Content extraction and storage from web articles to Milvus vector store

• Automate the extraction of article titles and content from web pages.
• Store and retrieve essay content in a vector database for quick access.
• Utilize AI models to generate embeddings for efficient information retrieval.

Manually trigger the workflow to start the process. Fetch the list of essays from the specified URL. Extract essay titles and URLs from the fetched HTML content. Retrieve the full text of each essay using the extracted URLs. Generate embeddings for the essay content using OpenAI models. Store the embeddings in the Milvus vector store for future retrieval.

1. 1
   Import the workflow into n8n.
2. 2
   Set up a Milvus server and create a collection named 'my_collection'.
3. 3
   Configure OpenAI credentials for embedding generation.
4. 4
   Run the workflow to start extracting and storing content.