AMDHackathon/user_context_schema.py at main · Alexander-Reyes9/AMDHackathon · GitHub

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"""Canonical JSON Schema for the transient mood-discovery user context."""

from __future__ import annotations

from copy import deepcopy
from typing import Any


# Keep this separate from FastAPI's flattened request model.  Clients can use this
# document to collect a complete, portable description of a person's current
# context without creating a persistent user profile.
USER_CONTEXT_SCHEMA: dict[str, Any] = {
    "$schema": "https://json-schema.org/draft/2020-12/schema",
    "$id": "https://amdhackathon.local/schemas/user_context.schema.json",
    "title": "User context",
    "description": (
        "One transient nearby-discovery request: current location, current mood, "
        "local time context, and availability preferences. This document does not "
        "describe or require a persisted user profile."
    ),
    "type": "object",
    "required": ["location", "feeling", "time_context"],
    "properties": {
        "location": {
            "type": "object",
            "required": ["latitude", "longitude"],
            "properties": {
                "latitude": {
                    "type": "number",
                    "minimum": -90,
                    "maximum": 90,
                    "description": "Current latitude in WGS84 decimal degrees.",
                },
                "longitude": {
                    "type": "number",
                    "minimum": -180,
                    "maximum": 180,
                    "description": "Current longitude in WGS84 decimal degrees.",
                },
                "radius_m": {
                    "type": "integer",
                    "minimum": 100,
                    "maximum": 40000,
                    "default": 3000,
                    "description": "Fixed search radius in metres around the current location.",
                },
            },
        },
        "feeling": {
            "type": "object",
            "required": ["mood_query"],
            "properties": {
                "mood_query": {
                    "type": "string",
                    "minLength": 1,
                    "maxLength": 500,
                    "description": "Free-text current mood or intent, such as 'hungry for ramen'.",
                },
                "resolved_mood_label": {
                    "type": "string",
                    "description": "Optional normalized label selected by the mood resolver.",
                },
                "mood_similarity": {
                    "type": "number",
                    "minimum": 0,
                    "maximum": 1,
                    "description": "Optional confidence score for the normalized mood label.",
                },
            },
        },
        "time_context": {
            "type": "object",
            "required": ["local_time_iso", "timezone_name"],
            "properties": {
                "local_time_iso": {
                    "type": "string",
                    "format": "date-time",
                    "description": "Current local time in ISO 8601 format.",
                },
                "timezone_name": {
                    "type": "string",
                    "description": "IANA timezone name, for example America/Los_Angeles.",
                },
                "time_bucket": {
                    "type": "string",
                    "enum": ["morning", "afternoon", "evening", "night"],
                },
            },
        },
        "preferences": {
            "type": "object",
            "properties": {
                "top_k": {
                    "type": "integer",
                    "minimum": 1,
                    "maximum": 50,
                    "default": 8,
                    "description": "Compatibility name for the number of ranked POIs to return.",
                },
                "max_results": {
                    "type": "integer",
                    "minimum": 1,
                    "maximum": 20,
                    "default": 8,
                    "description": "Number of ranked POIs the current API returns.",
                },
                "hero_limit": {
                    "type": "integer",
                    "minimum": 0,
                    "maximum": 20,
                    "default": 8,
                    "description": "Compatibility name for the number of representative hero images.",
                },
                "image_limit": {
                    "type": "integer",
                    "minimum": 0,
                    "maximum": 20,
                    "default": 8,
                    "description": "Number of PixArt representative images to generate; defaults to one per returned POI.",
                },
                "open_now_only": {
                    "type": "boolean",
                    "default": True,
                    "description": "Prefer businesses currently reported open by the provider.",
                },
                "generate_images": {
                    "type": "boolean",
                    "default": True,
                },
                "inference_steps": {
                    "type": "integer",
                    "minimum": 1,
                    "maximum": 50,
                    "default": 20,
                },
                "guidance_scale": {
                    "type": "number",
                    "minimum": 1,
                    "maximum": 20,
                    "default": 4.5,
                },
                "seed": {
                    "type": "integer",
                    "minimum": 0,
                    "maximum": 2147483647,
                    "default": 42,
                },
                "compile_transformer": {
                    "type": "boolean",
                    "default": False,
                },
            },
        },
    },
}


def schema_document() -> dict[str, Any]:
    """Return a copy so callers cannot mutate the canonical schema in memory."""

    return deepcopy(USER_CONTEXT_SCHEMA)