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2 | 2 | uid: ai-assistant |
3 | 3 | title: AI 助手 |
4 | 4 | author: Morten Lønskov |
5 | | -updated: 2026-03-19 |
| 5 | +updated: 2026-04-15 |
6 | 6 | applies_to: |
7 | 7 | products: |
8 | 8 | - product: Tabular Editor 2 |
@@ -72,7 +72,31 @@ AI 助手采用自带密钥 BYOK 模式。 你只需从受支持的提供商中 |
72 | 72 |
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73 | 73 | ### Azure OpenAI |
74 | 74 |
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75 | | -选择 **Azure OpenAI** 作为提供商。 输入你的 API 密钥,以及 Azure OpenAI 资源的服务端点 URL。 将模型名称设置为与你的部署名称保持一致。 |
| 75 | +Select **Azure OpenAI** as the provider and configure three fields: |
| 76 | + |
| 77 | +- **API key** — the access key for your Azure OpenAI resource |
| 78 | +- **Service endpoint** — the endpoint URL for your resource, for example `https://your-resource.openai.azure.com`. Use the resource URL, not the `privatelink` alias; the SSL certificate is issued for `*.openai.azure.com` and connecting directly to `*.privatelink.openai.azure.com` fails certificate validation |
| 79 | +- **Model name** — the **deployment name**, not the underlying model name and not the resource name |
| 80 | + |
| 81 | +Azure OpenAI requires the deployment name in every API call. A deployment name is chosen when the deployment is created, so it can be any string. Deployments are often named after the model they serve (for example `gpt-4o`), but that is a convention, not a requirement. If you enter the resource name or a raw model name that does not exist as a deployment, the request fails. |
| 82 | + |
| 83 | +#### Finding your deployment name |
| 84 | + |
| 85 | +In the [Azure AI Foundry portal](https://ai.azure.com): |
| 86 | + |
| 87 | +1. Sign in and select your Azure OpenAI resource |
| 88 | +2. Open **Deployments** (or **Models + endpoints** if the resource has been upgraded to Foundry) |
| 89 | +3. Copy the value from the **Name** column |
| 90 | + |
| 91 | +Deployments created before your organization adopted Azure AI Foundry may not appear in the portal. List them from the Azure CLI: |
| 92 | + |
| 93 | +```bash |
| 94 | +az cognitiveservices account deployment list --name "<resource-name>" --resource-group "<resource-group>" --output table |
| 95 | +``` |
| 96 | + |
| 97 | +See [Create and deploy an Azure OpenAI resource](https://learn.microsoft.com/azure/ai-foundry/openai/how-to/create-resource#deploy-a-model) for more details. |
| 98 | + |
| 99 | +For 403 errors, SSL failures or "DeploymentNotFound" responses, see @azure-openai-connection-errors. |
76 | 100 |
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77 | 101 | ### 自定义(OpenAI 兼容) |
78 | 102 |
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@@ -296,7 +320,7 @@ AI 助手在向 AI 提供商发送数据之前会先征求你的同意。 同意 |
296 | 320 |
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297 | 321 | 其他减少 token 使用量的方法: |
298 | 322 |
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299 | | -- 围绕特定的表、度量值或列提出更聚焦的问题,而不是对整个模型提出泛泛的问题 |
| 323 | +- Ask focused questions about specific tables, measures or columns rather than broad questions about the entire model. A vague prompt such as _"Set display folders on all measures"_ forces the assistant to retrieve metadata for the entire model. A specific prompt such as _"Set display folders on the measures I have selected"_ limits the context to the current selection and uses far fewer tokens |
300 | 324 | - 切换话题时开启新对话,避免累积过长的对话历史 |
301 | 325 | - 进行探索性提问时,使用更小或成本更低的模型 |
302 | 326 |
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