CausalBench — Causal Explanation Lambda

This repository provides the AWS Lambda implementation for CausalBench, a framework for causal analysis and recommendation.
It includes helper modules for causal scoring/explanations, conversion of YAML configs to CSV, and email delivery of results.

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Repository Structure

.
├── lambda_function.py           # Lambda entrypoint (AWS handler)
├── causal_analysis_helper.py    # Causal analysis utilities
├── causal_recommendation_helper.py
├── common_constants.py          # Configure env vars here (email ID, password)
├── mail_services.py             # SMTP email sender
├── mail_helper_services.py      # Email formatting and helpers
├── yaml_to_csv.py               # Convert YAML files downloaded from causalbench.org to CSV
├── media/                       # Static assets
├── requirements.txt             # Python dependencies
├── Dockerfile                   # Container build for AWS Lambda
└── LICENSE                      # Apache 2.0

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Installation (local)

1. Clone and create a virtual environment

   git clone https://github.com/CausalBenchOrg/CausalBench-Causal_Explanation.git
   cd CausalBench-Causal_Explanation
   python3 -m venv .venv && source .venv/bin/activate

2. Install dependencies

   pip install -r requirements.txt

3. Configure environment variables

   Set these in your shell (or via AWS Parameter Store/Secrets Manager):

   export SEND_AS_EMAIL="<your_sending_email>"
   export EMAIL="<your_email>"
   export EMAIL_PASSWORD="<your_app_password>"
   export SMTP_HOST="smtp.example.com"
   export SMTP_PORT="587"

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Usage

Convert YAML → CSV

python yaml_to_csv.py config.yaml --out out.csv

Run helpers locally

python causal_analysis_helper.py --input data.csv
python causal_recommendation_helper.py --input data.csv

Send a test email

python mail_services.py

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AWS Lambda Deployment

This project supports deployment as a container image.

1. Build the image

   docker build -t causal-expl-lambda .

2. (Optional) Test locally

   docker run --rm -p 9000:8080 causal-expl-lambda
   curl -XPOST "http://localhost:9000/2015-03-31/functions/function/invocations" \
        -d '{"action":"analyze","payload":{"dataset":"s3://.../input.csv"}}'

3. Deploy to AWS

   • Push the image to Amazon ECR.
   • Create a Lambda function with image type.
   • Configure environment variables in the Lambda console.

If deploying as a zip instead, set handler to:
lambda_function.lambda_handler

License

This project is licensed under the Apache License 2.0.