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Pagepiper

Self-hosted document search with BM25 full-text indexing and (with local Ollama) hybrid vector search and LLM-powered chat. Supports PDF, EPUB, DOCX, ODT, Apple Pages, XLSX, ODS, and Apple Numbers files.

Demo

Try it: pagepiper.circuitforge.tech

Screenshots

Library

Library view{ .only-light } Library view{ .only-dark }

Scan your PDF directory to index documents, or upload individual PDFs directly. Each document shows page count and shelving status.

Chat

Chat view{ .only-light } Chat view{ .only-dark }

Ask questions across your indexed documents. Results cite the source document and page number.

Tiers

Feature Free Paid (BYOK)
BM25 full-text search Yes Yes
All supported formats upload via browser Yes Yes
Unlimited local shelving Yes Yes
Hybrid vector search No Yes (local Ollama)
LLM chat over documents No Yes (local Ollama)

BYOK (Bring Your Own Key) means you supply your own Ollama instance. No cloud API keys required.

Self-Hosting Guide

Prerequisites

  • Docker and Docker Compose
  • PDFs you want to search
  • Optional: Ollama running locally for semantic search and LLM chat

Step 1: Get the code

git clone https://git.opensourcesolarpunk.com/Circuit-Forge/pagepiper
cd pagepiper

Step 2: Configure

cp .env.example .env

Open .env and set your directories:

# Where pagepiper stores its index database
PAGEPIPER_DATA_DIR=./data

# Directory to scan for PDFs (used by the "Scan for PDFs" button)
# You can also upload individual PDFs via the web UI without setting this
PAGEPIPER_BOOKS_DIR=/path/to/your/pdfs

To unlock hybrid vector search and LLM chat, add your Ollama endpoint:

PAGEPIPER_OLLAMA_URL=http://localhost:11434
PAGEPIPER_CHAT_MODEL=mistral:7b
PAGEPIPER_EMBED_MODEL=nomic-embed-text

Step 3: Start

docker compose up -d --build

Open http://localhost:8521 in your browser.

Step 4: Add your PDFs

Two ways to add documents:

Option A — Upload via browser (easiest for small collections):

Click the Upload PDF button in the Library view and select a file. It saves to data/uploads/ and begins indexing automatically.

Option B — Mount a directory (best for large collections):

Set PAGEPIPER_BOOKS_DIR in your .env to point at a folder of PDFs, then click Scan for PDFs. Pagepiper finds all .pdf files recursively and queues them for indexing.

Step 5: Search

Switch to the Chat tab and ask questions about your documents. The Free tier uses BM25 keyword matching. With Ollama configured, you get semantic (vector) search and LLM-generated answers with page-level citations.

Ollama Setup (optional)

Install Ollama from ollama.com, then pull the models:

ollama pull mistral:7b
ollama pull nomic-embed-text

Pagepiper's Docker container reaches Ollama at host.docker.internal — no extra network config needed on Linux/Mac with Docker Desktop. On a headless Linux server, make sure Ollama binds to 0.0.0.0:

OLLAMA_HOST=0.0.0.0 ollama serve

Managing the instance

# Check status
docker compose ps

# View API logs
docker compose logs -f api

# Stop
docker compose down

# Rebuild after updates
docker compose up -d --build

Notes

  • Pagepiper indexes PDFs at shelve time. Changes to the source file require a re-index (use the re-index button on the document card).
  • The data/ directory contains the SQLite index database and any uploaded files. Back it up to preserve your index.
  • Large PDFs (hundreds of pages) can take a few minutes to index. Watch the status badge on the document card.