Data processing workflow for language model integration

• Integrate language models with existing data storage solutions
• Enhance AI capabilities for data analysis and retrieval
• Streamline text processing and information extraction
• Utilize embeddings for improved machine learning applications

Trigger the workflow manually to start the process Split input text into tokens for processing Store processed data in Xata for easy access Parse output for structured results Retrieve additional information from Wikipedia Generate embeddings using Hugging Face for advanced analysis Store vectors in Supabase for efficient data management

1. 1
   Import the workflow template into n8n
2. 2
   Configure the Xata credentials for memory storage
3. 3
   Set up the Supabase vector store parameters
4. 4
   Adjust any necessary parameters for the token splitter and output parser
5. 5
   Execute the workflow to test the integration