Help Need for Custom Chatbot

[Justin_H]

I want to build a fully offline, private chatbot that runs locally and answers only from data I provide.

Requirements:

• No cloud / no external APIs

• Ingest my own data (PDFs, text, code, notes)

• Strictly limited to my data (no external knowledge leakage)

• Supports adding new data over time

Any pointers or real-world experiences appreciated.

[KrishnDhola]

Check “Ollama”

[TheStrength]

For a custom chatbot with RAG, your best starting points depend on how much you want to build yourself:

Ready-to-deploy stacks (fastest path):

• RAG Web UI — beginner-friendly, handles PDF/DOCX/Markdown out of the box
• DataBridge — open-source, supports text, PDFs, images, and video, fully local
• Offline RAG System (Docker + Llama 3) — containerized, no cloud APIs, good for sensitive data

Build-from-scratch guides (more control):

• RAG с нуля: doc loading, chunking, Qdrant + LLaMA — covers the full pipeline end-to-end
• ChromaDB + DeepSeek local assistant — lightweight, fully local, high-quality walkthrough
• 5 open-source tools RAG in one evening — minimalist stack, fast to get running

If privacy is critical: DocuDeeper (100% offline, GDPR-compliant) or RAG-Guard (zero-trust, browser-based, nothing leaves your device).

Choosing a vector DB? This comparative review of Qdrant, Milvus, ChromaDB, LanceDB, pgvector, Weaviate is the best single resource for that decision.

Pro tip: Start with ChromaDB as your vector store — it’s embedded (no separate server), has the simplest setup, and you can migrate to Qdrant or pgvector later when you need to scale.

[Justin_H]

Thank You.