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n8n-workflows/workflows/Extractfromfile/0741_Extractfromfile_Stickynote_Automation_Triggered.json
Praveen Mudalgeri c4885eee92 feat: add folder support for workflows (fixes #70)
2025-08-05 09:40:47 +05:30

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{
"id": "2Eba0OHGtOmoTWOU",
"meta": {
"instanceId": "9219ebc7795bea866f70aa3d977d54417fdf06c41944be95e20cfb60f992db19",
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},
"name": "RAG AI Agent with Milvus and Cohere",
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{
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"createdAt": "2025-05-03T17:14:30.099Z",
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}
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"value": "15gjDQZiHZuBeVscnK8Ic_kIWt3mOaVfs",
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{
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"toolName": "vector_store",
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{
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{
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"content": "## Why Milvus\nBased on comparisons and user feedback, **Milvus is often considered a more performant and scalable vector database solution compared to Supabase**, particularly for demanding use cases involving large datasets, high-volume vector search operations, and multilingual support.\n\n\n### Requirements\n- Create an account on [Zilliz](https://zilliz.com/) to generate the Milvus cluster. \n- There is no need to create docker containers or your own instance, Zilliz provides the cloud infraestructure to build it easily\n- Get your credentials ready from Drive, Milvus (Zilliz), and [Cohere](https://cohere.com)\n\n### Usage\nEvery time a new pdf is added into the Drive folder, it will be inserted into the Milvus Vector Store, allowing for the interaction with the RAG agent in seconds.\n\n## Calculate your company's RAG costs\n\nWant to run Milvus on your own server on n8n? Zilliz provides a great [cost calculator](https://zilliz.com/rag-cost-calculator/)\n\n### Get in touch with us\nWant to implement a RAG AI agent for your company? [Shoot us a message](https://1node.ai)\n"
},
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}
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},
"Download New": {
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},
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"main": [
[
{
"node": "RAG Agent",
"type": "main",
"index": 0
}
]
]
}
}
}
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