add AVM Post Deployment Guide with detailed setup instructions

Author: Harsh-Microsoft

docs/AVMPostDeploymentGuide

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+# AVM Post Deployment Guide
+
+This document provides guidance on post-deployment steps after deploying the Document Knowledge Mining Solution Accelerator from the [AVM (Azure Verified Modules) repository](https://github.com/Azure/bicep-registry-modules/tree/main/avm/ptn/sa/document-knowledge-mining).
+
+## Overview
+
+After deploying the infrastructure using AVM, you'll need to complete the application layer setup, which includes:
+- Configuring Kubernetes infrastructure
+- Building and deploying container images
+- Setting up certificates and ingress controllers
+- Configuring application settings
+
+## Prerequisites
+
+Before starting the post-deployment process, ensure you have the following:
+
+### Required Software
+
+1. **[PowerShell](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell?view=powershell-7.4)** <small>(v7.0+ recommended, v5.1+ minimum)</small> - Available for Windows, macOS, and Linux
+
+2. **[Azure CLI](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli)** <small>(v2.50+)</small> - Command-line tool for managing Azure resources
+
+3. **kubectl** - Kubernetes command-line tool  
+   Install using Azure CLI:
+   ```powershell
+   az aks install-cli
+   ```
+
+4. **aks-preview extension** - Azure CLI extension for AKS preview features  
+   ```powershell
+   az extension add --name aks-preview
+   ```
+
+5. **[Helm](https://helm.sh/docs/intro/install/)** <small>(v3.0+)</small> - Package manager for Kubernetes
+
+6. **[Docker Desktop](https://docs.docker.com/get-docker/)** - Container platform for building and publishing images
+   > ⚠️ **Important**: Ensure Docker Desktop is running before executing the deployment script
+
+### Azure Requirements
+
+7. **Azure Access** - One of the following roles on the subscription:
+   - `Owner` 
+   - `User Access Administrator`
+
+8. **Microsoft.Compute Registration** - Verify this resource provider is registered:
+   1. Navigate to [Azure Portal](https://portal.azure.com)
+   2. Go to your **Azure subscription**
+   3. Select **Settings** → **Resource Providers**
+   4. Search for **Microsoft.Compute** and ensure it's **Registered**
+   
+   <img src="./images/deployment/Subscription_ResourceProvider.png" alt="Resource Provider Registration" width="900">
+
+9. **Deployed Infrastructure** - A successful Document Knowledge Mining Accelerator deployment from the [AVM repository](https://github.com/Azure/bicep-registry-modules/tree/main/avm/ptn/sa/document-knowledge-mining)
+
+## Post-Deployment Steps
+
+### Step 1: Clone the Repository
+
+First, clone this repository to access the post-deployment scripts:
+
+```powershell
+git clone https://github.com/microsoft/Document-Knowledge-Mining-Solution-Accelerator.git
+```
+```powershell
+cd Document-Knowledge-Mining-Solution-Accelerator
+```
+
+### Step 2: Run the Post-Deployment Script
+
+The post-deployment process is automated through a single PowerShell script that completes the following tasks in approximately 20-30 minutes:
+
+#### What the Script Does:
+1. **Configure Kubernetes Infrastructure** - Set up AKS cluster settings and networking
+2. **Update Configuration Files** - Generate FQDN, container image paths, and certificate settings
+3. **Deploy Kubernetes Components** - Install Cert Manager, Ingress Controller, and application pods
+4. **Build and Push Container Images** - Compile and publish application containers to Azure Container Registry
+5. **Provide Access Information** - Display the final application URL and next steps
+
+#### Execute the Script:
+
+1. Navigate to the deployment directory:
+   ```powershell
+   cd .\Deployment\
+   ```
+
+2. Run the post-deployment script with your resource group name:
+   ```powershell
+   .\resourcedeployment.ps1 -ResourceGroupName "<your-resource-group-name>"
+   ```
+   
+   > **Note**: Replace `<your-resource-group-name>` with the actual name of the resource group containing your AVM-deployed resources.
+
+3. **If you encounter execution policy issues**, use this alternative command:
+   ```powershell
+   powershell.exe -ExecutionPolicy Bypass -File ".\resourcedeployment.ps1" -ResourceGroupName "<your-resource-group-name>"
+   ```
+
+### Step 3: Provide Required Information
+
+During script execution, you'll be prompted for:
+
+#### Email Address for SSL Certificates
+<img src="./images/deployment/Deployment_Input_Param_01.png" width="900" alt="Input Parameters">
+
+- **Purpose**: Used for issuing SSL certificates through [Let's Encrypt](https://letsencrypt.org/)
+- **Requirement**: Must be a valid email address
+
+#### Azure Authentication
+<img src="./images/deployment/Deployment_Login_02.png" width="900" alt="Azure Login">
+
+- You'll be prompted to authenticate with Azure
+- Select the appropriate Azure account
+- Ensure you have the required permissions on the target subscription
+
+### Step 4: Deployment Completion
+
+Upon successful completion, you'll see a success message with important information:
+
+<img src="./images/deployment/Deployment_Screen02.png" alt="Deployment Success" width="900">
+
+**🎉 Congratulations!** Your deployment is complete. 
+
+**Important**: Save the application URL displayed in the console - you'll need it for data upload and accessing the application.
+
+## Next Steps
+
+### 1. Configure Azure OpenAI Rate Limits
+
+> **⚠️ Critical**: The default deployment creates models with minimal TPM (Tokens Per Minute) limits. You **must** increase these limits for proper performance.
+
+#### Recommended TPM Thresholds
+
+| Model Name             | Recommended TPM | Minimum TPM |
+|------------------------|----------------|-------------|
+| GPT-4o-mini            | 100K TPM       | 10K TPM     |
+| text-embedding-3-large | 200K TPM       | 50K TPM     |
+
+> **⚠️ Warning**: Insufficient quota will cause failures during document upload and processing. Ensure adequate capacity before proceeding.
+
+#### How to Update TPM Limits:
+
+1. **Navigate to Azure AI Foundry**:
+   - Go to [Azure AI Foundry](https://ai.azure.com/)
+   - Select your project
+   - Go to **Deployments** section
+
+2. **Update Each Model**:
+
+   <img src="./images/deployment/Control_Model_TPM000.png" alt="Select Model" width="700">
+   
+   - Select each deployed model
+   - Click **Edit deployment**
+   - Increase the **Tokens per Minute Rate Limit**
+   
+   <img src="./images/deployment/Control_Model_TPM001.png" alt="Set TPM Limit" width="700">
+
+3. **Apply Changes**: Save the configuration for each model
+
+### 2. Upload and Process Sample Documents
+
+After configuring the TPM limits, upload sample documents:
+
+1. **Navigate to the deployment directory** (if not already there):
+   ```powershell
+   cd .\Deployment\
+   ```
+
+2. **Execute the upload script** with the URL from the deployment output:
+   ```powershell
+   .\uploadfiles.ps1 -EndpointUrl https://kmgs<your-dns-name>.<datacenter>.cloudapp.azure.com
+   ```
+
+3. **Alternative execution** (if you encounter policy issues):
+   ```powershell
+   powershell.exe -ExecutionPolicy Bypass -File ".\uploadfiles.ps1" -EndpointUrl https://kmgs<your-dns-name>.<datacenter>.cloudapp.azure.com
+   ```
+
+### 3. Access Your Application
+
+Once document upload is complete, you can:
+- **Access the web application** at the URL provided in the deployment output
+- **Start exploring** the knowledge mining capabilities
+- **Upload additional documents** through the web interface
+
+---
+
+> **📋 Note**: This guide is specifically for post-deployment steps after using the AVM template. For complete deployment from scratch, see the main [Deployment Guide](./DeploymentGuide.md).