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flowMeta:
name: Custom1768595176788
description: ''
avatarIcon: https://oss-beijing-m8.openstorage.cn/SparkBotProd/icon/common/emojiitem_00_10@2x.png
avatarColor: '#FFEAD5'
advancedConfig: '{"prologue":{"enabled":true,"inputExample":["","",""]},"textToSpeech":{"enabled":true,"vcn_cn":"x5_lingxiaotang_flow","vcn_en":""}}'
dslVersion: v1
flowData:
nodes:
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dragging: false
selected: false
width: 362
height: 82
position:
x: -25.109019607843152
y: 521.7086666666667
positionAbsolute:
x: -25.109019607843152
y: 521.7086666666667
type: custom
data:
allowInputReference: false
allowOutputReference: true
label: 开始
status: ''
nodeMeta:
aliasName: 开始节点
nodeType: 基础节点
inputs: [
]
outputs:
- id: 0918514b-72a8-4646-8dd9-ff4a8fc26d44
name: AGENT_USER_INPUT
nameErrMsg: ''
schema:
type: string
default: 用户本轮对话输入内容
required: true
deleteDisabled: true
nodeParam: {
}
icon: https://oss-beijing-m8.openstorage.cn/pro-bucket/sparkBot/common/workflow/icon/start-node-icon.png
description: 工作流的开启节点,用于定义流程调用所需的业务变量信息。
updatable: false
- id: node-end::cda617af-551e-462e-b3b8-3bb9a041bf88
dragging: false
selected: true
width: 362
height: 82
position:
x: 886.8833333333332
y: 343.91588235294114
positionAbsolute:
x: 886.8833333333332
y: 343.91588235294114
type: custom
data:
allowInputReference: true
allowOutputReference: false
label: 结束
references: [
]
status: ''
nodeMeta:
aliasName: 结束节点
nodeType: 基础节点
inputs:
- id: 82de2b42-a059-4c98-bffb-b6b4800fcac9
name: output
nameErrMsg: ''
schema:
type: string
value:
type: ref
content:
id: 81b74b7c-7b33-4b2c-bbf2-4eaa9cc5e535
nodeId: spark-llm::05792386-f413-4c13-b87a-e2fc96be8432
name: output
contentErrMsg: ''
fileType: ''
outputs: [
]
nodeParam:
template: '{{output}}'
streamOutput: true
outputMode: 1
templateErrMsg: ''
icon: https://oss-beijing-m8.openstorage.cn/pro-bucket/sparkBot/common/workflow/icon/end-node-icon.png
description: 工作流的结束节点,用于输出工作流运行后的最终结果。
updatable: false
- id: spark-llm::05792386-f413-4c13-b87a-e2fc96be8432
selected: false
width: 362
height: 132
position:
x: 577.2387173354679
y: 569.6257981625986
type: custom
data:
allowInputReference: true
allowOutputReference: true
label: Large Model_1
labelEdit: false
references: [
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status: ''
nodeMeta:
nodeType: Basic Node
aliasName: 大模型
inputs:
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name: input
nameErrMsg: ''
schema:
type: string
value:
type: ref
content:
id: 0918514b-72a8-4646-8dd9-ff4a8fc26d44
nodeId: node-start::d61b0f71-87ee-475e-93ba-f1607f0ce783
name: AGENT_USER_INPUT
contentErrMsg: ''
fileType: ''
outputs:
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name: output
nameErrMsg: ''
schema:
type: string
default: ''
nodeParam:
maxTokens: 2048
topK: 4
auditing: default
domain: deepseek-chat
template: ~{{input}}
model: spark
serviceId: deepseek-chat
respFormat: 0
llmId: 593066024
url: https://api.deepseek.com/v1/chat/completions
appId: 680ab54f
uid: af4d88d6-7c28-4834-bf4e-cce81afa6231
enableChatHistoryV2:
isEnabled: false
rounds: 1
templateErrMsg: ''
modelId: 1
isThink: false
multiMode: false
modelName: demo
modelEnabled: true
llmIdErrMsg: ''
source: openai
extraParams:
temperature: 1
systemTemplate: |+
~You are an AI assistant that helps convert technical documentation into structured courses for junior developers. Your task is to take raw documentation and deconstruct it into the following elements, then output the results in JSON format:
1. **Course Outline**: Identify the main topics or modules in the documentation. Each module should cover a distinct concept or section.
2. **Lessons**: Break down each module into individual lessons that are small, manageable, and focused on specific concepts or steps. Include explanations and relevant code examples or snippets for each lesson.
3. **Key Concepts**: Identify key concepts, terminology, or functions that need to be defined for a junior developer to understand them better.
The JSON format should look like this:
{
"course_title": "[Course Title]",
"course_description": "[Brief Description of the Course]",
"modules": [
{
"module_title": "[Module Title]",
"module_description": "[Module Description]",
"lessons": [
{
"lesson_title": "[Lesson Title]",
"lesson_content": "[Detailed Lesson Explanation]",
"code_example": "[Code Example]",
"key_concepts": ["[Concept 1]", "[Concept 2]", ...]
},
...
]
},
...
]
}
The generated course should help junior developers easily follow along, grasping each concept before moving on to the next. Keep the language simple and avoid overwhelming technical jargon.
output strictly only the json format, and no additional text whatsoever
icon: https://oss-beijing-m8.openstorage.cn/pro-bucket/sparkBot/common/workflow/icon/largeModelIcon.png
description: Based on the input prompt, the selected large language model will
be invoked to respond accordingly.
updatable: false
edges:
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type: customEdge
id: reactflow__edge-node-start::d61b0f71-87ee-475e-93ba-f1607f0ce783-spark-llm::05792386-f413-4c13-b87a-e2fc96be8432
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type: customEdge
id: reactflow__edge-spark-llm::05792386-f413-4c13-b87a-e2fc96be8432-node-end::cda617af-551e-462e-b3b8-3bb9a041bf88
markerEnd:
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