SkyRecoverAI

Agentic AI portfolio project for airline disruption recovery using Python, Streamlit, and LangGraph.

Tech Stack

• Python 3.11+
• Streamlit
• LangGraph
• OpenAI API

Project Layout

• agents
• workflows
• services
• data
• docs
• tests

Quick Start

1. Create and activate a virtual environment.

   • Windows PowerShell:
     • py -m venv .venv
     • ..venv\Scripts\Activate.ps1
   • macOS/Linux:
     • python3 -m venv .venvcd scripts
     • source .venv/bin/activate

2. Install dependencies.

   • python -m pip install -r requirements.txt

3. Configure environment variables.

   • Copy .env.example to .env
   • Set OPENAI_API_KEY in .env
   • Optional: set OPENAI_MODEL (default is gpt-4o-mini)

4. Run the Streamlit app.

   • Preferred (works even if streamlit is not on PATH):
     • python -m streamlit run streamlit_app.py

5. Open the app in your browser.

   • http://localhost:8501

Optional Validation

1. Run a workflow smoke test.

   • python -m pytest tests/test_workflow_smoke.py

2. Execute one simulation in UI and verify output.

   • data/output/cases_output.json should be created or updated.

Troubleshooting

• If streamlit command is not found, use:
  • python -m streamlit run streamlit_app.py
• If OpenAI calls fail, verify OPENAI_API_KEY is set in your active environment.

Architecture

• MVP Architecture
• Repository Structure Guide