The Trading agent we deployed earlier will automatically have session persistence when deployed on Agent Platform. You can test this by asking it a day later “What trades did you execute” from the same session that you executed the trades from. The full conversation history is … Continue reading Deterministic memories
To use Agent Platform services like Memory Bank, and Sessions from other environments, you need to first create a resource that is currently known as an “agent engine”. Note: if you are familiar with the Python ADK libraries, you can follow these instructions instead, to create … Continue reading Creating an Agent Platform resource identifier
ADK Agents will automatically have session persistence when deployed on Agent Platform. You can test this by asking follow up questions in the running sessions like “What trades did you execute?”. The full conversation history is preserved, even while the agent is suspended … Continue reading Agent memories with ADK
In my previous post, we created an agent with ADK and ran it locally. The next step is to deploy it to Agent Platform runtime. ADK deployments are typically deployed using a small Python script to configure the required properties. Create the following script in the root project … Continue reading Deploy an ADK agent to Agent Platform Runtime
The Agent Development Kit (ADK) is Google’s open-source Python framework for building AI agents. You write the agent’s logic and the tools it can call, and ADK handles orchestrating everything — with evaluation and deployment built in too. I wanted a slightly more interesting app … Continue reading Building a stock-trading agent with ADK