Cross Cloud Multi Agent Comic Builder with ADK, Amazon Lambda, and Gemini CLI

--- title: Cross Cloud Multi Agent Comic Builder with ADK, Amazon Lambda, and Gemini CLI published: true series: AWS tags: googleadk,python,geminicli,awslambda --- Leveraging the Google Agent Development Kit (ADK) and the underlying Gemini LLM to build low code apps with the Python programming language deployed to the Lambda service on AWS.  #### Aren’t There a Billion Python Agent Demos? Yes there are. Python has traditionally been the main coding language for ML and AI tools. The goal of this article is to provide a minimal viable basic working ADK server. #### What Is Python? Python is an interpreted language that allows for rapid development and testing and has deep libraries for working with ML and AI: [Welcome to Python.org](https://www.python.org/) #### Python Version Management One of the downsides of the wide deployment of Python has been managing the language versions across platforms and maintaining a supported version. The **pyenv** tool enables deploying consistent versions of Python: [GitHub - pyenv/pyenv: Simple Python version management](https://github.com/pyenv/pyenv) #### Amazon Lamba [AWS Lambda](https://www.serverless.com/aws-lambda) is a serverless, event-driven compute service that enables users to run code without provisioning or managing servers. With Lambda, developers can focus solely on their code (functions), while AWS handles all underlying infrastructure management, including capacity provisioning, automatic scaling, and operating system maintenance. Full details are here: [Serverless Computing Service - Free AWS Lambda - AWS](https://aws.amazon.com/pm/lambda) #### Gemini CLI If not pre-installed you can download the Gemini CLI to interact with the source files and provide real-time assistance: ```shell npm install -g @google/gemini-cli ``` #### Testing the Gemini CLI Environment Once you have all the tools and the correct Node.js version in place- you can test the startup of Gemini CLI. You will need to authenticate with a Key or your Google Account: ```plaintext ▝▜▄ Gemini CLI v0.33.1 ▝▜▄ ▗▟▀ Logged in with Google /auth ▝▀ Gemini Code Assist Standard /upgrade ``` #### Node Version Management Gemini CLI needs a consistent, up to date version of Node. The **nvm** command can be used to get a standard Node environment: [GitHub - nvm-sh/nvm: Node Version Manager - POSIX-compliant bash script to manage multiple active node.js versions](https://github.com/nvm-sh/nvm) #### Docker Version Management The AWS Cli tools need a current version of Docker. If your environment does not provide a recent docker tool- the Docker Version Manager can be used to downlaod the latest supported Docker: [Install](https://howtowhale.github.io/dvm/install.html) #### AWS CLI The AWS CLI provides a command line tool to directly access AWS services from your current environment. Full details on the CLI are available here: [Install Docker, AWS CLI, and the Lightsail Control plugin for containers](https://docs.aws.amazon.com/lightsail/latest/userguide/amazon-lightsail-install-software.html) #### Agent Development Kit The [Google Agent Development Kit](https://www.google.com/search?q=Google+Agent+Development+Kit&rlz=1CAIWTJ_enUS1114&oq=what+is+the+adk+google&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIICAEQABgWGB4yCAgCEAAYFhgeMggIAxAAGBYYHjIICAQQABgWGB4yCAgFEAAYFhgeMggIBhAAGBYYHjIKCAcQABgKGBYYHjINCAgQABiGAxiABBiKBTIKCAkQABiABBiiBNIBCDMxODlqMGo3qAIAsAIA&sourceid=chrome&ie=UTF-8&mstk=AUtExfB5Oo7ZHHcDEHu7aqZiPBA2l1c-QGh5dB7xkkDPIiYcn8O1Imt2IHNR7bzA6JnyDCSDCUGpGWTeBW14namlN_QqzJLLI5-px1BE9jfSxwli6njPDPERjm5pRqNP3uC6HhUKiRcTJ1T8x5LHQrCkVxylw7QWg0N8B4dQDIcWpnVX9Gc&csui=3&ved=2ahUKEwjYu-G8p-uSAxXrv4kEHUbpLo0QgK4QegQIARAB) (ADK) is an open-source, Python-based framework designed to streamline the creation, deployment, and orchestration of sophisticated, multi-agent AI systems. It treats agent development like software engineering, offering modularity, state management, and built-in tools (like Google Search) to build autonomous agents. The ADK can be installed from here: [Agent Development Kit (ADK)](https://google.github.io/adk-docs/) #### This seems like a lot of Configuration! Getting the key tools in place is the first step to working across Cloud environments. For a deeper dive- a project with a similar setup can be found here: [MCP Development with Amazon Lambda and Gemini CLI](https://towardsaws.com/mcp-development-with-amazon-lambda-and-gemini-cli-ab1389c1ac1c) #### Where do I start? The strategy for starting low code agent development is a incremental step by step approach. The agents in the demo are based on the original code lab: [Create and deploy low code ADK (Agent Deployment Kit) agents using ADK Visual Builder | Google Codelabs](https://codelabs.developers.google.com/codelabs/create-low-code-agent-with-ADK-visual-builder#0) First, the basic development environment is setup with the required system variables, and a working Gemini CLI configuration. Then, a minimal ADK Agent is built with the visual builder. Next — the entire solution is deployed to Amazon Lambda. #### Setup the Basic Environment At this point you should have a working Python environment and a working Gemini CLI installation. The next step is to clone the GitHub samples repository with support scripts: ```shell cd ~ git clone https://github.com/xbill9/gemini-cli-aws cd adkui-lambda ``` Then run **init.sh** from the cloned directory. The script will attempt to determine your shell environment and set the correct variables: ```shell source init.sh ``` If your session times out or you need to re-authenticate- you can run the **set\_env.sh** script to reset your environment variables: ```shell source set_env.sh ``` Variables like PROJECT\_ID need to be setup for use in the various build scripts- so the **set\_env** script can be used to reset the environment if you time-out. #### Verify The ADK Installation To verify the setup, run the ADK CLI locally with Agent1: ```console xbill@penguin:~/gemini-cli-aws/adkui-lambda$ adk run Agent1 /home/xbill/.pyenv/versions/3.13.13/lib/python3.13/site-packages/authlib/_joserfc_helpers.py:8: AuthlibDeprecationWarning: authlib.jose module is deprecated, please use joserfc instead. It will be compatible before version 2.0.0. from authlib.jose import ECKey /home/xbill/.pyenv/versions/3.13.13/lib/python3.13/site-packages/google/adk/features/_feature_decorator.py:72: UserWarning: [EXPERIMENTAL] feature FeatureName.PLUGGABLE_AUTH is enabled. check_feature_enabled() Log setup complete: /tmp/agents_log/agent.20260420_230436.log To access latest log: tail -F /tmp/agents_log/agent.latest.log /home/xbill/.pyenv/versions/3.13.13/lib/python3.13/site-packages/google/adk/cli/utils/agent_loader.py:277: UserWarning: [EXPERIMENTAL] _load_from_yaml_config: This feature is experimental and may change or be removed in future versions without notice. It may introduce breaking changes at any time. if root_agent := self._load_from_yaml_config(actual_agent_name, agents_dir): /home/xbill/.pyenv/versions/3.13.13/lib/python3.13/site-packages/google/adk/features/_feature_decorator.py:81: UserWarning: [EXPERIMENTAL] feature FeatureName.AGENT_CONFIG is enabled. check_feature_enabled() /home/xbill/.pyenv/versions/3.13.13/lib/python3.13/site-packages/google/adk/cli/cli.py:204: UserWarning: [EXPERIMENTAL] InMemoryCredentialService: This feature is experimental and may change or be removed in future versions without notice. It may introduce breaking changes at any time. credential_service = InMemoryCredentialService() /home/xbill/.pyenv/versions/3.13.13/lib/python3.13/site-packages/google/adk/auth/credential_service/in_memory_credential_service.py:33: UserWarning: [EXPERIMENTAL] BaseCredentialService: This feature is experimental and may change or be removed in future versions without notice. It may introduce breaking changes at any time. super(). __init__ () Running agent Agent1, type exit to exit. [user]: hello [Agent1]: Hello! How can I help you today? [user]: 0.0s 0.0s ``` #### Deploying to Amazon Lambda First authenticate: ```shell aws login --remote ``` Then cache the credentials locally: ```console xbill@penguin:~/gemini-cli-aws/adkui-lambda$ source save-aws-creds.sh Exporting AWS credentials... Successfully saved credentials to .aws_creds The Makefile will now automatically use these for deployments. xbill@penguin:~/gemini-cli-aws/adkui-lambda$ ``` Then start the deployment: ```console xbill@penguin:~/gemini-cli-aws/adkui-lambda$ make deploy Exporting AWS credentials... Successfully saved credentials to .aws_creds The Makefile will now automatically use these for deployments. Ensuring IAM role McpLambdaExecutionRole exists... Checking if ECR repository exists... Logging in to Amazon ECR... ``` You can validate the final result by checking the messages: ```json Updating Function URL to BUFFERED mode (Stateless HTTP)... { "FunctionUrl": "https://u3lvibtqxtj7h3nzzadl7p73dq0ngjql.lambda-url.us-west-1.on.aws/", "FunctionArn": "arn:aws:lambda:us-west-1:106059658660:function:adkui-lambda", "AuthType": "NONE", "CreationTime": "2026-04-20T13:46:11.689938731Z", "LastModifiedTime": "2026-04-21T03:06:25.769054157Z", "InvokeMode": "BUFFERED" } ``` You can then get the endpoint: ```console xbill@penguin:~/gemini-cli-aws/adkui-lambda$ make status ------------------------------------------------------------ | GetFunction | +-------------------------------+----------------+---------+ | LastModified | Name | Status | +-------------------------------+----------------+---------+ | 2026-04-21T03:06:23.000+0000 | adkui-lambda | Active | +-------------------------------+----------------+---------+ https://u3lvibtqxtj7h3nzzadl7p73dq0ngjql.lambda-url.us-west-1.on.aws/ ``` The service will be visible in the AWS Lambda console:  #### Running the ADK Web Interface Start a connection to the Lamba Deployed ADK:  To test the Comic Agent Flow- select Agent 3. This will generate the Comic by using a multi-agent pipeline:  #### Run the Online Viewer Once Agent3 has completed — the artifacts are available on the deployment:  #### View the Final Artifacts You can use the final comic.html visualize the results of the agent pipeline:  #### Summary The Agent Development Kit was used to visually define a multi Agent pipeline to generate comic book style HTML. This Agent was tested locally with the CLI and then with the ADK web tool. Then, several sample ADK agents were run directly from the Lambda deployment in AWS. This approach validates that cross cloud tools can be used — even with more complex agents.