Ross ROSS = Recommend OSS · open-source software intelligence for agents

nashsu/FreeAskInternet

FreeAskInternet is a completely free, PRIVATE and LOCALLY running search aggregator & answer generate using MULTI LLMs, without GPU needed. The user can ask a question and the system will make a multi engine search and combine the search result to LLM and generate the answer based on search results. It's all FREE to use. observed · 2026-08-28

github.com/nashsu/FreeAskInternet · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

25/100

  • Activity 0
  • Release rhythm 35
  • Longevity 62

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 880
  • days_rel: n/a
  • days_push: 867
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

8746 stars · 905 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

FreeAskInternet is a self-hosted, Perplexity-like search aggregator and answer generator that runs multi-engine searches via SearXNG and feeds results to free LLM APIs (ChatGPT3.5, Qwen, Kimi, ZhipuAI) or custom LLMs like Ollama. It runs entirely locally without GPU or API keys and is deployed via Docker Compose with a web and mobile-friendly chat UI.

Use cases

  • run a private perplexity alternative locally
  • search the web and get AI-generated answers without API keys
  • self-host an AI answer engine with ollama
  • aggregate multi-engine search results into an LLM answer
  • chat with an LLM grounded in live web search results
  • use an AI search assistant without a GPU

When to choose

  • you want a free, private, locally running AI search/answer app
  • you have no GPU and want LLM answers based on web search
  • you want to plug in custom LLMs like Ollama or llama.cpp
  • you prefer Docker Compose one-command deployment

When to avoid

  • you need a production-grade, actively maintained product
  • you require official paid LLM APIs with API keys
  • you need RAG over your own documents rather than web search
  • your network cannot freely access the search engines and LLM endpoints it relies on

Facets

application · maturity experimental

search-engine rag llm-inference chat-interface web-scraping self-hosted large-language-models artificial-intelligence self-hosted self-hosted python cross-platform perplexity-clone searxng ollama local-first privacy docker-compose answer-engine retrieval-augmented-generation search docker web-server

1 source

Member repositories

RepositoryRoleHealth v2
nashsu/FreeAskInternetmain25

For agents

markdown · JSON · MCP: product_card(name="nashsu/FreeAskInternet")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem