Chatbot for answering questions from PDFs with local…

This automation enables uploading PDF documents and answering questions about their content via chat using semantic search powered by a vector database. All processing runs locally—your data never leaves your infrastructure. Ideal for organizations prioritizing privacy and control over sensitive information.

## Who it´s for
- Companies needing a private chatbot for internal documentation
- Developers implementing RAG without cloud APIs
- Support teams automating responses based on PDF manuals
- Educational platforms providing access to learning materials

## What the automation does
- Accepts PDF files via an n8n form
- Splits documents into chunks and generates embeddings using Ollama
- Stores vector representations in a local Qdrant database
- On receiving a chat message, retrieves relevant context via semantic search
- Generates natural language responses using a LangChain RAG agent and local LLM
- Replies directly in the chat interface

## What´s included
- Ready-to-use n8n workflow
- Trigger logic for form submission and incoming chat messages
- Integrations with Local Ollama service, Qdrant Vector Store, n8n Form, and n8n Chat Interface
- Basic text instructions for setup and adaptation

## Requirements for setup
- Running n8n instance
- Locally deployed Ollama with a chosen model (e.g., llama3)
- Installed and running Qdrant (local or Docker)
- Access to configure n8n nodes for paths and parameters

## Benefits and outcomes
- Full data privacy—no documents sent to external services
- Instant access to knowledge without manual file searches
- Reduced workload for support staff and managers
- Immediate usability of newly added documents in conversations
- Support for complex queries with contextual understanding
- Scalability through vector storage and RAG architecture

## Important: template only
Important: you are purchasing a ready-made automation workflow template only. Rollout into your infrastructure, connecting specific accounts and services, 1:1 setup help, custom adjustments for non-standard stacks and any consulting support are provided as a separate paid service at an individual rate. To discuss custom work or 1:1 help, contact via Telegram: @gleb923.