Curie-Web/README.md

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# Curie-Web
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![Backend Tessts](https://github.com/navanchauhan/Curie-Web/workflows/Test%20Backend/badge.svg)
![Database Tests](https://github.com/navanchauhan/Curie-Web/workflows/Test%20Database/badge.svg)
[![DeepSource](https://static.deepsource.io/deepsource-badge-dark-mini.svg)](https://deepsource.io/gh/navanchauhan/Curie-Web/?ref=repository-badge)
Tested on:
* macOS 10.15 (Catalina)
* Ubuntu 20.04 - Raspberry Pi 4
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**Do Not Forget To Change DB Host configuration!**
## 1. Installing Dependencies
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### 1.1 Docker
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Once you have installed docker, make sure to pull the following images (Otherwise, these will automatically get downloaded when you run the web-server)
* navanchauhan/curie-cli (amd64/aarch64)
* navanchauhan/usd-from-gltf (aarch64)
* leon/usd-from-gltf (amd64)
### 1.2 PLIP
Install from [pharmai/plip](https://github.com/pharmai/plip).
In case you have problems installing it, install it from the forked repo [navanchauhan/plip](https://github.com/navanchauhan/plip)
### 1.3 PyMOL with Python Bindings (version >= 2.0)
* macOS users can use Homebrew to install it via `brew install pymol`
* Users using apt can install it via `sudo apt install pymol`
### 1.4 Open-Babel (version >= 3.0)
macOS users can use Homebrew to install it via `brew install open-babel`
Users using apt can install it via `sudo apt install openbabel python3-openbabel`
## 2. Changing the Configuration
Replace the values in `app/__init__.py`, `app/dock-single.py` and `app/dock-docker.py`
## 3. Enabling LSTM Generator
Open `app/views.py`
Make sure you have installed Tensorflow. Replace the following:
```python
tfWorking = 0
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```
with
```python
tfWorking = -1
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```
## 4. Adding AR Model Support
Make sure you have PyMOL 2.0 or higher
Either download the precompiled binaries from [COLLADA2GLTF](https://github.com/KhronosGroup/COLLADA2GLTF) or compile it on your own
Once you have the `COLLADA2GLTF-bin` file, run the following:
```
cp COLLADA2GLTF-bin /usr/local/bin/collada2gltf
```
## Running
### Without FastAPI
`gunicorn api:app -b "0.0.0.0:7589"`
### With FastAPI
`gunicorn api:app -k uvicorn.workers.UvicornWorker -b "0.0.0.0:7589"`