This directory contains Jupyter notebooks for testing the AWS infrastructure.

You requested to use pyenv and uv. Here is an analysis of this choice:

1. Speed: uv is an extremely fast Python package installer and resolver, written in Rust. It is significantly faster than pip and poetry.
2. Isolation: pyenv ensures that the project uses a specific Python version, independent of the system's Python. This prevents version conflicts.
3. Modern Workflow: This combination represents a modern, efficient Python development workflow.

1. Tool Availability: Requires both tools to be installed (which we verified you have).
2. Kernel Registration: For Jupyter to "see" the virtual environment, it must be registered as a kernel. The setup.sh script handles this.

1. Configure Environment Variables: Copy .env.example to .env and fill in your AWS details.

   cp .env.example .env

2. Run Setup Script: This script will use pyenv to set the local Python version, create a virtual environment with uv, install dependencies, and register the Jupyter kernel.

   chmod +x setup.sh
   ./setup.sh

3. Run the Notebook: Open infrastructure_test.ipynb in VS Code or Jupyter Lab. Ensure the kernel selected is aws-infra-test.

4. Run Vector Search Test: Open s3_vector_search.ipynb to test vector generation and search capabilities.