When building an Agentic System, you’ll need an API to serve your Agents, a database to store session and vector data and an admin interface for testing and evaluation. You’ll also need cron jobs, alerting and data pipelines for ingestion and cleaning. This system would generally take a few months to build, we’re open-sourcing it for the community for free.
Workspaces are standardized codebases for production Agentic Systems. They contain:
Workspaces are setup to run locally using docker and be easily deployed to AWS. They’re a fantastic starting point and exactly what we use for our customers. You’ll definitely need to customize them to fit your specific needs, but they’ll get you started much faster.
They contain years of learnings, available for free for the open-source community.
ag ws create
ag ws up
ag ws up prd:aws
We recommend starting with the agent-app
template and taking it from there.
An Agentic System built with FastAPI, Streamlit and a Postgres database.
An Agent API built with FastAPI and Postgres.
When building Agents, we experiment locally till we achieve 6/10 quality. This helps us see quick results and get a rough idea of how our solution should look like in production.
Then, we start moving to a production environment and iterate from there. Here’s how we build production systems:
Having built 100s of such systems, we have a standard set of codebases we use and we call them Workspaces. They help us manage our Agentic System as code.
We strongly believe that your AI applications should run securely inside your VPC. We fully support BYOC (Bring Your Own Cloud) and encourage you to use your own cloud account.
When building an Agentic System, you’ll need an API to serve your Agents, a database to store session and vector data and an admin interface for testing and evaluation. You’ll also need cron jobs, alerting and data pipelines for ingestion and cleaning. This system would generally take a few months to build, we’re open-sourcing it for the community for free.
Workspaces are standardized codebases for production Agentic Systems. They contain:
Workspaces are setup to run locally using docker and be easily deployed to AWS. They’re a fantastic starting point and exactly what we use for our customers. You’ll definitely need to customize them to fit your specific needs, but they’ll get you started much faster.
They contain years of learnings, available for free for the open-source community.
ag ws create
ag ws up
ag ws up prd:aws
We recommend starting with the agent-app
template and taking it from there.
An Agentic System built with FastAPI, Streamlit and a Postgres database.
An Agent API built with FastAPI and Postgres.
When building Agents, we experiment locally till we achieve 6/10 quality. This helps us see quick results and get a rough idea of how our solution should look like in production.
Then, we start moving to a production environment and iterate from there. Here’s how we build production systems:
Having built 100s of such systems, we have a standard set of codebases we use and we call them Workspaces. They help us manage our Agentic System as code.
We strongly believe that your AI applications should run securely inside your VPC. We fully support BYOC (Bring Your Own Cloud) and encourage you to use your own cloud account.