How it works
To connect Postgres and Embeddings OpenAI, you don't need a developer: a ready-made scenario links them in minutes.
- Starts when: When clicking ‘Test workflow’
- Then: Wordpress - Get all posts
- Check: Merge Wordpress Posts and Pages
- Then: Set fields1
- Check: Filter - Only published & unprotected content
- Then: HTML To Markdown
- Then: Supabase Vector Store
- Then: Aggregate
- Then: Supabase - Store workflow execution
- Then: Wordpress - Get all pages
- Then: Embeddings OpenAI
- Then: Default Data Loader
- Then: Token Splitter
- Then: Embeddings OpenAI1
- Then: OpenAI Chat Model
- Then: Postgres Chat Memory
- Starts when: Respond to Webhook
- Then: Set fields
- Then: AI Agent
- Then: Embeddings OpenAI2
- Then: Default Data Loader1
- Then: Token Splitter1
- Then: Markdown1
- Then: Store documents on Supabase
- Then: Aggregate1
- Then: Store workflow execution id and timestamptz
- Then: Postgres
- Then: Wordpress - Get posts modified after last workflow execution
- Check: Merge retrieved WordPress posts and pages
- Then: Set fields2
- Check: Filter - Only published and unprotected content
- Check: Loop Over Items
- Then: Postgres - Filter on existing documents
- Check: Switch
- If yes: Supabase - Delete row if documents exists
- Then: Aggregate2
- Then: Set fields3
- If no: Set fields4
- Then: Wordpress - Get posts modified after last workflow execution1
- Starts when: Every 30 seconds
- Then: Aggregate documents
- Then: Postgres - Create documents table
- Then: Postgres - Create workflow execution history table
- Starts when: When chat message received
- Then: Supabase - Retrieve documents from chatinput
You can launch this Postgres + Embeddings OpenAI integration in Scriptera: describe the task in plain words — the scenario is built, launched and monitored for you.