Document-Grounded Dialog Composition Framework is an end-to-end framework for generating conversational data grounded in the documents via crowdsourcing.
NOTE: more code release in Auguest 2019.
- MongoDB: On MacOS,
brew install [email protected]. Please refer to MongoDB community edition installation instructions for other platforms. - On MacOS,
homebrewwill automatically start themongodbservice. If not, open terminal & runsudo mongodfromhomedirectory.
This package requires Python 3.6 or higher. We recommend creating a new virtual environment for this project (using virtualenv or conda).
Run the following commands:
pip install -r requirements.txt
Please import the COLLNAME.json files to your local mongodb (use name "demodb") with commands such as,
mongoimport --db demodb --collection COLLNAME --drop --file COLLNAME.json
We are in process of acquiring appropriate licences for the data consist of sample documents and crowd-sourced annotations. We plan to release it next couple of weeks. We will be releasing code to push that data in to a MongoDB instance as well.
Run the following commands:
python3 run.py -d demo -p 8081
- Go to
http://localhost:8081 - Login as an
adminwithpassword o replaced with 0as password - Please make sure you select a task to explore before clicking
Start
You can visit https://ibm.biz/doc2dial to see the Doc2Dial in action.
There is also a short video on YouTube demonstrating doc2dial's capabilities.
If you have any questions, bug reports, and feature requests, please open an issue on Github.
We appreciate any kind of feedback or contribution. Feel free to proceed with small issues like bug fixes, documentation improvement. For major contributions and new features, please discuss with the collaborators in corresponding issues.