DataRobot APIのリソース > APIリファレンスドキュメント > DataRobot REST API > Generative AI > Chat Prompts

Chat Prompts (GenAI)¶

This page outlines the operations, endpoints, parameters, and example requests and responses for the Chat Prompts (GenAI).

GET /api/v2/genai/chatPrompts/¶

List chat prompts.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/genai/chatPrompts/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
playgroundId	query	string	false	Only retrieve the chat prompts associated with this playground ID.
llmBlueprintId	query	string	false	Only retrieve the chat prompts associated with this LLM blueprint ID. If specified, will retrieve the chat prompts for the oldest chat in this LLM blueprint.
chatId	query	string	false	Only retrieve the chat prompts associated with this chat ID.
offset	query	integer	false	Skip the specified number of values.
limit	query	integer	false	Retrieve only the specified number of values.

Example responses¶

200 Response

{
  "count": 0,
  "data": [
    {
      "chatContextId": "string",
      "chatId": "string",
      "chatPromptIdsIncludedInHistory": [
        "string"
      ],
      "citations": [
        {
          "chunkId": 0,
          "metadata": {},
          "page": 0,
          "similarityScore": 0,
          "source": "string",
          "startIndex": 0,
          "text": "string"
        }
      ],
      "confidenceScores": {
        "bleu": 0,
        "meteor": 0,
        "rouge": 0
      },
      "creationDate": "2019-08-24T14:15:22Z",
      "creationUserId": "string",
      "executionStatus": "NEW",
      "id": "string",
      "llmBlueprintId": "string",
      "llmId": "azure-openai-gpt-3.5-turbo",
      "llmSettings": {
        "maxCompletionLength": 0,
        "systemPrompt": "string",
        "temperature": 0,
        "topP": 0
      },
      "metadataFilter": {},
      "resultMetadata": {
        "blockedResultText": "string",
        "cost": 0,
        "errorMessage": "string",
        "estimatedDocsTokenCount": 0,
        "feedbackResult": {
          "negativeUserIds": [],
          "positiveUserIds": []
        },
        "finalPrompt": "string",
        "inputTokenCount": 0,
        "latencyMilliseconds": 0,
        "metrics": [],
        "outputTokenCount": 0,
        "providerLLMGuards": [
          {
            "name": "string",
            "satisfyCriteria": true,
            "stage": "prompt",
            "value": "string"
          }
        ],
        "totalTokenCount": 0
      },
      "resultText": "string",
      "text": "string",
      "userName": "string",
      "vectorDatabaseId": "string",
      "vectorDatabaseSettings": {
        "addNeighborChunks": false,
        "maxDocumentsRetrievedPerPrompt": 1,
        "maxTokens": 1
      }
    }
  ],
  "next": "string",
  "previous": "string",
  "totalCount": 0
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Successful Response	ListChatPromptsResponse
422	Unprocessable Entity	Validation Error	HTTPValidationErrorResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

POST /api/v2/genai/chatPrompts/¶

Request the execution of a new prompt within a chat or an LLM blueprint.

Code samples¶

# You can also use wget
curl -X POST https://app.datarobot.com/api/v2/genai/chatPrompts/ \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}" \
  -d '{CreateChatPromptRequest}'

Body parameter¶

{
  "chatId": "string",
  "llmBlueprintId": "string",
  "llmId": "azure-openai-gpt-3.5-turbo",
  "llmSettings": {
    "maxCompletionLength": 0,
    "systemPrompt": "string",
    "temperature": 0,
    "topP": 0
  },
  "metadataFilter": {},
  "text": "string",
  "vectorDatabaseId": "string",
  "vectorDatabaseSettings": {
    "addNeighborChunks": false,
    "maxDocumentsRetrievedPerPrompt": 1,
    "maxTokens": 1
  }
}

Parameters

Name	In	Type	Required	Description
body	body	CreateChatPromptRequest	true	none

Example responses¶

202 Response

{
  "chatContextId": "string",
  "chatId": "string",
  "chatPromptIdsIncludedInHistory": [
    "string"
  ],
  "citations": [
    {
      "chunkId": 0,
      "metadata": {},
      "page": 0,
      "similarityScore": 0,
      "source": "string",
      "startIndex": 0,
      "text": "string"
    }
  ],
  "confidenceScores": {
    "bleu": 0,
    "meteor": 0,
    "rouge": 0
  },
  "creationDate": "2019-08-24T14:15:22Z",
  "creationUserId": "string",
  "executionStatus": "NEW",
  "id": "string",
  "llmBlueprintId": "string",
  "llmId": "azure-openai-gpt-3.5-turbo",
  "llmSettings": {
    "maxCompletionLength": 0,
    "systemPrompt": "string",
    "temperature": 0,
    "topP": 0
  },
  "metadataFilter": {},
  "resultMetadata": {
    "blockedResultText": "string",
    "cost": 0,
    "errorMessage": "string",
    "estimatedDocsTokenCount": 0,
    "feedbackResult": {
      "negativeUserIds": [],
      "positiveUserIds": []
    },
    "finalPrompt": "string",
    "inputTokenCount": 0,
    "latencyMilliseconds": 0,
    "metrics": [],
    "outputTokenCount": 0,
    "providerLLMGuards": [
      {
        "name": "string",
        "satisfyCriteria": true,
        "stage": "prompt",
        "value": "string"
      }
    ],
    "totalTokenCount": 0
  },
  "resultText": "string",
  "text": "string",
  "userName": "string",
  "vectorDatabaseId": "string",
  "vectorDatabaseSettings": {
    "addNeighborChunks": false,
    "maxDocumentsRetrievedPerPrompt": 1,
    "maxTokens": 1
  }
}

Responses¶

Status	Meaning	Description	Schema
202	Accepted	Successful Response	ChatPromptResponse
422	Unprocessable Entity	Validation Error	HTTPValidationErrorResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

DELETE /api/v2/genai/chatPrompts/{chatPromptId}/¶

Delete an existing chat prompt.

Code samples¶

# You can also use wget
curl -X DELETE https://app.datarobot.com/api/v2/genai/chatPrompts/{chatPromptId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
chatPromptId	path	string	true	The ID of the chat prompt to delete.

Example responses¶

422 Response

{
  "detail": [
    {
      "loc": [
        "string"
      ],
      "msg": "string",
      "type": "string"
    }
  ]
}

Responses¶

Status	Meaning	Description	Schema
204	No Content	Successful Response	None
422	Unprocessable Entity	Validation Error	HTTPValidationErrorResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

GET /api/v2/genai/chatPrompts/{chatPromptId}/¶

Retrieve an existing chat prompt.

Code samples¶

# You can also use wget
curl -X GET https://app.datarobot.com/api/v2/genai/chatPrompts/{chatPromptId}/ \
  -H "Accept: application/json" \
  -H "Authorization: Bearer {access-token}"

Parameters

Name	In	Type	Required	Description
chatPromptId	path	string	true	The ID of the chat prompt to retrieve.

Example responses¶

200 Response

{
  "chatContextId": "string",
  "chatId": "string",
  "chatPromptIdsIncludedInHistory": [
    "string"
  ],
  "citations": [
    {
      "chunkId": 0,
      "metadata": {},
      "page": 0,
      "similarityScore": 0,
      "source": "string",
      "startIndex": 0,
      "text": "string"
    }
  ],
  "confidenceScores": {
    "bleu": 0,
    "meteor": 0,
    "rouge": 0
  },
  "creationDate": "2019-08-24T14:15:22Z",
  "creationUserId": "string",
  "executionStatus": "NEW",
  "id": "string",
  "llmBlueprintId": "string",
  "llmId": "azure-openai-gpt-3.5-turbo",
  "llmSettings": {
    "maxCompletionLength": 0,
    "systemPrompt": "string",
    "temperature": 0,
    "topP": 0
  },
  "metadataFilter": {},
  "resultMetadata": {
    "blockedResultText": "string",
    "cost": 0,
    "errorMessage": "string",
    "estimatedDocsTokenCount": 0,
    "feedbackResult": {
      "negativeUserIds": [],
      "positiveUserIds": []
    },
    "finalPrompt": "string",
    "inputTokenCount": 0,
    "latencyMilliseconds": 0,
    "metrics": [],
    "outputTokenCount": 0,
    "providerLLMGuards": [
      {
        "name": "string",
        "satisfyCriteria": true,
        "stage": "prompt",
        "value": "string"
      }
    ],
    "totalTokenCount": 0
  },
  "resultText": "string",
  "text": "string",
  "userName": "string",
  "vectorDatabaseId": "string",
  "vectorDatabaseSettings": {
    "addNeighborChunks": false,
    "maxDocumentsRetrievedPerPrompt": 1,
    "maxTokens": 1
  }
}

Responses¶

Status	Meaning	Description	Schema
200	OK	Successful Response	ChatPromptResponse
422	Unprocessable Entity	Validation Error	HTTPValidationErrorResponse

To perform this operation, you must be authenticated by means of one of the following methods:

BearerAuth

Schemas¶

ChatPromptResponse

{
  "chatContextId": "string",
  "chatId": "string",
  "chatPromptIdsIncludedInHistory": [
    "string"
  ],
  "citations": [
    {
      "chunkId": 0,
      "metadata": {},
      "page": 0,
      "similarityScore": 0,
      "source": "string",
      "startIndex": 0,
      "text": "string"
    }
  ],
  "confidenceScores": {
    "bleu": 0,
    "meteor": 0,
    "rouge": 0
  },
  "creationDate": "2019-08-24T14:15:22Z",
  "creationUserId": "string",
  "executionStatus": "NEW",
  "id": "string",
  "llmBlueprintId": "string",
  "llmId": "azure-openai-gpt-3.5-turbo",
  "llmSettings": {
    "maxCompletionLength": 0,
    "systemPrompt": "string",
    "temperature": 0,
    "topP": 0
  },
  "metadataFilter": {},
  "resultMetadata": {
    "blockedResultText": "string",
    "cost": 0,
    "errorMessage": "string",
    "estimatedDocsTokenCount": 0,
    "feedbackResult": {
      "negativeUserIds": [],
      "positiveUserIds": []
    },
    "finalPrompt": "string",
    "inputTokenCount": 0,
    "latencyMilliseconds": 0,
    "metrics": [],
    "outputTokenCount": 0,
    "providerLLMGuards": [
      {
        "name": "string",
        "satisfyCriteria": true,
        "stage": "prompt",
        "value": "string"
      }
    ],
    "totalTokenCount": 0
  },
  "resultText": "string",
  "text": "string",
  "userName": "string",
  "vectorDatabaseId": "string",
  "vectorDatabaseSettings": {
    "addNeighborChunks": false,
    "maxDocumentsRetrievedPerPrompt": 1,
    "maxTokens": 1
  }
}

ChatPromptResponse

Properties¶

Name	Type	Required	Description
chatContextId	string¦null	false	The ID of the chat context for this prompt.
chatId	string¦null	false	The ID of the chat this chat prompt belongs to.
chatPromptIdsIncludedInHistory	[string]¦null	false	The list of IDs of the chat prompts included in this prompt's history.
citations	[Citation]	true	The list of relevant vector database citations (in case of using a vector database).
confidenceScores	ConfidenceScores¦null	true	The confidence scores that measure the similarity between the prompt context and the prompt completion.
creationDate	string(date-time)	true	The creation date of the chat prompt (ISO 8601 formatted).
creationUserId	string	true	The ID of the user that created the chat prompt.
executionStatus	ExecutionStatus	true	The execution status of the chat prompt.
id	string	true	The ID of the chat prompt.
llmBlueprintId	string	true	The ID of the LLM blueprint the chat prompt belongs to.
llmId	LanguageModelTypeId	true	The ID of the LLM used by the chat prompt.
llmSettings	any	false	A key/value dictionary of LLM settings.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	CommonLLMSettings	false		The settings that are available for all non-custom LLMs.

or

Name	Type	Required	Restrictions	Description
» anonymous	CustomModelLLMSettings	false		The settings that are available for custom model LLMs.

continued

Name	Type	Required	Description
metadataFilter	object¦null	false	The metadata dictionary defining the filters that documents must match in order to be retrieved.
resultMetadata	ResultMetadata¦null	true	The additional information about the chat prompt results.
resultText	string¦null	true	The text of the prompt completion.
text	string	true	The text of the user prompt.
userName	string	true	The name of the user that created the chat prompt.
vectorDatabaseId	string¦null	false	The ID of the vector database linked to this LLM blueprint.
vectorDatabaseSettings	VectorDatabaseSettings¦null	false	A key/value dictionary of vector database settings.

Citation

{
  "chunkId": 0,
  "metadata": {},
  "page": 0,
  "similarityScore": 0,
  "source": "string",
  "startIndex": 0,
  "text": "string"
}

Citation

Properties¶

Name	Type	Required	Description
chunkId	integer¦null	false	The ID of the chunk in the vector database index.
metadata	object¦null	false	LangChain Document metadata information holder.
page	integer¦null	false	The source page number where the citation was found.
similarityScore	number¦null	false	The similarity score between the citation and the user prompt.
source	string¦null	true	The source of the citation (e.g., a filename in the original dataset).
startIndex	integer¦null	false	The chunk's start character index in the source document.
text	string	true	The text of the citation.

CommonLLMSettings

{
  "maxCompletionLength": 0,
  "systemPrompt": "string",
  "temperature": 0,
  "topP": 0
}

CommonLLMSettings

Properties¶

Name	Type	Required	Restrictions	Description
maxCompletionLength	integer¦null	false		Maximum number of tokens allowed in the completion. The combined count of this value and prompt tokens must be below the model's maximum context size, where prompt token count is comprised of system prompt, user prompt, recent chat history, and vector database citations.
systemPrompt	string¦null	false	maxLength: 500000	System prompt guides the style of the LLM response. It is a "universal" prompt, prepended to all individual prompts.
temperature	number¦null	false		Temperature controls the randomness of model output, where higher values return more diverse output and lower values return more deterministic results.
topP	number¦null	false		Top P sets a threshold that controls the selection of words included in the response, based on a cumulative probability cutoff for token selection. For example, 0.2 considers only the top 20% probability mass. Higher numbers return more diverse options for outputs.

ConfidenceScores

{
  "bleu": 0,
  "meteor": 0,
  "rouge": 0
}

ConfidenceScores

Properties¶

Name	Type	Required	Description
bleu	number	true	BLEU score.
meteor	number	true	METEOR score.
rouge	number	true	ROUGE score.

CreateChatPromptRequest

{
  "chatId": "string",
  "llmBlueprintId": "string",
  "llmId": "azure-openai-gpt-3.5-turbo",
  "llmSettings": {
    "maxCompletionLength": 0,
    "systemPrompt": "string",
    "temperature": 0,
    "topP": 0
  },
  "metadataFilter": {},
  "text": "string",
  "vectorDatabaseId": "string",
  "vectorDatabaseSettings": {
    "addNeighborChunks": false,
    "maxDocumentsRetrievedPerPrompt": 1,
    "maxTokens": 1
  }
}

CreateChatPromptRequest

Properties¶

Name	Type	Required	Description
chatId	string¦null	false	The ID of the chat this prompt belongs to. If LLM and vector database settings are not specified in the request, then the prompt will use the current settings of the chat.
llmBlueprintId	string¦null	false	The ID of the LLM blueprint this prompt belongs to. If LLM and vector database settings are not specified in the request, then the prompt will use the current settings of the LLM blueprint.
llmId	LanguageModelTypeId¦null	false	If specified, uses this LLM ID for the prompt and updates the settings of the corresponding chat or LLM blueprint to use this LLM ID.
llmSettings	any	false	If specified, uses these LLM settings for the prompt and updates the settings of the corresponding chat or LLM blueprint to use these LLM settings.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	CommonLLMSettings	false		The settings that are available for all non-custom LLMs.

or

Name	Type	Required	Restrictions	Description
» anonymous	CustomModelLLMSettings	false		The settings that are available for custom model LLMs.

continued

Name	Type	Required	Restrictions	Description
metadataFilter	object¦null	false		The metadata fields to add to the chat prompt.
text	string	true	maxLength: 500000	The text of the user prompt.
vectorDatabaseId	string¦null	false		If specified, uses this vector database ID for the prompt and updates the settings of the corresponding chat or LLM blueprint to use this vector database ID.
vectorDatabaseSettings	VectorDatabaseSettings¦null	false		If specified, uses these vector database settings for the prompt and updates the settings of the corresponding chat or LLM blueprint to use these vector database settings.

CustomModelLLMSettings

{
  "externalLlmContextSize": 128,
  "systemPrompt": "string",
  "validationId": "string"
}

CustomModelLLMSettings

Properties¶

Name	Type	Required	Restrictions	Description
externalLlmContextSize	integer¦null	false	maximum: 128000 minimum: 128	The external LLM's context size, in tokens. This value is only used for pruning documents supplied to the LLM when a vector database is associated with the LLM blueprint. It does not affect the external LLM's actual context size in any way and is not supplied to the LLM.
systemPrompt	string¦null	false	maxLength: 500000	System prompt guides the style of the LLM response. It is a "universal" prompt, prepended to all individual prompts.
validationId	string¦null	false		The validation ID of the custom model LLM.

ExecutionStatus

"NEW"

ExecutionStatus

Properties¶

Name	Type	Required	Restrictions	Description
ExecutionStatus	string	false		Job and entity execution status.

Enumerated Values¶

Property	Value
ExecutionStatus	[`NEW`, `RUNNING`, `COMPLETED`, `REQUIRES_USER_INPUT`, `SKIPPED`, `ERROR`]

FeedbackResult

{
  "negativeUserIds": [],
  "positiveUserIds": []
}

FeedbackResult

Properties¶

Name	Type	Required	Restrictions	Description
negativeUserIds	[string]	false		The list of user IDs whose feedback is negative.
positiveUserIds	[string]	false		The list of user IDs whose feedback is positive.

HTTPValidationErrorResponse

{
  "detail": [
    {
      "loc": [
        "string"
      ],
      "msg": "string",
      "type": "string"
    }
  ]
}

HTTPValidationErrorResponse

Properties¶

Name	Type	Required	Restrictions	Description
detail	[ValidationError]	false		none

LanguageModelTypeId

"azure-openai-gpt-3.5-turbo"

LanguageModelTypeId

Properties¶

Name	Type	Required	Restrictions	Description
LanguageModelTypeId	string	false		The ID that defines the type of the LLM.

Enumerated Values¶

Property	Value
LanguageModelTypeId	[`azure-openai-gpt-3.5-turbo`, `azure-openai-gpt-3.5-turbo-16k`, `azure-openai-gpt-4`, `azure-openai-gpt-4-32k`, `azure-openai-gpt-4-turbo`, `azure-openai-gpt-4-o`, `amazon-titan`, `anthropic-claude-2`, `anthropic-claude-3-haiku`, `anthropic-claude-3-sonnet`, `anthropic-claude-3-opus`, `google-bison`, `google-gemini-1.5-flash`, `google-gemini-1.5-pro`, `custom-model`]

ListChatPromptsResponse

{
  "count": 0,
  "data": [
    {
      "chatContextId": "string",
      "chatId": "string",
      "chatPromptIdsIncludedInHistory": [
        "string"
      ],
      "citations": [
        {
          "chunkId": 0,
          "metadata": {},
          "page": 0,
          "similarityScore": 0,
          "source": "string",
          "startIndex": 0,
          "text": "string"
        }
      ],
      "confidenceScores": {
        "bleu": 0,
        "meteor": 0,
        "rouge": 0
      },
      "creationDate": "2019-08-24T14:15:22Z",
      "creationUserId": "string",
      "executionStatus": "NEW",
      "id": "string",
      "llmBlueprintId": "string",
      "llmId": "azure-openai-gpt-3.5-turbo",
      "llmSettings": {
        "maxCompletionLength": 0,
        "systemPrompt": "string",
        "temperature": 0,
        "topP": 0
      },
      "metadataFilter": {},
      "resultMetadata": {
        "blockedResultText": "string",
        "cost": 0,
        "errorMessage": "string",
        "estimatedDocsTokenCount": 0,
        "feedbackResult": {
          "negativeUserIds": [],
          "positiveUserIds": []
        },
        "finalPrompt": "string",
        "inputTokenCount": 0,
        "latencyMilliseconds": 0,
        "metrics": [],
        "outputTokenCount": 0,
        "providerLLMGuards": [
          {
            "name": "string",
            "satisfyCriteria": true,
            "stage": "prompt",
            "value": "string"
          }
        ],
        "totalTokenCount": 0
      },
      "resultText": "string",
      "text": "string",
      "userName": "string",
      "vectorDatabaseId": "string",
      "vectorDatabaseSettings": {
        "addNeighborChunks": false,
        "maxDocumentsRetrievedPerPrompt": 1,
        "maxTokens": 1
      }
    }
  ],
  "next": "string",
  "previous": "string",
  "totalCount": 0
}

ListChatPromptsResponse

Properties¶

Name	Type	Required	Description
count	integer	true	The number of records on this page.
data	[ChatPromptResponse]	true	The list of records.
next	string¦null	true	The URL to the next page, or `null` if there is no such page.
previous	string¦null	true	The URL to the previous page, or `null` if there is no such page.
totalCount	integer	true	The total number of records.

MetricMetadata

{
  "costConfigurationId": "string",
  "customModelId": "string",
  "errorMessage": "string",
  "evaluationDatasetConfigurationId": "string",
  "executionStatus": "NEW",
  "formattedName": "string",
  "formattedValue": "string",
  "name": "string",
  "nemoMetricId": "string",
  "ootbMetricId": "string",
  "sidecarModelMetricValidationId": "string",
  "stage": "prompt_pipeline",
  "value": null
}

MetricMetadata

Properties¶

Name	Type	Required	Description
costConfigurationId	string¦null	false	The ID of the cost configuration.
customModelId	string¦null	false	The ID of the custom model used for the metric.
errorMessage	string¦null	false	The error message associated with the metric computation.
evaluationDatasetConfigurationId	string¦null	false	The ID of the evaluation dataset configuration.
executionStatus	ExecutionStatus¦null	false	The creation status of the vector database.
formattedName	string¦null	false	The formatted name of the metric.
formattedValue	string¦null	false	The formatted value of the metric.
name	string	true	The name of the metric.
nemoMetricId	string¦null	false	The id of the NeMo Pipeline configuration.
ootbMetricId	string¦null	false	The id of the OOTB metric configuration.
sidecarModelMetricValidationId	string¦null	false	The validation ID of the sidecar model validation(in case of using a sidecar model deployment for the metric).
stage	PipelineStage¦null	false	The stage (prompt or response) that the metric applies to.
value	any	true	The value of the metric.

PipelineStage

"prompt_pipeline"

PipelineStage

Properties¶

Name	Type	Required	Restrictions	Description
PipelineStage	string	false		Enum that describes at which stage the metric may be calculated.

Enumerated Values¶

Property	Value
PipelineStage	[`prompt_pipeline`, `response_pipeline`]

ProviderGuardStage

"prompt"

ProviderGuardStage

Properties¶

Name	Type	Required	Restrictions	Description
ProviderGuardStage	string	false		The data stage where the provider guard metric is acting upon.

Enumerated Values¶

Property	Value
ProviderGuardStage	[`prompt`, `response`]

ProviderGuardsMetadata

{
  "name": "string",
  "satisfyCriteria": true,
  "stage": "prompt",
  "value": "string"
}

ProviderGuardsMetadata

Properties¶

Name	Type	Required	Description
name	string	true	The name of the provider guard metric.
satisfyCriteria	boolean	true	Whether the configured provider guard metric satisfied its hidden internal guard criteria.
stage	ProviderGuardStage	true	The data stage where the provider guard metric is acting upon.
value	any	true	The value of the provider guard metric.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	number	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

ResultMetadata

{
  "blockedResultText": "string",
  "cost": 0,
  "errorMessage": "string",
  "estimatedDocsTokenCount": 0,
  "feedbackResult": {
    "negativeUserIds": [],
    "positiveUserIds": []
  },
  "finalPrompt": "string",
  "inputTokenCount": 0,
  "latencyMilliseconds": 0,
  "metrics": [],
  "outputTokenCount": 0,
  "providerLLMGuards": [
    {
      "name": "string",
      "satisfyCriteria": true,
      "stage": "prompt",
      "value": "string"
    }
  ],
  "totalTokenCount": 0
}

ResultMetadata

Properties¶

Name	Type	Required	Description
blockedResultText	string¦null	false	The message to replace the result text if it is non empty, which represents a blocked response.
cost	number¦null	false	The estimated cost of executing the prompt.
errorMessage	string¦null	false	The error message for the prompt (in case of an errored prompt).
estimatedDocsTokenCount	integer	false	The estimated number of tokens in the documents retrieved from the vector database.
feedbackResult	FeedbackResult	false	The user feedback associated with the prompt.
finalPrompt	any	false	The final representation of the prompt that was submitted to the LLM.

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	[object]	false		none
»» additionalProperties	any	false		none

anyOf

Name	Type	Required	Restrictions	Description
»»» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	[object]	false		none
»»»» additionalProperties	any	false		none

anyOf

Name	Type	Required	Restrictions	Description
»»»»» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
»»»»» anonymous	object	false		none
»»»»»» additionalProperties	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	object	false		none
»» additionalProperties	any	false		none

anyOf

Name	Type	Required	Restrictions	Description
»»» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
»»» anonymous	[object]	false		none
»»»» additionalProperties	string	false		none

continued

Name	Type	Required	Description
inputTokenCount	integer	false	The number of tokens in the LLM input. This number includes the tokens in the system prompt, the user prompt, the chat history (for history-aware chats) and the documents retrieved from the vector database (in case of using a vector database).
latencyMilliseconds	integer	true	The latency of the LLM response (in milliseconds).
metrics	[MetricMetadata]	false	The evaluation metrics for the prompt.
outputTokenCount	integer	false	The number of tokens in the LLM output.
providerLLMGuards	[ProviderGuardsMetadata]¦null	false	The provider llm guards metadata.
totalTokenCount	integer	false	The combined number of tokens in the LLM input and output.

ValidationError

{
  "loc": [
    "string"
  ],
  "msg": "string",
  "type": "string"
}

ValidationError

Properties¶

Name	Type	Required	Restrictions	Description
loc	[anyOf]	true		none

anyOf

Name	Type	Required	Restrictions	Description
» anonymous	string	false		none

or

Name	Type	Required	Restrictions	Description
» anonymous	integer	false		none

continued

Name	Type	Required	Restrictions	Description
msg	string	true		none
type	string	true		none

VectorDatabaseSettings

{
  "addNeighborChunks": false,
  "maxDocumentsRetrievedPerPrompt": 1,
  "maxTokens": 1
}

VectorDatabaseSettings

Properties¶

Name	Type	Required	Restrictions	Description
addNeighborChunks	boolean	false		Add neighboring chunks to those that the similarity search retrieves, such that when selected, search returns i, i-1, and i+1.
maxDocumentsRetrievedPerPrompt	integer¦null	false	maximum: 10 minimum: 1	The maximum number of chunks to retrieve from the vector database.
maxTokens	integer¦null	false	maximum: 51200 minimum: 1	The maximum number of tokens to retrieve from the vector database.

更新しました January 15, 2025

このページは役に立ちましたか？

ありがとうございます。どのような点が役に立ちましたか？

より良いコンテンツを提供するには、どうすればよいでしょうか？

アンケートにご協力いただき、ありがとうございました。