runLLMCode
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工作流图谱
YAML 源码
app:
description: ''
icon: 🤖
icon_background: '#FFEAD5'
mode: workflow
name: runLLMCode
use_icon_as_answer_icon: false
kind: app
version: 0.1.4
workflow:
conversation_variables: []
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:
audio_file_size_limit: 50
batch_count_limit: 5
file_size_limit: 15
image_file_size_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
sourceType: start
targetType: code
id: 1733304372042-source-1733304400929-target
source: '1733304372042'
sourceHandle: source
target: '1733304400929'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
sourceType: llm
targetType: code
id: 1733308734162-source-1733309556954-target
source: '1733308734162'
sourceHandle: source
target: '1733309556954'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
sourceType: code
targetType: http-request
id: 1733309556954-source-1733305706063-target
source: '1733309556954'
sourceHandle: source
target: '1733305706063'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
sourceType: http-request
targetType: code
id: 1733305706063-source-1733310096303-target
source: '1733305706063'
sourceHandle: source
target: '1733310096303'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
sourceType: code
targetType: end
id: 1733310096303-source-1733304425429-target
source: '1733310096303'
sourceHandle: source
target: '1733304425429'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
sourceType: code
targetType: code
id: 1733304400929-source-1733364687479-target
source: '1733304400929'
sourceHandle: source
target: '1733364687479'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
sourceType: code
targetType: llm
id: 1733364687479-source-1733308734162-target
source: '1733364687479'
sourceHandle: source
target: '1733308734162'
targetHandle: target
type: custom
zIndex: 0
nodes:
- data:
desc: ''
selected: false
title: 开始
type: start
variables:
- allowed_file_extensions: []
allowed_file_types:
- document
- image
- audio
- video
allowed_file_upload_methods:
- local_file
- remote_url
label: File
max_length: 48
options: []
required: true
type: file
variable: File
- label: query
max_length: 1000
options: []
required: true
type: paragraph
variable: query
height: 116
id: '1733304372042'
position:
x: 30
y: 258
positionAbsolute:
x: 30
y: 258
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 244
- data:
code: "import os\nimport time\nfrom datetime import datetime, timedelta\n\n\
def main(filesize):\n # 存储符合条件的文件列表\n matched_files = []\n \n \
\ # 获取当前时间\n current_time = time.time()\n \n # 检查 upload_files\
\ 文件夹\n upload_dir = '/upload_files'\n \n # 确保文件夹存在\n if not\
\ os.path.exists(upload_dir):\n return {\"file_path\":\"None\"}\n\
\ \n # 递归遍历文件夹中的所有文件\n for root, dirs, files in os.walk(upload_dir):\n\
\ for filename in files: # 只处理文件，忽略文件夹\n file_path =\
\ os.path.join(root, filename)\n \n # 获取文件状态信息\n \
\ file_stat = os.stat(file_path)\n \n #\
\ 获取文件修改时间\n file_mtime = file_stat.st_mtime\n \n\
\ # 计算文件时间差（分钟）\n time_diff = (current_time - file_mtime)\
\ / 60\n \n # 检查文件大小和修改时间是否符合条件\n if file_stat.st_size\
\ == filesize:\n matched_files.append((file_path, file_mtime))\n\
\n if matched_files:\n # 按修改时间排序，取最新的文件\n newest_file =\
\ max(matched_files, key=lambda x: x[1])\n return {\"file_path\"\
:str(newest_file[0])}\n else:\n return {\"file_path\":\"None\"\
}\n"
code_language: python3
desc: ''
outputs:
file_path:
children: null
type: string
selected: false
title: 获取文件路径
type: code
variables:
- value_selector:
- '1733304372042'
- File
- size
variable: filesize
height: 54
id: '1733304400929'
position:
x: 334
y: 258
positionAbsolute:
x: 334
y: 258
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 244
- data:
desc: ''
outputs:
- value_selector:
- '1733310096303'
- result
variable: output
selected: false
title: 结束
type: end
height: 90
id: '1733304425429'
position:
x: 942
y: 779.4285714285714
positionAbsolute:
x: 942
y: 779.4285714285714
selected: true
sourcePosition: right
targetPosition: left
type: custom
width: 244
- data:
authorization:
config: null
type: no-auth
body:
data:
- id: key-value-707
key: ''
type: text
value: '{"code":{{#1733309556954.code#}},"language":"python3"}'
type: json
desc: ''
headers: X-Api-Key:dify-sandbox
method: post
params: ''
selected: false
timeout:
max_connect_timeout: 0
max_read_timeout: 0
max_write_timeout: 0
title: sandbox 执行代码
type: http-request
url: http://sandbox:8194/v1/sandbox/run
variables: []
height: 110
id: '1733305706063'
position:
x: 942
y: 543.7142857142858
positionAbsolute:
x: 942
y: 543.7142857142858
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 244
- data:
context:
enabled: false
variable_selector: []
desc: ''
model:
completion_params:
temperature: 0.7
mode: chat
name: deepseek-coder
provider: deepseek
prompt_template:
- id: fb5ec31d-3aef-4b55-bb45-b5e0910ab916
role: system
text: '你是一个数据处理专家，擅长需求分析和数据处理，你可以和用户进行基本的对话，习惯使用 pandas 编写代码处理数据处理的需求。
'
- id: ab066e1b-b7c0-4984-991d-fe2972312bd4
role: user
text: "<UserMessage>\n{{#1733304372042.query#}}\n</UserMessage>\n\n\n##\
\ 步骤\n1、首先，根据 xml 标签 <UserMessage></UserMessage> 中的内容，思考这是否是一个数据处理需求？如果这不是处理数据的需求，你可以请求用户澄清需要如何处理数据。如果这是一个数据处理请求，请结合下面的背景信息，给出处理步骤。\n\
2、根据处理步骤，使用 pandas 生成代码，无需注释，直接输出代码即可。\n3、csv的数据路径为：{{#1733304400929.file_path#}}\n\
4、python代码最终输出的内容为markdown的文本\n\n\n### 背景\n下面我会用 xml 的格式给你提供每个 DataSample\
\ 的数据样本。\n\n<DATA>\n <DataFrame>\n <DataSample>{{#1733364687479.result#}}</DataSample>\n\
\ </DataFrame>\n</DATA>"
selected: false
title: LLM
type: llm
variables: []
vision:
enabled: false
height: 98
id: '1733308734162'
position:
x: 942
y: 258
positionAbsolute:
x: 942
y: 258
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 244
- data:
code: "import re\nimport json\n\ndef main(markdown_text):\n \"\"\"\n \
\ 从Markdown文本中提取Python代码块。\n :param markdown_text: Markdown内容字符串\n \
\ :return: 提取的Python代码列表\n \"\"\"\n # 使用正则表达式匹配Markdown中的Python代码块\n\
\ code_blocks = re.findall(r'```python(.*?)```', markdown_text, re.DOTALL)\n\
\ code_string = [code.strip() for code in code_blocks][0]\n return\
\ {\"code\":json.dumps(code_string)}\n"
code_language: python3
desc: ''
outputs:
code:
children: null
type: string
selected: false
title: 提取LLM中都代码
type: code
variables:
- value_selector:
- '1733308734162'
- text
variable: markdown_text
height: 54
id: '1733309556954'
position:
x: 942
y: 423.7142857142857
positionAbsolute:
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