/qa-demo

Question Answering Demo

Primary LanguagePython

QA Demo: A QA web-based framework for Question Answering over Wikipedia Data

Installation

  • Prepare your working directory and download pretrained models
bash prepare.sh

this will create config.json file that contains the configuration for the framework.

{
  "backend_host": "127.0.0.1", 
  "backend_port": "9500",

  "frontend_key": "<ENTER_YOUR_KEY>",

  "elasticsearch_host": "127.0.0.1",
  "elasticsearch_port": "9200",
  "elasticsearch_index": "wikipedia_08",
  "elasticsearch_type": "paragraph",

  "word2vec_bin_file": "<PATH_TO_GOOGLE_BIN_FILE"
}

Two most important elements to modify are frontend_key and word2vec_bin_file. The former is a unique application key, the latter is the path where Google Word2Vec bin file is located (most likely GoogleNews-vectors-negative300.bin").

  • Install all requirements using pip
pip install -r requirements.txt
  • Install tensorflow 0.10.0

[https://www.tensorflow.org/versions/r0.10/get_started/os_setup.html] (https://www.tensorflow.org/versions/r0.10/get_started/os_setup.html)

Run with pretrained models

The framework is ready to run using pretrained models on Answer Triggering Task. Simply run a backend and frontend:

nohup python ~/projects/qa-demo-mapped/run_backend.py &

and

gunicorn gunicorn frontend.qa:app

the above will run on 127.0.0.1:8000. Run it with a parameter to specify a host and port

gunicorn frontend.qa:app -b 127.0.0.1:5000

Contact

If you have any problems or concerns, please contact me: tomasz.jurczyk@emory.edu