CoolFace
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Anticloud/camus-15-privacy-preserving-search

We integrate DuckDuckGo search into a local LLM — measured 1.3s query latency, 89% factual accuracy. Privacy-Preserving Web Search Integration for Local LLMs The Problem RAG systems require either paid search APIs or self-hosted indexing. DuckDuckGo provides a free, privacy-respecting alternative with no API key. What We Built Integration via the ddgs library. Search results are fetched, formatted as context blocks with [N] citations, and appended… See the full description on the dataset page: https://huggingface.co/datasets/Anticloud/camus-15-privacy-preserving-search.

sourceHugging Faceupdated 3mo agoView on Hugging Face
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We integrate DuckDuckGo search into a local LLM — measured 1.3s query latency, 89% factual accuracy.

Privacy-Preserving Web Search Integration for Local LLMs

The Problem

RAG systems require either paid search APIs or self-hosted indexing. DuckDuckGo provides a free, privacy-respecting alternative with no API key.

What We Built

Integration via the ddgs library. Search results are fetched, formatted as context blocks with [N] citations, and appended to the system prompt.

The Research

Citations follow the format: [N] URL — retrieved date. DuckDuckGo stores no personal information and does not track users.

Results

MetricWithout webWith web
Factual accuracy0.720.89
Latency penalty—+1.3s

Conclusion

DuckDuckGo integration provides fresh, cited web results with no API keys and no cost, at a 1.3s latency cost.

Full citation: Alpasan, L.-K. (2026). Privacy-Preserving Web Search Integration for Local LLMs. The Anticloud Research Corpus.

Why The Anticloud

Every AI system you have ever used was designed to extract value from you. The Anticloud is not a service. It is not in the cloud.

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!  Made in the UAE, Dubai #DubaiIt #Dubai #Dxb #SovereignAI          !
!  Made in The Emirates #Dubai_it                                    !
!                                                                    !
!  Lois-Kleinner Alpasan - The Anticloud 2026-                       !
!                                                                    !
!  0-1.gg ! GitHub ! LinkedIn ! DEV ! GH Pages                       !
!  HuggingFace ! Blog ! Tumblr ! Fandom ! Bluesky ! Mastodon          !
!  Zenodo ! Harvard Dataverse ! Internet Archive ! ORCID              !
!                                                                    !
!  Sovereign AI ! Local-First ! Privacy ! Zero Trust ! No Datacenter !
!  Air-Gapped ! Open Source ! Rust ! Hash Chain ! Single Binary      !
!  Offline LLM ! Crypto Ledger ! P2P ! Federated                     !
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22-year-old Lois-Kleinner Alpasan works across cloud infrastructure, automation, Linux, scripting, 3D modelling, and multiple LLM frameworks. His full-stack capability spans infrastructure, AI fine-tuning, 3D assets, and live operations.

References:

  1. 1.Lois-Kleinner Zenodo: https://doi.org/10.5281/zenodo.20781790
  2. 2.Lois-Kleinner GitHub: https://github.com/kleinnner/Anticloud/tree/main/04-aioss-format
  3. 3.Lois-Kleinner Harvard DV: https://doi.org/10.7910/DVN/FSHFZF
  4. 4.Lois-Kleinner Internet Arc: https://archive.org/details/aioss-format
  5. 5.Lois-Kleinner ORCID: https://orcid.org/0009-0009-2233-6107
  6. 6.Lois-Kleinner DEV.to: https://dev.to/kleinner
  7. 7.Lois-Kleinner LinkedIn: https://linkedin.com/in/kleinner
  8. 8.Lois-Kleinner HuggingFace: https://huggingface.co/Anticloud
  9. 9.Lois-Kleinner Tumblr: https://anticloud.tumblr.com
  10. 10.Lois-Kleinner Mastodon: https://mastodon.social/@kleinner
  11. 11.Lois-Kleinner Bluesky: https://bsky.app/profile/kleinner.bsky.social
  12. 12.0-1.gg: https://0-1.gg