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Add app scaffold and workflows
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Madava
2025-12-03 08:58:34 +01:00
parent 5a8b773e40
commit d6b61ae8fb
51 changed files with 10252 additions and 3 deletions
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app/.dockerignore Normal file
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# ==============================================================================
# .dockerignore – Python + Next.js (Docker Compose)
# ==============================================================================
# ----------------------------------------------------------------------------
# Git & Version Control
# ----------------------------------------------------------------------------
.git
.gitignore
.gitattributes
.github
.gitpod.yml
# ----------------------------------------------------------------------------
# Python-specific (already in .gitignore, but repeat for safety)
# ----------------------------------------------------------------------------
__pycache__/
*.py[cod]
*$py.class
*.so
*.egg-info/
.installed.cfg
*.egg
*.manifest
*.spec
# Virtual environments & caches
.venv
venv/
env/
ENV/
.pixi/
__pypackages__/
.tox/
.nox/
.pdm-python
.pdm-build/
# Testing & coverage
htmlcov/
.coverage
.coverage.*
.pytest_cache/
.coverage/
.ruff_cache/
.mypy_cache/
.pyre/
.pytype/
# Jupyter / notebooks
.ipynb_checkpoints
# IDEs & editors
.idea/
.vscode/
*.swp
*.swo
*~
# ----------------------------------------------------------------------------
# Next.js / Node.js
# ----------------------------------------------------------------------------
node_modules/
.next/
out/
build/
dist/
.npm
.pnp.*
.yarn/
.yarn-cache/
.yarn-unplugged/
# TypeScript build info
*.tsbuildinfo
next-env.d.ts
# Logs & debug
npm-debug.log*
yarn-debug.log*
yarn-error.log*
.pnpm-debug.log*
# ----------------------------------------------------------------------------
# Environment & Secrets (never send to Docker daemon)
# ----------------------------------------------------------------------------
.env
.env.local
.env*.local
.env.production
.env.development
.envrc
*.pem
*.key
*.crt
*.secrets
.streamlit/secrets.toml
# ----------------------------------------------------------------------------
# Docker & Compose (avoid recursive inclusion)
# ----------------------------------------------------------------------------
Dockerfile*
docker-compose*.yml
docker-compose*.yaml
.dockerignore
# ----------------------------------------------------------------------------
# Misc / OS
# ----------------------------------------------------------------------------
.DS_Store
Thumbs.db
desktop.ini
# Local documentation builds
/site
docs/_build/
# Temporary files
tmp/
temp/
*.tmp
*.log
# ==============================================================================
# End of file
# ==============================================================================

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#
# Sample environment for docker compose. Copy to .env and adjust.
#
# Profiles:
# dev - laptop development (hot reload + localhost ports)
# prod - VPS behind Caddy (no public container ports; secrets provided by CI/CD)
#
COMPOSE_PROFILES=dev
DOCKER_RESTART_POLICY=unless-stopped
# PostgreSQL
POSTGRES_USER=postgres
POSTGRES_PASSWORD=postgres
POSTGRES_DB=avaaz
POSTGRES_HOST=postgres
POSTGRES_PORT=5432
DATABASE_URL=postgresql+psycopg://${POSTGRES_USER}:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/${POSTGRES_DB}
# Backend
ENVIRONMENT=development
SECRET_KEY=dev-secret-change-me
GUNICORN_WORKERS=4
GUNICORN_TIMEOUT=120
OPENAI_API_KEY=
GOOGLE_API_KEY=
# LiveKit
LIVEKIT_API_KEY=devkey
LIVEKIT_API_SECRET=devsecret
LIVEKIT_LOG_LEVEL=info
LIVEKIT_WS_URL=ws://livekit:7880
LIVEKIT_URL=http://livekit:7880
# Frontend
NEXT_PUBLIC_API_URL=http://localhost:8000
NEXT_PUBLIC_LIVEKIT_WS_URL=ws://localhost:7880
# Production overrides (supply via secrets/CI, not committed):
# COMPOSE_PROFILES=prod
# ENVIRONMENT=production
# SECRET_KEY=<strong-random-secret>
# NEXT_PUBLIC_API_URL=https://api.avaaz.ai
# NEXT_PUBLIC_LIVEKIT_WS_URL=wss://rtc.avaaz.ai
# LIVEKIT_WS_URL=ws://livekit:7880
# LIVEKIT_API_KEY=<lk-key>
# LIVEKIT_API_SECRET=<lk-secret>
# OPENAI_API_KEY=<openai-key>
# GOOGLE_API_KEY=<gemini-key>

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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

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

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

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app/backend/api/v1/__init__.py Normal file
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"""API v1 package."""

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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)

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

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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()

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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

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"""Domain feature modules."""

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"""Auth feature placeholder."""

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"""Adapters for auth integrations."""

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

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

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

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

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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"}

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

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

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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()

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"""Domain operation modules."""

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"""Health feature package."""

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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

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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.")

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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,
)

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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"

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"""Test suite for backend."""

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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)

720
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231
app/docker-compose.yml Normal file
View File

@@ -0,0 +1,231 @@
# COMPOSE_PROFILES controls which services start:
# - dev : laptop-friendly; mounts source, exposes localhost ports, enables reloaders
# - prod : VPS-friendly; no host ports for app containers, joins proxy network for Caddy
x-service-defaults: &service-defaults
env_file: .env
restart: ${DOCKER_RESTART_POLICY:-unless-stopped}
networks:
- app
logging:
driver: "json-file"
options:
max-size: "10m"
max-file: "3"
x-backend-common: &backend-common
<<: *service-defaults
depends_on:
postgres:
condition: service_healthy
services:
# --------------------------------------------------------------------------
# Next.js Frontend
# --------------------------------------------------------------------------
frontend:
<<: *service-defaults
profiles: [prod]
container_name: frontend
build:
context: ./frontend
dockerfile: Dockerfile
target: runner
environment:
NODE_ENV: production
NEXT_TELEMETRY_DISABLED: 1
PORT: 3000
expose:
- "3000"
depends_on:
backend:
condition: service_healthy
healthcheck:
test:
[
"CMD-SHELL",
"node -e \"require('http').get('http://127.0.0.1:3000', (res) => { process.exit(res.statusCode < 500 ? 0 : 1); }).on('error', () => process.exit(1));\"",
]
interval: 30s
timeout: 5s
retries: 5
start_period: 10s
networks:
- app
- proxy
# Caddy from the infra stack reverse-proxies to this container on the proxy network.
frontend-dev:
<<: *service-defaults
profiles: [dev]
container_name: frontend-dev
build:
context: ./frontend
dockerfile: Dockerfile
target: dev
command: ["npm", "run", "dev", "--", "--hostname", "0.0.0.0", "--port", "3000"]
environment:
NODE_ENV: development
NEXT_TELEMETRY_DISABLED: 1
ports:
- "3000:3000" # Localhost access during development
volumes:
- ./frontend:/app
- frontend-node_modules:/app/node_modules
depends_on:
backend-dev:
condition: service_healthy
networks:
app:
aliases:
- frontend
# --------------------------------------------------------------------------
# FastAPI Backend
# --------------------------------------------------------------------------
backend:
<<: *backend-common
profiles: [prod]
container_name: backend
build:
context: ./backend
dockerfile: Dockerfile
target: production
environment:
ENVIRONMENT: production
command:
[
"gunicorn",
"main:app",
"-k",
"uvicorn.workers.UvicornWorker",
"-w",
"${GUNICORN_WORKERS:-4}",
"--bind",
"0.0.0.0:8000",
"--access-logfile",
"-",
"--error-logfile",
"-",
"--timeout",
"${GUNICORN_TIMEOUT:-120}",
]
expose:
- "8000"
healthcheck:
test:
[
"CMD-SHELL",
"python -c \"import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health/live').close()\"",
]
interval: 30s
timeout: 5s
retries: 5
start_period: 10s
networks:
- app
- proxy
backend-dev:
<<: *backend-common
profiles: [dev]
container_name: backend-dev
build:
context: ./backend
dockerfile: Dockerfile
target: development
environment:
ENVIRONMENT: development
PYTHONPATH: /app
command: ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--reload"]
ports:
- "8000:8000" # Localhost access during development
volumes:
- ./backend:/app
- backend-venv:/app/.venv
healthcheck:
test:
[
"CMD-SHELL",
"python -c \"import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health/live').close()\"",
]
interval: 15s
timeout: 5s
retries: 5
start_period: 10s
networks:
app:
aliases:
- backend
# --------------------------------------------------------------------------
# PostgreSQL + pgvector
# --------------------------------------------------------------------------
postgres:
<<: *service-defaults
container_name: postgres
image: pgvector/pgvector:pg16
profiles:
- dev
- prod
volumes:
- postgres-data:/var/lib/postgresql/data
ports:
- "127.0.0.1:${POSTGRES_PORT:-5432}:5432" # Local-only binding keeps DB off the public interface
healthcheck:
test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-postgres} -d ${POSTGRES_DB:-postgres}"]
interval: 10s
timeout: 5s
retries: 5
# --------------------------------------------------------------------------
# LiveKit Real-Time Server
# --------------------------------------------------------------------------
livekit:
<<: *service-defaults
container_name: livekit
image: livekit/livekit-server:latest
profiles:
- dev
- prod
# UDP/TCP ports remain published in prod so external clients can complete WebRTC/TURN;
# Caddy still proxies signaling over the shared proxy network.
environment:
LIVEKIT_KEYS: "${LIVEKIT_API_KEY}:${LIVEKIT_API_SECRET}"
LIVEKIT_PORT: 7880
LIVEKIT_LOG_LEVEL: ${LIVEKIT_LOG_LEVEL:-info}
command:
[
"livekit-server",
"--dev",
"--port",
"7880",
"--rtc.port-range-start",
"${LIVEKIT_RTC_PORT_RANGE_START:-60000}",
"--rtc.port-range-end",
"${LIVEKIT_RTC_PORT_RANGE_END:-60100}",
]
ports:
- "7880:7880" # HTTP/WS signaling (Caddy terminates TLS)
- "7881:7881" # TCP fallback for WebRTC
- "3478:3478/udp" # TURN
- "5349:5349/tcp" # TURN over TLS
- "${LIVEKIT_RTC_PORT_RANGE_START:-60000}-${LIVEKIT_RTC_PORT_RANGE_END:-60100}:${LIVEKIT_RTC_PORT_RANGE_START:-60000}-${LIVEKIT_RTC_PORT_RANGE_END:-60100}/udp" # WebRTC media plane
networks:
- app
- proxy
volumes:
postgres-data:
backend-venv:
frontend-node_modules:
networks:
app:
name: app_network
proxy:
name: proxy
# In prod, set PROXY_NETWORK_EXTERNAL=true so this attaches to the shared
# Caddy network created by infra. In dev, leave false to let Compose create
# a local network automatically.
external: ${PROXY_NETWORK_EXTERNAL:-false}

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#
# FRONTEND DOCKERFILE
#
# Multi-stage image for the Next.js SPA/SSR frontend.
# - runner: production server with minimal footprint
# - builder: compiles the Next.js app
# - dev: hot-reload friendly image
#
# COMPOSE_PROFILES decides which stage is used by docker-compose.yml.
#
FROM node:22-slim AS base
WORKDIR /app
ENV NPM_CONFIG_LOGLEVEL=warn \
NODE_OPTIONS="--enable-source-maps" \
NEXT_TELEMETRY_DISABLED=1
# ------------------------------------------------------------------------------
# Dependencies cache
# ------------------------------------------------------------------------------
FROM base AS deps
COPY package*.json ./
RUN if [ -f package-lock.json ]; then npm ci; else npm install; fi \
&& chown -R node:node /app
# ------------------------------------------------------------------------------
# Production dependencies only (pruned to omit dev tooling)
# ------------------------------------------------------------------------------
FROM base AS prod-deps
COPY package*.json ./
RUN if [ -f package-lock.json ]; then npm ci --omit=dev; else npm install --omit=dev; fi
# ------------------------------------------------------------------------------
# Builder: compile the application for production
# ------------------------------------------------------------------------------
FROM base AS builder
COPY --from=deps /app/node_modules ./node_modules
COPY . .
ENV NODE_ENV=production
ENV NEXT_TELEMETRY_DISABLED=1
RUN npm run build
# ------------------------------------------------------------------------------
# Production runner: serve the built Next.js app
# ------------------------------------------------------------------------------
FROM node:22-slim AS runner
WORKDIR /app
ENV NODE_ENV=production \
NEXT_TELEMETRY_DISABLED=1
USER node
COPY --from=prod-deps --chown=node:node /app/node_modules ./node_modules
COPY --from=builder --chown=node:node /app/.next ./.next
COPY --from=builder --chown=node:node /app/public ./public
COPY --from=builder --chown=node:node /app/package.json ./package.json
COPY --from=builder --chown=node:node /app/package-lock.json ./package-lock.json
EXPOSE 3000
CMD ["npm", "run", "start"]
# ------------------------------------------------------------------------------
# Development: keeps node_modules and sources mounted for hot reload
# ------------------------------------------------------------------------------
FROM deps AS dev
WORKDIR /app
ENV NODE_ENV=development \
NEXT_TELEMETRY_DISABLED=1
USER node
EXPOSE 3000
CMD ["npm", "run", "dev", "--", "--hostname", "0.0.0.0", "--port", "3000"]

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@import "tailwindcss";
@source "./app/**/*.{js,ts,jsx,tsx,mdx}";
@source "./components/**/*.{js,ts,jsx,tsx,mdx}";
@theme {
--color-ink: #0f172a;
--color-inkSoft: #1e293b;
--color-inkMuted: #64748b;
--color-sand: #f7f7fb;
--color-card: #ffffff;
--color-success: #22c55e;
--color-danger: #ef4444;
--color-pulse: #f59e0b;
--color-accent-blue: #60a5fa;
--color-accent-mint: #34d399;
--color-accent-coral: #fb7185;
--font-sans: "Plus Jakarta Sans", "Inter", system-ui, -apple-system, "Segoe UI",
sans-serif;
--font-display: "Plus Jakarta Sans", "Inter", system-ui, -apple-system, "Segoe UI",
sans-serif;
}
:root {
color-scheme: light;
background-color: #f7f7fb;
}
body {
@apply min-h-screen bg-gradient-to-br from-[#f9fafb] via-[#f2f4f6] to-[#e7eaee] text-ink antialiased;
}
* {
@apply selection:bg-blue-200 selection:text-ink;
}

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import "./globals.css";
import type { Metadata } from "next";
import type { ReactNode } from "react";
export const metadata: Metadata = {
title: "avaaz.ai | Live Health Console",
description: "Live ECG-style monitoring for avaaz.ai health endpoints.",
icons: {
icon: [{ url: "/favicon.png", type: "image/png" }],
shortcut: ["/favicon.png"],
},
};
export default function RootLayout({ children }: { children: ReactNode }) {
return (
<html lang="en">
<body className="bg-sand font-sans text-ink">{children}</body>
</html>
);
}

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"use client";
import Image from "next/image";
import {
useCallback,
useEffect,
useMemo,
useRef,
useState,
} from "react";
import { ECGMonitorCard } from "@/components/ECGMonitorCard";
import type { PollState } from "@/types/monitor";
interface HealthSummary {
status: string;
version?: string;
serviceId?: string;
description?: string;
checks?:
| Record<string, { status: string; output?: string; details?: string }>
| {
name?: string;
key?: string;
check?: string;
status: string;
output?: string;
details?: string;
}[];
}
const POLL_INTERVALS = {
live: 10_000,
ready: 30_000,
health: 60_000,
} as const;
const WAVE_SAMPLES = 140;
const WAVE_WIDTH = 360;
const BASELINE = 68;
const MIN_Y = 20;
const MAX_Y = 110;
const NOISE = 1.4;
function formatTime(timestamp: string | null) {
if (!timestamp) return "Pending";
return new Date(timestamp).toLocaleTimeString([], {
hour: "2-digit",
minute: "2-digit",
second: "2-digit",
});
}
function useNowString() {
const [now, setNow] = useState<string>("");
useEffect(() => {
const tick = () =>
setNow(
new Date().toLocaleTimeString([], {
hour: "2-digit",
minute: "2-digit",
second: "2-digit",
})
);
tick();
const id = setInterval(tick, 1_000);
return () => clearInterval(id);
}, []);
return now;
}
function hasStatusField(value: unknown): value is { status?: unknown } {
return typeof value === "object" && value !== null && "status" in value;
}
function isStatusHealthy(value: unknown): boolean {
if (!value) return false;
if (typeof value === "string") {
return ["ok", "pass", "healthy", "up", "ready", "live"].includes(
value.toLowerCase()
);
}
if (hasStatusField(value) && typeof value.status === "string") {
return ["ok", "pass", "healthy", "up", "ready", "live"].includes(
value.status.toLowerCase()
);
}
return false;
}
/**
* Drives the shared ECG waveform: keeps the line scrolling and injects pulse spikes
* whenever a poll occurs so the right edge always shows the freshest activity.
*/
function useWaveform() {
const [wave, setWave] = useState<number[]>(() =>
Array.from({ length: WAVE_SAMPLES }, () => BASELINE)
);
const queueRef = useRef<number[]>([]);
const tickRef = useRef(0);
// Queue sharp spikes that get blended into the scrolling ECG line.
const triggerPulse = useCallback((strength = 18) => {
queueRef.current.push(
BASELINE - 6,
BASELINE + strength,
BASELINE - 10,
BASELINE + strength * 0.6
);
}, []);
useEffect(() => {
const id = setInterval(() => {
setWave((prev) => {
const queue = queueRef.current;
const drift =
Math.sin(tickRef.current / 6) * NOISE +
Math.cos(tickRef.current / 9) * (NOISE / 1.6);
tickRef.current += 1;
const nextVal = queue.length
? queue.shift() ?? BASELINE
: BASELINE + drift;
const clamped = Math.max(MIN_Y, Math.min(MAX_Y, nextVal));
const next = prev.slice(1);
next.push(clamped);
return next;
});
}, 110);
return () => clearInterval(id);
}, []);
const wavePoints = useMemo(
() =>
wave
.map((value, idx) => {
const x = (idx / (wave.length - 1)) * WAVE_WIDTH;
return `${x.toFixed(1)},${value.toFixed(1)}`;
})
.join(" "),
[wave]
);
return { wavePoints, waveHeight: wave[wave.length - 1], triggerPulse };
}
/**
* Polls an endpoint on a cadence, parsing the response and surfacing status metadata.
*/
function usePoller<T>(opts: {
baseUrl: string;
path: string;
intervalMs: number;
parser: (res: Response) => Promise<T>;
onPoll?: () => void;
}): { state: PollState<T>; pollNow: () => Promise<void> } {
const { baseUrl, path, intervalMs, parser, onPoll } = opts;
const [state, setState] = useState<PollState<T>>({
data: null,
error: null,
loading: false,
lastUpdated: null,
attemptedUrl: `${baseUrl}${path}`,
});
const poll = useCallback(async () => {
const url = `${baseUrl}${path}`;
onPoll?.();
setState((prev) => ({
...prev,
loading: true,
attemptedUrl: url,
}));
try {
const res = await fetch(url, { cache: "no-store" });
if (!res.ok) throw new Error(`${path} responded with ${res.status}`);
const parsed = await parser(res);
setState((prev) => ({
...prev,
data: parsed,
error: null,
lastUpdated: new Date().toISOString(),
loading: false,
}));
} catch (error) {
const message = error instanceof Error ? error.message : "Unknown error";
setState((prev) => ({
...prev,
data: null,
error: message,
lastUpdated: new Date().toISOString(),
loading: false,
}));
}
}, [baseUrl, path, parser, onPoll]);
useEffect(() => {
void poll();
const id = setInterval(() => void poll(), intervalMs);
return () => clearInterval(id);
}, [poll, intervalMs]);
return { state, pollNow: poll };
}
export default function Home() {
const apiBase = useMemo(
() => process.env.NEXT_PUBLIC_API_URL ?? "http://localhost:8000",
[]
);
const now = useNowString();
const unifiedWave = useWaveform();
const liveWave = useWaveform();
const readyWave = useWaveform();
const healthWave = useWaveform();
const parseHealth = useCallback(async (res: Response) => {
return (await res.json()) as HealthSummary;
}, []);
const parseText = useCallback(async (res: Response) => res.text(), []);
const pulseHealth = useCallback(() => {
unifiedWave.triggerPulse(22);
healthWave.triggerPulse(22);
}, [unifiedWave.triggerPulse, healthWave.triggerPulse]);
const pulseReady = useCallback(() => {
unifiedWave.triggerPulse(16);
readyWave.triggerPulse(16);
}, [unifiedWave.triggerPulse, readyWave.triggerPulse]);
const pulseLive = useCallback(() => {
unifiedWave.triggerPulse(12);
liveWave.triggerPulse(12);
}, [unifiedWave.triggerPulse, liveWave.triggerPulse]);
const { state: healthState, pollNow: pollHealth } = usePoller<HealthSummary>({
baseUrl: apiBase,
path: "/health",
intervalMs: POLL_INTERVALS.health,
parser: parseHealth,
onPoll: pulseHealth,
});
const { state: readyState, pollNow: pollReady } = usePoller<string>({
baseUrl: apiBase,
path: "/health/ready",
intervalMs: POLL_INTERVALS.ready,
parser: parseText,
onPoll: pulseReady,
});
const { state: liveState, pollNow: pollLive } = usePoller<string>({
baseUrl: apiBase,
path: "/health/live",
intervalMs: POLL_INTERVALS.live,
parser: parseText,
onPoll: pulseLive,
});
const healthOk = isStatusHealthy(healthState.data?.status) && !healthState.error;
const readyOk = isStatusHealthy(readyState.data) && !readyState.error;
const liveOk = isStatusHealthy(liveState.data) && !liveState.error;
const overallOk = healthOk && readyOk && liveOk;
const checks = useMemo(() => {
const source = healthState.data?.checks;
if (!source) return [];
if (Array.isArray(source)) {
return source.map((item, idx) => ({
label: item.name ?? item.key ?? item.check ?? `Check ${idx + 1}`,
status: item.status ?? "unknown",
output: item.output ?? item.details ?? "",
}));
}
return Object.entries(source).map(([label, val]) => ({
label,
status: (val as { status?: string }).status ?? "unknown",
output:
(val as { output?: string; details?: string }).output ??
(val as { details?: string }).details ??
"",
}));
}, [healthState.data?.checks]);
const overallLabel = overallOk
? "All probes healthy"
: "Attention needed";
const overallLoading =
healthState.loading || readyState.loading || liveState.loading;
const overallStrokeColor = overallLoading
? "var(--color-pulse)"
: overallOk
? "var(--color-success)"
: "var(--color-danger)";
return (
<main className="relative min-h-screen overflow-hidden">
<div className="pointer-events-none absolute inset-0 bg-[radial-gradient(circle_at_20%_10%,rgba(148,163,184,0.18),transparent_45%),radial-gradient(circle_at_80%_0%,rgba(203,213,225,0.18),transparent_35%),radial-gradient(circle_at_40%_90%,rgba(226,232,240,0.22),transparent_40%)]" />
<div className="absolute inset-0 bg-gradient-to-b from-white/80 via-[#f3f4f6cc] to-[#e5e7eb80] backdrop-blur-[1px]" />
<div className="relative mx-auto flex w-full max-w-6xl flex-col gap-6 px-4 pb-16 pt-10 sm:px-6 lg:px-8">
<header className="flex flex-col gap-4 rounded-3xl border border-black/5 bg-white/80 px-5 py-4 shadow-card backdrop-blur md:flex-row md:items-center md:justify-between">
<div className="flex items-center gap-3">
<div className="flex h-12 w-12 items-center justify-center rounded-2xl border border-black/5 bg-gradient-to-br from-white via-white to-slate-50 shadow-sm">
<Image
src="/logo.png"
alt="avaaz.ai logo"
width={40}
height={40}
priority
className="h-9 w-9 rounded-xl object-contain"
/>
</div>
<div>
<p className="text-lg font-semibold text-ink">avaaz.ai</p>
<p className="text-sm text-inkMuted">
Unified ECG monitoring for live, ready, and health probes.
</p>
</div>
</div>
<div className="flex flex-wrap items-center gap-2">
<span
className={`inline-flex items-center gap-2 rounded-full border px-3 py-2 text-sm font-semibold shadow-sm ${
overallOk
? "border-emerald-200 bg-emerald-50 text-emerald-800"
: "border-rose-200 bg-rose-50 text-rose-800"
}`}
>
<span
className={`h-2.5 w-2.5 rounded-full ${
overallOk ? "bg-success" : "bg-danger"
}`}
/>
{overallLabel}
</span>
<span className="inline-flex items-center gap-2 rounded-full border border-black/5 bg-black/5 px-3 py-2 text-xs font-semibold uppercase tracking-[0.1em] text-inkMuted">
Live clock
<span className="font-mono text-sm">{now || "— — : — —"}</span>
</span>
</div>
</header>
<section className="grid gap-5 md:grid-cols-[1.1fr,1.4fr]">
<div className="rounded-3xl border border-black/5 bg-white/80 p-6 shadow-card backdrop-blur">
<p className="text-xs uppercase tracking-[0.2em] text-inkMuted">
Live dashboard
</p>
<h1 className="mt-2 text-3xl font-semibold leading-tight text-ink md:text-4xl">
ECG-style observability for avaaz.ai
</h1>
<p className="mt-3 text-base text-inkMuted">
A continuous, scrolling signal shows every poll with sharp blips
whenever a probe fires. Color shifts between healthy (green),
unhealthy (red), and active polling (amber).
</p>
<div className="mt-4 grid grid-cols-1 gap-3 text-sm text-ink">
<div className="flex items-center justify-between rounded-2xl border border-black/5 bg-white/70 px-4 py-3">
<span className="text-inkMuted">/health/live</span>
<span className="font-semibold">
{liveOk ? "Live" : "Down"} · 10s cadence
</span>
</div>
<div className="flex items-center justify-between rounded-2xl border border-black/5 bg-white/70 px-4 py-3">
<span className="text-inkMuted">/health/ready</span>
<span className="font-semibold">
{readyOk ? "Ready" : "Not ready"} · 30s cadence
</span>
</div>
<div className="flex items-center justify-between rounded-2xl border border-black/5 bg-white/70 px-4 py-3">
<span className="text-inkMuted">/health</span>
<span className="font-semibold">
{healthOk ? "Healthy" : "Degraded"} · 60s cadence
</span>
</div>
</div>
</div>
<div className="relative overflow-hidden rounded-3xl border border-black/5 bg-gradient-to-br from-white via-[#f3f4f6] to-white p-6 shadow-card">
<div className="pointer-events-none absolute inset-0 bg-[radial-gradient(circle_at_20%_10%,rgba(148,163,184,0.18),transparent_35%),radial-gradient(circle_at_80%_10%,rgba(203,213,225,0.14),transparent_30%),radial-gradient(circle_at_40%_90%,rgba(226,232,240,0.14),transparent_28%)]" />
<div className="flex items-center justify-between text-sm text-inkMuted">
<span className="font-semibold uppercase tracking-[0.12em]">
Unified ECG strip
</span>
<span className="inline-flex items-center gap-2 rounded-full border border-black/5 bg-white/70 px-3 py-1 font-semibold text-ink">
<span className="h-2 w-2 rounded-full bg-success" />
Healthy
<span className="h-2 w-2 rounded-full bg-danger" />
Unhealthy
<span className="h-2 w-2 rounded-full bg-pulse" />
Polling
</span>
</div>
<div className="mt-3 rounded-2xl border border-black/5 bg-white/80 p-4 shadow-inner">
<svg
viewBox="0 0 360 120"
preserveAspectRatio="none"
className="h-32 w-full"
>
<polyline
points={unifiedWave.wavePoints}
fill="none"
stroke={overallStrokeColor}
strokeWidth="4"
strokeLinecap="round"
strokeLinejoin="round"
/>
<circle
cx="360"
cy={unifiedWave.waveHeight}
r="7"
className="stroke-white/50"
style={{ fill: overallStrokeColor }}
/>
</svg>
</div>
<div className="mt-3 grid grid-cols-2 gap-3 text-sm text-ink">
<div className="rounded-2xl border border-black/5 bg-white/70 px-3 py-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Last health update
</p>
<p className="text-base font-semibold text-ink">
{formatTime(healthState.lastUpdated)}
</p>
</div>
<div className="rounded-2xl border border-black/5 bg-white/70 px-3 py-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Next pulse cadence
</p>
<p className="text-base font-semibold text-ink">
10s / 30s / 60s
</p>
</div>
</div>
</div>
</section>
<section className="grid grid-cols-1 gap-5 md:grid-cols-2 xl:grid-cols-3">
<ECGMonitorCard
title="Live probe"
endpoint="/health/live"
intervalLabel="10 seconds"
tone="blue"
now={now}
wavePoints={liveWave.wavePoints}
waveHeight={liveWave.waveHeight}
healthy={liveOk}
loading={liveState.loading}
statusLabel={
liveState.loading
? "Polling"
: liveOk
? "Operational"
: "Attention"
}
statusDetail={liveState.error ?? liveState.data ?? "Awaiting data"}
lastUpdatedLabel={formatTime(liveState.lastUpdated)}
state={liveState}
onManualTrigger={pollLive}
>
<div className="rounded-2xl border border-black/5 bg-white/80 px-3 py-2 text-sm">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Signal
</p>
<p className="font-semibold text-ink">
{liveState.data ?? liveState.error ?? "No response yet"}
</p>
</div>
</ECGMonitorCard>
<ECGMonitorCard
title="Readiness"
endpoint="/health/ready"
intervalLabel="30 seconds"
tone="mint"
now={now}
wavePoints={readyWave.wavePoints}
waveHeight={readyWave.waveHeight}
healthy={readyOk}
loading={readyState.loading}
statusLabel={
readyState.loading
? "Polling"
: readyOk
? "Operational"
: "Attention"
}
statusDetail={
readyState.error ??
readyState.data ??
"Waiting for first readiness signal"
}
lastUpdatedLabel={formatTime(readyState.lastUpdated)}
state={readyState}
onManualTrigger={pollReady}
>
<div className="rounded-2xl border border-black/5 bg-white/80 px-3 py-2 text-sm">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Response
</p>
<p className="font-semibold text-ink">
{readyState.data ?? readyState.error ?? "No response yet"}
</p>
</div>
</ECGMonitorCard>
<ECGMonitorCard
title="Deep health"
endpoint="/health"
intervalLabel="1 minute"
tone="coral"
now={now}
wavePoints={healthWave.wavePoints}
waveHeight={healthWave.waveHeight}
healthy={healthOk}
loading={healthState.loading}
statusLabel={
healthState.loading
? "Polling"
: healthOk
? "Operational"
: "Attention"
}
statusDetail={
healthState.error ??
healthState.data?.status ??
"Waiting for first health payload"
}
lastUpdatedLabel={formatTime(healthState.lastUpdated)}
state={healthState}
onManualTrigger={pollHealth}
>
<div className="grid grid-cols-2 gap-3 text-sm">
{healthState.data?.version && (
<div className="rounded-2xl border border-black/5 bg-white/80 px-3 py-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Version
</p>
<p className="font-semibold text-ink">{healthState.data.version}</p>
</div>
)}
{healthState.data?.serviceId && (
<div className="rounded-2xl border border-black/5 bg-white/80 px-3 py-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Service
</p>
<p className="font-semibold text-ink">
{healthState.data.serviceId}
</p>
</div>
)}
{healthState.data?.description && (
<div className="col-span-2 rounded-2xl border border-black/5 bg-white/80 px-3 py-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Notes
</p>
<p className="text-ink">{healthState.data.description}</p>
</div>
)}
</div>
<div className="mt-3 space-y-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Checks
</p>
{checks.length > 0 ? (
<div className="grid grid-cols-1 gap-2 sm:grid-cols-2">
{checks.map((check) => (
<div
key={check.label}
className="rounded-2xl border border-black/5 bg-white/70 px-3 py-2"
>
<div className="flex items-center justify-between text-xs text-inkMuted">
<span>{check.label}</span>
<span
className={`h-2 w-2 rounded-full ${
isStatusHealthy(check.status) ? "bg-success" : "bg-danger"
}`}
/>
</div>
<p className="text-sm font-semibold text-ink">{check.status}</p>
{check.output && (
<p className="text-xs text-inkMuted">{check.output}</p>
)}
</div>
))}
</div>
) : (
<p className="text-sm text-inkMuted">Awaiting check details.</p>
)}
</div>
</ECGMonitorCard>
</section>
</div>
</main>
);
}

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import type { ReactNode } from "react";
import type { PollState } from "@/types/monitor";
type Tone = "mint" | "blue" | "coral";
const toneStyles: Record<Tone, string> = {
mint: "from-white via-white to-emerald-50 ring-emerald-100",
blue: "from-white via-white to-sky-50 ring-sky-100",
coral: "from-white via-white to-rose-50 ring-rose-100",
};
interface ECGMonitorCardProps<T> {
title: string;
endpoint: string;
intervalLabel: string;
tone?: Tone;
now: string;
wavePoints: string;
waveHeight: number;
healthy: boolean;
loading: boolean;
statusLabel: string;
statusDetail: string;
lastUpdatedLabel: string;
state: PollState<T>;
children?: ReactNode;
onManualTrigger: () => void;
}
/**
* Presentational card that renders endpoint status and the shared ECG waveform with
* consistent tone, status badges, and contextual metadata.
*/
export function ECGMonitorCard<T>({
title,
endpoint,
intervalLabel,
tone = "mint",
now,
wavePoints,
waveHeight,
healthy,
loading,
statusLabel,
statusDetail,
lastUpdatedLabel,
state,
children,
onManualTrigger,
}: ECGMonitorCardProps<T>) {
const signalId = `${endpoint.replace(/[^a-z0-9]/gi, "-")}-stroke`;
const badgeColor = loading
? "border-amber-200 bg-amber-50 text-amber-800"
: healthy
? "border-emerald-200 bg-emerald-50 text-emerald-800"
: "border-rose-200 bg-rose-50 text-rose-800";
const dotColor = loading ? "bg-pulse" : healthy ? "bg-success" : "bg-danger";
const strokeColor = loading ? "#f59e0b" : healthy ? "#22c55e" : "#ef4444";
return (
<article
className={`relative overflow-hidden rounded-3xl border border-black/5 bg-gradient-to-br ${toneStyles[tone]} p-5 shadow-card ring-4 ring-transparent transition hover:-translate-y-1 hover:shadow-[0_24px_60px_rgba(15,23,42,0.16)]`}
>
<div className="absolute inset-0 -z-10 bg-[radial-gradient(circle_at_20%_10%,rgba(96,165,250,0.08),transparent_30%),radial-gradient(circle_at_80%_0%,rgba(52,211,153,0.1),transparent_30%)]" />
<div className="flex items-start justify-between gap-3">
<div className="space-y-2 min-w-0">
<div className="inline-flex max-w-full items-center gap-2 rounded-full border border-black/5 bg-black/5 px-3 py-1 text-xs font-semibold uppercase tracking-[0.12em] text-inkMuted">
<span className="break-words">{endpoint}</span>
<span className="h-1.5 w-1.5 shrink-0 rounded-full bg-gradient-to-r from-accent-blue to-accent-mint" />
</div>
<h3 className="text-lg font-semibold text-ink">{title}</h3>
<p className="text-sm text-inkMuted">every {intervalLabel}</p>
</div>
<div className="flex flex-col items-end gap-2 text-right">
<div className="flex items-center gap-2">
<span
className={`inline-flex items-center gap-2 rounded-full border px-3 py-2 text-sm font-semibold shadow-sm ${badgeColor}`}
>
<span className={`h-2.5 w-2.5 rounded-full ${dotColor}`} />
{statusLabel}
</span>
<button
type="button"
onClick={onManualTrigger}
className="inline-flex items-center gap-2 rounded-full bg-ink text-white px-3 py-2 text-xs font-semibold shadow-card transition hover:bg-inkSoft focus-visible:outline focus-visible:outline-2 focus-visible:outline-offset-2 focus-visible:outline-ink"
>
<span className="h-2 w-2 rounded-full bg-white" aria-hidden />
Poll now
</button>
</div>
<span className="text-xs font-semibold uppercase tracking-[0.08em] text-inkMuted">
{now}
</span>
</div>
</div>
<div className="mt-4 flex flex-col gap-3">
<div className="rounded-2xl border border-black/5 bg-white/80 px-3 py-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">
Last updated
</p>
<p className="text-base font-semibold text-ink">{lastUpdatedLabel}</p>
</div>
<div className="relative overflow-hidden rounded-2xl border border-black/5 bg-gradient-to-br from-white via-white to-slate-50 p-4">
<div className="pointer-events-none absolute inset-0 opacity-60 mix-blend-multiply">
<div className="absolute inset-0 bg-[radial-gradient(circle_at_10%_20%,rgba(96,165,250,0.12),transparent_35%),radial-gradient(circle_at_80%_0%,rgba(52,211,153,0.12),transparent_30%)]" />
</div>
<div className="flex items-center justify-between text-xs text-inkMuted">
<span>ECG signal</span>
<span className="inline-flex items-center gap-2 rounded-full bg-black/5 px-2 py-1 font-semibold">
<span className={`h-2 w-2 rounded-full ${dotColor}`} />
{loading ? "Polling" : healthy ? "Healthy" : "Unhealthy"}
</span>
</div>
<svg
viewBox="0 0 360 120"
preserveAspectRatio="none"
className="mt-2 h-28 w-full text-success drop-shadow-sm"
>
<defs>
<linearGradient id={signalId} x1="0%" y1="0%" x2="100%" y2="0%">
<stop offset="0%" stopColor={strokeColor} stopOpacity="0.9" />
<stop offset="50%" stopColor={strokeColor} stopOpacity="0.75" />
<stop offset="100%" stopColor={strokeColor} stopOpacity="0.95" />
</linearGradient>
</defs>
<polyline
points={wavePoints}
fill="none"
stroke={`url(#${signalId})`}
strokeWidth="3"
strokeLinecap="round"
strokeLinejoin="round"
/>
<circle
cx="360"
cy={waveHeight}
r="6"
className={`stroke-white/40 ${dotColor}`}
/>
</svg>
</div>
<div className="grid grid-cols-2 gap-3 text-sm">
<div className="rounded-2xl border border-black/5 bg-white/80 px-3 py-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">Status</p>
<p className="text-base font-semibold text-ink">{statusDetail}</p>
</div>
<div className="rounded-2xl border border-black/5 bg-white/80 px-3 py-2">
<p className="text-xs uppercase tracking-[0.08em] text-inkMuted">Endpoint</p>
<p className="text-xs font-mono text-ink">{state.attemptedUrl}</p>
</div>
</div>
{children}
</div>
</article>
);
}

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import nextPlugin from "@next/eslint-plugin-next";
import globals from "globals";
import tseslint from "typescript-eslint";
export default tseslint.config(
{
ignores: [
"**/.next/**",
"node_modules/**",
"dist/**",
"tailwind.config.js",
"postcss.config.mjs",
],
},
{
files: ["**/*.{js,jsx,ts,tsx}"],
extends: [
...tseslint.configs.recommendedTypeChecked,
...tseslint.configs.stylisticTypeChecked,
nextPlugin.configs.recommended,
nextPlugin.configs["core-web-vitals"],
],
languageOptions: {
parserOptions: {
project: "./tsconfig.json",
},
globals: {
...globals.browser,
...globals.node,
},
},
rules: {
"@typescript-eslint/consistent-type-imports": [
"error",
{ prefer: "type-imports", fixStyle: "separate-type-imports" },
],
"@typescript-eslint/no-misused-promises": [
"error",
{ checksVoidReturn: false },
],
"@typescript-eslint/no-floating-promises": "error",
},
}
);

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/** @type {import('next').NextConfig} */
const nextConfig = {
reactStrictMode: true,
};
export default nextConfig;

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{
"name": "avaaz-frontend",
"version": "0.1.0",
"private": true,
"scripts": {
"dev": "next dev",
"build": "next build --webpack",
"start": "next start",
"lint": "eslint ."
},
"type": "module",
"dependencies": {
"@tailwindcss/postcss": "^4.1.17",
"next": "^16.0.5",
"react": "^19.2.0",
"react-dom": "^19.2.0"
},
"devDependencies": {
"@types/node": "^24.10.1",
"@types/react": "^19.2.7",
"@types/react-dom": "^19.2.3",
"autoprefixer": "^10.4.20",
"eslint": "^9.39.1",
"eslint-config-next": "^16.0.5",
"globals": "^16.5.0",
"postcss": "^8.4.49",
"tailwindcss": "^4.1.17",
"typescript": "^5.9.3",
"typescript-eslint": "^8.48.0"
}
}

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export default {
plugins: {
"@tailwindcss/postcss": {},
autoprefixer: {},
},
};

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{
"compilerOptions": {
"target": "ES2022",
"lib": [
"dom",
"dom.iterable",
"ES2022"
],
"allowJs": false,
"skipLibCheck": true,
"strict": true,
"noEmit": true,
"esModuleInterop": true,
"module": "ESNext",
"moduleResolution": "Bundler",
"resolveJsonModule": true,
"isolatedModules": true,
"jsx": "react-jsx",
"incremental": true,
"types": [
"node"
],
"plugins": [
{
"name": "next"
}
],
"paths": {
"@/*": [
"./*"
]
}
},
"include": [
"next-env.d.ts",
"**/*.ts",
"**/*.tsx",
".next/types/**/*.ts",
".next/dev/types/**/*.ts"
],
"exclude": [
"node_modules"
]
}

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export interface PollState<T> {
data: T | null;
error: string | null;
loading: boolean;
lastUpdated: string | null;
attemptedUrl: string;
}