How it works
To move data from Qdrant Vector Store to Telegram automatically, use a ready-made scenario — no manual exports.
- Starts when: When chat message received
- Then: Set Message6
- Then: Update Agent Details
- Then: Sales Agent
- Check: Switch1
- If yes: Send message (Whatsapp)
- If no: Send message (facebook)
- If no: Send message (instagram)
- If no: Send message (embedded)
- If no: Send message (telegram)
- Then: Postgres Chat Memory
- Then: Consultation Agent
- Then: CRM Agent
- Then: Vector Database
- Then: Company Database
- Then: Reply To User1
- Starts when: Telegram Trigger
- Check: Route Message
- If yes: Set Message
- If no: Get Audio1
- Then: Transcribe1
- Then: Set Message1
- If no: Reply to user
- Starts when: Facebook Trigger
- Starts when: Respond to Webhook - facebook post
- Check: If not echo
- If yes: Set Message5
- If yes: Facebook Typing Effect
- Starts when: Respond to Webhook - facebook get
- Starts when: Instagram Trigger
- Starts when: Respond to Webhook - instagram post
- Check: If not echo1
- If yes: Set Message4
- Starts when: Respond to Webhook - instagram get
- Starts when: WhatsApp Trigger
- Then: Get Lead Info
- Check: Route Messages
- If yes: Get Audio
- Then: Download Audio
- Then: Transcribe
- Then: Set Message2
- If no: Set Message3
- Starts when: When clicking ‘Execute workflow’
- Then: Download file
- Then: PGVector
- Then: Default Data Loader
- Then: Gemini
- Then: Response
- Then: Try Again
- Starts when: When Executed by Another Workflow
- Then: CRM Assistant
- Then: get_schema
- Then: list_records
- Then: Window Buffer Memory
- Then: create_opportunity
- Then: update_opportunity
- Then: create_contact
- Then: update_contact
- Then: Success
- Then: Calendar Agent
- Then: Try Again1
- Then: Create Event with Attendee
- Then: Get Events
- Then: Delete Event
- Then: Update Event
- Then: OpenAI Chat Model
- Then: OpenAI Chat Model1
- Then: OpenAI Chat Model2
- Then: OpenAI Chat Model3
- Then: Embeddings OpenAI
You can launch this Qdrant Vector Store + Telegram integration in Scriptera: describe the task in plain words — the scenario is built, launched and monitored for you.