adding CLI examples and removing starter toolkit

01-tutorials/01-AgentCore-runtime/01-hosting-agent/01-strands-with-bedrock-model/README.md

@@ -2,7 +2,7 @@
 
 ## Overview
 
-In this tutorial we will learn how to host your existing agent, using Amazon Bedrock AgentCore Runtime. 
+In this tutorial we will learn how to host your existing agent, using Amazon Bedrock AgentCore Runtime.
 
 We will focus on a Strands Agents with Amazon Bedrock model example. For LangGraph with Amazon Bedrock model check [here](../02-langgraph-with-bedrock-model)
 and for a Strands Agents with an OpenAI model check [here](../03-strands-with-openai-model).
@@ -21,20 +21,129 @@ and for a Strands Agents with an OpenAI model check [here](../03-strands-with-op
 | Example complexity  | Easy                                                                             |
 | SDK used            | Amazon BedrockAgentCore Python SDK and boto3                                     |
 
-### Tutorial Architecture
+---
 
-In this tutorial we will describe how to deploy an existing agent to AgentCore runtime. 
+## Architecture
 
-For demonstration purposes, we will  use a Strands Agent using Amazon Bedrock models
+When hosting agents, the SDK automatically:
 
-In our example we will use a very simple agent with two tools: `get_weather` and `get_time`. 
+- Hosts your agent on port `8080`
+- Provides two key endpoints:
+  - **`/invocations`**: Primary agent interaction (JSON input → JSON/SSE output)
+  - **`/ping`**: Health check for monitoring
 
 <div style="text-align:left">
     <img src="images/architecture_runtime.png" width="100%"/>
 </div>
 
+Once deployed, your AgentCore Runtime receives requests from clients via `invoke_agent_runtime` (boto3 or AWS SDK). Each session runs in an isolated microVM. The lifecycle looks as following:
+
+1. **Local experimentation** — run your agent as a Python script
+2. **Wrap with SDK** — add `BedrockAgentCoreApp` decorator
+3. **Deploy to Runtime** — package code, upload to S3, create runtime via boto3
+4. **Invoke** — call via boto3 `invoke_agent_runtime`
+
+---
+
+## What's This Feature
+
+Amazon Bedrock AgentCore Runtime lets you deploy any Python-based agent (Strands, LangGraph, CrewAI, etc.) as a scalable, serverless HTTP service. You wrap your agent's invocation function with the `@app.entrypoint` decorator from the `bedrock_agentcore` SDK — no other code changes required.
+
 ### Tutorial Key Features
 
 * Hosting Agents on Amazon Bedrock AgentCore Runtime
 * Using Amazon Bedrock models
 * Using Strands Agents
+* CodeZip deployment (no Docker required) via boto3 `create_agent_runtime`
+* Session lifecycle management with `stop_runtime_session`
+* Lifecycle configuration (idle session timeout) via `update_agent_runtime`
+
+---
+
+## CLI Commands
+
+> **CLI version**: `[email protected]`
+>
+> Install or update: `npm install -g @aws/[email protected]`
+
+The `agentcore` CLI provides an alternative end-to-end workflow for creating, deploying, invoking, and monitoring your runtime without writing deployment code.
+
+### 1. Create a new project
+
+```bash
+agentcore create \
+  --name stransclaude \
+  --framework Strands \
+  --model-provider Bedrock \
+  --build CodeZip \
+  --skip-git \
+  --skip-install \
+  --json
+```
+
+This scaffolds a project with `agentcore/agentcore.json` config, CDK stack, and a starter `main.py`.
+
+### 2. Replace the generated agent code
+
+Copy your agent code (`strands_claude.py`) into the project:
+
+```bash
+cp strands_claude.py app/stransclaude/main.py
+cp requirements.txt app/stransclaude/requirements.txt
+```
+
+### 3. Deploy to AgentCore Runtime
+
+```bash
+cd stransclaude
+agentcore deploy -y --json
+```
+
+This creates the IAM role, packages the code, and calls `create_agent_runtime`. Wait for `READY` status.
+
+### 4. Check deployment status
+
+```bash
+agentcore status --json
+```
+
+### 5. Invoke the deployed agent
+
+```bash
+agentcore invoke "What is the weather in Athens?" --json
+```
+
+### 6. View logs
+
+```bash
+agentcore logs --since 30m -n 50
+```
+
+---
+
+## Cleanup
+
+To delete the runtime and associated resources:
+
+**Using boto3** (from the notebook cleanup cell):
+
+```python
+import boto3
+agentcore_control = boto3.client('bedrock-agentcore-control', region_name=region)
+agentcore_control.delete_agent_runtime(agentRuntimeId=agent_runtime_id)
+```
+
+**Using CLI** (if deployed via `agentcore deploy`):
+
+```bash
+# Remove the agent from project config and redeploy to tear down
+agentcore remove agent --name stransclaude --json
+agentcore deploy -y --json
+```
+
+Also delete the S3 deployment artifact:
+
+```python
+s3 = boto3.client('s3', region_name=region)
+s3.delete_object(Bucket=bucket_name, Key=s3_key)
+```

01-tutorials/01-AgentCore-runtime/01-hosting-agent/01-strands-with-bedrock-model/requirements.txt

@@ -2,5 +2,4 @@ strands-agents
 strands-agents-tools
 uv
 boto3
-bedrock-agentcore<=0.1.5
-bedrock-agentcore-starter-toolkit==0.1.14
+bedrock-agentcore