seq2seq-chatbot | Chatbot in 200 lines of code using TensorLayer | Chat library

by tensorlayer Python Version: 0.1 License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | seq2seq-chatbot Summary

seq2seq-chatbot is a Python library typically used in Messaging, Chat, Tensorflow, Neural Network applications. seq2seq-chatbot has no bugs, it has no vulnerabilities, it has build file available and it has medium support. You can download it from GitHub.

This is a 200 lines implementation of Twitter/Cornell-Movie Chatbot, please read the following references before you read the code:.

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Quality

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seq2seq-chatbot has a medium active ecosystem.

It has 786 star(s) with 310 fork(s). There are 41 watchers for this library.

It had no major release in the last 12 months.

There are 25 open issues and 14 have been closed. On average issues are closed in 30 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of seq2seq-chatbot is 0.1

Quality

seq2seq-chatbot has 0 bugs and 0 code smells.

Security

seq2seq-chatbot has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

seq2seq-chatbot code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

seq2seq-chatbot does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

seq2seq-chatbot releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 5843 lines of code, 350 functions and 25 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed seq2seq-chatbot and discovered the below as its top functions. This is intended to give you an instant insight into seq2seq-chatbot implemented functionality, and help decide if they suit your requirements.

Gathers the data from the filter
Filtering out the chunks that are not in the input
Filter the data based on the filter
Given a sequence of tokens and a w2idx
Gathers the dataset
Calculate word2 index
Get movie id2line dict
Pad a sequence into a sequence
Return a list of conversations
Returns a new line with the given whitelist
Read lines from a file

Get all kandi verified functions for this library.

seq2seq-chatbot Key Features

No Key Features are available at this moment for seq2seq-chatbot.

seq2seq-chatbot Examples and Code Snippets

No Code Snippets are available at this moment for seq2seq-chatbot.

Community Discussions

Trending Discussions on seq2seq-chatbot

Attribute Error: 'module' object has no attribute 'GraphKeys'

QUESTION

Attribute Error: 'module' object has no attribute 'GraphKeys'

Asked 2020-Apr-25 at 13:37

I'm currently trying to get a chatbot running with tensorflow. The example for the chatbot is from this repository: Github

I ran into some issues when I tried to run this in my tensorflow docker container. When starting the script the script exits with an Attribute Error.

...

ANSWER

Answered 2019-Jun-20 at 14:18

Maybe tl mismatch tf, you need to update your tensorlayer to 2.0+.you can use this instruction：

Source https://stackoverflow.com/questions/55133928

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install seq2seq-chatbot

You can download it from GitHub.
You can use seq2seq-chatbot like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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