AutoOps Retail Optimisation

A multi-agent AI system for retail optimisation using AWS Strands Agents framework, powered by Amazon Nova Micro via AWS Bedrock.

Overview

This system consists of three specialised AI agents (Pricing, Inventory, and Promotion) that collaborate to reduce waste and maximise profit through intelligent decision-making and real-time adaptations to market conditions.

Architecture

• AWS Strands Agents: Multi-agent orchestration framework
• Amazon Nova Micro: LLM via AWS Bedrock
• ChromaDB: Vector database for agent memory
• Langfuse: Observability and tracing

Prerequisites

• Python 3.9 or higher
• uv package manager
• AWS account with Bedrock access
• AWS credentials configured

Installation

1. Install uv (if not already installed):

   curl -LsSf https://astral.sh/uv/install.sh | sh

2. Clone and setup the project:

   git clone https://github.com/errchh/aws-ai-hackathon-autoops.git
   cd aws-ai-hackathon-autoops

3. Create virtual environment and install dependencies:

   uv venv
   source .venv/bin/activate  
   uv sync 

4. Configure environment variables:

   cp .env.example .env
   # Edit .env with your AWS credentials and configuration

5. Start simulation engine:

   uv run main.py

Configuration

AWS Setup

1. Enable AWS Bedrock access for Amazon Nova Micro model in your AWS account
2. Configure AWS credentials in .env file or use AWS CLI/IAM roles
3. Ensure proper IAM permissions for Bedrock model access

Langfuse Setup

1. Create a Langfuse account at langfuse.com
2. Create a new project in your Langfuse dashboard
3. Get your API credentials from the project settings

Environment Variables

Key configuration variables in .env:

AWS Configuration:

• AWS_REGION: AWS region (default: us-east-1)
• AWS_ACCESS_KEY_ID: Your AWS access key
• AWS_SECRET_ACCESS_KEY: Your AWS secret key
• BEDROCK_MODEL_ID: Amazon Nova Micro model ID

Langfuse Configuration:

• LANGFUSE_PUBLIC_KEY: Your Langfuse public key
• LANGFUSE_SECRET_KEY: Your Langfuse secret key
• LANGFUSE_HOST: Langfuse host URL (default: https://cloud.langfuse.com)

ChromaDB Configuration:

• CHROMADB_PERSIST_DIRECTORY: Local directory for vector database