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Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: YOLO

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: YOLO

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Suuunboy/README.md

Ivan Afanasov

Backend & AI engineer. I build production LLM agent systems: RAG pipelines, tool-using agents, and the Django/Celery backends that keep them reliable.

  • 4+ years of commercial Python backend development
  • Currently: AI agents and RAG for enterprise clients
  • Stack: Python · Django / DRF · Celery · PostgreSQL · Redis · Qdrant · LangGraph / LangChain · Langflow · Docker
  • Also into audio DSP on embedded hardware (STM32, Daisy Seed)

Selected work

  • langflow-parsers — Langflow components that parse DOCX/PDF into text with image placeholders plus normalized PNGs, for multimodal RAG
  • tempo-benchmark — C++17 real-time BPM detectors for Daisy Seed, benchmarked against librosa via pybind11
  • code-documentation-skill — Claude Code skill: docstrings/Doxygen to the project's own convention, plus doc-coverage audit
  • commit-message-skill — Claude Code skill: diff-aware commit messages that follow the repo's convention

Pinned Loading

  1. code-documentation-skill code-documentation-skill Public

    Claude Code skill for documenting code to your project's existing convention — Python docstrings, C/C++ Doxygen, READMEs, and documentation audits.

    Python 2

  2. commit-message-skill commit-message-skill Public

    Claude Code skill for writing git commit messages — diff-aware, convention-matching, attribution-free.

    1

  3. tempo-benchmark tempo-benchmark Public

    Testbench for real-time BPM detection algorithms in C++17: streams audio block by block like an embedded audio callback and compares results against librosa

    Python

  4. langflow-parsers langflow-parsers Public

    Custom Langflow components that parse DOCX and PDF into text with <imageN> placeholders plus normalized PNG images, ready for multimodal RAG with vision LLMs.

    Python