ETL pipeline for text processing

This workflow allows you to collect tweets, store them in MongoDB, analyse their sentiment, insert them into a Postgres database, and post positive tweets in a Slack channel. Cron node: Schedule the workflow to run every day Twitter node: Collect tweets MongoDB node: Insert the collected tweets in MongoDB Google Cloud Natural Language node: Analyse the sentiment of the collected tweets Set node: Extract the sentiment score and magnitude Postgres node: Insert the tweets and their sentiment score and magnitude in a Posgres database IF node: Filter tweets with positive and negative sentiment scores Slack node: Post tweets with a positive sentiment score in a Slack channel NoOp node: Ignore twee

Help me set up the n8n workflow "ETL pipeline for text processing" (https://n8n.io/workflows/1045). It uses: Postgres, Slack, MongoDB, X (Formerly Twitter), Google Cloud Natural Language. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.