
x: 680
y: 410
sourcePosition: right
targetPosition: left
type: custom
width: 241
- data:
answer: '{{#1782029621885.text#}}'
selected: false
title: 结果回复
type: answer
variables: []
height: 102
id: '1782029787536'
position:
x: 981
y: 410
positionAbsolute:
x: 981
y: 410
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 241
viewport:
x: -3.0244270527634853
y: -142.5635470219047
zoom: 0.8705505632961246
rag_pipeline_variables: []