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Hi, I'm Osama Ansar

Senior Software Engineer with 5+ years shipping production web apps (Angular, React, Vue, Node.js) — now going deep on TypeScript RAG systems, agentic pipelines, and LLM evaluation infrastructure.

I read library source before I trust it. That habit has turned into six live PRs against real vector-database clients this month.


🔭 Independent AI/RAG projects

All TypeScript, all with real test suites and live demos — no framework hiding the mechanics.

  • refract-rag — hybrid BM25 + HNSW retrieval fused with Reciprocal Rank Fusion, multi-hop agentic decomposition, and a UI that visualizes every retrieval score live instead of hiding it behind a spinner. → demo
  • rag-eval-harness — LLM-judge eval harness for RAG pipelines (faithfulness, relevance, context precision/recall) with a CI regression gate. → live report
  • agentic-rag — multi-hop agentic RAG: decomposes questions, retrieves per sub-question with from-scratch BM25, checks sufficiency, synthesizes a cited answer.
  • hnsw-vector-index — HNSW approximate-nearest-neighbor search implemented from scratch, benchmarked against brute-force (recall@k: 66% → 100% as efSearch increases).
  • doc-chat-citations — a docs chat assistant where every claim cites and jumps to its exact source passage, built on from-scratch BM25.
  • generative-ui-chat — a chat assistant that streams back real interactive React components (charts, tables, booking cards) instead of plain text.

🌱 Open source

🛠️ Stack

TypeScript Next.js Node.js Vercel AI SDK LangChain.js Vector Databases (Qdrant, Weaviate, Pinecone, Supabase) Vitest Angular React Vue

📫 Reach me

Portfolio · LinkedIn · osama.ansar.pk@gmail.com

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