AI Search Open Platform provides component-based services for intelligent search and Retrieval-Augmented Generation (RAG), including document parsing, document chunking, text embedding, retrieval, re-ranking, and large language model answer generation. The following example uses the text embedding service to show how to access the platform through the console, API, or SDKs.
Prerequisites
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You have activated AI Search Open Platform. For more information, see Activate service.
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To call the service via an API or SDK, you need an API key. For more information, see Manage API keys.
Try the service in the console
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Log on to the AI Search Open Platform console.
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Select the China (Shanghai) region, and then select the AI Search Open Platform service.
Note-
AI Search Open Platform is available only in the China (Shanghai) and Germany (Frankfurt) regions.
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Users in the China (Hangzhou), China (Shenzhen), China (Beijing), China (Zhangjiakou), and China (Qingdao) regions can use a VPC endpoint to call AI Search Open Platform services across regions.
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In the navigation pane, choose Experience Center.
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For Service Category, select Text Embedding, and then select a specific vector service type.
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Use document to vectorize documents from a knowledge base. Use Query to vectorize search queries.
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Click Get Results to generate a text embedding for the input text.
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Result: Shows the generated text embedding.
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Result source code: Displays the response code. You can click Copy Code or Download File to save the code locally.
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Sample code: Shows sample calls using curl and Python.
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Call service via API or SDK
For more information, see text embedding and sparse text embedding.