[BUG] ImportError: No module named 'fcntl' on Windows in model_discovery.py

[ReyanshAgrawal]

Pre-check

• I have searched the existing issues and none cover this bug.

Description

The module fcntl being used in the code is a POSIX-only module. Upon running the current PrivateGPT version on Windows, after running private-gpt serve, and opening http://localhost:8080, the server crashes because in a particular file, the code tries to import fcntl

Steps to Reproduce

1. Install PrivateGPT

Windows

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

uv tool install --python 3.11 `
  --find-links https://wheels.privategpt.dev/packages/ `
  "private-gpt[core]"

2. Start your LLM server
    ```
# Example with Ollama
    ollama pull qwen3.5:35b         # LLM (~24 GB)
    ollama pull mxbai-embed-large   # Embeddings (~670 MB)
    ollama serve 

3. Run PrivateGPT

Windows (PowerShell)

$env:OPENAI_API_BASE = "http://localhost:<llm-port>/v1"
$env:OPENAI_EMBEDDING_API_BASE = "http://localhost:<embedding-port>/v1"
private-gpt serve

4. Go to the port you are told to visit in the terminal

### Expected Behavior

The webpage should go directly to the PrivateGPT setup page or whatever page it is supposed to lead me to.

### Actual Behavior

After visiting the webpage (which says that the page refused to connect), going back to the terminal will display a boatload of errors and tracebacks.

### Environment

The only relevant part for this issue is that my OS is Windows.

### Additional Information

Till this issue is resolved, Windows users could navigate to to C:\Users\<username>\AppData\Roaming\uv\tools\private-gpt\Lib\site-packages\private_gpt\components\llm\tokenizers\models\model_discovery.py, and then edit line 4 to be wrapped in "if _os_check.name == 'posix':", and the line "import os as _os_check". They may then wrap line 131 with "if _os_check.name == 'posix':", and then line 153 with "if _os_check.name == 'posix':". If you are not a Python developer, I suggest taking Claude's support to do so.

### Version

v1.0.1

### Setup Checklist

- [x] Confirm that you have followed the installation instructions in the project’s documentation.
- [x] Check that you are using the latest version of the project.
- [x] Verify disk space availability for model storage and data processing.
- [x] Ensure that you have the necessary permissions to run the project.

### NVIDIA GPU Setup Checklist

- [ ] Check that the all CUDA dependencies are installed and are compatible with your GPU (refer to [CUDA's documentation](https://docs.nvidia.com/deploy/cuda-compatibility/#frequently-asked-questions))
- [ ] Ensure an NVIDIA GPU is installed and recognized by the system (run `nvidia-smi` to verify).
- [ ] Ensure proper permissions are set for accessing GPU resources.
- [ ] Docker users - Verify that the NVIDIA Container Toolkit is configured correctly (e.g. run `sudo docker run --rm --gpus all nvidia/cuda:11.0.3-base-ubuntu20.04 nvidia-smi`)

[ReyanshAgrawal]

Sidenote: I listed how to fix this bug for yourself at home till the devs fix it. It probably looks quite dirty, so if you prefer a tidier version, continue reading.

model_discovery.py
Select my entire model_discovery.py, copy it, select your entire model_discovery.py, and then press ctrl + v