How it works
To connect Notion and SeaTable, you don't need a developer: a ready-made scenario links them in minutes.
- Starts when: Webhook
- Then: config
- Check: auth
- If yes: mensagem_tipo
- If yes: arquivo_id
- Then: deletar_arquivos_antigos
- If no: Convert to File
- Then: OpenAI
- Then: edit1
- Then: mensagem_cliente_inicial
- Then: Lista Mensagens1
- If no: base
- Then: Convert to File1
- Then: OpenAI1
- Then: Edit Fields
- If no: edit2
- Then: OpenAI Chat Model
- Then: Message Delay
- Then: Puxar as Mensagens
- Check: If1
- If yes: Edit Fields2
- Then: Database
- Then: setar_supabase_tabelas_vectoriais
- Then: Default Data Loader
- Then: Embeddings OpenAI1
- Then: Recursive Character Text Splitter
- Then: extrair_pdf
- Then: exportar_texto
- Then: supabase_vectorstore
- Then: Embeddings OpenAI
- Then: OpenAI Chat Model2
- Then: agendamentos
- Then: criar_cerebro
- Then: puxar_prompt
- Check: Merge
- Then: classificador_de_intencao
- Check: Switch
- If yes: tratamento
- Then: atualizar_prompt
- If no: recepcionista
- Then: Postgres Chat Memory
- Then: Deletar_todas_as_mensagens1
- Then: convert_to_file
- Check: tipo_arquivo
- Then: base64
- Then: OpenAI Chat Model1
- Then: Merge Database Data1
- Then: resumo
- Then: atualizar_lista_de_arquivos
- Then: criar_rag_controle
- Then: rag_resumos
- Then: Merge Database Data2
- Then: Supabase Vector Store
- Then: excluir_rag_arquivo
- Then: emails
- Then: adicionar_conhecimento
- Then: buscar_conhecimento
- Then: Merge Database Data3
- Then: excluir_conhecimento
- Then: mensagem_cliente
- Then: deletar_arquivo
- Then: Postgres Chat Memory1
- Then: deletar_conhecimento
- Then: RAG
You can launch this Notion + SeaTable integration in Scriptera: describe the task in plain words — the scenario is built, launched and monitored for you.