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SupportOps AI Monitor

CI Python 3.11+ Streamlit License: MIT Live Demo

Simulates enterprise AI support operations — ticket generation, GPT-4o-mini triage, API health monitoring, and an observability dashboard. Runs entirely in simulation mode with no API key required.


Features

  • Realistic ticket generation — 5 categories (API, billing, account, safety, other) with Faker-powered enterprise data
  • AI triage — classifies category, analyses sentiment, and produces a one-line summary via gpt-4o-mini
  • API health monitoring — logs every API call with latency, HTTP status code, and error type
  • Observability dashboard — Streamlit + Plotly charts for ticket volume, priority distribution, sentiment trends, and API health
  • Simulation mode — full demo at zero cost, no API key needed
  • CSV/Excel upload — bring your own ticket data, auto-triaged by the AI pipeline

Quick Start

git clone https://github.com/Archit-Konde/supportops-ai-monitor.git
cd supportops-ai-monitor
pip install -r requirements.txt
streamlit run src/app.py

Opens at http://localhost:8501. Use the sidebar to generate and triage tickets.

Simulation mode is the default. Add OPENAI_API_KEY to .env for real triage. See .env.example.


How It Works

ticket_generator.py  →  database.py  →  ai_triage.py  →  app.py (dashboard)

Tickets are generated from Faker-powered templates, stored in SQLite, triaged by GPT-4o-mini (or simulation), and visualised in real time. Every API call is logged with latency, status code, and error type for observability.

For architecture diagrams, database schema, and simulation details, see docs/ARCHITECTURE.md.


Tech Stack

Python 3.11+ · Streamlit · OpenAI (gpt-4o-mini) · SQLite · Plotly · Pandas · Faker · pytest · Docker


Contributing

See CONTRIBUTING.md for guidelines and local CI checks.


License

MIT


Author

Archit Konde Portfolio · GitHub · LinkedIn

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Enterprise AI support ops dashboard — ticket triage, API health monitoring, observability

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