Please see the documentation for more details.
Note: Adviser 2.0 is currently only tested on Linux and Mac (Windows is possible using WSL2 (Ubuntu), for M1 chips see the extra section near the bottom of this file).
If Git
is not installated on your machine, just download the Adviser 2.0 file available in relases
section. Then unzip and navigate to the main folder.
Note that this method has some disadvantages (you'll only be able to run basic text-to-text terminal conversations).
If Git
is installed on your machine, you may instead clone the repository by entering in a terminal window:
git clone https://github.com/DigitalPhonetics/adviser.git
- If you want to use speech in-/output, please make sure you have the hdf5, portaudio and sndfile libraries installed.
- If you want to make use of the function
services.service.Service.draw_system_graph
,
you will need to install the graphviz
library via your system's package manager.
If you can't install it (no sufficient user rights), don't use this function in your scripts.
On Ubuntu e.g.:
sudo apt-get install graphviz
On Mac, you will need to install homebrew by executing:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"
and then calling brew install graphviz
.
For other OS please see https://graphviz.gitlab.io/download/.
ADvISER needs to be executed in a Python3 environment.
Once you obtained the code, navigate to its top level directory where you will find the file
requirements_base.txt
, which lists all modules you need to run a basic text-to-text version of ADvISER. We suggest to create a
virtual environment from the top level directory, as shown below, followed by installing the necessary packages.
- (Requires pip or pip3) Make sure you have virtualenv installed by executing
python3 -m pip install --user virtualenv
- Create the virtual environment (replace envname with a name of your choice)
python3 -m venv <path-to-env>
3. Source the environment (this has to be repeated every time you want to use ADVISER inside a new terminal session)
source <path-to-env>/bin/activate
- Install the required packages
pip install -r requirements_base.txt
(NOTE: or requirements_multimodal.txt if you want to use ASR / TTS)
- Navigate to the adviser folder
cd adviser
and, to make sure your installation is working, execute
python run_chat.py lecturers
You can type text to chat with the system (confirm your utterance by pressing the Enter
-Key once) or type bye
(followed by pressing the Enter
-Key once) to end the conversation.
To see more of the available options, run
python run_chat.py --help
- OPTIONAL: If you want to use multimodal functionallity, e.g. ASR / TTS/ ..., download the models via the script
download_models.sh
found in the top level folder
sh download_models.sh
NOTE: this also requires you to install requirements_multimodal.txt
in step 4
.
You can enable ASR / TTS by adding --asr
and --tts
to the command line options of run_chat.py
(NOTE: for TTS, we recommend you run the code on a CUDA-enabled device and append --cuda
to the command line options for drastic performance increase).
- OPTIONAL: If you want to run the demo with all services enabled, please make sure you executed step 6 and installed the
requirements_multimodal.txt
. Then, additional requirements must be compiled by yourself - follow the guide intools/OpenFace/how_to_install.md
for this.
Then, try running
python run_demo_multidomain.py
In general, everything should work if you're using conda
instead of pip
.
For pip users, the following installation instructions worked:
- Install the system library requirements as stated above (using
homebrew
). - pip install -i https://pypi.anaconda.org/numba/label/wheels_experimental_m1/simple numba
- Remove pyaudio from the requirements file and instead execute this command to install pyaudio:
python -m pip install --global-option='build_ext' --global-option='-I/opt/homebrew/Cellar/portaudio/19.7.0/include' --global-option='-L/opt/homebrew/Cellar/portaudio/19.7.0/lib' pyaudio
- Proceed with installing requirements as described above
- Switch to the adviser folder
cd adviser
(containing therun_chat.py
file) - Copy the snd library into the current folder:
cp /opt/homebrew/lib/libsndfile.dylib
- Install the Python packages from
requirements_doc.txt
. - Run
PYTHONPATH=./adviser mkdocs build
orPYTHONPATH=./adviser mkdocs gh-deploy
for pushing directly to GitHub Pages.
You can ask questions by sending emails to adviser-support@ims.uni-stuttgart.de.
You can also post bug reports and feature requests in GitHub issues.
If you use or reimplement any of this source code, please cite the following paper:
@InProceedings{
title = {ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents},
author = {Chia-Yu Li and Daniel Ortega and Dirk V{\"{a}}th and Florian Lux and Lindsey Vanderlyn and Maximilian Schmidt and Michael Neumann and Moritz V{\"{o}}lkel and Pavel Denisov and Sabrina Jenne and Zorica Karacevic and Ngoc Thang Vu},
booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020) - System Demonstrations},
publisher = {Association for Computational Linguistics},
location = {Seattle, Washington, USA},
year = {2020}
}
Adviser is published under the GNU GPL 3 license.