🧠 Agent Workshop

Requirements

• Docker
• Valid Lambda API Key

Setup Instructions

(If you are attending the in-person workshop, please checkout to part_1 or workshop_part_2 and ignore the instructions below.)

1. Clone the Repository and Checkout the Correct Branch

   git clone https://github.com/LambdaLabsML/AI_Agent_Masterclass.git
   cd <path_where_cloned_repo_lives>/AI_Agent_Masterclass
   

2. Create a .env File in the Root Directory

   LAMBDA_API_BASE="https://api.lambda.ai/v1"
   LAMBDA_API_KEY=<your_lambda_api_key>
   LAMBDA_MODEL="openai/llama-4-maverick-17b-128e-instruct-fp8"
   

3. Test that you can connect to Lambda's Inference API

   source .env
   curl https://api.lambdalabs.com/v1/lambda/models -H "Authorization: Bearer $LAMBDA_API_KEY"
   

4. Run with Docker Compose (Recommended)

   # Default (crews will run async and MLFlow will be launched)
   docker compose up --build
   
   # Once the container is up and running, you can visit the following link in your browser, to track the execution traces on MLFlow:
   http://0.0.0.0:8000/
   

5. (Optional) Run the Crews Synchronously Without MLflow

   # Build the Docker image
   docker build -f Dockerfile.sync -t ml_agent_workshop_sync .
   
   # Run the container
   docker run ml_agent_workshop_sync
   
   # After the Docker Container is finished, get container ID
   docker ps -a
   
   # Copy reports from container to local machine
   docker cp <container_id>:/app/state_of_the_business/reports <your_local_computer_path>
   

6. (Optional) Run the Crews Asynchronously Without MLflow

   # Build the Docker image
   docker build -f Dockerfile.async -t ml_agent_workshop_async .
   
   # Run the container
   docker run ml_agent_workshop_async
   
   # After the Docker Container is finished, get container ID
   docker ps -a
   
   # Copy reports from container to local machine
   docker cp <container_id>:/app/state_of_the_business/reports <your_local_computer_path>