Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Ringkasan
Untuk memberikan saran, Agent Assist mengandalkan data dalam bentuk dokumen atau transkrip percakapan. Anda harus mengupload data sebelum dapat menggunakan Agent Assist. Tutorial tertaut di bagian bawah halaman ini akan memandu Anda melakukan langkah-langkah yang diperlukan untuk mengupload data menggunakan konsol Agent Assist.
Anda dapat menggunakan konsol untuk mengonfigurasi fitur Agent Assist dan menguji cara kerjanya.
Jenis data
Agent Assist menggunakan dua jenis data untuk memberikan saran kepada agen manusia:
Set data percakapan, yang merupakan kumpulan transkrip percakapan,
dan pusat informasi, yang merupakan kumpulan dokumen informasi
(artikel atau dokumen FAQ). Fitur Agent Assist menganalisis percakapan secara real-time dan memberikan saran kepada agen manusia berdasarkan set data percakapan atau basis pengetahuan.
Smart Reply dan
Summarization menampilkan saran yang dilatih pada set data percakapan. Smart Reply menyarankan respons teks kepada agen saat mereka bercakap-cakap dengan pengguna akhir, dan Ringkasan menyarankan ringkasan percakapan setelah percakapan dengan pengguna akhir selesai. Setiap model secara definisi bersifat kustom karena setiap set data percakapan terdiri dari data transkrip percakapan Anda sendiri.
Fitur Bantuan FAQ dan
Saran Artikel memanfaatkan
pusat informasi untuk memberikan rekomendasi, bukan set data percakapan. Saran Artikel
menyarankan dokumen pengetahuan (seperti artikel) kepada agen selama
percakapan. Bantuan FAQ memberikan saran berdasarkan pasangan FAQ (pertanyaan FAQ dan jawaban terkait) dan bukan seluruh artikel. Anda tidak perlu melatih model kustom untuk menggunakan fitur ini: Agent Assist menggunakan model saran dasar default untuk memberikan saran dari basis pengetahuan Anda. Jika Anda ingin mengupload data percakapan Anda sendiri untuk melatih model saran kustom untuk Saran Artikel, hubungi perwakilan Google Anda. Model saran kustom tidak tersedia untuk Bantuan FAQ.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[[["\u003cp\u003eAgent Assist uses either conversation transcripts or knowledge documents to provide suggestions, requiring data upload before use.\u003c/p\u003e\n"],["\u003cp\u003eConversation datasets, used for features like Smart Reply and Summarization, are collections of conversation transcripts that train custom suggestion models.\u003c/p\u003e\n"],["\u003cp\u003eKnowledge bases, used for FAQ Assist and Article Suggestion, are collections of knowledge documents that use baseline suggestion models, without requiring custom model training.\u003c/p\u003e\n"],["\u003cp\u003eThe Agent Assist console is utilized for design-time and model testing, while all live operations must be executed via the API.\u003c/p\u003e\n"],["\u003cp\u003eUsers can begin by creating a conversation dataset or a knowledge base to start using Agent Assist features.\u003c/p\u003e\n"]]],[],null,["# Upload data\n\nOverview\n--------\n\nIn order to make suggestions, Agent Assist relies on data in the form of\neither documents or conversation transcripts. You must upload your data\nbefore you can use Agent Assist. The linked tutorials at the bottom of\nthis page walk you through the steps required to upload your data using the\n[Agent Assist console](https://agentassist.cloud.google.com).\nYou can use the console to configure Agent Assist features and test out\nhow they function.\n| **Note:** The Agent Assist console can be used during design-time and model testing phases only. All runtime operations must call the API directly. You can use the API to carry out the same actions described in the [tutorials](/agent-assist/docs/tutorials), which focus on using the console. See the Agent Assist [how-to guides](/agent-assist/docs/how-to) for details on sending API requests.\n\nData types\n----------\n\nAgent Assist uses two types of data to make suggestions to human agents:\n**Conversation datasets** , which are collections of conversation transcripts,\nand **knowledge bases** , which are collections of *knowledge documents*\n(articles or FAQ documents). Agent Assist features analyze a conversation\nin real time and make suggestions to human agents based on either conversation\ndatasets or knowledge bases.\n\n[Smart Reply](/agent-assist/docs/smart-reply) and\n[Summarization](/agent-assist/docs/summarization-console) surface suggestions\ntrained on conversation datasets. Smart Reply suggests text responses to agents\nas they converse with an end-user, and Summarization suggests conversation\nsummaries after an exchange with an end-user has completed. Each model is custom\nby definition because each conversation dataset is made up of your own\nconversation transcript data.\n\nThe [FAQ Assist](/agent-assist/docs/faq) and\n[Article Suggestion](/agent-assist/docs/article-suggestion) features draw on\nknowledge bases to make recommendations instead of conversation datsets. Article\nSuggestion suggests *knowledge documents* (such as articles) to agents during a\nconversation. FAQ Assist makes suggestions based on FAQ pairs (an FAQ question\nand its associated answer) rather than entire articles. You do not need\nto train a custom model in order to use these features: Agent Assist\nuses default baseline suggestion models to make suggestions from your\nknowledge base. If you want to upload your own conversation data to train a\ncustom suggestion model for Article Suggestion, please contact your Google\nrepresentative. Custom suggestion models are not available for FAQ Assist.\n\nWhat's next\n-----------\n\nCreate a [conversation dataset](/agent-assist/docs/conversation-dataset) or a\n[knowledge base](/agent-assist/docs/knowledge-base)."]]
