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Update the sql assistant workflow (#9329) 

### What problem does this PR solve?
Update the sql assistant workflow
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
tags/v0.20.1
YyBoom 2 months ago
parent
d102a6bb71
commit
7ce64cb265
No account linked to committer's email address
2 changed files with 724 additions and 721 deletions
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{
"id": 17,
"title": "SQL Assistant",
"description": "SQL Assistant is an AI-powered tool that lets business users turn plain-English questions into fully formed SQL queries. Simply type your question (e.g., “Show me last quarter’s top 10 products by revenue”) and SQL Assistant generates the exact SQL, runs it against your database, and returns the results in seconds. ",
"canvas_type": "Marketing",
"dsl": {
"components": {
"Agent:WickedGoatsDivide": {
"downstream": [
"ExeSQL:TiredShirtsPull"
],
"obj": {
"component_name": "Agent",
"params": {
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"description": "",
"exception_default_value": "",
"exception_goto": [],
"exception_method": "",
"frequencyPenaltyEnabled": false,
"frequency_penalty": 0.7,
"llm_id": "qwen-max@Tongyi-Qianwen",
"maxTokensEnabled": false,
"max_retries": 3,
"max_rounds": 5,
"max_tokens": 256,
"mcp": [],
"message_history_window_size": 12,
"outputs": {
"content": {
"type": "string",
"value": ""
}
},
"presencePenaltyEnabled": false,
"presence_penalty": 0.4,
"prompts": [
{
"content": "User's query: {sys.query}\n\nSchema: {Retrieval:HappyTiesFilm@formalized_content}\n\nSamples about question to SQL: {Retrieval:SmartNewsHammer@formalized_content}\n\nDescription about meanings of tables and files: {Retrieval:SweetDancersAppear@formalized_content}",
"role": "user"
}
],
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"temperature": 0.1,
"temperatureEnabled": false,
"tools": [],
"topPEnabled": false,
"top_p": 0.3,
"user_prompt": "",
"visual_files_var": ""
}
},
"upstream": [
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"Retrieval:SmartNewsHammer",
"Retrieval:SweetDancersAppear"
]
},
"ExeSQL:TiredShirtsPull": {
"downstream": [
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"obj": {
"component_name": "ExeSQL",
"params": {
"database": "",
"db_type": "mysql",
"host": "",
"max_records": 1024,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
},
"json": {
"type": "Array<Object>",
"value": []
}
},
"password": "20010812Yy!",
"port": 3306,
"sql": "Agent:WickedGoatsDivide@content",
"username": "13637682833@163.com"
}
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"upstream": [
"Agent:WickedGoatsDivide"
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},
"Message:ShaggyMasksAttend": {
"downstream": [],
"obj": {
"component_name": "Message",
"params": {
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}
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"upstream": [
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]
},
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"empty_response": "",
"kb_ids": [
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"outputs": {
"formalized_content": {
"type": "string",
"value": ""
}
},
"query": "sys.query",
"rerank_id": "",
"similarity_threshold": 0.2,
"top_k": 1024,
"top_n": 8,
"use_kg": false
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"downstream": [
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],
"obj": {
"component_name": "Retrieval",
"params": {
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"empty_response": "",
"kb_ids": [
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],
"keywords_similarity_weight": 0.7,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
}
},
"query": "sys.query",
"rerank_id": "",
"similarity_threshold": 0.2,
"top_k": 1024,
"top_n": 8,
"use_kg": false
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},
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},
"Retrieval:SweetDancersAppear": {
"downstream": [
"Agent:WickedGoatsDivide"
],
"obj": {
"component_name": "Retrieval",
"params": {
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"empty_response": "",
"kb_ids": [
"4ad1f9d0727311f0827dbafe6e7908e6"
],
"keywords_similarity_weight": 0.7,
"outputs": {
"formalized_content": {
"type": "string",
"value": ""
}
},
"query": "sys.query",
"rerank_id": "",
"similarity_threshold": 0.2,
"top_k": 1024,
"top_n": 8,
"use_kg": false
}
},
"upstream": [
"begin"
]
},
"begin": {
"downstream": [
"Retrieval:HappyTiesFilm",
"Retrieval:SmartNewsHammer",
"Retrieval:SweetDancersAppear"
],
"obj": {
"component_name": "Begin",
"params": {
"enablePrologue": true,
"inputs": {},
"mode": "conversational",
"prologue": "Hi! I'm your SQL assistant, what can I do for you?"
}
},
"upstream": []
}
},
"globals": {
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"sys.files": [],
"sys.query": "",
"sys.user_id": ""
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"inputs": {},
"mode": "conversational",
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},
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"name": "begin"
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"outputs": {
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"value": ""
}
},
"query": "sys.query",
"rerank_id": "",
"similarity_threshold": 0.2,
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"query": "sys.query",
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"similarity_threshold": 0.2,
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"outputs": {
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"value": ""
}
},
"query": "sys.query",
"rerank_id": "",
"similarity_threshold": 0.2,
"top_k": 1024,
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"llm_id": "qwen-max@Tongyi-Qianwen",
"maxTokensEnabled": false,
"max_retries": 3,
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"content": "User's query: {sys.query}\n\nSchema: {Retrieval:HappyTiesFilm@formalized_content}\n\nSamples about question to SQL: {Retrieval:SmartNewsHammer@formalized_content}\n\nDescription about meanings of tables and files: {Retrieval:SweetDancersAppear@formalized_content}",
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"tools": [],
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"top_p": 0.3,
"user_prompt": "",
"visual_files_var": ""
},
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"name": "SQL Generator "
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"type": "agentNode"
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"db_type": "mysql",
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"max_records": 1024,
"outputs": {
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},
"json": {
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}
},
"password": "20010812Yy!",
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"username": "13637682833@163.com"
},
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"name": "ExeSQL"
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"text": "Searches for relevant database creation statements.\n\nIt should label with a knowledgebase to which the schema is dumped in. You could use \" General \" as parsing method, \" 2 \" as chunk size and \" ; \" as delimiter."
},
"label": "Note",
"name": "Note Schema"
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"dragHandle": ".note-drag-handle",
"dragging": false,
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"id": "Note:ThickClubsFloat",
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"text": "Searches for samples about question to SQL. \n\nYou could use \" Q&A \" as parsing method.\n\nPlease check this dataset:\nhttps://huggingface.co/datasets/InfiniFlow/text2sql"
},
"label": "Note",
"name": "Note: Question to SQL"
},
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"data": {
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"text": "Searches for description about meanings of tables and fields.\n\nYou could use \" General \" as parsing method, \" 2 \" as chunk size and \" ### \" as delimiter."
},
"label": "Note",
"name": "Note: Database Description"
},
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"data": {
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"text": "The Agent learns which tables may be available based on the responses from three knowledge bases and converts the user's input into SQL statements."
},
"label": "Note",
"name": "Note: SQL Generator"
},
"dragHandle": ".note-drag-handle",
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"data": {
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"text": "Connect to your database to execute SQL statements."
},
"label": "Note",
"name": "Note: SQL Executor"
},
"dragHandle": ".note-drag-handle",
"dragging": false,
"id": "Note:HungryBatsLay",
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},
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}

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