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PERPLEXICA
Open-source AI search engine with cited answers and deep web understanding
MIT
ABOUT
Traditional search engines return ranked links, not answers — users must click through multiple results and synthesize information manually. Perplexica combines LLMs with embeddings and web search to answer natural language questions with inline citations. It runs locally with SearXNG for private web crawling and supports pluggable LLM backends, giving users answer-engine capabilities without sending queries to commercial search APIs or exposing browsing habits.
INSTALL
docker compose upINTEGRATION GUIDE
1. Answer complex research questions with AI-generated summaries that cite sources for each claim
2. Build a private knowledge search system that indexes internal documents alongside public web results
3. Create a customer-facing search assistant that provides sourced answers from product documentation
4. Deploy a self-hosted alternative to Perplexity AI with full control over data privacy and model choice
TAGS
ragsearchaiopen-sourceretrievalembeddingsdocker