https://github.com/mrdvince/pytorch_chatbot
A chatbot implemented using PyTorch, using Cornell Movie-Quotes Corpus which contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts
https://github.com/mrdvince/pytorch_chatbot
bot chatbot deep-learning machine-learning machinelearning python pytorch
Last synced: about 1 year ago
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A chatbot implemented using PyTorch, using Cornell Movie-Quotes Corpus which contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts
- Host: GitHub
- URL: https://github.com/mrdvince/pytorch_chatbot
- Owner: mrdvince
- License: mit
- Created: 2018-11-29T00:52:19.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-11-29T15:47:48.000Z (over 7 years ago)
- Last Synced: 2025-04-11T21:14:20.160Z (about 1 year ago)
- Topics: bot, chatbot, deep-learning, machine-learning, machinelearning, python, pytorch
- Language: Python
- Homepage:
- Size: 29.3 KB
- Stars: 3
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Chatbot Built Using Pytorch
## Getting Started
------------
To start, Download the data ZIP file
`here `
and put in a ``data/`` directory under the current directory.
## Preparation
```
mkdir data
wget http://www.cs.cornell.edu/~cristian/data/cornell_movie_dialogs_corpus.zip
unzip cornell_movie_dialogs_corpus.zip
cd ..
```
#### run python file using ipython kernel
``` %run chatbot.py ```
### Sample Chat
```
> hello?
bot: hello .
> where am I?
bot: you re in a hospital .
> who are you?
bot: i m a lawyer .
> how are you doing?
bot: i m fine .
> are you my friend?
bot: no .
> you're under arrest
bot: i m trying to help you !
> i'm just kidding
bot: i m sorry .
> where are you from?
bot: san francisco .
> it's time for me to leave
bot: i know .
> goodbye
bot: goodbye .
```
## **Acknowledgements**
1) Yuan-Kuei Wu’s pytorch-chatbot implementation:
https://github.com/ywk991112/pytorch-chatbot
2) Sean Robertson’s practical-pytorch seq2seq-translation example:
https://github.com/spro/practical-pytorch/tree/master/seq2seq-translation
3) FloydHub’s Cornell Movie Corpus preprocessing code:
https://github.com/floydhub/textutil-preprocess-cornell-movie-corpus