Skip to content

ArcticRaven/PDFPal

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PDF Pal

A fully local PDF Q&A app for organizations that can't send documents to cloud AI services. Upload a PDF, ask questions, get cited answers - nothing leaves your local machine.

Capable of running entirely on CPU - GPU not required.

At this time, its not suited for multi-user workloads, but is capable of running in a server environment behind Caddy or your flavor of reverse proxy. There is NO auth support at this time, consider something like Cloudflare Access if required.


Requirements

  • Docker with Compose
  • ~5 GB disk space for models on first run
  • An NVIDIA GPU is supported but not required — CPU mode works out of the box

Quick start

git clone https://github.com/your-username/pdf-pal.git
cd pdf-pal
docker compose up --build

Open http://localhost:7842 in your browser.

this port is configurable via the .env file

Models are pulled from Ollama automatically on first launch. This may take a few minutes. Subsequent starts are instant — models are cached in a Docker volume.


Configuration

All settings live in .env at the project root:

APP_PORT=7842               # Host port the app is exposed on

CHAT_MODEL_GPU=llama3.1:8b  # Model used when USE_GPU=true
CHAT_MODEL_CPU=llama3.2:3b  # Model used when USE_GPU=false
EMBED_MODEL=nomic-embed-text

USE_GPU=false               # Set to true if you have an NVIDIA GPU

Recommended chat models:

Mode Options
CPU llama3.2:3b, llama3.2:1b, phi4-mini
GPU llama3.1:8b, gemma3:12b, mistral:7b

Avoid reasoning models — they are significantly slower and not suited for Q&A workloads.

Changes to .env take effect on the next docker compose up.

To remove all data including cached models:

docker compose down -v

Privacy & safety

  • 100% local — no data is sent to any external service. All LLM inference runs on your own hardware via Ollama.
  • Session isolation — each session gets its own database. Starting a new session wipes all uploaded documents and embeddings.
  • No accounts or tracking — no logins, no telemetry, no persistent user data.
  • 50 MB upload limit — enforced server-side.
  • Read-only PDF parsing — documents are parsed for text only; original files are not stored.

About

A local-only AI analysis tool for reviewing large PDFs and sourcing information quickly.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors