Merge pull request #21 from MicrosoftCloudEssentials-LearningHub/PoC-test

PoC test

Author: brown9804

README.md

@@ -43,7 +43,7 @@ Last updated: 2026-02-02
   - **Cart Manager**: Cart operations and checkout-oriented help
   - **Product Management Specialist**: Handles product-centric workflows and coordinates lookups across services
 - **Intent routing + handoff planning**: Classifies user intent and plans a multi-step sequence of agent calls (instead of a single “one agent answers everything” flow)
-- **Factual data integration**: Uses **Azure AI Search** (vector/keyword retrieval) and **Azure Cosmos DB** (catalog/state) during workflows
+- **Factual data integration (pipeline-first)**: Terraform runs pipelines that ingest the catalog into **Azure Cosmos DB** and build an **Azure AI Search** index; runtime lookups can be enabled/extended as needed
 - **Real persistent agents**: Uses Azure AI Foundry Agents with saved runtime IDs (OpenAI-style `asst_*`) provisioned during deployment
 - **Zero-touch deployment**: `terraform apply` provisions infra, ingests data, creates/updates agents, wires secrets/config, and deploys the Container Apps revision
 - **UI-visible diagnostics**: Correlated `error_id` responses and optional tracebacks via `A2A_DEBUG=true` for faster troubleshooting
@@ -72,7 +72,7 @@ This repo contains **two multi-agent implementations**:
 - **Intent routing**: classifies the user request and selects the primary domain (`src/services/handoff_service.py`)
 - **Handoff planning**: builds a multi-step sequence of which agents to call (`src/chat_app_multi_agent.py`)
 - **Remote agent execution**: calls Azure AI Foundry Agents using the saved `asst_*` IDs (`src/app/agents/agent_processor.py`)
-- **Factual lookups**: uses Azure AI Search and Cosmos DB during workflows (called from the app runtime)
+- **Factual lookups (optional)**: Terraform creates/loads Cosmos DB and Azure AI Search data; the default chat runtime can be extended to query these sources during workflows
 
 > A2A components included in this repo (optional server)
 
@@ -137,27 +137,25 @@ graph TD
 1. **Infrastructure Provisioning**:
    - Creates Resource Group, Cosmos DB, MSFT Foundry, AI Search, Storage Account, Key Vault, and Container Registry (ACR).
    - Deploys AI Models (`gpt-4o-mini`, `text-embedding-3-small`).
-   - Sets up A2A protocol infrastructure including event queues and monitoring.
+   - Sets up monitoring (Log Analytics + Application Insights). Optional A2A components (like an in-memory event queue) are part of the app codebase, not separate Azure resources.
 
       > E.g Web App approach:
       
        <img width="1859" height="900" alt="image" src="https://github.com/user-attachments/assets/cd24ab7f-5ddd-46de-b266-0d0a24c45803" />
 
 2. **A2A Framework Deployment**:
-   - Initializes the Agent-to-Agent protocol server components.
-   - Sets up event queue system for inter-agent communication.
-   - Configures agent discovery and registration services.
-   - Deploys A2A monitoring and automation frameworks.
+   - Includes an optional A2A-style server implementation under `src/a2a/` (routers, coordinator, in-memory event queue, monitoring helpers).
+   - Note: the default deployed runtime uses `src/chat_app_multi_agent.py` (`/ws`). The A2A server endpoints are only available if you deploy/run the `src/a2a/main.py` entrypoint.
 
 3. **Data Pipeline Execution**:
    - Sets up a Python virtual environment.
-   - Ingests `product_catalog.csv` into Cosmos DB with A2A event notifications.
+   - Ingests `src/data/updated_product_catalog(in).csv` into Cosmos DB.
 
         > E.g Web App approach: 
 
         <https://github.com/user-attachments/assets/41bf0976-0ca8-47fe-a2fa-8750bcc6f848>
 
-   - Creates and populates an Azure AI Search index with vector embeddings through A2A coordination.
+   - Creates and populates an Azure AI Search index with vector embeddings.
 
         > E.g Web App approach:
         
@@ -201,9 +199,13 @@ graph TD
        <https://github.com/user-attachments/assets/a1139528-6b37-4ac2-a1cb-771788ff45a4>
 
 2. **Verify A2A Protocol Endpoints**:
-   - Check A2A Chat API: `https://<your-app-name>.azurecontainerapps.io/a2a/chat`
-   - Check A2A Server API: `https://<your-app-name>.azurecontainerapps.io/a2a/api/docs`
+   - These endpoints are **only available if you deploy/run the A2A server entrypoint** (`src/a2a/main.py`).
+   - A2A Chat API (HTTP): `https://<your-app-name>.azurecontainerapps.io/a2a/chat/message`
+   - A2A Chat API (WebSocket): `wss://<your-app-name>.azurecontainerapps.io/a2a/chat/ws`
+   - A2A Chat streaming: `https://<your-app-name>.azurecontainerapps.io/a2a/chat/stream`
+   - A2A Chat stats: `https://<your-app-name>.azurecontainerapps.io/a2a/chat/stats`
    - Verify agent discovery: `https://<your-app-name>.azurecontainerapps.io/a2a/server/agents`
+   - OpenAPI docs (FastAPI default): `https://<your-app-name>.azurecontainerapps.io/docs`
 
 3. **Verify Enhanced Agent Architecture**:
    - Go to the [MSFT Foundry Portal](https://ai.azure.com).
@@ -221,12 +223,9 @@ graph TD
       | Prompt | E.g Output | 
       | --- | --- |
       | **General**: <br/> “Hi, who are you?” <br/> (Routed to **Cora**) | <img width="1142" height="950" alt="image" src="https://github.com/user-attachments/assets/72a60b47-dbd6-48b8-bff6-48ebd92fff48" /> | 
-      |  **Inventory**: <br/>  “Do you have the classic leather sofa in stock?” <br/> (Routed to **Inventory Manager**) | | 
-      | **Design**: <br/>  “What colors of green paint do you have?” <br/> (Routed to **Interior Design Specialist**) | | 
-      | **Product Recommendations**: <br/>  “Recommend modern furniture for my living room” <br/> (Routed to **Product Management Specialist**; may consult catalog/search depending on its prompt/tools) | | 
-      | **Product Comparisons**: <br/>  “Compare sectional sofas” <br/> (Routed to **Product Management Specialist**; comparison is handled within that agent) | | 
-      | **Product Details**: <br/> “What are the specifications of product SOFA-001?” <br/> (Routed to **Product Management Specialist**; details are handled within that agent) | | 
-      | **Multi-Agent**: <br/> “Find a sofa, then verify my loyalty points, and add it to my cart” <br/> (Coordinated across **Product Management → Customer Loyalty → Cart Manager** via the app’s multi-step routing) | | 
+      | **Design**: <br/>  “Recommend modern furniture for my living room” <br/> (Routed to **Interior Design Specialist**) | <img width="1167" height="963" alt="image" src="https://github.com/user-attachments/assets/5e602f08-06ca-4866-9892-ade211a3a413" /> | 
+      | **Product Comparisons**: <br/>  “Compare sectional sofas” <br/> (Routed to **Product Management Specialist**; comparison is handled within that agent) | <img width="1208" height="836" alt="image" src="https://github.com/user-attachments/assets/0649f459-e8d5-4916-a442-4cbec9b85fa6" /> | 
+      | **Loyalty Details**: <br/> “Give me a summary of my loyalty account benefits” <br/> (Routed to **Customer Loyalty**) | <img width="1211" height="955" alt="image" src="https://github.com/user-attachments/assets/45dec561-4f9a-433e-a264-09af2bff4453" /> | 
             
 <!-- START BADGE -->
 <div align="center">

src/a2a/status_automation.ps1

@@ -11,7 +11,7 @@ if () {
 
 # Check automation endpoint
 try {
-   = Invoke-RestMethod -Uri "https://zava-8e5461ee-app.azurewebsites.net/a2a/automation/status" -TimeoutSec 5
+   = Invoke-RestMethod -Uri "https://zava-6a7d57fb-app.azurewebsites.net/a2a/automation/status" -TimeoutSec 5
   Write-Host "Automation Status: "
 } catch {
   Write-Host "Automation endpoint not accessible"

terraform-infrastructure/main.tf

@@ -283,6 +283,17 @@ resource "azurerm_search_service" "search" {
   identity { type = "SystemAssigned" }
 }
 
+# Grant the current Terraform principal access to Search *data-plane* operations
+# (view/create indexes, query documents). Without this, the Azure Portal may not
+# show indexes even if they exist.
+resource "azurerm_role_assignment" "search_index_data_contributor_user" {
+  scope                = azurerm_search_service.search.id
+  role_definition_name = "Search Index Data Contributor"
+  principal_id         = local.principal_id
+
+  depends_on = [azurerm_search_service.search]
+}
+
 resource "azurerm_log_analytics_workspace" "law" {
   name                = local.log_analytics_name
   location            = var.location