Food-AI Library (food-ai-swiggy) 🍊

An automated, background activity-tracking daemon that checks user working hours on Windows, performs a psychological personality mapping, and automatically orders a surprise Swiggy food treat based on their profile.

Features

• 16-Personalities Style Onboarding: A 10-question Likert-scale CLI questionnaire mapping psychological/behavioral traits to food preferences (e.g. Adventure, Complexity, Heat Tolerance, Social Sharing).
• Windows Activity Tracking: A background tracking daemon using native Windows APIs (GetLastInputInfo via ctypes) that tracks user keystrokes and mouse movements system-wide without polling loops or keyboard logging.
• Aesthetic Tkinter Popup: A beautiful dark-theme popup asking the user: "You've been working too much, let me surprise you?" when they exceed the continuous work threshold.
• Swiggy Food MCP Client: A native JSON-RPC-over-HTTP client for calling Swiggy Food MCP tools.
• Simulation / Dry-Run Mode: Automatically runs in a visual dry-run mode when no live API token is supplied, allowing testing of the complete checkout, ordering, and tracking flow.

Directory Structure

• pyproject.toml - Packaging metadata and dependencies.
• config.json - Daemon threshold configurations, idle timeout limits, and dry-run toggles.
• main.py - Entry point for CLI.
• food_ai/
  • personality.py - Likert questionnaire & scoring profile engine.
  • mcp_client.py - JSON-RPC HTTP client for Swiggy Food MCP tools.
  • tracker.py - Windows user input monitor via ctypes.
  • popup.py - Tkinter dark-theme user break pop-up modal.
  • order_bot.py - Swiggy Food MCP ordering orchestrator.
• tests/
  • test_food_ai.py - Automated tests for personality mapping and client.

Setup & Installation

Ensure you have Python 3.8+ installed. Navigate to the project directory and install in editable mode:

pip install -e .

Usage

1. Onboarding Assessment

Complete the 10-question CLI questionnaire to establish your food profile:

python main.py --onboard

2. Start Activity Tracking Daemon

Launches the background monitor that tracks continuous working hours:

python main.py --track

Testing Tip: By default, config.json has use_test_threshold set to true, which sets the active tracking threshold to 15 seconds instead of 5 hours. Move your mouse or type to trigger the popup in seconds!

3. Test Surprise Order Flow Directly

Triggers the entire Swiggy Food MCP flow immediately using your stored personality:

python main.py --surprise

4. Test Pop-Up Window Interface

Review the Tkinter styling of the notification window directly:

python main.py --test-popup

Configuration (config.json)

Modify values in config.json to change thresholds and live API connection settings:

{
  "tracking_threshold_hours": 5.0,
  "tracking_threshold_test_sec": 15,
  "use_test_threshold": true,
  "idle_timeout_min": 5.0,
  "default_address_label": "Home",
  "dry_run": true
}

To connect to a live Swiggy MCP account, set "dry_run": false and set the SWIGGY_ACCESS_TOKEN environment variable.