Close httplib2 connections.
generate(parent, body=None, x__xgafv=None)
Generates and returns a suggestion for a conversation that does not have a resource created for it.
close()
Close httplib2 connections.
generate(parent, body=None, x__xgafv=None)
Generates and returns a suggestion for a conversation that does not have a resource created for it.
Args:
parent: string, Required. The parent resource to charge for the Suggestion's generation. Format: `projects//locations/`. (required)
body: object, The request body.
The object takes the form of:
{ # The request message for Conversations.GenerateStatelessSuggestion.
"contextReferences": { # Optional. A section of ingested context information. The key is the name of the context reference and the value contains the contents of the context reference. The key is used to incorporate ingested context references to enhance the generator.
"a_key": { # Represents a piece of ingested context information.
"contextContents": [ # Required. The list of content updates for a context reference.
{ # Contents ingested.
"content": "A String", # Required. The information ingested in a single request.
"contentFormat": "A String", # Required. The format of the ingested string.
"ingestionTime": "A String", # Output only. The time when this information was incorporated into the relevant context reference.
},
],
"createTime": "A String", # Output only. The time the context reference was first created.
"languageCode": "A String", # Optional. The language of the information ingested, defaults to "en-US" if not set.
"updateMode": "A String", # Required. The mode in which context reference contents are updated.
},
},
"conversationContext": { # Context of the conversation, including transcripts. # Optional. Context of the conversation, including transcripts.
"messageEntries": [ # Optional. List of message transcripts in the conversation.
{ # Represents a message entry of a conversation.
"createTime": "A String", # Optional. Create time of the message entry.
"languageCode": "A String", # Optional. The language of the text. See [Language Support](https://cloud.google.com/dialogflow/docs/reference/language) for a list of the currently supported language codes.
"role": "A String", # Optional. Participant role of the message.
"text": "A String", # Optional. Transcript content of the message.
},
],
},
"generator": { # LLM generator. # Uncreated generator. It should be a complete generator that includes all information about the generator.
"createTime": "A String", # Output only. Creation time of this generator.
"description": "A String", # Optional. Human readable description of the generator.
"freeFormContext": { # Free form generator context that customer can configure. # Input of free from generator to LLM.
"text": "A String", # Optional. Free form text input to LLM.
},
"inferenceParameter": { # The parameters of inference. # Optional. Inference parameters for this generator.
"maxOutputTokens": 42, # Optional. Maximum number of the output tokens for the generator.
"temperature": 3.14, # Optional. Controls the randomness of LLM predictions. Low temperature = less random. High temperature = more random. If unset (or 0), uses a default value of 0.
"topK": 42, # Optional. Top-k changes how the model selects tokens for output. A top-k of 1 means the selected token is the most probable among all tokens in the model's vocabulary (also called greedy decoding), while a top-k of 3 means that the next token is selected from among the 3 most probable tokens (using temperature). For each token selection step, the top K tokens with the highest probabilities are sampled. Then tokens are further filtered based on topP with the final token selected using temperature sampling. Specify a lower value for less random responses and a higher value for more random responses. Acceptable value is [1, 40], default to 40.
"topP": 3.14, # Optional. Top-p changes how the model selects tokens for output. Tokens are selected from most K (see topK parameter) probable to least until the sum of their probabilities equals the top-p value. For example, if tokens A, B, and C have a probability of 0.3, 0.2, and 0.1 and the top-p value is 0.5, then the model will select either A or B as the next token (using temperature) and doesn't consider C. The default top-p value is 0.95. Specify a lower value for less random responses and a higher value for more random responses. Acceptable value is [0.0, 1.0], default to 0.95.
},
"name": "A String", # Output only. Identifier. The resource name of the generator. Format: `projects//locations//generators/`
"publishedModel": "A String", # Optional. The published Large Language Model name. * To use the latest model version, specify the model name without version number. Example: `text-bison` * To use a stable model version, specify the version number as well. Example: `text-bison@002`.
"summarizationContext": { # Summarization context that customer can configure. # Input of Summarization feature.
"fewShotExamples": [ # Optional. List of few shot examples.
{ # Providing examples in the generator (i.e. building a few-shot generator) helps convey the desired format of the LLM response.
"conversationContext": { # Context of the conversation, including transcripts. # Optional. Conversation transcripts.
"messageEntries": [ # Optional. List of message transcripts in the conversation.
{ # Represents a message entry of a conversation.
"createTime": "A String", # Optional. Create time of the message entry.
"languageCode": "A String", # Optional. The language of the text. See [Language Support](https://cloud.google.com/dialogflow/docs/reference/language) for a list of the currently supported language codes.
"role": "A String", # Optional. Participant role of the message.
"text": "A String", # Optional. Transcript content of the message.
},
],
},
"extraInfo": { # Optional. Key is the placeholder field name in input, value is the value of the placeholder. E.g. instruction contains "@price", and ingested data has <"price", "10">
"a_key": "A String",
},
"output": { # Suggestion generated using a Generator. # Required. Example output of the model.
"freeFormSuggestion": { # Suggestion generated using free form generator. # Optional. Free form suggestion.
"response": "A String", # Required. Free form suggestion.
},
"summarySuggestion": { # Suggested summary of the conversation. # Optional. Suggested summary.
"summarySections": [ # Required. All the parts of generated summary.
{ # A component of the generated summary.
"section": "A String", # Required. Name of the section.
"summary": "A String", # Required. Summary text for the section.
},
],
},
"toolCallInfo": [ # Optional. List of request and response for tool calls executed.
{ # Request and response for a tool call.
"toolCall": { # Represents a call of a specific tool's action with the specified inputs. # Required. Request for a tool call.
"action": "A String", # Required. The name of the tool's action associated with this call.
"createTime": "A String", # Output only. Create time of the tool call.
"inputParameters": { # Optional. The action's input parameters.
"a_key": "", # Properties of the object.
},
"tool": "A String", # Required. The tool associated with this call. Format: `projects//locations//tools/`.
},
"toolCallResult": { # The result of calling a tool's action. # Required. Response for a tool call.
"action": "A String", # Required. The name of the tool's action associated with this call.
"content": "A String", # Only populated if the response content is utf-8 encoded.
"createTime": "A String", # Output only. Create time of the tool call result.
"error": { # An error produced by the tool call. # The tool call's error.
"message": "A String", # Optional. The error message of the function.
},
"rawContent": "A String", # Only populated if the response content is not utf-8 encoded. (by definition byte fields are base64 encoded).
"tool": "A String", # Required. The tool associated with this call. Format: `projects//locations//tools/`.
},
},
],
},
"summarizationSectionList": { # List of summarization sections. # Summarization sections.
"summarizationSections": [ # Optional. Summarization sections.
{ # Represents the section of summarization.
"definition": "A String", # Optional. Definition of the section, for example, "what the customer needs help with or has question about."
"key": "A String", # Optional. Name of the section, for example, "situation".
"type": "A String", # Optional. Type of the summarization section.
},
],
},
},
],
"outputLanguageCode": "A String", # Optional. The target language of the generated summary. The language code for conversation will be used if this field is empty. Supported 2.0 and later versions.
"summarizationSections": [ # Optional. List of sections. Note it contains both predefined section sand customer defined sections.
{ # Represents the section of summarization.
"definition": "A String", # Optional. Definition of the section, for example, "what the customer needs help with or has question about."
"key": "A String", # Optional. Name of the section, for example, "situation".
"type": "A String", # Optional. Type of the summarization section.
},
],
"version": "A String", # Optional. Version of the feature. If not set, default to latest version. Current candidates are ["1.0"].
},
"tools": [ # Optional. Resource names of the tools that the generator can choose from. Format: `projects//locations//tools/`.
"A String",
],
"triggerEvent": "A String", # Optional. The trigger event of the generator. It defines when the generator is triggered in a conversation.
"updateTime": "A String", # Output only. Update time of this generator.
},
"generatorName": "A String", # The resource name of the existing created generator. Format: `projects//locations//generators/`
"triggerEvents": [ # Optional. A list of trigger events. Generator will be triggered only if it's trigger event is included here.
"A String",
],
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The response message for Conversations.GenerateStatelessSuggestion.
"generatorSuggestion": { # Suggestion generated using a Generator. # Required. Generated suggestion for a conversation.
"freeFormSuggestion": { # Suggestion generated using free form generator. # Optional. Free form suggestion.
"response": "A String", # Required. Free form suggestion.
},
"summarySuggestion": { # Suggested summary of the conversation. # Optional. Suggested summary.
"summarySections": [ # Required. All the parts of generated summary.
{ # A component of the generated summary.
"section": "A String", # Required. Name of the section.
"summary": "A String", # Required. Summary text for the section.
},
],
},
"toolCallInfo": [ # Optional. List of request and response for tool calls executed.
{ # Request and response for a tool call.
"toolCall": { # Represents a call of a specific tool's action with the specified inputs. # Required. Request for a tool call.
"action": "A String", # Required. The name of the tool's action associated with this call.
"createTime": "A String", # Output only. Create time of the tool call.
"inputParameters": { # Optional. The action's input parameters.
"a_key": "", # Properties of the object.
},
"tool": "A String", # Required. The tool associated with this call. Format: `projects//locations//tools/`.
},
"toolCallResult": { # The result of calling a tool's action. # Required. Response for a tool call.
"action": "A String", # Required. The name of the tool's action associated with this call.
"content": "A String", # Only populated if the response content is utf-8 encoded.
"createTime": "A String", # Output only. Create time of the tool call result.
"error": { # An error produced by the tool call. # The tool call's error.
"message": "A String", # Optional. The error message of the function.
},
"rawContent": "A String", # Only populated if the response content is not utf-8 encoded. (by definition byte fields are base64 encoded).
"tool": "A String", # Required. The tool associated with this call. Format: `projects//locations//tools/`.
},
},
],
},
}