Schedule-Pro

Agentic RAG–powered assistant built with LangGraph that answers user queries from a knowledge base and guides users to create, update, or cancel Google Meet calls, managing availability and sending meeting links via email.

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Setup Instructions

1. Clone the Repository

git clone [https://github.com/BennisonDevadoss/schedule-pro.git](https://github.com/BennisonDevadoss/schedule-pro.git)
cd schedule-pro

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2. Set Up Conda Environment

If you don't have Conda installed, refer to the Conda Installation Guide.

Once Conda is installed:

# Create the environment
conda env create --name agentic-rag python=3.11

# Activate the environment
conda activate agentic-rag

# Install required dependencies
pip install -r requirements.txt

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3. Set Up Environment Variables

cp .env.example .env.staging
cp .env.example .env.production
cp .env.example .env.development

Edit the values in each .env.{environment_name} file as needed.

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4. Set the Active Environment

Set the appropriate environment before running the application:

export ENVIRONMENT=development  # or staging / production

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5. Apply Database Migrations

alembic upgrade head

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6. Seed the Database

cd app/seeders/
python seed.py
cd ../..

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7. Set Up crawl4ai

To configure and initialize the crawl4ai component used for document ingestion:

crawl4ai-setup

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8. Run the Application

You can run the app in two ways:

Option 1: Inline environment variable

ENVIRONMENT=development python main.py

Option 2: Export and run

export ENVIRONMENT=development
python main.py

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9. Run Celery Worker

To run background tasks (e.g., ingestion, summarization, etc.), start the Celery worker: Make sure you are in app dir.

PYTHONPATH=. celery -A queues.worker worker --loglevel=info -Q <queue_name>

Replace <queue_name> with the desired queue (e.g., default, ingestion, etc.)

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Environment Usage Guidelines

• Development (ENVIRONMENT=development): For local development and testing. Includes debug logs and test configs.

• Staging (ENVIRONMENT=staging): For pre-production testing. Mimics the production setup with test data.

• Production (ENVIRONMENT=production): For live deployment. Connects to production-grade services and uses secure configs.

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