Description
Build your own intelligent chatbot that remembers context, pulls knowledge from documents, and gives accurate, human-like responses — all powered by RAG (Retrieval-Augmented Generation) and integrated with Pinecone + PostgreSQL.
Whether you're creating a customer support bot, research assistant, or internal helpdesk, this n8n workflow gives you full control over memory, retrieval, and intelligence.
🔹 How It Works:
✅ User sends a message (via web, app, or Telegram)
✅ Postgres tracks and updates Session ID and chat history
✅ The message is passed to a Retriever Agent
✅ Pinecone searches the vector database for relevant context chunks
✅ Retrieved context + user query is sent to an LLM (e.g., GPT-4o)
✅ The final AI response is generated and sent back to the user
It Automates:
🗂️ Session-based Context Management using PostgreSQL
🧠 Semantic Search using Pinecone Vector DB
📚 Knowledge Retrieval from indexed documents
💬 LLM-Generated Responses via OpenAI or any LLM
🔁 Memory-aware Interactions with thread/session tracking
💡 Why Choose This Workflow?
🔍 Accurate Retrieval – Your chatbot finds real context, not just guesses
🧠 Contextual Memory – Understands prior questions in a conversation
📚 Document-Aware Chat – Connect your own PDFs, Notion pages, wikis, etc.
🛠️ Modular & Scalable – Swap out Pinecone/Postgres for other services
🤖 Customizable Bot Logic – Easily modify prompts, fallback behavior, and logging
👤 Who Is This For?
✔️ Founders building customer-facing bots
✔️ Internal teams managing document Q&A tools
✔️ Product builders creating AI chat assistants
✔️ Researchers enabling smart search
✔️ Educators building tutoring or FAQ bots
🔗 Consult for Integrations:
🔗 Pinecone Vector DB – For storing and searching embedded chunks
🔗 PostgreSQL – For session management and memory persistence
🔗 OpenAI / GPT-4o – For smart, context-aware responses
🔗 n8n HTTP/Database Nodes – For building the chat + memory pipeline
🚀 Get Started Today!
Scale your bot from simple Q&A to truly intelligent, memory-powered conversations.
