A chat assistant with memory and answers from your documents

The assistant remembers the conversation and answers from your materials; new documents are picked up from a folder, and the chat history is logged and emailed to you.

  • Remembers the conversation context, not answering blind
  • Leans on your documents, not general knowledge
  • New files from a folder feed the knowledge base themselves
  • The chat history is logged and emailed to you
Google DriveDefault Data LoaderEmbeddings OpenAIGoogle Sheets ToolPinecone Vector Store
Connect Qdrant Vector Store and launchScriptera

How it works

To connect Qdrant Vector Store and Keap, you don't need a developer: a ready-made scenario links them in minutes.

  1. Starts when: When chat message received
  2. Then: Format Data For AI Agent
  3. Then: AI Agent (Chat Composer)
  4. Then: Conversation Logging
  5. Then: Short-Term Memory
  6. Then: Output Parser (JSON Enforcement)
  7. Then: OpenAI Chat Model
  8. Starts when: Google Drive Trigger
  9. Then: Download file
  10. Then: Pinecone Vector Store Insert
  11. Then: Default Data Loader
  12. Then: Recursive Character Text Splitter
  13. Then: Embeddings OpenAI
  14. Starts when: Schedule Trigger
  15. Then: Get Data from Sheet.
  16. Then: Aggregate
  17. Then: Convert Data to file
  18. Check: Check File Exist
  19. If yes: Send Chat History with attachment
  20. Then: Get Previous Content from Sheet
  21. Then: Pinecone Vector Store Query for Knowledge Base
  22. Then: Embeddings OpenAI Query for Chat modal

You can launch this Qdrant Vector Store + Keap integration in Scriptera: describe the task in plain words — the scenario is built, launched and monitored for you.

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