🪟 Running mmore on Windows

Overview

mmore was developed and tested mainly on Linux. It runs on Windows too, but a few things behave differently. This page lists those differences and the fix for each one.

If you work on Linux or macOS, you can skip this page.

1. Install the prerequisites

Unlike most Linux distributions, Windows does not ship Python, Git, or FFmpeg. Install them first with winget:

winget install Python.Python.3.11
winget install Git.Git
winget install astral-sh.uv
winget install Gyan.FFmpeg

Then clone the repo and install mmore into a virtual environment:

git clone https://github.com/EPFLiGHT/mmore.git
cd mmore
uv venv
.venv\Scripts\activate
uv pip install -e ".[all,cu126]"

Use cu126 for an NVIDIA GPU, or cpu otherwise. See the README for the full list of extras.

2. milvus-lite is not available on Windows

Every example config whose db.uri is ./proc_demo.db relies on milvus-lite (examples/index/config.yaml, examples/retriever_api/config.yaml, examples/rag/config.yaml, examples/rag/config_api.yaml). There is no Windows build of milvus-lite, so any of them fails with:

ModuleNotFoundError: No module named 'milvus_lite'

Fix: run Milvus in Docker

This repo ships no Compose file, so download the official Milvus standalone one matching your installed pymilvus version (see the Milvus install docs):

# Download the Milvus docker compose file from GitHub
Invoke-WebRequest `
  -Uri "https://github.com/milvus-io/milvus/releases/download/v2.6.6/milvus-standalone-docker-compose.yml" `
  -OutFile "milvus-docker-compose.yml"
# Start Milvus containers
docker compose -f milvus-docker-compose.yml up -d

Wait about a minute, then check docker ps shows the three containers (etcd, minio, milvus-standalone) as (healthy).

Create the database

mmore does not create the database automatically when connecting to a remote Milvus. Run this once:

python -c "from pymilvus import connections, db; connections.connect(uri='http://127.0.0.1:19530'); db.create_database('my_db')"

Point the configs at the Docker instance

The db block lives at a different level depending on the config. Change uri: ./proc_demo.db to uri: http://127.0.0.1:19530 in each one you use.

examples/retriever_api/config.yaml (and examples/rag/config*.yaml) — db is at the root:

db:
  uri: http://127.0.0.1:19530
  name: my_db

examples/index/config.yaml — db is nested under indexer:

indexer:
  db:
    uri: http://127.0.0.1:19530
    name: my_db

Check that the setup works

Once Milvus is running, confirm the connection:

python -c "from pymilvus import MilvusClient; c = MilvusClient(uri='http://127.0.0.1:19530', db_name='my_db'); print(c.list_collections())"

This returns a list of collections (empty before you index anything).

3. Surya OCR can crash the process on large PDFs

When processing large PDFs, the surya-based OCR may crash with:

Process finished with exit code 0xC0000005

This is a hard crash inside a native dependency. On Windows, use the fast processors instead, which rely on PyMuPDF rather than surya.

In your process config, use_fast_processors goes under dispatcher_config:

dispatcher_config:
  use_fast_processors: true

You lose some accuracy on heavily scanned PDFs, but the pipeline no longer crashes.

See also

• Installation

• Quickstart