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Aryan1718/README.md
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Software Developer currently working as an AI/ML intern.
Focused on Python · React · Next · Docker · SQL · NoSQL · Redis · Cloud

About Me

  • MS in Computer Science — California State University, Fullerton
  • Building end-to-end AI systems across backend, frontend, and model integration
  • Strong focus on backend architecture, scalable APIs, and production-ready systems
  • Experience working on LLM-powered applications using both cloud and open-source models
  • Tech stack includes Python, React, Next.js, and JavaScript
  • Currently exploring Rust to better understand memory-efficient and high-performance system design
  • Contact: aryanjp1718@gmail.com

📊 GitHub Stats

🛠️ Tech Stack

Languages

Frontend

Backend & Infra

Databases & Caching

Tools & Cloud

📈 Contribution Activity

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  1. enterprise-rag-platform enterprise-rag-platform Public

    Production-ready Enterprise RAG system with Supabase, pgvector, strict grounded retrieval, token budget engine, and scalable worker-based ingestion pipeline.

    Python

  2. mini-redis mini-redis Public

    A Redis-like in-memory key-value database built from scratch, featuring RESP protocol support, core command handling, key expiration, and persistence for learning and experimentation.

    Python

  3. OverLeaf-MCP OverLeaf-MCP Public

    This MCP server lets you connect to your Overleaf project and perform all tasks directly from ChatGPT or any other platform that supports adding an MCP server.

    Python 2 3

  4. fake-review-detector fake-review-detector Public

    A production-style fake review detection system combining LLMs, transformers, and ML models via ensemble voting.

    Jupyter Notebook

  5. latex-resume-engine latex-resume-engine Public

    Containerized FastAPI service for generating LaTeX resumes with Tectonic. Supports structured input, PDF rendering, and Overleaf-style preview workflows.

    Python

  6. resume-normalizer resume-normalizer Public

    FastAPI microservice that converts resumes (PDF, DOCX, or text) into a validated, canonical JSON schema using Google Gemini, with LLM-driven extraction and Pydantic-based normalization.

    Python