Manual Assistant Troubleshooting Backend¶

Reference implementation for a RAG-based backend to search and answer questions from household manuals.

What it is¶

A FastAPI-based backend that integrates with ChromaDB to perform hybrid (vector + metadata filtered) search across OCR'd manuals and provides an interface for LLM-based troubleshooting.

What problem it solves¶

It centralizes the "brain" for the AI-Powered Warranty & Manual Assistant, allowing users to ask natural language questions like "How do I clean the filter on my Bosch dishwasher?" and get answers directly from the scanned PDF.

Where it fits in the stack¶

Upstream: Paperless-ngx (source of PDFs), scripts/process_manuals.py (ingestion to ChromaDB).
This Layer: API for searching and LLM orchestration.
Downstream: Streamlit or Open WebUI (frontend for family use).

Typical use cases¶

Troubleshooting appliance error codes.
Finding maintenance schedules in manuals.
Verifying warranty terms for specific products.

Strengths¶

Metadata Filtering: Quickly narrows search to the correct manufacturer/model.
Async Execution: Built on FastAPI for high performance.
Decoupled: Can be used by multiple frontends (web, mobile, voice).

Limitations¶

Requires pre-indexed manuals in ChromaDB.
Accuracy depends heavily on OCR quality from Paperless-ngx.

When to use it¶

When you want to build a custom chat interface for your homelab that goes beyond simple keyword search in Paperless-ngx.

When not to use it¶

If you only have a few manuals; simple full-text search in Paperless-ngx might be sufficient.

Sources / References¶

Contribution Metadata¶

Last reviewed: 2025-05-20
Confidence: high