[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC):2025-09-04。"],[[["\u003cp\u003eAgent Assist Summarization provides conversation summaries to agents, aiding in the creation of conversation notes and understanding end-user communication history.\u003c/p\u003e\n"],["\u003cp\u003eThe summarization feature can be implemented using either a custom model or an out-of-the-box baseline model for both chat and voice interactions.\u003c/p\u003e\n"],["\u003cp\u003eTo use the baseline summarization model, you must create a conversation profile and, instead of providing a model ID, set the \u003ccode\u003ebaseline_model_version\u003c/code\u003e to \u003ccode\u003e1.0\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eThe baseline model is configured within a conversation profile by setting the appropriate \u003ccode\u003esuggestionFeature\u003c/code\u003e type, either \u003ccode\u003eCONVERSATION_SUMMARIZATION\u003c/code\u003e for chat or \u003ccode\u003eCONVERSATION_SUMMARIZATION_VOICE\u003c/code\u003e for voice, within the \u003ccode\u003efeatureConfigs\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eThe page provided outlines the necessary steps to configure and implement the baseline model for conversation summarization.\u003c/p\u003e\n"]]],[],null,["# Summarization V1 baseline model for chat and voice\n\nThe Agent Assist Summarization provides\nconversation summaries to your agents after each conversation completes.\nThe summaries help agents create their conversation notes to review and understand\nend-user communication history.\n\nThis feature is available in the following regions:\nus-central1, us-east1, us-west1, us, northamerica-northeast1, europe-west1, europe-west2, europe-west3, asia-southeast1, asia-northeast1, asia-south1, australia-southeast1, global.\n\nThere are two ways to implement the Summarization feature:\n\n- You can train a *custom model* ([chat](/agent-assist/docs/summarization) or [voice](/agent-assist/priv/docs/summarization-voice)).\n- You can use the out-of-the-box *baseline model* (chat and voice).\n\nThis page provides the steps required to implement the baseline model.\n\nFor example, here is a sample input conversation:\n\nA baseline model summary output about the conversation might look similar to the\nfollowing:\n\n| **Note:** Low quality summaries might get deleted. In these cases the returned summaries are empty.\n\nConfigure a conversation profile\n--------------------------------\n\nA *conversation profile* configures a set of parameters that control the\nsuggestions made to an agent during a conversation. The following steps create a\n[`ConversationProfile`](/dialogflow/es/docs/reference/rest/v2/projects.conversationProfiles)\nwith a\n[`HumanAgentAssistantConfig`](/dialogflow/es/docs/reference/rest/v2/projects.conversationProfiles#ConversationProfile.HumanAgentAssistantConfig)\nobject.\n\n### Create a conversation profile\n\n| **Note:** If using Agent Assist's [`generateStatelessSummary`](/dialogflow/es/docs/reference/rest/v2beta1/projects.locations.suggestions/generateStatelessSummary) API, this step can be skipped to instead provide the fields of the [conversation profile](/dialogflow/es/docs/reference/rest/v2/projects.conversationProfiles) within the request.\n\nTo create a conversation profile, do the following:\n\n1. Call the `create` method on the [`ConversationProfile`](/dialogflow/es/docs/reference/rest/v2/projects.conversationProfiles) resource.\n2. Provide a name for the new conversation profile.\n3. Enter your Google Cloud project ID.\n4. Enter your model ID. To use the baseline summarization model, don't specify the model ID. Instead, set `baseline_model_version` to `1.0`.\n5. In the `CreateConversationProfileRequest` for the suggestion feature, specify `CONVERSATION_SUMMARIZATION` for chat or `CONVERSATION_SUMMARIZATION_VOICE` for voice.\n\n### Baseline model example for voice\n\nThe following is a JSON example that uses a baseline summarization model for voice: \n\n```\n{\n \"parent\": \"projects/PROJECT_ID/locations/global\",\n \"conversationProfile\": {\n \"displayName\": \"CONVERSATION_PROFILE_NAME\",\n \"humanAgentAssistantConfig\": {\n \"humanAgentSuggestionConfig\": {\n \"featureConfigs\": [{\n \"suggestionFeature\": {\n \"type\": \"CONVERSATION_SUMMARIZATION_VOICE\"\n },\n \"conversationModelConfig\": {\n \"baseline_model_version\": \"1.0\",\n }\n }]\n }\n },\n \"languageCode\": \"en-US\"\n }\n}\n```\n\nThe response is a `ConversationProfile` object containing the conversation\nprofile `name`: \n\n```\n{\n \"name\": \"projects/PROJECT_ID/locations/global/conversationProfiles/CONVERSATION_PROFILE_ID\",\n \"displayName\": \"CONVERSATION_PROFILE_NAME\",\n \"automatedAgentConfig\": {\n },\n \"humanAgentAssistantConfig\": {\n \"notificationConfig\": {\n },\n \"humanAgentSuggestionConfig\": {\n \"featureConfigs\": [{\n \"suggestionFeature\": {\n \"type\": \"CONVERSATION_SUMMARIZATION_VOICE\"\n },\n \"conversationModelConfig\": {\n }\n }]\n },\n \"messageAnalysisConfig\": {\n }\n },\n \"languageCode\": \"en-US\",\n \"createTime\": \"2022-06-06T21:06:46.841816Z\",\n \"updateTime\": \"2022-06-06T21:06:46.841816Z\",\n \"projectNumber\": \"344549229138\"\n}\n```\n\n### Baseline model example for chat\n\nThe following is a JSON example that uses a baseline summarization model for chat: \n\n```\n{\n \"parent\": \"projects/PROJECT_ID/locations/global\",\n \"conversationProfile\": {\n \"displayName\": \"CONVERSATION_PROFILE_NAME\",\n \"humanAgentAssistantConfig\": {\n \"humanAgentSuggestionConfig\": {\n \"featureConfigs\": [{\n \"suggestionFeature\": {\n \"type\": \"CONVERSATION_SUMMARIZATION\"\n },\n \"conversationModelConfig\": {\n \"baseline_model_version\": \"1.0\",\n }\n }]\n }\n },\n \"languageCode\": \"en-US\"\n }\n}\n```\n\nThe response is a `ConversationProfile` object containing the conversation\nprofile `name`: \n\n```\n{\n \"name\": \"projects/PROJECT_ID/locations/global/conversationProfiles/CONVERSATION_PROFILE_ID\",\n \"displayName\": \"CONVERSATION_PROFILE_NAME\",\n \"automatedAgentConfig\": {\n },\n \"humanAgentAssistantConfig\": {\n \"notificationConfig\": {\n },\n \"humanAgentSuggestionConfig\": {\n \"featureConfigs\": [{\n \"suggestionFeature\": {\n \"type\": \"CONVERSATION_SUMMARIZATION\"\n },\n \"conversationModelConfig\": {\n }\n }]\n },\n \"messageAnalysisConfig\": {\n }\n },\n \"languageCode\": \"en-US\",\n \"createTime\": \"2022-06-06T21:06:46.841816Z\",\n \"updateTime\": \"2022-06-06T21:06:46.841816Z\",\n \"projectNumber\": \"344549229138\"\n}\n```\n\nHandle conversations at runtime\n-------------------------------\n\nConversations are handled the same at runtime whether you're using the baseline model or a custom model. See the\n[Summarization custom model](/agent-assist/docs/summarization#handle_conversations_at_runtime)\ndocumentation for details."]]