KO | EN

GitLite

Minimalist Open Source Repository Search Engine

gitlite — search

#dsh #dsh-plugin #ai-agent #developer-tools #codex #typescript #cli #deepseek-harness #claude-code #ai-agents #mcp #rust

seq2seq_chatbot_links

★ 275 Open GitHub ↗

Links to the implementations of neural conversational models for different frameworks

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

## seq2seq chatbot links
Links to the implementations of neural conversational models for different frameworks.
Contributions are welcomed.

___
**Theano, Lasagne**

##### [lukalabs/cakechat](https://github.com/lukalabs/cakechat)
A dialog system that is able to express emotions in a text conversation. [See online demo.](https://cakechat.replika.ai/)

Sample results for neutral emotions:

hi                                → hey you
    how are you ?                     → i ' m fine , what about you ?
    how old are you ?                 → i ' m 16 , how old are you ?
    are you a leader or a follower ?  → i ' m a man who is a politician .
    my name is david . what is my name ?    → i love your name .
    is the sky blue or black ?        → the sky is blue
    you love anime .                  → i ' m not a weeb
    
___
**Tensorflow**

##### [Conchylicultor/DeepQA](https://github.com/Conchylicultor/DeepQA)
Nice results:

Hi			            	→ Hi.
    What is your name ?			→ Laura.
    What does that mean ?		→ I dunno.
    How old are you ?			→ thirty-five.
    Who is Laura ?				→ My brother.
    Say 'goodbye'				→ Alright.
    Two plus two				→ manny...

##### [nicolas-ivanov/tf_seq2seq_chatbot](https://github.com/nicolas-ivanov/tf_seq2seq_chatbot)
Modified code of [machine translation model](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/models/rnn/translate).
No answering randomisation is implemented in this code, so the models answers with the same phrase way each time:

hello baby					→ hello
    how old are you ?			→ twenty .
    i am lonely					→ i am not
    nice						→ you ' re not going to be okay .
    so rude						→ i ' m sorry .
    are you a robot or human?	→ no .
    are you better than siri?	→ yes .

___
**Torch**

##### [jiweil/Neural-Dialogue-Generation](https://github.com/jiweil/Neural-Dialogue-Generation)
Source code for a bunch of super nice articles by Jiwei Li - one of my favorite researches in the domain of neural conversational systems. Worth checking out.

tell me ... how long have you had this falling sickness ?   → a few months, I guess .
    so i had the doctors test sammy ’s response to conditioning .   → so he took the pills .
    what are you going to do ?  → i ’m going to get you a new car .
    they fear your power your intellect .   → i ’m not afraid of your power .
    
##### [macournoyer/neuralconvo](https://github.com/macournoyer/neuralconvo)

Hello?					→ Hi.
    How are you?			→ I'm fine.
    What's your name?		→ It's hard to describe.
    How so?					→ I'm not sure.
    What color is the sky?	→ It's blue.
    What is your job?		→ It's not that i'm a fucking werewolf!

___
**Keras**

##### [farizrahman4u/seq2seq](https://github.com/farizrahman4u/seq2seq)
The most popular implementation of Seq2seq architecture on GitHub. 
However, there is still no evidence of getting good results with this repo.

##### [nicolas-ivanov/debug_seq2seq](https://github.com/nicolas-ivanov/debug_seq2seq)
A wrapper for [farizrahman4u/seq2seq](https://github.com/farizrahman4u/seq2seq) used for running experiments. No good results were achieved so far.

##### [codekansas/keras-language-modeling](https://github.com/codekansas/keras-language-modeling)
Need to check this up.

##### [oswaldoludwig/Seq2seq-Chatbot-for-Keras](https://github.com/oswaldoludwig/Seq2seq-Chatbot-for-Keras)
A new generative chatbot whose training converges in few epochs, including a model pre-trained on a small but consistent dataset collected from dialogues of English courses online.

user: Hello! How are you?
    computer:  i am fine , ok , well , thank you  .    (with probability of 0.540239)
    user: What's your name?
    computer:  janet .     (with probability of 0.319482)
    user:  What do you like to do now?
    computer:  let me think a minute .     (with probability of 0.286760)
    user: I want to chat about computer science.
    computer:  i am glad to hear there .     (with probability of 0.293063)
    user: Are you a real girl or a computer program?
    computer:  i am self employed . i would love to be well .     (with probability of 0.026870)
    user: Why don't you look for a job?
    computer:  i do not know . i am the bank .     (with probability of 0.053494)
    user: So, you don't need a job!
    computer:  no . i have to make a lot of money .     (with probability of 0.001279)

## Corpora
##### [A Survey of Available Corpora for Building Data-Driven Dialogue Systems](https://breakend.github.io/DialogDatasets/)
A great overview of existing conversational datasets.

##### [AlJohri/OpenSubtitles](https://github.com/AlJohri/OpenSubtitles)
Get a lot of raw movie subtitles (~1.2Gb)

##### [Cornell Movie-Dialogs Corpus](http://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html)
~ 40Mb after clearing out the technical data.

## Papers
Refer to this great review by Richard Krisztian Csaky:
[Chatbot and Related Research Paper Notes with Images](https://github.com/ricsinaruto/Seq2seqChatbots/wiki/Chatbot-and-Related-Research-Paper-Notes-with-Images)

as well as to his report paper in pdf: [Deep Learning Based Chatbot Models](https://tdk.bme.hu/VIK/DownloadPaper/asdad)

seq2seq_chatbot_links

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README