Pandeyycodes/phonelens

# PhoneLens PhoneLens is an editorial, ultra-minimalist phone validation, threat analysis, and risk scoring dashboard. ## 🖼️ Dashboard Showcase  ## Overview PhoneLens allows users to parse international phone numbers, extract country flags, timezones, carrier information, and compute a comprehensive risk score by aggregating intelligence from NumVerify and AbstractAPI concurrently. The interface is meticulously designed around typography, whitespace, and a high-end, light-theme minimalist aesthetic. ## Tech Stack - **Backend**: FastAPI (Python 3.11+), Uvicorn, SQLAlchemy 2.0 (with aiosqlite async SQLite driver), Pydantic v2, and phonenumbers library. - **Frontend**: React 18, Vite, Tailwind CSS, Axios, and Custom CSS cubic-bezier transitions. - **Containerization**: Docker & Docker Compose. ## Prerequisites - **Python**: `3.11+` - **Node.js**: `18+` - **Poetry**: For python package management - **Docker & Docker Compose**: Optional for containerized setup ## Obtaining API Keys PhoneLens queries external APIs in parallel for threat risk aggregation. You can obtain free keys at the following links: 1. **NumVerify Key**: Register at [numverify.com](https://numverify.com/) to receive your free access key. 2. **AbstractAPI Phone Validation Key**: Sign up at [abstractapi.com/api/phone-validation-validation](https://www.abstractapi.com/api/phone-validation-validation) for a free account. Once obtained, rename `backend/.env.example` to `backend/.env` and paste your credentials: NUMVERIFY_KEY=your_numverify_key_here ABSTRACT_KEY=your_abstractapi_key_here *Note: If keys are left empty, the application falls back gracefully to local threat assessment and returns a safe standard score (0, `unknown`) without crashing.* ## Project Structure phonelens/ ├── backend/ │ ├── app/ │ │ ├── main.py # FastAPI application & endpoints │ │ ├── lookup.py # Core parsing & country data resolution │ │ ├── sources.py # Parallel third-party API aggregations │ │ ├── models.py # SQLAlchemy SQLite models │ │ └── schemas.py # Pydantic v2 data models │ ├── tests/ │ │ └── test_lookup.py # Pytest automated testing suite │ ├── Dockerfile # Backend container instructions │ ├── pyproject.toml # Poetry dependency manifest │ └── .env.example # Environment keys template ├── frontend/ │ ├── src/ │ │ ├── components/ │ │ │ ├── SearchBar.jsx # Minimalist search, select & pulse loader │ │ │ ├── ResultSection.jsx # Staggered reveal data partitions │ │ │ ├── RiskBar.jsx # Mount-animated color-coded threat bar │ │ │ └── HistorySection.jsx # Search logs table with lookup quicklinks │ │ ├── api/ │ │ │ └── lookup.js # Frontend Axios client │ │ ├── App.jsx # State coordinator & keyframes style │ │ ├── index.css # Custom global css animations │ │ └── main.jsx # React main DOM hook │ ├── Dockerfile # Frontend container instructions │ ├── index.html # HTML core importing Google Font Inter │ ├── tailwind.config.js # Editorial typography & theme overrides │ ├── postcss.config.js # PostCSS configs │ ├── vite.config.js # Vite proxy configurations │ └── package.json # Frontend package manifests ├── docker-compose.yml # Orchestrated multi-service local builds └── README.md # General user documentation ## Setup Instructions ### Path A: Docker Setup (Recommended) Launch the entire system inside insulated containers in a single command: 1. Ensure your `.env` keys are updated in the `backend/.env` file. 2. Build and start both services: docker-compose up --build 3. Open your browser and navigate to: - **Frontend**: [http://localhost:5173](http://localhost:5173) - **Interactive API Docs**: [http://localhost:8000/docs](http://localhost:8000/docs) ### Path B: Manual Installation #### 1. Backend Service 1. Navigate to the backend directory: cd backend 2. Install Python dependencies via Poetry: poetry install 3. Copy environment configuration and input keys: cp .env.example .env 4. Spin up the FastAPI server via Uvicorn: poetry run uvicorn app.main:app --reload *The backend starts at [http://localhost:8000](http://localhost:8000).* #### 2. Frontend Application 1. Open a new terminal and navigate to the frontend directory: cd frontend 2. Install npm packages: npm install 3. Launch the Vite development server: npm run dev *The frontend starts at [http://localhost:5173](http://localhost:5173).* ## Automated Verification Tests You can run automated pytests in the backend directory to check standard compliance: cd backend poetry run pytest -v ## Example API Curl Commands ### 1. Perform a Lookup curl -X GET "http://localhost:8000/lookup/%2B14155552671" -H "accept: application/json" ### 2. Retrieve Lookup Logs curl -X GET "http://localhost:8000/history" -H "accept: application/json" ### 3. Clear Lookup Database curl -X DELETE "http://localhost:8000/history" -H "accept: application/json"

标签：自定义脚本