I will build a rag chatbot and ai knowledge base from your documents

L
leiyang_dev
L
leiyang_dev
Lei

About this gig

Turn your PDFs, docs, and website content into an AI assistant that answers

  questions with source citations. I build RAG pipelines in Python (LangChain

  or LlamaIndex) with vector databases (pgvector, Qdrant, Pinecone), powered

  by OpenAI, Claude, or open-source models.


  You get: a working chatbot (web UI, Slack bot, or API), answers with

  citations, and deployment to your server or cloud.


  Why work with me: 13 years in backend engineering, shipping production LLM

  apps RAG knowledge bases, agents, and automation with clear written

  English and honest estimates.

Get to know Lei

Lei

Full Stack Developer Go Python AI Agents

  • FromChina
  • Member sinceAug 2026
  • Languages

    Chinese, English
I'm a full-stack developer with 13 years of experience — 8 building high-concurrency game backends in Go and Python. WHAT I DO BEST • AI — LLM agents, function calling, RAG chatbots (Python, LangChain) • Backends — Go/Python APIs, MySQL/Redis, Docker, serverless • Full-stack — React/Vue frontends on solid backends RESULTS • Migrated a live game from Python to Go — 4x capacity, Redis -50% • Core dev on a $14M+ annual revenue game • Shipped LLM agents end to end, plus open-source agent infra GitHub: github.com/NinjaSln-labs Hours 10:00–22:00 (GMT+8), EU+US overlap.