rasa_chatbot | 基于rasa_nlu，rasa_core，rasa_core_sdk构建的聊天机器人 | Bot library

by xiaoxiong74 Python Version: Current License: No License

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

kandi X-RAY | rasa_chatbot Summary

rasa_chatbot is a Python library typically used in Automation, Bot applications. rasa_chatbot has no bugs, it has no vulnerabilities and it has low support. However rasa_chatbot build file is not available. You can download it from GitHub.

基于rasa_nlu，rasa_core，rasa_core_sdk构建的聊天机器人

Support

Quality

Security

License

Reuse

Support

rasa_chatbot has a low active ecosystem.

It has 102 star(s) with 40 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 12 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of rasa_chatbot is current.

Quality

rasa_chatbot has 0 bugs and 0 code smells.

Security

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

rasa_chatbot code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

rasa_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

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

rasa_chatbot has no build file. You will be need to create the build yourself to build the component from source.

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

rasa_chatbot saves you 206 person hours of effort in developing the same functionality from scratch.

It has 506 lines of code, 35 functions and 13 files.

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

Top functions reviewed by kandi - BETA

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

R Compute the tensor
Mask input tensors
Tries to utterance
Get response from Tuler
Reset all slots
Extract support from support_search
Render a template
Train the nlu model
Get response from ThreatConnect123

Get all kandi verified functions for this library.

rasa_chatbot Key Features

No Key Features are available at this moment for rasa_chatbot.

rasa_chatbot Examples and Code Snippets

No Code Snippets are available at this moment for rasa_chatbot.

Community Discussions

Trending Discussions on rasa_chatbot

Rasa chatbot : "Failed to install frontend dependencies. Check logs for details."

QUESTION

Rasa chatbot : "Failed to install frontend dependencies. Check logs for details."

Asked 2020-Apr-01 at 17:13

I have an issue with Rasa X. Installation part is successful but when I executed "rasa x" command I'm getting below error and a new browser window is opened and showing cat images with text: "Frontend compiling-and now ...we wait"

...

ANSWER

Answered 2020-Mar-30 at 09:04

Rasa X latest version (0.27.1) has bug, so just follow the steps below to make Rasa X work-

Uninstall “rasa”, “rasa-sdk”, & “rasa-x” (if you have it installed)
Install Rasa X 0.26.3 by this command-

pip install rasa-x==0.26.3 --extra-index-url https://pypi.rasa.com/simple
- (automatically this will install the compatible rasa version)
- (also make sure to use pip / pip3 as per your default python)
create a demo bot by “rasa init”
type “rasa x”

Source https://stackoverflow.com/questions/60898764

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

Vulnerabilities

No vulnerabilities reported

Install rasa_chatbot

You can download it from GitHub.
You can use rasa_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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