Build a Tax Code Assistant with Qdrant, Mistral.ai and OpenAI

This n8n workflows builds another example of creating a knowledgebase assistant but demonstrates how a more deliberate and targeted approach to ingesting the data can produce much better results for your chatbot. In this example, a government tax code policy document is used. Whilst we could split the document into chunks by content length, we often lose the context of chapters and sections which may be required by the user. Our approach then is to first split the document into chapters and sections before importing into our vector store. Additionally, using metadata correctly is key to allow filtering and scoped queries. Example Human: "Tell me about what the tax code says about cargo for i

Help me set up the n8n workflow "Build a Tax Code Assistant with Qdrant, Mistral.ai and OpenAI" (https://n8n.io/workflows/2341). It uses: HTTP Request, Compression, AI Agent, OpenAI Chat Model, Simple Memory, Recursive Character Text Splitter, Call n8n Workflow Tool, Default Data Loader, Embeddings Mistral Cloud, Qdrant Vector Store. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.