Rpg Maker Vx Runtime Package

[Carlos Beirise]

AzureOpenAI On Your Data utilizes large language models (LLMs) to produce similar results to QnA Maker. If you wish to migrate your QnA Maker project to Azure OpenAI On Your Data, please check out our guide.

You must have a QnA Maker resource, to use the key and resource name. You entered the resource Name during resource creation, then the key was created for you. The resource name is used as the subdomain for your endpoint. To retrieve your key and resource name, select Quickstart for your resource in the Azure portal. The resource name is the first subdomain of the endpoint URL:

In a console window (such as cmd, PowerShell, or Bash), use the dotnet new command to create a new console app with the name qna-maker-quickstart. This command creates a simple "Hello World" C# project with a single source file: program.cs.

The value of QNA_MAKER_ENDPOINT has the format -RESOURCE-NAME.cognitiveservices.azure.com. Go to the Azure portal and find the QnA Maker resource you created in the prerequisites. Select Keys and Endpoint page, under resource management to locate Authoring (Subscription) key and QnA Maker Endpoint.

Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like Azure Key Vault. See the Azure AI services security article for more information.

The knowledge base in this quickstart starts with 2 conversational QnA pairs, this is done on purpose to simplify the example and to have highly predictable Ids to use in the Update method, associating follow-up prompts with questions to new pairs. This was planned and implemented in a specific order for this quickstart.

Manage your knowledge base by sending a JSON object. For immediate operations, a method usually returns a JSON object indicating status. For long-running operations, the response is the operation ID. Call the client.Operations.GetDetailsAsync method with the operation ID to determine the status of the request.

The prediction QnA Maker client is a QnAMakerRuntimeClient object that authenticates to Azure using Microsoft.Rest.ServiceClientCredentials, which contains your prediction runtime key, returned from the authoring client call, client.EndpointKeys.GetKeys after the knowledgebase is published.

You can update a knowledge base by passing in the knowledge base ID and an UpdatekbOperationDTO containing add, update, and delete DTO objects to the UpdateAsync method. Use the MonitorOperation method to determine if the update succeeded.

Use the DownloadAsync method to download the database as a list of QnADocumentsDTO. This is not equivalent to the QnA Maker portal's export from the Settings page because the result of this method is not a file.

Publish the knowledge base using the PublishAsync method. This takes the current saved and trained model, referenced by the knowledge base ID, and publishes that at your endpoint. This is a necessary step in order to query your knowledgebase.

Generate an answer from a published knowledgebase using the RuntimeClient.GenerateAnswerAsync method. This method accepts the knowledge base ID and the QueryDTO. Access additional properties of the QueryDTO, such a Top and Context to use in your chat bot.

Some methods, such as create and update, can take enough time that instead of waiting for the process to finish, an operation is returned. Use the operation ID from the operation to poll (with retry logic) to determine the status of the original method.

Manage your knowledge base by sending a JSON object. For immediate operations, a method usually returns a JSON object indicating status. For long-running operations, the response is the operation ID. Call the client.operations.getDetails method with the operation ID to determine the status of the request.

The prediction QnA Maker client is a QnAMakerRuntimeClient object that authenticates to Azure using Microsoft.Rest.ServiceClientCredentials, which contains your prediction runtime key, returned from the authoring client call, client.EndpointKeys.getKeys after the knowledgebase is published.

When the create method returns, pass the returned operation ID to the wait_for_operation method to poll for status. The wait_for_operation method returns when the operation completes. Parse the resourceLocation header value of the returned operation to get the new knowledge base ID.

You can update a knowledge base by passing in the knowledge base ID and an UpdateKbOperationDTO containing add, update, and delete DTO objects to the update method. The DTOs are also basically JSON objects. Use the wait_for_operation method to determine if the update succeeded.

Use the download method to download the database as a list of QnADocumentsDTO. This is not equivalent to the QnA Maker portal's export from the Settings page because the result of this method is not a TSV file.

Publish the knowledge base using the publish method. This takes the current saved and trained model, referenced by the knowledge base ID, and publishes that at an endpoint. Check the HTTP response code to validate that the publish succeeded.

Generate an answer from a published knowledge base using the RuntimeClient.runtime.generateAnswer method. This method accepts the knowledge base ID and the QueryDTO. Access additional properties of the QueryDTO, such a Top and Context to use in your chat bot.

Manage your knowledge base by sending a JSON object. For immediate operations, a method usually returns a JSON object indicating status. For long-running operations, the response is the operation ID. Call the operations.get_details method with the operation ID to determine the status of the request.

The prediction QnA Maker client is a QnAMakerRuntimeClient object that authenticates to Azure using Microsoft.Rest.ServiceClientCredentials, which contains your prediction runtime key, returned from the authoring client call, client.EndpointKeysOperations.get_keys after the knowledgebase is published.

You can update a knowledge base by passing in the knowledge base ID and an UpdateKbOperationDTO containing add, update, and delete DTO objects to the update method. Use the Operation.getDetail method to determine if the update succeeded.

Generate an answer from a published knowledge base using the QnAMakerRuntimeClient.runtime.generate_answer method. This method accepts the knowledge base ID and the QueryDTO. Access additional properties of the QueryDTO, such a Top and Context to use in your chat bot.

For immediate operations, a method usually returns the result, if any. For long-running operations, the response is an Operation object. Call the getDetails method with the operation.operationId value to determine the status of the request.

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