Quick overview
This workflow downloads a sample product catalog and a GAEB X83 tender file, extracts tender positions with flinq.ai, and reranks catalog items against each position to return the best-matching SKU and relevance score.
How it works
- Starts manually when you execute the workflow.
- Downloads a sample catalog CSV file and parses it into catalog item records.
- Builds a list of catalog document texts (name + description) and keeps the corresponding SKU list for later lookup.
- Downloads a sample GAEB X83 LV file and sends it to the flinq.ai /v1/extract endpoint to extract the tender structure.
- Flattens the extracted tender tree into individual positions with quantity, unit, and combined short/long text.
- For each position, calls flinq.ai /v1/rerank (paced to one request every 2 seconds) to find the top 3 matching catalog entries.
- Selects the best rerank result and outputs the position details along with the matched SKU and a rounded relevance score.
Setup
- Create a flinq.ai account, generate an API key, and add it to an n8n HTTP Header Auth credential as
Authorization: Bearer <your_key>.
- Assign that HTTP Header Auth credential to the two requests that call
https://api.flinq.ai/v1/extract and https://api.flinq.ai/v1/rerank.
- Keep the custom
User-Agent header on both file-download requests (catalog and LV), as the file host may reject n8n’s default agent.
- Adjust the rerank pacing (batch interval) only if your flinq.ai rate limits allow it, since the template is configured for one request every 2 seconds.