DVD Rental Assistant with Google Gemini + GenAI Toolbox + LlamaIndex

A modern DVD rental assistant powered by Google's Gemini AI, built with FastAPI and Streamlit. This project demonstrates the integration of Google's latest AI technology with GenAI Toolbox and LlamaIndex to create an intelligent DVD rental management system.

📚 Table of Contents

• Architecture
  • Core Technologies
  • Technology Highlights
• Features
• Implementation Details
  • GenAI Toolbox Integration
  • LlamaIndex AgentWorkflow Setup
• Getting Started
  • Prerequisites
  • Installation Steps
    • Clone Repository
    • Environment Setup
    • Configuration
    • GenAI Toolbox Setup
    • Database Setup
    • Start Services
    • Access Application
• Project Structure
• API Documentation
  • Endpoints
• Author
• License

Architecture

The DVD Rental Assistant follows a streamlined request flow that combines the power of Google Gemini, LlamaIndex, and GenAI Toolbox to process user queries and provide intelligent responses.

Core Technologies

Layer	Technologies	Description
AI/ML	Google Gemini, LlamaIndex, GenAI Toolbox	LLM-driven conversational AI and tool calls
Backend	FastAPI, PostgreSQL, WebSocket	Async API with structured DB integration
Frontend	Streamlit, Real-time UI	Interactive, responsive user interface

Technology Highlights

• Google Gemini
  Powers conversational AI and context-aware interactions.

• LlamaIndex
  Manages conversation flow and tool orchestration.

• GenAI Toolbox
  Handles secure database operations and SQL execution.

• FastAPI
  Provides async API services, automatic documentation, and data validation.

• Streamlit
  Enables real-time, interactive, and intuitive frontend experiences.

• Pydantic
  Ensures data integrity through structured validation and serialization.

Features

• Natural language understanding for DVD rental queries
• Real-time database operations through GenAI Toolbox
• Intelligent conversation flow with LlamaIndex
• Context-aware responses with Google Gemini
• Structured data presentation with emojis
• Smart search capabilities across film database

Implementation Details

GenAI Toolbox Integration

from toolbox_llamaindex import ToolboxClient

# Initialize toolbox client
client = ToolboxClient("http://127.0.0.1:5000")

# Load database tools
tools = client.load_toolset()

LlamaIndex AgentWorkflow Setup

from llama_index.core.agent import AgentWorkflow
from llama_index.core.tools import ToolMetadata
from llama_index.llms import GoogleGenAI

# Initialize the agent with tools and LLM
agent = AgentWorkflow.from_tools_or_functions(
    tools,
    llm=GoogleGenAI(
        model="gemini-1.5-pro",
        vertexai_config={
            "project": "vertex-ai-experminent",
            "location": "us-central1"
        }
    ),
    system_prompt=DVD_RENTAL_PROMPT
)

Getting Started

Prerequisites

• Python 3.9+
• PostgreSQL with Pagila database
• Google API key for Gemini
• GenAI Toolbox access

Installation Steps

1. Clone Repository

git clone https://github.com/arjunprabhulal/gemini-toolbox-dvd-rental-assistant.git
cd gemini-toolbox-dvd-rental-assistant

2. Environment Setup

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

3. Configuration

cp .env.example .env
# Edit .env with your credentials:
# GOOGLE_API_KEY=your_gemini_api_key
# TOOLBOX_URL=http://127.0.0.1:5000

4. GenAI Toolbox Setup

curl -L https://github.com/google/generative-ai-toolbox/releases/latest/download/toolbox-darwin-amd64 -o toolbox
chmod +x toolbox
./toolbox --version

5. Database Setup

This project uses the Pagila database — an example schema designed for PostgreSQL, inspired by the Sakila schema for MySQL.

Special thanks to devrimgunduz/pagila for providing the schema and sample data used in this project.

# Step 1: Create and load database
psql -U postgres
CREATE DATABASE toolbox_db;
\c toolbox_db
\q

# Step 2: Download Pagila schema and data
mkdir -p database/pagila
cd database/pagila
curl -O https://raw.githubusercontent.com/devrimgunduz/pagila/master/pagila-schema.sql
curl -O https://raw.githubusercontent.com/devrimgunduz/pagila/master/pagila-data.sql

# Step 3: Load Pagila into the toolbox_db
psql -U postgres -d toolbox_db -f pagila-schema.sql
psql -U postgres -d toolbox_db -f pagila-data.sql

6. Start Services

# Start GenAI Toolbox
./toolbox --tools_file "dvdrental_tools.yaml"

# Start Backend
uvicorn backend:app --reload

# Start Frontend
streamlit run streamlit_app.py

7. Access Application

Backend: http://localhost:8000
Frontend: http://localhost:8501

Project Structure

gemini-toolbox-dvd-rental-assistant/
├── database/
│   └── pagila/
│       ├── pagila-schema.sql    # Database schema
│       ├── pagila-data.sql      # Initial data
│       └── pagila-insert-data.sql # Additional data
├── backend.py                   # FastAPI backend
├── streamlit_app.py            # Streamlit frontend
├── prompts.py                  # System prompts
├── dvdrental_tools.yaml        # Database configuration
├── requirements.txt            # Dependencies
└── .env                        # Environment variables

API Documentation

Endpoints

Endpoint	Method	Description
/health	GET	System health check
/chat	POST	Process user queries
/reset-context/{user_id}	POST	Reset user conversation context

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

For more articles on AI/ML and Generative AI, follow me on medium Arjun Prabhulal