Add app scaffold and workflows

app/backend/Dockerfile

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+#
+# BACKEND DOCKERFILE
+#
+# Multi-stage image for the FastAPI + LiveKit Agent backend using uv.
+# - production: smallest runtime image with gunicorn/uvicorn worker
+# - development: hot-reload friendly image with full toolchain
+# - builder: installs dependencies once for reuse across stages
+#
+# Keep dependency definitions aligned with docs/architecture.md.
+
+FROM python:3.12-slim AS base
+
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1 \
+    PIP_NO_CACHE_DIR=1 \
+    PIP_DISABLE_PIP_VERSION_CHECK=1 \
+    UV_PROJECT_ENVIRONMENT=/app/.venv \
+    UV_LINK_MODE=copy
+
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends \
+        build-essential \
+        curl \
+        libpq-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN groupadd --system app && useradd --system --home /app --gid app app
+WORKDIR /app
+
+# Install uv globally so subsequent stages share the toolchain.
+RUN pip install --upgrade pip uv
+
+# ------------------------------------------------------------------------------
+# Builder: install prod dependencies into an in-project virtualenv
+# ------------------------------------------------------------------------------
+FROM base AS builder
+
+COPY . .
+RUN test -f pyproject.toml || (echo "pyproject.toml is required for uv sync"; exit 1)
+RUN if [ -f uv.lock ]; then \
+      uv sync --frozen --no-dev --compile-bytecode; \
+    else \
+      uv sync --no-dev --compile-bytecode; \
+    fi
+
+# ------------------------------------------------------------------------------
+# Production: minimal runtime image with gunicorn as the entrypoint
+# ------------------------------------------------------------------------------
+FROM python:3.12-slim AS production
+
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1 \
+    PIP_NO_CACHE_DIR=1
+
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends libpq5 \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN groupadd --system app && useradd --system --home /app --gid app app
+WORKDIR /app
+
+COPY --from=builder --chown=app:app /app /app
+ENV PATH="/app/.venv/bin:$PATH"
+
+USER app
+EXPOSE 8000
+CMD ["gunicorn", "-w", "4", "-k", "uvicorn.workers.UvicornWorker", "main:app", "--bind", "0.0.0.0:8000"]
+
+# ------------------------------------------------------------------------------
+# Development: includes dev dependencies and keeps uvicorn reload-friendly
+# ------------------------------------------------------------------------------
+FROM base AS development
+
+COPY . .
+RUN test -f pyproject.toml || (echo "pyproject.toml is required for uv sync"; exit 1)
+RUN if [ -f uv.lock ]; then \
+      uv sync --frozen --dev --compile-bytecode; \
+    else \
+      uv sync --dev --compile-bytecode; \
+    fi
+
+ENV PATH="/app/.venv/bin:$PATH"
+USER app
+EXPOSE 8000

app/backend/__init__.py

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+"""Backend package for avaaz.ai."""

app/backend/api/__init__.py

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+"""API package with versioned routers."""

app/backend/api/v1/__init__.py

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+"""API v1 package."""

app/backend/api/v1/router.py

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+"""Version 1 API router aggregator for features."""
+
+from fastapi import APIRouter
+
+from features.auth.router import router as auth_router
+
+router = APIRouter()
+router.include_router(auth_router)

app/backend/core/__init__.py

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+"""Core infrastructure (config, database, etc.)."""

app/backend/core/config.py

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+"""Environment configuration derived from environment variables."""
+
+from functools import lru_cache
+from pydantic import SecretStr # Import SecretStr for sensitive data
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+class Settings(BaseSettings):
+    """
+    Application settings class using Pydantic BaseSettings.
+    Settings are loaded from environment variables and have default values defined here.
+    """
+
+    service_name: str = "avaaz-backend" # A unique functional identifier for the microservice
+    environment: str = "development" # Defines the current deployment stage (e.g., 'development', 'staging', 'production')
+
+    title: str = "Avaaz Language Tutoring API"
+    description: str = """
+        # Avaaz Language Tutoring API
+
+        This API powers the **avaaz.ai** mobile and web applications, providing the robust backend services for our AI-driven oral language skills tutor. The platform is specifically engineered to help students achieve oral proficiency using adaptive, conversational AI agents.
+
+        ## Key Services Provided:
+        *   **Conversational AI Engine:** Facilitates ultra-low-latency speech-to-speech interaction and provides instant corrective feedback (grammar, pronunciation, fluency).
+        *   **Curriculum Management:** Delivers structured, CEFR aligned lessons and scenarios focused on real-life immigrant contexts (healthcare, workplace, school).
+        *   **Assessment & Gamification:** Manages progress tracking, mock oral exam simulations, performance summaries, and motivational mechanics (streaks, badges).
+        *   **Cross-Platform Sync:** Ensures seamless learning continuity and progress synchronization across all user devices.
+        """
+    
+    version: str = "0.1.0" # The current semantic version of the API application
+    
+    # Use SecretStr to prevent accidental logging of credentials.
+    # Access the actual value using settings.database_url.get_secret_value()
+    database_url: SecretStr = SecretStr("postgresql+psycopg://postgres:postgres@postgres:5432/avaaz")
+
+    model_config = SettingsConfigDict(
+        env_prefix="",  # Load variables without a specific prefix (e.g., `DATABASE_URL` instead of `APP_DATABASE_URL`)
+        case_sensitive=False # Environment variable names are treated as case-insensitive during loading
+    )
+
+@lru_cache(maxsize=1)
+def get_settings() -> Settings:
+    """
+    Return a cached singleton instance of the application settings.
+    
+    This function leverages functools.lru_cache to ensure that environment variables
+    are read only once during the application's lifecycle, improving performance
+    and ensuring consistency across requests.
+    """
+    return Settings()

app/backend/core/database.py

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+"""Database connection placeholders."""
+
+from contextlib import contextmanager
+from typing import Iterator
+
+
+@contextmanager
+def get_db() -> Iterator[None]:
+    """
+    Yield a database session placeholder.
+
+    Replace with a real session (e.g., SQLAlchemy) when persistence is added.
+    """
+    yield None

app/backend/features/__init__.py

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+"""Domain feature modules."""

app/backend/features/auth/__init__.py

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+"""Auth feature placeholder."""

app/backend/features/auth/adapters/__init__.py

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+"""Adapters for auth integrations."""

app/backend/features/auth/adapters/fastapi_users.py

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+"""Placeholder for FastAPI Users integration."""
+
+# Add glue code for FastAPI Users when adopting that library.

app/backend/features/auth/dependencies.py

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+"""Authentication dependencies placeholder."""
+
+# Add FastAPI dependencies (e.g., current_user) when auth is implemented.

app/backend/features/auth/models.py

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+"""Authentication models placeholder."""
+
+# Add ORM models (e.g., SQLAlchemy) when auth is implemented.

app/backend/features/auth/permissions.py

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+"""Authentication permission placeholder."""
+
+# Define scopes/roles when auth is implemented.

app/backend/features/auth/router.py

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+"""Authentication router placeholder."""
+
+from fastapi import APIRouter
+
+router = APIRouter(prefix="/auth", tags=["auth"])
+
+
+@router.get("/noop", include_in_schema=False)
+def auth_not_implemented() -> dict:
+    """Placeholder endpoint to keep router wired."""
+    return {"status": "not_implemented"}

app/backend/features/auth/schemas.py

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+"""Authentication schemas placeholder."""
+
+# Add Pydantic models for auth requests/responses when implemented.

app/backend/features/auth/service.py

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+"""Authentication service placeholder."""
+
+# Add token generation/verification logic here.

app/backend/main.py

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+"""
+API Application Entrypoint and Router Wiring.
+
+This module initializes the core FastAPI application instance, loads
+configuration, applies middleware, and wires up all defined API routers.
+"""
+
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from typing import List
+
+from api.v1.router import router as api_v1_router
+from operations.health.router import router as health_router
+from core.config import get_settings, Settings # Import Settings type for clarity
+
+def create_app(settings: Settings = get_settings()) -> FastAPI:
+    """
+    Create and configure the FastAPI application instance.
+
+    Args:
+        settings: Configuration object from core.config. Defaults to current settings.
+
+    Returns:
+        A configured FastAPI application instance.
+    """
+    app = FastAPI(
+        title=settings.title,
+        description=settings.description,
+        version=settings.version,
+        docs_url="/docs",
+        redoc_url=None,
+        openapi_url="/openapi.json",
+    )
+
+    # Define allowed origins dynamically based on local dev environment needs
+    # In a production setting, this list would typically be sourced from environment variables.
+    allowed_origins: List[str] = ["http://localhost:3000", "http://127.0.0.1:3000"]
+    
+    # Configure CORS middleware
+    # TODO: Tightly restrict origins in production deployment.
+    app.add_middleware(
+        CORSMiddleware,
+        allow_origins=allowed_origins,
+        allow_credentials=True,
+        allow_methods=["*"],
+        allow_headers=["*"],
+    )
+
+    # Include API routers
+    app.include_router(health_router)
+    app.include_router(api_v1_router, prefix="/api/v1")
+
+    return app
+
+# Main entry point for services like Uvicorn (e.g., `uvicorn main:app --reload`)
+app = create_app()

app/backend/operations/__init__.py

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+"""Domain operation modules."""

app/backend/operations/health/__init__.py

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+"""Health feature package."""

app/backend/operations/health/router.py

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+"""Health endpoints for FastAPI application health checks (Liveness, Readiness, Detailed Status)."""
+
+from fastapi import APIRouter, Depends, HTTPException
+from fastapi.responses import PlainTextResponse
+
+# Dependencies for application configuration and schema definitions
+from core.config import Settings, get_settings
+from operations.health.schemas import HealthStatus, HealthStatusEnum
+from operations.health.service import get_detailed_health, readiness_check
+
+# Initialize the API router for health endpoints, grouping them under the "/health" prefix
+router = APIRouter(prefix="/health", tags=["health"])
+
+
+@router.get(
+    "/live",
+    summary="Liveness Probe",
+    response_class=PlainTextResponse,
+    status_code=200,
+)
+def liveness() -> str:
+    """
+    **Liveness Probe:** Confirms the application process is running and responsive.
+
+    This endpoint is used by automated systems (like Kubernetes) to determine if
+    the instance should be kept running or restarted. It must be extremely lightweight,
+    performing no deep checks on external dependencies.
+
+    **Success Response:** HTTP 200 OK with "live" body.  
+    **Failure Response:** The orchestrator will interpret a *TCP connection timeout* as a failure.
+    """
+    # Simply returning a string confirms the Python process and FastAPI are functional.
+    return "live"
+
+
+@router.get(
+    "/ready",
+    summary="Readiness Probe",
+    response_class=PlainTextResponse,
+    status_code=200,
+)
+async def readiness() -> str:
+    """
+    **Readiness Probe:** Determines if the application can accept user traffic.
+
+    This endpoint is used by load balancers or service meshes to decide whether
+    to route traffic to this specific instance. It performs deep checks
+    on all critical dependencies (e.g., database connection, external services).
+
+    **Success Response:** HTTP 200 OK with "ready" body.  
+    **Failure Response:** HTTP 503 Service Unavailable if any critical dependency fails.
+    """
+    # Call the service layer function that runs all critical checks concurrently
+    ok = await readiness_check()
+    
+    if not ok:
+        # If any check fails, signal 'Service Unavailable' so traffic is diverted
+        raise HTTPException(status_code=503, detail="not ready")
+
+    return "ready"
+
+
+@router.get(
+    "",
+    summary="Detailed Health Status Page",
+    response_model=HealthStatus,
+)
+async def detailed_health(settings: Settings = Depends(get_settings)) -> HealthStatus:
+    """
+    **Detailed Status Page:** Provides granular health information for human operators/monitoring tools.
+
+    This endpoint runs all readiness checks and returns a structured JSON object
+    containing the status of each individual component.
+    The top-level HTTP status code reflects the overall application health (200 OK for 'pass', 503 for 'fail').
+    """
+    # Retrieve the comprehensive health status model
+    detailed_health = await get_detailed_health(settings)
+
+    if detailed_health.status != HealthStatusEnum.passed:
+        # Align the HTTP status code with the overall health status for easy monitoring
+        raise HTTPException(status_code=503, detail="not ready")
+
+    # Status code is 200
+    return detailed_health

app/backend/operations/health/schemas.py

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+"""
+Pydantic schemas for defining health check responses, following IETF standards.
+"""
+
+from datetime import datetime
+from enum import Enum
+
+# Import ConfigDict from pydantic to resolve the deprecation warning
+from pydantic import BaseModel, Field, ConfigDict
+
+# Define acceptable statuses as an Enum for robust validation
+class HealthStatusEnum(str, Enum):
+    """Enumeration for standard health check statuses."""
+    passed = "pass"
+    warned = "warn"
+    failed = "fail"
+
+class ComponentCheck(BaseModel):
+    """
+    Represents the status and metrics for a single internal component or dependency.
+    """
+    # Use ConfigDict instead of the class Config approach
+    model_config = ConfigDict(
+        populate_by_name=True  # Allows instantiation using either 'observed_value' or 'observedValue'
+    )
+
+    name: str = Field(description="The unique name of the component being checked (e.g., 'postgres', 'redis').")
+    status: HealthStatusEnum = Field(description="The status of the check: 'pass', 'warn', or 'fail'.")
+    time: datetime | None = Field(default=None, description="The time at which the check was performed in ISO 8601 format.")
+    output: str | None = Field(default=None, description="Additional details, error messages, or logs if the status is 'fail' or 'warn'.")
+    
+    # Python uses snake_case internally, JSON uses camelCase for the alias
+    observed_value: float | int | None = Field(
+        default=None, 
+        alias="observedValue", 
+        description="The value observed during the check (e.g., latency in ms)."
+    )
+    # Python uses snake_case internally, JSON uses camelCase for the alias
+    observed_unit: str | None = Field(
+        default=None, 
+        alias="observedUnit", 
+        description="The unit of the observed value (e.g., 'ms', 'count', 'bytes')."
+    )
+
+class HealthStatus(BaseModel):
+    """
+    The overall system health response model, aggregating all individual component checks.
+    """
+    # Use ConfigDict instead of the class Config approach
+    model_config = ConfigDict(
+        populate_by_name=True
+    )
+
+    status: HealthStatusEnum = Field(description="The aggregate status of the entire service: 'pass', 'warn', or 'fail'.")
+    version: str | None = Field(default=None, description="The application version (e.g., Git SHA or semantic version number).")
+    environment: str | None = Field(default=None, description="The deployment environment (e.g., 'production', 'staging').")
+    
+    # Python uses snake_case internally, JSON uses camelCase for the alias
+    service_name: str | None = Field(
+        default=None, 
+        alias="serviceName", 
+        description="The name of the service."
+    )
+    description: str | None = Field(default=None, description="A brief description of the service.")
+    checks: dict[str, ComponentCheck] = Field(description="A dictionary mapping check keys (e.g., 'Database') to their detailed ComponentCheck results.")

app/backend/operations/health/service.py

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+import asyncio
+from datetime import datetime, timezone
+from typing import Callable, Coroutine, Any, List, Dict
+
+from core.config import Settings
+# Assuming schemas now contains the Enum definition and uses it in the models
+from operations.health.schemas import ComponentCheck, HealthStatus, HealthStatusEnum 
+
+# Type alias for a function that returns an awaitable ComponentCheck.
+HealthCheckFunc = Callable[[], Coroutine[Any, Any, ComponentCheck]]
+
+async def _run_check_with_timeout(
+    check_coroutine: Coroutine[Any, Any, None], 
+    name: str, 
+    timeout_ms: int
+) -> ComponentCheck:
+    """
+    A utility wrapper that executes a given async coroutine with a strict timeout constraint.
+    It standardizes the exception handling and timing calculation for health checks.
+    """
+    start_time = datetime.now(timezone.utc)
+    # Convert milliseconds timeout to a float in seconds for asyncio
+    timeout_seconds = timeout_ms / 1000.0
+
+    try:
+        # Enforce the timeout using the modern asyncio.timeout context manager (Python 3.11+)
+        async with asyncio.timeout(timeout_seconds):
+            await check_coroutine
+        
+        # If execution reaches here, the check passed within the time limit.
+        duration = datetime.now(timezone.utc) - start_time
+        observed_value = int(duration.total_seconds() * 1000) # value stored in ms
+
+        return ComponentCheck(
+            name=name,
+            # Use the Enum value for status
+            status=HealthStatusEnum.passed,
+            time=datetime.now(timezone.utc),
+            observedValue=observed_value,
+            observedUnit="ms",
+        )
+
+    except asyncio.TimeoutError:
+        # The operation specifically took too long and the timeout context manager raised an exception.
+        return ComponentCheck(
+            name=name,
+            # Use the Enum value for status
+            status=HealthStatusEnum.failed,
+            time=datetime.now(timezone.utc),
+            output=f"Check timed out after {timeout_seconds:.2f}s",
+        )
+    except Exception as e:
+        # Catch any other general exceptions (e.g., connection refused, network down)
+        return ComponentCheck(
+            name=name,
+            # Use the Enum value for status
+            status=HealthStatusEnum.failed,
+            time=datetime.now(timezone.utc),
+            output=f"An error occurred: {str(e)}",
+        )
+
+async def check_database_status() -> ComponentCheck:
+    """
+    Initiates the check for the primary database connection.
+    Calls the generic wrapper with specific logic and timeout for Postgres.
+    """
+    async def db_logic():
+        # IMPORTANT: Replace this sleep simulation with the actual async DB client call (e.g., await database.ping())
+        await asyncio.sleep(0.045) 
+    
+    return await _run_check_with_timeout(db_logic(), name="postgres", timeout_ms=50)
+
+async def check_media_server_status() -> ComponentCheck:
+    """
+    Initiates the check for the media server connection.
+    Calls the generic wrapper with specific logic and timeout for LiveKit/Media Server.
+    """
+    async def media_logic():
+        # IMPORTANT: Replace this sleep simulation with the actual network I/O call (e.g., await http_client.get('...'))
+        await asyncio.sleep(0.02)
+
+    return await _run_check_with_timeout(media_logic(), name="livekit", timeout_ms=50)
+
+# This dictionary serves as the single source of truth for all critical health checks.
+CRITICAL_CHECKS: Dict[str, HealthCheckFunc] = {
+    "Database": check_database_status,
+    "Media Server": check_media_server_status
+}
+
+async def readiness_check() -> bool:
+    """
+    Performs a readiness probe. The service is considered "ready" only if *all* critical checks pass.
+    """
+    tasks = [check_func() for check_func in CRITICAL_CHECKS.values()]
+    results: List[ComponentCheck] = await asyncio.gather(*tasks)
+
+    # Check if every result status is equal to the HealthStatusEnum.passed value ('pass')
+    return all(result.status == HealthStatusEnum.passed for result in results)
+
+async def get_detailed_health(settings: Settings) -> HealthStatus:
+    """
+    Builds a detailed health payload that conforms to the health+json specification.
+    Aggregates results from all CRITICAL_CHECKS and includes system metadata.
+    """
+    
+    tasks = [check_func() for check_func in CRITICAL_CHECKS.values()]
+    results: List[ComponentCheck] = await asyncio.gather(*tasks)
+
+    # Initialize overall status using the Enum value
+    overall = HealthStatusEnum.passed
+    checks = {}
+    
+    # Iterate through results, mapping them back to their original dictionary keys
+    for key, result in zip(CRITICAL_CHECKS.keys(), results):
+        checks[key] = result
+        # Compare status against the Enum value
+        if result.status != HealthStatusEnum.passed:
+            # If any individual check fails, the overall system status must be 'fail'
+            overall = HealthStatusEnum.failed
+
+    # Assemble the final, comprehensive health report object using provided settings
+    return HealthStatus(
+        status=overall,
+        version=settings.version,
+        environment=settings.environment,
+        serviceName=settings.service_name,
+        description=settings.title,
+        checks=checks,
+    )

app/backend/pyproject.toml

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+[project]
+name = "avaaz-backend"
+version = "0.1.0"
+description = "FastAPI backend for avaaz.ai with health check."
+authors = [{ name = "avaaz.ai" }]
+requires-python = ">=3.12"
+dependencies = [
+  "fastapi>=0.115.4,<0.116",
+  "uvicorn[standard]>=0.30.6,<0.31",
+  "pydantic-settings>=2.6.1,<3",
+  "gunicorn>=22.0,<23",
+]
+
+[project.optional-dependencies]
+dev = [
+  "pytest>=8.3,<9",
+  "pytest-cov>=5.0,<6",
+  "hypothesis>=6.112,<7",
+  "httpx>=0.27,<0.28",
+]
+
+[dependency-groups]
+dev = [
+  "pytest>=8.3,<9",
+  "pytest-cov>=5.0,<6",
+  "hypothesis>=6.112,<7",
+  "httpx>=0.27,<0.28",
+]
+
+[tool.pytest.ini_options]
+addopts = "-ra"
+testpaths = ["tests"]
+
+[tool.setuptools]
+py-modules = ["main"]
+
+[tool.setuptools.packages.find]
+include = ["api*", "core*", "features*", "operations*"]
+
+[build-system]
+requires = ["setuptools>=68", "wheel"]
+build-backend = "setuptools.build_meta"

app/backend/tests/__init__.py

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+"""Test suite for backend."""

app/backend/tests/test_health.py

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+from fastapi.testclient import TestClient
+from hypothesis import given, settings
+from hypothesis import strategies as st
+
+# Import the main FastAPI application instance from your source code
+from main import app
+
+# Initialize the TestClient to make requests against your FastAPI app instance
+client = TestClient(app)
+
+def test_liveness_ok():
+    """
+    Test the basic liveness endpoint.
+    A liveness probe checks if the container is running and responsive.
+    It should always return a 200 OK status and the text 'live'.
+    """
+    response = client.get("/health/live")
+    assert response.status_code == 200
+    assert response.text == "live"
+
+@given(st.text(min_size=0, max_size=16))
+@settings(max_examples=10)
+def test_liveness_resilience_to_query_noise(noise: str):
+    """
+    Use Hypothesis for property-based testing.
+    This test ensures that the liveness endpoint is robust and remains functional
+    even when unexpected or garbage query parameters ("noise") are provided in the URL.
+    The `given` decorator generates various string inputs for the 'noise' parameter.
+    """
+    # Pass arbitrary query parameters to the endpoint
+    response = client.get("/health/live", params={"noise": noise})
+    assert response.status_code == 200
+    assert response.text == "live"
+
+def test_readiness_ok():
+    """
+    Test the basic readiness endpoint.
+    A readiness probe checks if the container is ready to accept traffic (e.g., database connection established).
+    It should return a 200 OK status and the text 'ready' when healthy.
+    """
+    response = client.get("/health/ready")
+    assert response.status_code == 200
+    assert response.text == "ready"
+
+@given(st.text(min_size=0, max_size=16))
+@settings(max_examples=10)
+def test_readiness_resilience_to_query_noise(noise: str):
+    """
+    Use Hypothesis for property-based testing.
+    This test ensures that the readiness endpoint is robust and remains functional
+    even when unexpected or garbage query parameters ("noise") are provided in the URL.
+    The `given` decorator generates various string inputs for the 'noise' parameter.
+    """
+    # Pass arbitrary query parameters to the endpoint
+    response = client.get("/health/ready", params={"noise": noise})
+    assert response.status_code == 200
+    assert response.text == "ready"
+
+def test_detailed_health_pass():
+    """
+    Test the detailed health check endpoint, often conforming to the
+    [IETF health check standard](datatracker.ietf.org).
+    It should return a 200 OK status, and the JSON body should have a
+    "status" of "pass" and a dictionary of individual "checks".
+    """
+    response = client.get("/health")
+    assert response.status_code == 200
+    body = response.json()
+    assert body["status"] == "pass"
+    assert isinstance(body["checks"], dict)
+
+@given(st.text(min_size=0, max_size=16))
+@settings(max_examples=10)
+def test_health_resilience_to_query_noise(noise: str):
+    """
+    Use Hypothesis for property-based testing.
+    This test ensures that the health endpoint is robust and remains functional
+    even when unexpected or garbage query parameters ("noise") are provided in the URL.
+    The `given` decorator generates various string inputs for the 'noise' parameter.
+    """
+    # Pass arbitrary query parameters to the endpoint
+    response = client.get("/health", params={"noise": noise})
+    assert response.status_code == 200
+    body = response.json()
+    assert body["status"] == "pass"
+    assert isinstance(body["checks"], dict)

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