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yasirrazaa/README.md

Yasir Raza

AI Engineer · LLM Agents · Voice AI · MCP Tooling

PyPI Downloads GitHub Repos Kaggle LinkedIn

I build AI agents, LLM-powered tools, and voice systems that actually ship —
backed by open-source code with 5,700+ downloads.

📍 Islamabad, Pakistan · 📧 yasirabdali6@gmail.com


🚀 What I Build

Area Tools & Frameworks
LLM Agents & Orchestration LangGraph, LangChain, LlamaIndex, FastMCP
Voice & Multimodal AI ElevenLabs, Fish-Speech, ChatterBox, Gemini
Model Fine-tuning LoRA, QLoRA, Unsloth, PEFT, Transformers
Deployment & Infra RunPod serverless, Docker, FastAPI, AWS
RAG & Memory Chroma, semantic chunking, hybrid retrieval

📦 Featured Projects

🔌 NotebookLLM MCP Server · PyPI · 5.7K+ Downloads · Listed on LobeHub

Production-ready MCP server for efficient LLM interactions with Jupyter Notebooks. Converts .ipynb files to plain text before sending to the LLM — cutting token usage dramatically.

pip install notebookllm_mcp

🤖 Telegram Multimodal Agent

LangGraph agent with cloned voice (ElevenLabs), image understanding (Gemini), and RAG memory (Chroma). Accepts text, voice, and image input — responds in audio or text with a persona-aligned voice.

Stack: LangGraph · Telegram API · Gemini · ElevenLabs · Chroma


📱 WhatsApp Multimodal Agent

LangGraph + Twilio agent handling text, voice, and image inputs. Outputs contextual, persona-grounded responses using vector memory.

Stack: LangGraph · Twilio · Gemini · Chroma


🧮 LaTeX → Executable Python (Fine-tuned LLM)

Fine-tuned NuminaMath-7B with LoRA to generate executable Python code from LaTeX math. Includes synthetic data generation pipeline and SymPy-based validation.

Stack: Unsloth · QLoRA · SymPy · HuggingFace


🔊 Voice TTS Deployments (Fish-Speech & ChatterBox)

Deployed state-of-the-art open-source TTS models as serverless endpoints on RunPod using Docker multi-stage builds with chunked long-text processing.


🧠 Intelloquium Autonomous Agent

Autonomous research agent with real-time voice/video assistance, browser automation, full-stack software generation, and MCP server extensibility.


📊 Stats at a Glance

Metric Value
PyPI Package Downloads 5,700+
Published PyPI Packages 2 (notebookllm, notebookllm_mcp)
GitHub Repositories 51
Remote Work Experience 18 months (Teamlift, US)
Kaggle Status Expert
NER pipeline scale 100,000+ job descriptions

🏢 Experience

Junior Data Scientist — Teamlift (US Remote · Jan 2024 – Dec 2024)
Built end-to-end automated data pipelines with Human-in-the-Loop design. Engineered prompts for skill extraction and implemented function calling for ambiguous skill verification.

ML Intern — Teamlift (US Remote · Jul 2023 – Dec 2023)
Web scraping at scale (Scrapy, Playwright, BeautifulSoup), NER on 100K+ job descriptions, time-series forecasting for job trend prediction.


🎓 Education & Certifications

  • B.Sc. Software Engineering — NUML, Islamabad (Graduating 2026)
  • Advanced LLM Bootcamp — NUST & Sky Electric (2024)
  • Google: Generative AI Fundamentals · Responsible AI · LLMs
  • DataCamp: Data Scientist Track · Kaggle Expert

🤝 Work With Me

I'm available for freelance projects in:

  • Custom LLM agent systems (LangGraph, LangChain)
  • Voice AI & multimodal agents
  • LLM fine-tuning (LoRA/QLoRA/Unsloth)
  • MCP server / tool development
  • RAG chatbots & document QA systems

📬 Email: yasirabdali6@gmail.com

💼 Upwork: upwork.com/freelancers/~0136d3079a657bfcbb

💼 Fiverr: fiverr.com/sellers/yasirrazaa

🔗 LinkedIn: linkedin.com/in/yasir-raza

🔗 Kaggle: kaggle.com/yasirabdaali

🔗 PyPi: pypi.org/user/yasirabdali6

Pinned Loading

  1. notebookllm notebookllm Public

    A Python package to bridge the gap between Jupyter Notebooks and Large Language Models (LLMs).

    Python 1

  2. notebookllm_mcp notebookllm_mcp Public

    A Model Context Protocol server for working with Jupyter Notebooks (.ipynb files) in a way that is efficient for Large Language Models (LLMs). It converts notebooks to a simplified plain text forma…

    Python 4 1

  3. Latex---Executable-Python-Code Latex---Executable-Python-Code Public

    Generating Executable Python Code from Latex Expressions

    Jupyter Notebook