Chat with Your Email History using Telegram, Mistral and Pgvector for RAG

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 ope

Help me set up the n8n workflow "Chat with Your Email History using Telegram, Mistral and Pgvector for RAG" (https://n8n.io/workflows/3763). It uses: Telegram, Code, AI Agent, OpenAI Chat Model, Simple Memory, Call n8n Workflow Tool, Embeddings Ollama, Postgres PGVector Store. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.