Running Agents in production is hard, we need to:
Phidata not only makes building Agents easy but also provides pre-built templates for agentic systems that you can deploy to your own AWS account. Here’s how they work:
phi ws create
phi ws up
phi ws up prd:aws
We strongly believe that the data used by Agents should be stored securely inside your VPC.
We fully support BYOC (Bring Your Own Cloud) and encourage you to use your own AWS account.
Let’s build an agent-app
which includes a Streamlit UI, FastApi server and Postgres database for memory and knowledge. Run it locally using docker or deploy to production on AWS.
Create a virtual environment
Install phidata
Install docker
Install docker desktop to run your app locally
Export your OpenAI key
You can get an API key from here.
Create your codebase using the agent-app
template
This will create a folder agent-app
with the following structure:
Streamlit allows us to build micro front-ends for testing our Agents. Start the app
using:
Press Enter to confirm and give a few minutes for the image to download (only the first time). Verify container status and view logs on the docker dashboard.
app
folderAgents
are defined in the agents
folder.Streamlit is great for building micro front-ends but any production application will be built using a front-end framework like next.js backed by a RestApi built using FastApi.
Your Agent App comes ready-to-use with FastApi endpoints. Start the api
using:
/v1/playground/agent/run
endpoint withThe agent-app
comes with common endpoints that you can use to build your AI product. This API is developed in close collaboration with real AI Apps and are a great starting point.
The general workflow is:
/v1/playground/agent/run
to run Agents.session_id
returned, your product can continue and serve chats to its users.Play around and stop the workspace using:
or stop individual Apps using:
Congratulations on running an Agent App locally. Next Steps: