Perplexica
Open-source AI search engine that searches the web and synthesizes cited answers, self-hostable with Ollama or any OpenAI-compatible model, with 15k+ GitHub stars.
Perplexica is an open-source AI-powered search engine that works similarly to Perplexity.ai - querying the web in real time and synthesizing a cited answer - but can be fully self-hosted using local models via Ollama for complete privacy. It supports multiple search focus modes including web, academic papers, YouTube, Reddit, and news, each optimized for different research contexts. Built with Next.js and a Python backend, Perplexica connects to SearXNG as its search provider for maximum privacy and can use any OpenAI-compatible API including Groq, Anthropic, or OpenRouter for the synthesis layer. The project has reached 15,000+ GitHub stars and is widely used as a private alternative to commercial AI search tools.
Key Features
- Real-time web search with AI synthesis and inline source citations for every answer
- Multiple focus modes: web, academic papers, YouTube, Reddit, and news search
- Self-hostable with Docker and Ollama for fully local and private AI search
- Support for any OpenAI-compatible API including Groq, Anthropic, and OpenRouter
- SearXNG integration as the search backend for privacy-preserving query routing
- Conversation memory for multi-turn search sessions with retained context across questions
Use Cases
- Privacy-focused users wanting AI search without queries reaching commercial providers
- Self-hosters running a private AI search engine on local infrastructure with Ollama models
- Researchers using academic and YouTube focus modes to search specialized content types
- Organizations requiring AI-powered search with full data sovereignty and no external calls
Pros
- Fully self-hostable with Ollama for private AI search with zero external data sharing
- Multiple focus modes enable contextually optimized search beyond basic web results
- 15k+ GitHub stars with active development and responsive issue tracking
Cons
- Requires Docker and technical setup compared to zero-config use of perplexity.ai
- Search quality depends on the LLM used - local models produce lower-quality synthesis than GPT-4
- No dedicated mobile app - browser interface only with no iOS or Android native experience
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