Demo 2

RAG Demo (Technical)

This demo answers questions over a fixed corpus of real NIST and NASA documents. It translates when needed, retrieves the matching passages and answers with page citations – ask in German, source in English, answer in your language.

The document base

We don't host the PDFs ourselves but link the original sources (public domain, NIST/NASA).

Topics & sensible questions

Clicking copies the question. Paste it into the demo below and send.

Expected: the core focus areas of the AI profile, citing NIST IR 8596.

Expected: a short definition plus attack categories, citing NIST AI 100-2e2025.

Expected: the foundational activities from NIST IR 8259r1.

Expected: key subsystems, citing the NASA SoA report.

Live demo

The demo runs on a separate subdomain and loads only after you click.

Security & privacy

  • - The corpus consists solely of public-domain documents (NIST/NASA).
  • - Every answer cites its source and location – traceable, not guessed.
  • - Abuse protection via request and input-length limits.
  • - Inputs are not stored as training data.
  • - Please do not enter confidential or personal data.
  • - Answers may contain errors – when in doubt, check the linked original source.

Technical details

  • - Adaptive/corrective RAG pipeline orchestrated with LangGraph (retrieve → grade → optional self-correction → generate).
  • - Cross-lingual embeddings (qwen3-embedding-8b, 4096 dims): German questions retrieve English passages without translation.
  • - Vector search with Qdrant over ~4,000 chunks; exact and semantic caching for fast repeats.
  • - Two modes: “fast” (1 LLM call) and “showcase” (full graph with grading & self-correction).
  • - Answer model openai/gpt-oss-120b via OpenRouter; hosted on dedicated infrastructure (Hetzner, EU).