update

.workshop_instance/.workshop-state.json

@@ -1 +1,4 @@
-{"current_step": 0, "schema_version": 1}
+{
+  "current_step": 0,
+  "schema_version": 1
+}

.workshop_instance/workshop_backups/reset-20260818184435/.azdignore

@@ -0,0 +1,3 @@
+agent.manifest.yaml
+agent.yaml
+.env.example

.workshop_instance/workshop_backups/reset-20260818184435/.dockerignore

@@ -0,0 +1,7 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
+.env

.workshop_instance/workshop_backups/reset-20260818184435/Dockerfile

@@ -0,0 +1,12 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY . user_agent/
+WORKDIR /app/user_agent
+
+RUN if [ -f requirements.txt ]; then         pip install -r requirements.txt;     else         echo "No requirements.txt found";     fi
+
+EXPOSE 8088
+
+CMD ["python", "main.py"]

.workshop_instance/workshop_backups/reset-20260818184435/STEP_README.md

@@ -0,0 +1 @@
+You're now on step 01. The TravelBuddy agent files are present: `agent.yaml` and `agent.manifest.yaml` are ready to use, and you complete one small edit — write TravelBuddy's instructions in `main.py`. The `Dockerfile`, `.dockerignore`, and `.azdignore` that package and deploy the agent are also included (read-only) and explained in the Step 1 doc. The model you deployed in Step 0 is used at runtime via `AZURE_AI_MODEL_DEPLOYMENT_NAME`, so there's no model to provision here. Follow Step 1 in the root `README.md`.

.workshop_instance/workshop_backups/reset-20260818184435/agent.manifest.yaml

@@ -0,0 +1,42 @@
+# travel_assistant/agent.manifest.yaml — AgentManifest: a parameterized template
+# that deployment tooling (azd ai agent init / Foundry Toolkit) reads to scaffold
+# your hosted agent. It has top-level metadata (name, description, tags), a
+# `template` block (the hosted-agent definition), and a `resources` list.
+# This file is provided ready to use — skim it so you know what it declares.
+# Reference (each field explained):
+# https://learn.microsoft.com/azure/foundry/agents/concepts/agent-yaml-reference
+# NOTE: `name` (and `template.name` below) must be a hardcoded literal here — do
+# NOT use ${VAR} or {{VAR}}. `azd ai agent init` reads and validates the agent
+# name as-is, BEFORE any substitution: it never expands ${VAR} (those resolve later
+# at deploy/run from .env / Bicep outputs) and only substitutes {{VAR}} for values
+# declared under a `parameters:` block, which happens AFTER the name is validated.
+# The validator rejects `$`, `{`, and `}`, so a placeholder here fails with
+# "invalid agent name". The runtime-configurable prefix still lives in agent.yaml's
+# `name` and in the WORKSHOP_RESOURCE_PREFIX environment variable below.
+name: travel-buddy
+description: >
+  A basic Agent Framework travel assistant hosted by Foundry.
+metadata:
+  tags:
+    - Agent Framework
+    - AI Agent Hosting
+    - Azure AI AgentServer
+    - Responses Protocol
+    - Travel Assistant
+template:
+  name: travel-buddy
+  kind: hosted
+  protocols:
+    - protocol: responses
+      version: 2.0.0
+  environment_variables:
+    - name: AZURE_AI_PROJECT_ENDPOINT
+      value: ${AZURE_AI_PROJECT_ENDPOINT}
+    - name: AZURE_AI_MODEL_DEPLOYMENT_NAME
+      value: ${AZURE_AI_MODEL_DEPLOYMENT_NAME}
+    - name: WORKSHOP_RESOURCE_PREFIX
+      value: ${WORKSHOP_RESOURCE_PREFIX}
+# No provisioned resources: you already deployed a model in setup (Step 0), and the
+# agent selects it at runtime through the AZURE_AI_MODEL_DEPLOYMENT_NAME env var
+# above — so we don't declare a `kind: model` resource for azd to create.
+resources: []

.workshop_instance/workshop_backups/reset-20260818184435/agent.yaml

@@ -0,0 +1,25 @@
+# travel_assistant/agent.yaml — AgentDefinition (kind: hosted): the concrete
+# runtime definition for your agent. It names the hosted agent, declares the
+# `responses` protocol, sets a small CPU/memory shape, and lists the environment
+# variables the container needs. This file is ready to run as-is — skim it so you
+# understand each block. Reference:
+# https://learn.microsoft.com/azure/foundry/agents/concepts/agent-yaml-reference
+# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/ContainerAgent.yaml
+kind: hosted
+name: ${WORKSHOP_RESOURCE_PREFIX}-travel-buddy
+protocols:
+  - protocol: responses
+    version: 2.0.0
+resources:
+  cpu: "0.25"
+  memory: "0.5Gi"
+environment_variables:
+  # These values come from your .env at run/deploy time — keep the ${...} refs as-is.
+  - name: AZURE_AI_PROJECT_ENDPOINT
+    value: ${AZURE_AI_PROJECT_ENDPOINT}
+  - name: AZURE_AI_MODEL_DEPLOYMENT_NAME
+    value: ${AZURE_AI_MODEL_DEPLOYMENT_NAME}
+  # WORKSHOP_RESOURCE_PREFIX keeps your agent's name unique so it doesn't collide
+  # with other attendees deploying into a shared project.
+  - name: WORKSHOP_RESOURCE_PREFIX
+    value: ${WORKSHOP_RESOURCE_PREFIX}

.workshop_instance/workshop_backups/reset-20260818184435/main.py

@@ -0,0 +1,38 @@
+# travel_assistant/main.py — Python entry point that hosts TravelBuddy: it creates
+# the Foundry model client, defines the agent, and starts the Responses server.
+# Complete the one TODO inside main() below.
+import os
+
+from agent_framework import Agent
+from agent_framework.foundry import FoundryChatClient
+from agent_framework_foundry_hosting import ResponsesHostServer
+from azure.identity import DefaultAzureCredential
+from dotenv import load_dotenv
+
+load_dotenv(override=True)
+
+
+def main() -> None:
+    # Foundry model client, built from your .env settings.
+    client = FoundryChatClient(
+        project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
+        model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+        credential=DefaultAzureCredential(),
+    )
+
+    # TODO: write TravelBuddy's system instructions. Describe a friendly travel
+    # assistant that gives practical, concise trip-planning advice — local context,
+    # budget awareness, and safety-minded tips.
+    agent = Agent(
+        client=client,
+        name="travel-buddy",
+        instructions="TODO: write TravelBuddy's system instructions here.",
+        # History is managed by the hosting infrastructure, so don't store it server-side.
+        default_options={"store": False},
+    )
+
+    ResponsesHostServer(agent).run()
+
+
+if __name__ == "__main__":
+    main()