From dce1395529c8497c4b799322482a5f4495eed6b0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Tiago=20Ara=C3=BAjo=20=5BSSW=5D?= Date: Thu, 11 Jun 2026 15:11:32 -0700 Subject: [PATCH] Update deployment instructions for AI models Improvements to https://ssweagleeye.com/docs/deploy-ai-model As per --- content/docs/EagleEye/deploy-ai-model.mdx | 60 ++++++++++++----------- 1 file changed, 32 insertions(+), 28 deletions(-) diff --git a/content/docs/EagleEye/deploy-ai-model.mdx b/content/docs/EagleEye/deploy-ai-model.mdx index 2df54ad2..ad872ea3 100644 --- a/content/docs/EagleEye/deploy-ai-model.mdx +++ b/content/docs/EagleEye/deploy-ai-model.mdx @@ -23,7 +23,7 @@ If you plan to use **Non-AI Tags** only, you can skip this guide. At the moment, EagleEye supports **chat models only**, so make sure you choose a compatible chat model. -**EagleEye supported models include:** +✅ **EagleEye supported models include:** * `gpt-4.1-mini (recommended)` * `gpt-4o-mini` @@ -32,7 +32,7 @@ At the moment, EagleEye supports **chat models only**, so make sure you choose a * `gpt-4.1`, `gpt-4o` * `gpt-3.5-turbo` -**Do not use:** +⚠️ **Do not use:** * Reasoning models such as `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-5-pro`, `gpt-5-codex`, `gpt-5.4-mini`, `o1`, `o1-mini`, `o3-mini`, `o4-mini` * Non-OpenAI Foundry catalog models such as Llama, Mistral, Grok, DeepSeek, Cohere, Kimi, `gpt-oss-*`, and Phi @@ -40,28 +40,31 @@ At the moment, EagleEye supports **chat models only**, so make sure you choose a ## Step 1 - Deploy an AI chat model in Azure AI Foundry -You have two options. Pick the one that best fits your workflow. +You have 2 options. Pick the one that best fits your workflow. ### Option A - Deploy via Azure AI Foundry portal -1. Go to your EagleEye resource group used during Step 3 installation (e.g., `Northwind.EagleEye.RG`). -2. Find your `openai-shared-xxx` resource and open it. +1. Go to your EagleEye resource group used during Step 3 installation (e.g., `Northwind.EagleEye.RG`) +2. Find your `openai-shared-xxx` resource and open it ![](/EagleEye/Guides/OpenAI-Shared.png) -3. Click **Go to Azure AI Foundry portal**. +3. Click **Go to Azure AI Foundry portal** ![](/EagleEye/Guides/Foundry-Portal-Link.png) -4. In Foundry portal, click **Model catalog**. +4. In Foundry portal, click **Model catalog** ![](/EagleEye/Guides/Model-Catalog.png) 5. Pick a compatible chat model > Use this model ![](/EagleEye/Guides/GPT-4.1-Mini.png) 6. On the deployment screen, set: * **Deployment name** to exactly `eagleeye` - * **Deployment type** to `Global Standard` if available. If not, choose another compatible deployment type with available quota. + * **Deployment type** to `Global Standard` if available. If not, choose another compatible deployment type with available quota * **Tokens per Minute Rate Limit** to at least `100` ![](/EagleEye/Guides/Model-Config.png) -7. Click **Deploy** and wait for the deployment to become active. +7. Click **Deploy** and wait for the deployment to become active -> **Important:** -> The deployment name must be exactly `eagleeye`. If you use a different name, EagleEye will fail to find the model at runtime. + + ❗️ **Important:** The deployment name must be exactly `eagleeye`. If you use a different name, EagleEye will fail to find the model at runtime. + } +/> ### Option B - Deploy via AI agent @@ -76,14 +79,17 @@ Create the deployment with the name exactly `eagleeye`. The agent should: -1. Ask for the resource group you used during Step 3 installation (e.g., `Northwind.EagleEye.RG`). -2. Find the `openai-shared-xxx` Azure OpenAI resource in that resource group. -3. Show which compatible non-reasoning chat models have available quota. -4. Ask which model and capacity you want to deploy. -5. Create the deployment with the exact name `eagleeye`. +1. Ask for the resource group you used during Step 3 installation (e.g., `Northwind.EagleEye.RG`) +2. Find the `openai-shared-xxx` Azure OpenAI resource in that resource group +3. Show which compatible non-reasoning chat models have available quota +4. Ask which model and capacity you want to deploy +5. Create the deployment with the exact name `eagleeye` -> **Tip:** -> Review the commands your agent proposes before approving them. AI agents can still make mistakes. + + 💡 **Tip:** Review the commands your agent proposes before approving them. AI agents can still make mistakes. + } +/> ## Step 2 - Verify AI email analysis works @@ -99,19 +105,15 @@ Use EagleEye's built-in test flow to verify the model deployment without sending 4\. In the **AI decision prompt** field, enter a simple test prompt such as: -```text -Check if the email has been checked by someone by looking for keywords like "Checked by xx", "Checked by xx & xx", or similar variations. -``` +> Check if the email has been checked by someone by looking for keywords like "Checked by xx", "Checked by xx & xx", or similar variations. 5\. Paste sample email content such as: -```plain -(Checked by Adam) - -Hi team, I just checked the invoice from Acme Corp and everything looks good. -Regards, -Hark -``` +> (Checked by Adam) +> +> Hi team, I just checked the invoice from Acme Corp and everything looks good. +> Regards, +> Hark 6\. Click **Test**. @@ -127,6 +129,8 @@ Hark } /> +--- + ## References * [Step 3 - Install from Azure Marketplace](./step-3-install-from-marketplace)