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Chat with your email history using Telegram, Mistral and Pgvector for RAG

n8nn8n16 modulesv1.0
agentchatTriggercodeembeddingsOllamaiflmChatOpenAimemoryBufferWindownoOpsetsplitInBatchestelegramtelegramTriggertoolWorkflowvectorStorePGVector

Who is this for? Everyone! Did you dream of asking an AI "what hotel did I stay in for holidays last summer?" or "what were my marks last semester like?". Dream no more, as vector similarity searches and this workflow are the foundations to make it possible (as long as the information appears in your e-mails 😅). 100% Local and Open Source! This workflow is designed to use locally-hosted open source. Ollama as LLM provider, nomic-embed-text as the embeddings model, and pgvector as the vector data

At a glance

Chat with your email history using Telegram, Mistral and Pgvector for RAG is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects agent, chatTrigger, code, embeddingsOllama. It's free to download. Follow the 5-step import below to go live in minutes.

Platform
n8n
Connects
agent, chatTrigger, code, embeddingsOllama, if, lmChatOpenAi
Modules
16
Price
Free
Version
v1.0
Chat with your email history using Telegram, Mistral and Pgvector for RAG workflow diagram

About this workflow

Who is this for? Everyone! Did you dream of asking an AI "what hotel did I stay in for holidays last summer?" or "what were my marks last semester like?". Dream no more, as vector similarity searches and this workflow are the foundations to make it possible (as long as the information appears in your e-mails 😅). 100% Local and Open Source! This workflow is designed to use locally-hosted open source. Ollama as LLM provider, nomic-embed-text as the embeddings model, and pgvector as the vector database engine, on top of Postgres. Structured AND Vectorized This workflow combines structured and semantic search on your e-mail. No need for enterprise setups! Leverage the convenience of n8n and open source to get a bleeding edge solution. Setup 1. You will need a PGVector database with embeddings for all your email. Use my other template Gmail to Vector Embeddings with PGVector and Ollama to set it up in a breeze! 2. Make a copy of my Email Assistant: Convert Natural Language to SQL Queries with Phi4-mini and PostgreSQL, you will need it for structured searches. 3. Install this template and modify the Call the SQL composer Workflow step, to point at your copy of the SQL workflow. 4. Adjust the rest of necessary steps: Telegram Trigger, AI Chat model, AI Embeddings... Activate the workflow and chat around!

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How to import this n8n workflow

  1. 1

    Download the workflow JSON file after purchase.

  2. 2

    Open n8n → click the menu → Import from File.

  3. 3

    Select the downloaded JSON and import.

  4. 4

    Set up credentials for each node that requires them.

  5. 5

    Click Execute Workflow to test, then activate.

Setup guide

Setup guide included

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