How to Install and Uninstall python39-azure-ai-language-conversations Package on openSuSE Tumbleweed

Last updated: November 23,2024

1. Install "python39-azure-ai-language-conversations" package

Here is a brief guide to show you how to install python39-azure-ai-language-conversations on openSuSE Tumbleweed


    
        
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                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                python39-azure-ai-language-conversations
            
                    
    
    Copied

2. Uninstall "python39-azure-ai-language-conversations" package

Please follow the guidance below to uninstall python39-azure-ai-language-conversations on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                python39-azure-ai-language-conversations
            
                    
    
    Copied

3. Information about the python39-azure-ai-language-conversations package on openSuSE Tumbleweed

Information for package python39-azure-ai-language-conversations:
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Repository : openSUSE-Tumbleweed-Oss
Name : python39-azure-ai-language-conversations
Version : 1.1.0-1.4
Arch : noarch
Vendor : openSUSE
Installed Size : 1.5 MiB
Installed : No
Status : not installed
Source package : python-azure-ai-language-conversations-1.1.0-1.4.src
Upstream URL : https://github.com/Azure/azure-sdk-for-python
Summary : Microsoft Azure Conversational Language Understanding Client Library for Python
Description :
Conversational Language Understanding, aka CLU for short, is a cloud-based conversational
AI service which is mainly used in bots to extract useful information from user utterance
(natural language processing). The CLU analyze api encompasses two projects; conversation,
and orchestration projects. You can use the "conversation" project if you want to extract
intents (intention behind a user utterance) and custom entities. You can also use the
"orchestration" project which orchestrates multiple language apps to get the best response
(language apps like Question Answering, Luis, and Conversation).