windbag | chatbot based on Deep Learning | Machine Learning library

by tongda Python Version: Current License: MIT

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

kandi X-RAY | windbag Summary

windbag is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. windbag has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

A chatbot based on Deep Learning. Mainly for proof of concept, not for production.

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Quality

Security

License

Reuse

Support

windbag has a low active ecosystem.

It has 15 star(s) with 6 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 11 open issues and 0 have been closed. On average issues are closed in 1172 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of windbag is current.

Quality

windbag has 0 bugs and 0 code smells.

Security

windbag has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

windbag code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

windbag is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

windbag releases are not available. You will need to build from source code and install.

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

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

windbag saves you 312 person hours of effort in developing the same functionality from scratch.

It has 750 lines of code, 74 functions and 16 files.

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

Top functions reviewed by kandi - BETA

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

Create a chat bot
Get user input
Loads parameters for the chatbot
Constructs a response from logits
Prepare data for training
Convert a text file into a list of ids
Builds a vocabulary from a file
Return a list of tokens
Prepare raw data into train set and test set
Prepare a dataset
Return a list of convos
Return a dict of line ID2line lines
Build an AttentionChatBot model
Compute the train op
Perform bucketing
Create a loss function
Perform a single step
Compute logits
Compute the normalized score function
Generate a batch of data
Reshape a single batch
Performs a single step
Determine model directory
Argument parser
A mapping of question vocabulary
Return the answer vocab mapping

Get all kandi verified functions for this library.

windbag Key Features

No Key Features are available at this moment for windbag.

windbag Examples and Code Snippets

No Code Snippets are available at this moment for windbag.

Community Discussions

Trending Discussions on windbag

Problem with using Python's Struct Unpack Recently

QUESTION

Problem with using Python's Struct Unpack Recently

Asked 2019-Nov-29 at 17:00

In a Python script I record some audio with the following command:

...

ANSWER

Answered 2019-Nov-29 at 17:00

I couldn't figure out the problem with struct unpack as described above so I programmed around it and used numpy. So the code for getWaveIntegers should be:

Source https://stackoverflow.com/questions/59063553

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

Vulnerabilities

No vulnerabilities reported

Install windbag

You can download it from GitHub.
You can use windbag 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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