I will build a production grade rag chatbot with langchain and qdrant for your docs

V
vacha59
V
vacha59
VKalek
Einige Informationen werden in englischer Sprache angezeigt.

Über diesen Service

Turn your documents, website, or knowledge base into a chatbot that actually knows your business not a generic ChatGPT wrapper that hallucinates answers. I build custom RAG (Retrieval-Augmented Generation) chatbots that retrieve real answers from your own data before generating a response.

What you get:

  • A chatbot connected to OpenAI (GPT-4/4o) or Anthropic Claude API
  • A vector database (Pinecone, Chroma, or pgvector) indexing your documents/FAQ/website content
  • A backend API (FastAPI or Express) serving the chatbot ready to embed on your site or connect to Slack/Telegram/WhatsApp
  • Accurate answers grounded in your actual content, with source citation on request

How it works:

  1. Share your documents/website/FAQ content (PDF, docs, URLs).
  2. I set up the retrieval pipeline (chunking, embeddings, vector store) and connect it to the LLM.
  3. I deliver a tested chatbot API + basic integration (widget or endpoint) with a short handover doc.

Tech: Python (FastAPI, LangChain) or Node.js, OpenAI/Anthropic API, Pinecone/Chroma/pgvector.

Lerne VKalek kennen

VKalek

Backend Developer

  • AusUkraine
  • Mitglied seitJuli 2026
  • ⌀ Antwortzeit1 Stunde
  • Sprachen

    Ukrainisch, Russisch, Englisch
I am a hands-on backend developer specializing in high-stress debugging, system stabilization, and connecting chaotic APIs into clean production code. I specialize in jumping into messy codebases to find root causes of errors and building robust payment infrastructure and data pipelines.