docs: update AGENTS.md and llm-context for container support

Document container build type, dev server architecture, packaging
pipeline, and template rendering across all AGENTS.md files.
Add missing modelProvider field to llm-compacted agentcore.ts.

Author: tejaskash

AGENTS.md

@@ -27,18 +27,25 @@ Note: CDK L3 constructs are in a separate package `@aws/agentcore-cdk`.
 - `remove` - Remove resources (agent, memory, identity, target, all)
 - `deploy` - Deploy infrastructure to AWS
 - `status` - Check deployment status
-- `dev` - Local development server
+- `dev` - Local development server (CodeZip: uvicorn with hot-reload; Container: Docker build + run with volume mount)
 - `invoke` - Invoke agents (local or deployed)
-- `package` - Package agent artifacts without deploying
+- `package` - Package agent artifacts without deploying (zip for CodeZip, container image build for Container)
 - `validate` - Validate configuration files
 - `update` - Check for CLI updates
 - `help` - Display help information
 
 ### Agent Types
 
-- **Template agents**: Created from framework templates (Strands, LangChain_LangGraph, GoogleADK, OpenAIAgents)
+- **Template agents**: Created from framework templates (Strands, LangChain_LangGraph, CrewAI, GoogleADK, OpenAIAgents,
+  AutoGen)
 - **BYO agents**: Bring your own code with `agentcore add agent --type byo`
 
+### Build Types
+
+- **CodeZip**: Python source is packaged into a zip artifact and deployed to AgentCore Runtime (default)
+- **Container**: Agent is built as a Docker container image, deployed via ECR and CodeBuild. Requires a `Dockerfile` in
+  the agent's code directory. Supported container runtimes: Docker, Podman, Finch.
+
 ### Coming Soon
 
 - MCP gateway and tool support (`add gateway`, `add mcp-tool`) - currently hidden

src/assets/AGENTS.md

@@ -3,14 +3,36 @@
 This directory stores:
 
 - Template assets for agents written in different Languages, SDKs and having different configurations
+- Container templates (`container/python/`) with `Dockerfile` and `.dockerignore` for Container build agents
 
-The rendering logic is rooted in the `AgentEnvSpec` and must ALWAYS respect the configuration in the Spec
+### Directory Layout
+
+```
+assets/
+├── python/              # Framework templates (one per SDK)
+│   ├── strands/
+│   ├── langchain_langgraph/
+│   ├── crewai/
+│   ├── googleadk/
+│   ├── openaiagents/
+│   └── autogen/
+├── container/           # Container build templates
+│   └── python/
+│       ├── Dockerfile
+│       └── dockerignore.template
+└── agents/              # AGENTS.md vended to user projects
+```
+
+The rendering logic is rooted in the `AgentEnvSpec` and must ALWAYS respect the configuration in the Spec.
+
+For Container builds, `BaseRenderer.render()` automatically copies the `container/<language>/` templates (Dockerfile,
+.dockerignore) into the agent directory when `buildType === 'Container'`.
 
 ## Guidance for template changes
 
 - Always make sure the templates are as close to working code as possible
 - AVOID as much as possible using any conditionals within the templates
 
-# How to use the assets in this directory
+## How to use the assets in this directory
 
-- These assets are rendered by the CLI's template renderer in `packages/agentcore-cli/src/templates`.
+- These assets are rendered by the CLI's template renderer in `src/cli/templates/`.

src/assets/agents/AGENTS.md

@@ -60,21 +60,32 @@ file maps to a JSON config file and includes validation constraints as comments.
 
 ### Common Enum Values
 
-- **BuildType**: `'CodeZip'`
+- **BuildType**: `'CodeZip'` | `'Container'`
 - **NetworkMode**: `'PUBLIC'`
 - **RuntimeVersion**: `'PYTHON_3_10'` | `'PYTHON_3_11'` | `'PYTHON_3_12'` | `'PYTHON_3_13'`
 - **MemoryStrategyType**: `'SEMANTIC'` | `'SUMMARIZATION'` | `'USER_PREFERENCE'`
 
+### Build Types
+
+- **CodeZip**: Python source is packaged as a zip artifact and deployed directly to AgentCore Runtime.
+- **Container**: Agent code is built as a Docker container image. Requires a `Dockerfile` in the agent's `codeLocation`
+  directory. At deploy time, the source is uploaded to S3, built in CodeBuild (ARM64), pushed to a per-agent ECR
+  repository, and the container URI is provided to the AgentCore Runtime. For local development (`agentcore dev`), the
+  container is built and run locally with volume-mounted hot-reload.
+
 ### Supported Frameworks (for template agents)
 
 - **Strands** - Works with Bedrock, Anthropic, OpenAI, Gemini
 - **LangChain_LangGraph** - Works with Bedrock, Anthropic, OpenAI, Gemini
+- **CrewAI** - Works with Bedrock, Anthropic, OpenAI, Gemini
 - **GoogleADK** - Gemini only
 - **OpenAIAgents** - OpenAI only
+- **AutoGen** - Works with Bedrock, Anthropic, OpenAI, Gemini
 
 ### Specific Context
 
-Directory pathing to local projects is required for runtimes. Only Python offers a zip based direct code deploy option.
+Directory pathing to local projects is required for runtimes. Both CodeZip (Python zip) and Container (Docker image)
+deployment options are available.
 
 ## Deployment
 

src/cli/AGENTS.md

@@ -65,6 +65,16 @@ appropriate to test the relevant surface area.
 
 If start up issues are encountered, read the console error to troubleshoot bugs and update the harness.
 
+## Dev Server Architecture
+
+The `dev` command uses a strategy pattern with a `DevServer` base class and two implementations:
+
+- **CodeZipDevServer**: Runs uvicorn locally with Python venv hot-reload
+- **ContainerDevServer**: Builds and runs a Docker container with volume mount for hot-reload. Detects
+  Docker/Podman/Finch via the `detectContainerRuntime()` utility.
+
+The server selection is based on `agent.build` (`CodeZip` or `Container`).
+
 ## Commands Directory Structure
 
 Commands live in `commands/`. Each command has its own directory with an `index.ts` barrel file and a file called

src/cli/templates/AGENTS.md

@@ -6,6 +6,19 @@ Template **assets** live in the `assets/` directory at the repository root.
 
 The rendering logic is rooted in the `AgentEnvSpec` and must ALWAYS respect the configuration in the Spec.
 
+### Rendering Pipeline
+
+1. `createRenderer()` selects a renderer based on framework/language
+2. `BaseRenderer.render()` copies and renders the framework base template
+3. If `hasMemory`, capability templates are layered on top
+4. If `buildType === 'Container'`, the container templates (`Dockerfile`, `.dockerignore`) from
+   `assets/container/<language>/` are copied into the agent directory
+
+### LLM Context Files
+
+`schema-assets.ts` imports llm-compacted TypeScript files that are embedded at build time via the esbuild text-loader
+plugin. `CDKRenderer.writeLlmContext()` writes these to `agentcore/.llm-context/` during project initialization.
+
 ## Guidance for template changes
 
 - Always make sure the templates are as close to working code as possible

src/lib/AGENTS.md

@@ -5,9 +5,16 @@ module serves the important goal of making sure that the CDK implementations don
 
 ## Functions
 
-**Packaging**: Installing dependencies and then producing a `.zip` file artifact that is ready to be deployed on
-AgentCore runtime. This is surfaced as a modular function in the CLI and used as a bundling CDK asset in the CDK. A core
-problem this functionality solves is attempting to produce an artifact that can run on ARM64 arch hardware.
+**Packaging**: Producing deployment artifacts for AgentCore runtimes. Two packagers are available:
+
+- **PythonPackager / NodePackager** (CodeZip): Installs dependencies and produces a `.zip` artifact targeting ARM64
+  architecture.
+- **ContainerPackager** (Container): Validates the Dockerfile exists, detects a local container runtime
+  (Docker/Podman/Finch), builds the image locally, and validates the 1GB size limit. If no local runtime is available,
+  the local build is skipped (deploy uses CodeBuild).
+
+Container constants (`CONTAINER_RUNTIMES`, `DOCKERFILE_NAME`, `CONTAINER_INTERNAL_PORT`) and the `ContainerRuntime` type
+are in `lib/constants.ts`.
 
 **ConfigIO**: This module defines utilities to read and write configs which satisfy schemas to the local file system.
 Both the CLI and the CDK require this functionality.

src/schema/llm-compacted/agentcore.ts

@@ -28,6 +28,7 @@ type NodeRuntime = 'NODE_18' | 'NODE_20' | 'NODE_22';
 type RuntimeVersion = PythonRuntime | NodeRuntime;
 type NetworkMode = 'PUBLIC' | 'PRIVATE';
 type MemoryStrategyType = 'SEMANTIC' | 'SUMMARIZATION' | 'USER_PREFERENCE';
+type ModelProvider = 'Bedrock' | 'Gemini' | 'OpenAI' | 'Anthropic';
 
 // ─────────────────────────────────────────────────────────────────────────────
 // AGENT
@@ -43,6 +44,7 @@ interface AgentEnvSpec {
   envVars?: EnvVar[];
   networkMode?: NetworkMode; // default 'PUBLIC'
   instrumentation?: Instrumentation; // OTel settings
+  modelProvider?: ModelProvider; // Model provider used by this agent
 }
 
 interface Instrumentation {