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docs/DeploymentGuide.md

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**⚠️ Deployment Issues:** If you encounter errors or timeouts, try a different region as there may be capacity constraints. For detailed error solutions, see our [Troubleshooting Guide](./TroubleShootingSteps.md).
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## Step 5: Post-Deployment Script
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## Step 5: Post Deployment Configuration
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The post deployment process is very straightforward and simplified via a single [deployment script](../Deployment/resourcedeployment.ps1) that completes in approximately 20-30 minutes:
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### Automated Deployment Steps:
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- Docker build and push container images to Azure Container Registry.
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- Display the deployment result and following instructions.
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### 5.1 Script Execution
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### 5.1 Execute the Script
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#### 5.1.1 Open PowerShell, change directory where you code cloned, then run the deploy script:
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```shell
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cd .\Deployment\
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```
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#### 5.1.2 Choose the appropriate command based on your deployment method:
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**If you deployed using `azd up` command:**
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```shell
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.\resourcedeployment.ps1
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```
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**If you deployed using custom templates, ARM/Bicep deployments, or `az deployment group` commands:**
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```shell
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.\resourcedeployment.ps1 -ResourceGroupName "<your-resource-group-name>"
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```
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> **Note:** Replace `<your-resource-group-name>` with the actual name of the resource group containing your deployed Azure resources.
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> **💡 Tip**: Since this guide is for azd deployment, you'll typically use the first command without the `-ResourceGroupName` parameter.
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If you run into issue with PowerShell script file not being digitally signed, you can execute below command:
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```shell
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powershell.exe -ExecutionPolicy Bypass -File ".\resourcedeployment.ps1"
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```
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#### 5.1.3 You will be prompted for the following parameters with this Screen:
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<img src="./images/deployment/Deployment_Input_Param_01.png" width="900" alt-text="Input Parameters">
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1. Follow [Post Deployment Script Execution](./PostDeploymentConfiguration.md)
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2. Wait up to 20-30 minutes for completion of the script.
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##### 5.1.3.1 **Email** - used for issuing certificates in Kubernetes clusters from the [Let's Encrypt](https://letsencrypt.org/) service. Email address should be valid.
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### 5.2 Verify Deployment
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<img src="./images/deployment/Deployment_Login_02.png" width="900" alt-text="Login">
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1. Access your application using the URL from Step 5.1
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##### 5.1.3.2 You will be prompted to Login, Select a account and proceed to Login.
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##### 5.1.3.3 **GO !** - Post Deployment Script executes Azure Infrastructure configuration, Application code compile and publish into Kubernetes Cluster.
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##### 5.1.3.4 Deployment Complete
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#### 🥳🎉 First, congrats on finishing Deployment!
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Let's check the message and configure your model's TPM rate higher to get better performance.
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You can check the Application URL from the final console message.
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Don't miss this Url information. This is the application's endpoint URL and it should be used for your data importing process.
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<img src="./images/deployment/Deployment_Screen02.png" alt="Success Deployment" width="900">
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### 5.2 Manual Deployment Steps:
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**Create Content Filter** - Please follow below steps
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> * Navigate to project in Azure OpenAI, then go to Azure AI Foundry, select Safety + security
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> * Click on Create Content Filter and set the filters to a high threshold for the following categories:
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```
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Hate, Sexual, Self-harm, Violence
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```
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> * Please select the checkbox of profanity
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> * Leave all other configurations at their default settings and click on create
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### 5.3 Configure Azure OpenAI Rate Limits
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> **Capacity Note:**
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> * The deployment script creates models with a setting of 1 token per minute (TPM) rate limit.
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> * Faster performance can be achieved by increasing the TPM limit with Azure AI Foundry.
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> * Capacity varies for [regional quota limits](https://learn.microsoft.com/en-us/azure/ai-services/openai/quotas-limits#regional-quota-limits) as well as for [provisioned throughput](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/provisioned-throughput).
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> * As a starting point, we recommend the following quota threshold be set up for this service run.
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| Model Name | TPM Threshold |
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|------------------------|---------------|
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| GPT-4.1-mini | 100K TPM |
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| text-embedding-3-large | 200K TPM |
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> **⚠️ Warning:** **Insufficient quota can cause failures during the upload process.** Please ensure you have the recommended capacity or request for additional capacity before start uploading the files.
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#### 5.3.1 Browse to the project in Azure AI Foundry, and select **each of the 2 models** within the `Deployments` menu:
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<img src="./images/deployment/Control_Model_TPM000.png" alt="Select Model" width="700">
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#### 5.3.2 Increase the TPM value for **each model** for faster report generation:
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<img src="./images/deployment/Control_Model_TPM001.png" alt="Set Token per minute" width="700">
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### 5.4 Data Uploading and Processing
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After increasing the TPM limit for each model, let's upload and process the sample documents.
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Execute this command:
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<img src="./images/deployment/Deployment_last_step.png" alt="Set Token per minute" width="700">
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### 5.5 Verify Deployment
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1. Access your application using the URL from [Step 5.1.3.4](#5134-deployment-complete)
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2. Confirm the application loads successfully
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3. Verify you can sign in with your authenticated account
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### 5.3 Test the Application
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### 5.6 Test the Application
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Follow the detailed workflow to test the migration functionality:
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**Quick Test Steps:**
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1. Login to the application using the URL from Step 5.1
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1. Login to the application using the URL from [Step 5.1.3.4](#5134-deployment-complete)
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2. In "Chat with documents" options, ask any questions related to uploaded documents
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3. Click on "Details" of any document and go to "chat" option
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4. Ask questions according to document content
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5. Review the responses
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📖 **Sample Questions:** For a comprehensive list of test scenarios and example questions, see [Sample Questions Guide](./SampleQuestions.md)
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## Step 6: Clean Up (Optional)
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### Remove All Resources

docs/SampleQuestions.md

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# Sample Questions
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## 1. Launch Web Experience
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- Open the web experience interface.
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- Navigate to the **document list**.
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- Scroll and page through the list to explore available documents.
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- Ask in chat: **“What are the main factors contributing to the current housing affordability issues?”**
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![chat response image](./images/SampleQustion.png)
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- Review the AI response for relevant insights.
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- Click one of the **suggested follow-up questions** and check the response.
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- Reset the chat by clicking **[New topic]**.
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---
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## 2. Housing Report Search & Comparison
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- Search for: **“Housing Report”**.
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- Observe the filtered list of documents.
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- Select **Annual Housing Report 2022** and **Annual Housing Report 2023**.
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- Confirm the top panel shows **“2 Selected”**.
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- Ask in chat: **“Analyze the two annual reports and compare the positive and negative outcomes YoY. Show the results in a table.”**
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- Review the generated table for clarity and accuracy.
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---
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## 3. Detailed Review of Annual Housing Report 2023
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- Click **DETAILS** on **Annual Housing Report 2023**.
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- Review the **Extractive Summary** for accuracy.
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- Scroll to **pages 10 & 11**.
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- In the pop-up chat, ask:
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**“Can you summarize and compare the tables on page 10 and 11?”**
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- Review the summarized comparison.
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- Close the pop-up viewer.
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---
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## 4. Contracts Search & Analysis
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- Search for: **“Contracts”**.
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- Observe the filtered list of documents.
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- Select **3–4 handwritten contract documents**.
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- Ask in chat:
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**“Analyze these forms and create a table with all buyers, sellers, and corresponding purchase prices.”**
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- Review the table for correct buyer/seller names and purchase prices.
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---
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## 5. Contract Details & Liabilities
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- Click **DETAILS** on one of the handwritten contracts.
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- In the pop-up chat, ask:
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**“What liabilities is the buyer responsible for within the contract?”**
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- Review the response for specific obligations (e.g., fees, taxes, maintenance, contingencies).
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---

docs/images/SampleQustion.png

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