API developed by Angela Haydee Cobos as an exercise for Kiwibot.

• Python 3.11
• Flask: API routes.
• GTP-3 davinci model: Natural language recognition.
• Unittest Python module: Unit tests.
• Git: Version control.

1. Clone the Git repository.
2. Create a .env file on the root of the project. You can use the .env.example file to see what environment variables are needed.
3. Run flask --app main run to run the API locally

1. Run python test.py to run the tests locally.

Endpoint for bots to send status updates.

Body JSON:

{
    "bot_id": "string",
    "timestamp": "ISO 8601 Date",
    "location": {
        "lat": "float",
        "lon": "float"
    },
    "status": "available" | "busy" | "reserved",
    "battery_level": "float",
    "software_version": "string",
    "hardware_version": "string"
}

Respose codes:

• 200: OK

Retrieves the last status of each bot.

Respose codes:

• 200: OK

Retrieves the ticket with the given id.

Respose codes:

• 200: OK
• 404: Ticket not found

Update the status of the ticket with the given id.

Body JSON:

{
    "status": "available" | "busy" | "reserved"
}

Respose codes:

• 200: OK
• 400: Invalid status
• 404: Ticket not found

Endpoints for employees to send reports about problems with bots. A ticket is created and returned in the response.

Body Plaintext

Respose codes:

• 200: OK
• 400: Failed to parse report

Response JSON:

{
    "ticket_id": "string",
    "problem_location": "string",
    "problem_type": "software" | "hardware" | "field",
    "summary": "string",
    "bot_id": "string",
    "status": "open" | "in progress" | "closed"
}