ResumeParser

ResumeParser
Architected, engineered, and maintained by Abeer Al-Sayaari (Bibi)

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1. Project Overview & Real-World Utility

ResumeParser is a modern, cloud-native ai data tool built to address modern operational challenges in AI & Data Engineering Tools.

Smart NLP extractor parsing PDF resumes into structured JSON data.

In high-throughput environments, modern distributed systems often suffer from blind spots in data streaming, unverified schema shifts, and delayed incident responses. ResumeParser solves this by providing a unified, reactive pipeline with live health telemetry, zero-dependency embedded database persistence, and end-to-end automated UI validation.

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2. Selected Tech Stack & Architectural Justification

Every library and design pattern in this codebase was deliberately selected according to 2026 Engineering Standards:

Layer	Technology	Engineering Rationale
Backend Core	Python 3.13+ (Async Engine)	Chosen for asynchronous high-concurrency throughput and native type safety.
Framework	FastAPI + Ponytail Pipeline + Google Skills Core	Delivers lightning-fast routing with auto-generated OpenAPI documentation.
Persistence	Vector / SQLite Relational Schema	Relational schema with WAL mode ensures strict ACID compliance without overhead.
Frontend UI	Dynamic AI Analytics Canvas with Awesome Design MD & D3.js	Zero-bloat, responsive presentation layer following Awesome Design MD guidelines.

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3. Mandatory Ecosystem & Skills Integration

This project actively implements and integrates standard best practices from the following key repositories:

1. Google Skills Core: Applied for structured task orchestration and standard agent capabilities.
2. Microsoft Playwright CLI: Powering end-to-end browser testing and UI assertion workflows.
3. Awesome Design MD: Guiding the visual hierarchy, color palette, and layout aesthetic.
4. Wix & Domain Concepts: Adhering to zero-downtime routing standards and edge deployment logic.
5. TasteSkill Dev: Driving the clean-code architecture, loose coupling, and high cohesion.
6. Caveman Dev: Ensuring ultra-lightweight execution without bloated third-party dependencies.
7. Ponytail: Managing reactive data flows and stateful pipeline handling.
8. Vercel Labs Skills (Find-Skills): Dynamic tool lookup and capability expansion.
9. Oomol Lab Open Connector: Standardizing API connectors and cross-service ingestion pipelines.

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4. System Architecture

                       +---------------------------------------+
                       |   Client (Browser / Playwright CLI)   |
                       +---------------------------------------+
                                          |
                                          | HTTP / JSON / SSE
                                          v
                       +---------------------------------------+
                       |      Wix Edge / Gateway Router        |
                       +---------------------------------------+
                                          |
                        +-----------------+-----------------+
                        |                                   |
                        v                                   v
             +--------------------+              +--------------------+
             | Static UI (HTML5)  |              | FastAPI Controller |
             | Awesome Design MD  |              | TasteSkill Clean   |
             +--------------------+              +--------------------+
                                                           |
                                                           v
                                                 +--------------------+
                                                 | Ponytail Pipeline  |
                                                 | & Open Connector   |
                                                 +--------------------+
                                                           |
                                                           v
                                                 +--------------------+
                                                 | Relational Storage |
                                                 | SQLite / Postgres  |
                                                 +--------------------+

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5. Step-by-Step Installation & Local Execution

Prerequisites

• Python 3.11+ (Python 3.13 recommended)
• Git

Quickstart

1. Clone the repository:

   git clone https://github.com/Abeerr0/ResumeParser.git
   cd ResumeParser

2. Create and activate a virtual environment:

   python -m venv venv
   # On Windows:
   venv\Scripts\activate
   # On Linux/macOS:
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Initialize database & launch server:

   python -m app.main

5. Access the application:

   • Interactive Web Dashboard: http://localhost:8000/
   • Interactive API Documentation: http://localhost:8000/docs
   • Alternative ReDoc Specs: http://localhost:8000/redoc

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6. Running Tests

Execute the automated test suite:

pytest tests/

To run browser automation via Playwright CLI:

npx playwright test tests/playwright_e2e.js

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7. Developer Signature & Intellectual Property

Crafted with dedication by Abeer Al-Sayaari (known digitally as Bibi).
All rights reserved © 2026 Abeer Al-Sayaari. Released under the MIT Open Source License.