Practical overview
When it fits
Use it when developing a Python-based multi-agent system and you want a runtime, reusable tools, domain examples and registry-based selection of agents by session context.
Who it is for
- Developers building custom AI agents and multi-agent workflows on Google Cloud.
- Teams exploring domain-specific agent patterns across areas such as health and life sciences, financial services and retail.
Documented uses
- Coordinate multiple agents within a workflow.
- Select agents and prompts using industry and use-case session state.
- Integrate reusable tools and context utilities with agents.
- Explore example workflows for research synthesis, provider search, investment analysis, banking modernization and marketing content.
Requirements & limits
The repository is public and specifies an Apache-2.0 license. Local development prerequisites include Python 3.10 or later, pip or uv, Google ADK and a configured .env file.
- The repository is a framework and development starting point, rather than a finished end-user agent application.
- Agent selection is mapped through industry and use-case session state in agent_registry.py.
- The README separates local development setup from infrastructure provisioning and deployment instructions.
- The repository includes evaluation scripts and session data in its test directory.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Prepare a local development environment
Install the documented dependencies and configure the environment required for local development.
Before you start
- Python 3.10 or later
- pip or uv
- A configured .env file, including required values such as a Google Cloud project ID
Steps
Create and activate a Python virtual environment.
Install or upgrade pip, install google-adk, then install the repository with pip install -e .; alternatively, the README names make install.
Follow Section 2 of setup.md to create and configure the .env file.
Expected outcome
The local project environment has the documented dependencies and configuration for development.
Guide limitations
- The README refers to setup.md for environment values and infrastructure provisioning details.
- This guide covers setup only, not deployment or validation of an agent workflow.
Compare options for Agent orchestration
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Agentsmithy | Coordinate multiple agents within a workflow. | Cloud | The repository is public and specifies an Apache-2.0 license. Local development prerequisites include Python 3.10 or later, pip or uv, Google ADK and a configured .env file. |
| Massgen | Run multiple AI agents against the same user task. | CLI | The repository documents installation through pip or uv and requires Python 3.11 or later. Setup can configure API keys for OpenAI, Anthropic, Google and xAI; credentials are needed for the selected model backends. |
| Langchain Multi Agents Boilerplate | Route incoming football questions to model and agent workflows according to task complexity. | Web | The repository is public and specifies an MIT license. Running the application requires OpenAI and Groq API keys and a Redis server. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 13 October 2026
- Original website title
- GoogleCloudPlatform/agentsmithy · Official homepage title · retained in its source language