This n8n workflow automates the process of handling currency exchange information through a series of integrated nodes. It starts with a Webhook trigger that captures incoming POST requests on the ‘currency_exchange_estimator’ endpoint. The data is then split into manageable chunks by a Text Splitter node, preparing it for further processing. Leveraging HuggingFace Embeddings, the workflow indexes this data into a Weaviate vector database for efficient retrieval. When a query is received, it searches the database for relevant exchange data, which is then processed by a language model (ChatGPT) with memory capabilities for contextual understanding. An agent formulates a meaningful response based on the query, and the final output is logged into a Google Sheet for record-keeping. Overall, this workflow is ideal for automating currency exchange estimations, creating a searchable database of currency data, and providing intelligent responses to user inquiries, making it highly useful for financial services, trading platforms, or currency comparison tools.
Automated Currency Exchange Data Processing Workflow
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsHuggingFace, @n8n/n8n-nodes-langchain.lmChatHf, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter, @n8n/n8n-nodes-langchain.toolVectorStore, @n8n/n8n-nodes-langchain.vectorStoreWeaviate, googleSheets, stickyNote, webhook |
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