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Specifies
Aura tab collection
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Aura tab
summaryMDX Queries and MDX CalculationsGenerations
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Parameter/Field

Description

Connection Name

A unique name that identifies your GenAI connections.

Provider

The name of the GenAI provider the system will use to generate output.

URL

The LLM Service URL of the provider-specific endpoint for generating output.

For Azure

API EndPoint

Specify which endpoint to be used to generate AI-powered conversational responses.

Authentication Key

A unique key for authenticating and authorizing requests to the provider's endpoint.

Model

The name of the GenAI LLM model used to generate the output.

Is Model Fine Tuned

Select one of the following:
Yes: Select this option to fine-tune the model.
No: Select this option if you do not want to fine-tune the model.

Embedding Connection

Specify the name of the GenAI embedding provider that the system will use to generate embeddings.

Usage

Select one of the following:

  • MDX

Calculations

  • Generations

MDX Queries

  • Conversational Analytics

You can specify whether you want to use the feature for MDX calculations or MDX queries. If you want to create expressions for calculated measures or members, select MDX calculations. If you want to query on the semantic model, choose the MDX queries option. However:

  • If you select the MDX calculations option, the Kyvos Dialogues option will appear in the Calculated Measures dialog box for creating expressions for calculated measures and members.

  • If you select the MDX queries option, the Kyvos Dialogues option will appear in the Query Playground page.

You can also set a default connection to be used for MDX calculations, MDX queries. To configure this, select the appropriate checkboxes as needed:

  • Default Connection for MDX

Calculations

  • Generation: Select this checkbox to set the default connection for MDX calculations and MDX queries.

  • Default Connection

for MDX Queries: Select this checkbox to set the default connection for MDX queries.

Temperature

Configures temperature, controlling randomness. Lowering it results in less random completions. As the temperature approaches zero, the model becomes deterministic and repetitive. It is recommended to alter either this or top p, but not both.

  • Default Value: 1

  • Minimum Value: 0

  • Maximum Value: 2

Maximum length

  • for

Allow Sending Data for LLM

Select Yes or No to specify whether the generated questions should include values or not.

Generate Content

Select Title, Summary, or Key Insight to determine the content to be generated, such as the title, summary, and key insights. NOTE: For summary and key insights, the value for 'Allow Sending Data for NLG', should be set to 'Yes'.

Max Rows Summary

Enter the value to configure maximum values for row summary.

NOTE: The default value is 100.

Input Prompt Token Limit

Specify the maximum tokens allowed for a prompt in a single request for the current provider.

NOTE: The default value is 8000.

The minimum value is 0.

Output Prompt Token Limit

Specify the maximum number of tokens shared between the prompt and output, which varies by model. One token is

roughly

approximately four characters for English text.

  • Default Value: 1

  • Minimum Value: 0

    • Maximum Value: 10000

    NOTE: The default value is 8000.

    The minimum value is 0.

    Max Retry Count

    Specify maximum retry count attempted so that we get correct query.

    NOTE: The default value is 0.

    Summary Records Threshold

    Specify similarity threshold for query autocorrection.

    NOTE: The default value is 0.2

    The minimum value is 2.

    LLM Temperature

    Specify the LLM temperature, which controls the level of randomness in the output. Lowering the temperature results in less random completions. The responses of the model become increasingly deterministic and repetitive as it approaches zero. It is recommended to adjust either the temperature or top-p, but not both simultaneously.

    Top P

    Controls diversity via nucleus sampling. If set to 0.5, half of all likelihood-weighted options are considered. It is recommended to adjust either this or the temperature parameter, but not both.

    • Default Value: 1

    • Minimum Value: 0

    • Maximum Value: 1

    Frequency penalty

    Specifies a number between -2.0 and 2.0. Positive values penalize new tokens based on their frequency in the existing text. This reduces the likelihood of the model repeating the same line verbatim.

    • Default Value: 1

    • Minimum Value: -2

    • Maximum Value: 2

    Presence penalty

    Specifies a number between -2.0 and 2.0. Positive values penalize new tokens based on their appearance in the text so far, thereby increasing the model's likelihood of discussing new topics.

    • Default Value: 1

    • Minimum Value: -2

    • Maximum Value: 2

    Aura tab
    summaryConversational AI
    paramsJTdCJTIydGl0bGUlMjIlM0ElMjJDb252ZXJzYXRpb25hbCUyMEFJJTIwJTIyJTdE

    Parameter/Field

    Description

    Connection Name

    A unique name that identifies your GenAI connections.

    Provider

    The name of the GenAI provider the system will use to generate output.

    URL

    The LLM Service URL of the provider-specific endpoint for generating output.

    • For Azure OpenAI, provide the URL in the following format:
      https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/
      For example, https://kyv-openai.openai.azure.com/openai/deployments/

    API EndPoint

    Specify which endpoint to be used to generate AI-powered conversational responses.

    • For Azure OpenAI, provide the API Endpoint in the following format:
      /YOUR_DEPLOYMENT_NAME/chat/completions?api-version=2024-08-01-preview
      For example, /gpt-4o/chat/completions?api-version=2024-08-01-preview

    Authentication Key

    A unique key for authenticating and authorizing requests to the provider's endpoint

    .

    Usage

    Select the Conversational AI option.

    You can also set a default connection to be used for Conversational AI. To configure this, select the Default Connection for Conversational AI to set the default connection for Conversational AI purposes

    .

    Model

    The name of the GenAI LLM model used to generate the output.

    Is Model Fine Tuned

    Select one of the following:
    Yes: Select this option to fine-tune the model.
    No: Select this option if you do not want to fine-tune the model.

    Prompt Token Limit

    Embedding Connection

    Specify the

    maximum tokens allowed for a prompt in a single request for the current provider.

    NOTE: The default value is 8000.

    The minimum value is 0.

    Embedding Endpoint

    Specify a unique identifier for end-user, which can help OpenAI monitor and detect abuse.

    Allow Sending Data for NLGSpecify similarity threshold for query autocorrection

    name of the GenAI embedding provider that the system will use to generate embeddings.

    Usage

    Select one of the following:

    • MDX Generations

    • Conversational Analytics

    You can specify whether you want to use the feature for MDX calculations or MDX queries. If you want to create expressions for calculated measures or members, select MDX calculations. If you want to query on the semantic model, choose the MDX queries option. However:

    • If you select the MDX calculations option, the Kyvos Dialogues option will appear in the Calculated Measures dialog box for creating expressions for calculated measures and members.

    • If you select the MDX queries option, the Kyvos Dialogues option will appear in the Query Playground page.

    You can also set a default connection to be used for MDX calculations, MDX queries. To configure this, select the appropriate checkboxes as needed:

    • Default Connection for MDX Generation: Select this checkbox to set the default connection for MDX calculations and MDX queries.

    • Default Connection for

    Allow Sending Data for LLM

    Select Yes or No to specify whether the generated questions should include values or not.

    Template Folder Path

    Specify a folder path for templates.

    Open AI Invoke Endpoint

    Specify which model to be used to generate embedding.

    Embedding Model Name

    Specify model name to be used to generate embedding.

    Similarity Threshold (Auto Correction)

    Generate Content

    Select Title, Summary, or Key Insight to determine the content to be generated, such as the title, summary, and key insights. NOTE: For summary and key insights, the value for 'Allow Sending Data for NLG', should be set to 'Yes'.

    Max Rows Summary

    Enter the value to configure maximum values for row summary.

    NOTE: The default value is 100.

    Input Prompt Token Limit

    Specify the maximum tokens allowed for a prompt in a single request for the current provider.

    NOTE: The default value is 8000.

    The minimum value is 0.

    Output Prompt Token Limit

    Specify the maximum number of tokens shared between the prompt and output, which varies by model. One token is approximately four characters for English text.

    NOTE: The default value is

    0

    8000.

    2

    The minimum value is

    2

    0.

    Max Retry Count

    for SQL ExecutionEnter the value to control RAG record selection

    Specify maximum retry count attempted so that we get correct query.

    NOTE: The default value is 0.

    Upper Threshold

    Summary Records Threshold

    Specify similarity threshold for query autocorrection.

    NOTE: The default value is 0.

    7.

    Lower Threshold

    Enter the value to control RAG record selection.

    NOTE: The default value is 0.4.

    Maximum Records Requested

    Enter the value to configure maximum records (RAG) required in a user prompt.

    NOTE: The default value is 10.

    Max Rows Summary

    Enter the value to configure maximum values for row summary.

    NOTE: The default value is 100.

    Generate Content

    Select Title, Summary, or Key Insight to determine the content to be generated, such as the title, summary, and key insights. NOTE: For summary and key insights, the value for 'Allow Sending Data for NLG', should be set to 'Yes'

    2

    The minimum value is 2.

    LLM Temperature

    Specify the LLM temperature, which controls the level of randomness in the output. Lowering the temperature results in less random completions. The responses of the model become increasingly deterministic and repetitive as it approaches zero. It is recommended to adjust either the temperature or top-p, but not both simultaneously.

    1. Click Save. The GenAI connection details are saved.

    Configuring an embedding connection

    You can now specify the type of connection while uploading the custom provider.

    After specifying the connection type, users can upload the required JAR and configuration files in a ZIP format corresponding to the selected type

    ...

    To configure the GenAI embedding connection, perform the following steps: 

    ...

    Parameter/Field

    Description

    Connection Name

    A unique name that identifies your GenAI connections.

    Provider

    The name of the GenAI provider the system will use to generate output. Select the required provider from the list.

    Embedding Model

    Select the name of the model for generating embeddings.

    Authentication Key EndPoint

    A Specify a unique key for authenticating and authorizing requests to the provider's endpoint.

    LLM Service URL

    Provide the URL of the provider-specific endpoint for generating output.

    Embeddings identifier for the end user, which helps OpenAI monitor and detect abuse.

    • For Azure OpenAI, provide the endpoint in the following format:
      {deployment-id}/embeddings?api-version=2024-10-21
      For example, /text-embedding-ada-002/embeddings?api-version=2023-05-15

    Prompt Token Limit

    Specify maximum tokens allowed for prompt in single request for current model.

    Similarity Upper Threshold

    Specify upper threshold to control the selection of records for Retrieval Augmented Generation (RAG).

    Similarity Lower Threshold

    Specify lower threshold to control Retrieval Augmented Generation (RAG) record selection.

    Template Folder Path

    Provide the folder path for templates.

    RAG Max Records

    Specify the maximum number of records (RAG) required in a user prompt.

    Configuring GenAI Custom provider

    ...

    On the Custom Provider page, while configuring a custom provider, you must define the ‘applicable For’ field to indicate the type whether the details apply to an LLM Connection, an Embedding Connection, or Both.

    ...

    Parameter/Field

    Description

    Provider Name

    The name of the GenAI provider the system will use to generate output.

    GenAI Provider Zip

    Upload the GenAI provider zip file.

    GenAI Provider ZIP

    The zip file should include two folders:

    • conf: This folder must contain a metadata file named metadata.json.

    • lib: This folder must include the required .jar files.

    Callback Class Name Enter the callback class namefor LLM Service

    Provide fully qualified class name, including package name of the class which implements the GenAICallbackService interface for LLM Service.

    Callback Class Name for Embedding Service

    Provide fully qualified class name, including package name of the class which implements the GenAIEmbeddingCallbackService interface for Embedding generation.