Merge pull request #68 from microsoft/features/found-main-refactor

Features/found main refactor

Author: marktayl1

README.md

@@ -61,7 +61,7 @@ The sample data used in this repository is synthetic and generated using Azure O
 
 This diagram double-clicks into the agentic framework for the code conversion process. The conversion uses an agentic approach with each agent playing a specialized role in the process. The system gets a list of SQL files which are targeted for conversion. 
 
-**Step 1:** The system loops through the list of SQL files, converting each file, starting by passing the SQL to the Migrator agent. This agent will create several candidate SQL files that should be equivalent. It does this to ensure that the system acknowledges that most of these queries could be converted in a number of different ways. *Note that the processing time can vary depending on OpenAI and cloud services.*
+**Step 1:** The system loops through the list of SQL files, converting each file, starting by passing the SQL to the Migrator agent. This agent will create several candidate SQL files that should be equivalent. It does this to ensure that the system acknowledges that most of these queries could be converted in a number of different ways. *Note that the processing time can vary depending on Azure OpenAI service and cloud services.*
 
 **Step 2:** The Picker agent then examines these various possibilities and picks the one it believes is best using criteria such as simplicity, clarity of syntax, etc.
 
@@ -106,12 +106,12 @@ When you start the deployment, most parameters will have **default values**, but
 |------------|----------------|  ------------|
 | **Azure Region** | The region where resources will be created. | East US| 
 | **Resource Prefix** | Prefix for all resources created by this template. This prefix will be used to create unique names for all resources. The prefix must be unique within the resource group. | None |
-| **Ai Location** | Location for all Ai services resources. This location can be different from the resource group location | None |
-| **Capacity** | Configure capacity for **GPT models**. |  5k |
+| **AI Location** | Location for all AI services resources. This location can be different from the resource group location | None |
+| **Capacity** | Configure capacity for **gpt-4o**. |  5k |
 
 ### [Optional] Quota Recommendations  
 By default, the **GPT model capacity** in deployment is set to **5k tokens**.  
-> **We recommend increasing the capacity to 30k tokens for optimal performance.** 
+> **We recommend increasing the capacity to 200k tokens for optimal performance.** 
 
 To adjust quota settings, follow these [steps](./docs/AzureGPTQuotaSettings.md)  
 
@@ -262,7 +262,7 @@ You can try the [Azure pricing calculator](https://azure.microsoft.com/en-us/pri
 * Azure AI Foundry: Free tier. [Pricing](https://azure.microsoft.com/pricing/details/ai-studio/)
 * Azure Storage Account: Standard tier, LRS. Pricing is based on storage and operations. [Pricing](https://azure.microsoft.com/pricing/details/storage/blobs/)
 * Azure Key Vault: Standard tier. Pricing is based on the number of operations. [Pricing](https://azure.microsoft.com/pricing/details/key-vault/)
-* Azure AI Services: S0 tier, defaults to gpt-4o-mini and text-embedding-ada-002 models. Pricing is based on token count. [Pricing](https://azure.microsoft.com/pricing/details/cognitive-services/)
+* Azure AI Services: S0 tier, defaults to gpt-4o-mini. Pricing is based on token count. [Pricing](https://azure.microsoft.com/pricing/details/cognitive-services/)
 * Azure Container App: Consumption tier with 0.5 CPU, 1GiB memory/storage. Pricing is based on resource allocation, and each month allows for a certain amount of free usage. [Pricing](https://azure.microsoft.com/pricing/details/container-apps/)
 * Azure Container Registry: Basic tier. [Pricing](https://azure.microsoft.com/pricing/details/container-registry/)
 * Log analytics: Pay-as-you-go tier. Costs based on data ingested. [Pricing](https://azure.microsoft.com/pricing/details/monitor/)

docs/AzureGPTQuotaSettings.md

@@ -0,0 +1,10 @@
+## How to Check & Update Quota
+
+1. **Navigate** to the [Azure AI Foundry portal](https://ai.azure.com/).  
+2. **Select** the AI Project associated with this accelerator.  
+3. **Go to** the `Management Center` from the bottom-left navigation menu.  
+4. Select `Quota`  
+   - Click on the `GlobalStandard` dropdown.  
+   - Select the required **GPT model** (`GPT-4, GPT-4o`).  
+   - Choose the **region** where the deployment is hosted.  
+5. Request More Quota or delete any unused model deployments as needed.  

docs/CustomizingAzdParameters.md

@@ -0,0 +1,23 @@
+By default this template will use the environment name as the prefix to prevent naming collisions within Azure. The parameters below show the default values. You only need to run the statements below if you need to change the values. 
+
+
+> To override any of the parameters, run `azd env set <key> <value>` before running `azd up`. On the first azd command, it will prompt you for the environment name. Be sure to choose 3-20 charaters alphanumeric unique name. 
+
+Change the Model Deployment Type (allowed values: Standard, GlobalStandard)
+
+```shell
+azd env set AZURE_ENV_MODEL_DEPLOYMENT_TYPE Standard
+```
+
+Set the Model Name (allowed values: gpt-4)
+
+```shell
+azd env set AZURE_ENV_MODEL_NAME gpt-4
+```
+
+Change the Model Capacity (choose a number based on available GPT model capacity in your subscription)
+
+```shell
+azd env set AZURE_ENV_MODEL_CAPACITY 30
+```
+

docs/DeleteResourceGroup.md

@@ -0,0 +1,51 @@
+# Deleting Resources After a Failed Deployment in Azure Portal
+
+If your deployment fails and you need to clean up the resources manually, follow these steps in the Azure Portal.
+
+---
+
+## **1. Navigate to the Azure Portal**
+1. Open [Azure Portal](https://portal.azure.com/).
+2. Sign in with your Azure account.
+
+---
+
+## **2. Find the Resource Group**
+1. In the search bar at the top, type **"Resource groups"** and select it.
+2. Locate the **resource group** associated with the failed deployment.
+
+![Resource Groups](images/delete_resource/resourcegroup.png)
+
+![Resource Groups](images/delete_resource/resource-groups.png)
+
+---
+
+## **3. Delete the Resource Group**
+1. Click on the **resource group name** to open it.
+2. Click the **Delete resource group** button at the top.
+
+![Delete Resource Group](images/delete_resource/DeleteRG.png)
+
+3. Type the resource group name in the confirmation box and click **Delete**.
+
+📌 **Note:** Deleting a resource group will remove all resources inside it.
+
+---
+
+## **4. Delete Individual Resources (If Needed)**
+If you don’t want to delete the entire resource group, follow these steps:
+
+1. Open **Azure Portal** and go to the **Resource groups** section.
+2. Click on the specific **resource group**.
+3. Select the **resource** you want to delete (e.g., App Service, Storage Account).
+4. Click **Delete** at the top.
+
+![Delete Individual Resource](images/delete_resource/deleteservices.png)
+
+---
+
+## **5. Verify Deletion**
+- After a few minutes, refresh the **Resource groups** page.
+- Ensure the deleted resource or group no longer appears.
+
+📌 **Tip:** If a resource fails to delete, check if it's **locked** under the **Locks** section and remove the lock.

docs/EXAMPLE-CustomizingAzdParameters.md

@@ -11,12 +11,6 @@ Change the Content Understanding Location (allowed values: Sweden Central, Austr
 azd env set AZURE_ENV_CU_LOCATION 'swedencentral'
 ```
 
-Change the Secondary Location (example: eastus2, westus2, etc.)
-
-```shell
-azd env set AZURE_ENV_SECONDARY_LOCATION eastus2
-```
-
 Change the Model Deployment Type (allowed values: Standard, GlobalStandard)
 
 ```shell
@@ -34,15 +28,3 @@ Change the Model Capacity (choose a number based on available GPT model capacity
 ```shell
 azd env set AZURE_ENV_MODEL_CAPACITY 30
 ```
-
-Change the Embedding Model 
-
-```shell
-azd env set AZURE_ENV_EMBEDDING_MODEL_NAME text-embedding-ada-002
-```
-
-Change the Embedding Deployment Capacity (choose a number based on available embedding model capacity in your subscription)
-
-```shell
-azd env set AZURE_ENV_EMBEDDING_MODEL_CAPACITY 80
-```