Interact with Email History via Telegram Using Semantic and Structured Search
This workflow enables you to query your email history using both semantic and structured searches through Telegram. It leverages vector similarity searches and structured SQL queries to provide comprehensive answers from your email data.
This workflow integrates Telegram, Pgvector, and OpenAI to allow users to interact with their email history. By combining semantic vector searches with structured SQL queries, it provides a robust solution for retrieving specific information from emails. The workflow is designed to be run locally and uses open-source tools, making it accessible and customizable. Users need to set up a PGVector database and adjust the workflow to connect with their existing email data.
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How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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