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Perplexica - an open-source AI search engine that supports multiple search modes and real-time information updates.

Perplexica is an open-source, AI-driven search engine and an open-source alternative to Perplexity AI. It uses machine learning algorithms and natural language processing to understand user queries and provide accurate answers. Perplexica supports various search methods...

What is Perplexica?

Perplexica is an open-source, AI-driven search engine and an open-source alternative to Perplexity AI. It understands user queries and provides accurate answers based on machine learning algorithms and natural language processing technology. Perplexica supports multiple search modes, including web search, writing assistance, academic search, YouTube search, Wolfram Alpha search, and Reddit search. Perplexica supports large local language models, integrates search functionality into other applications via API, and integrates SearxNG search technology to ensure up-to-date information.

Perplexica's main functions

  • Local LLM supportPerplexica supports the use of local large language models (LLMs) such as Llama3 and Mixtral to improve search accuracy.
  • Normal mode: Process user queries and execute web searches.
  • Focus modeThis includes various specific search patterns, such as:
    • Full web search modeSearch the entire network to find the best results.
    • Writing Assistant ModeIt helps with writing tasks that don't require web searches.
    • Academic search modeSearch for academic articles and papers; suitable for academic research.
  • YouTube search modeThe search query yielded YouTube videos.
  • Wolfram Alpha search modeUse Wolfram Alpha to perform queries that require calculations or data analysis.
  • Reddit search patternsSearch Reddit to find discussions and opinions related to your query.
  • API IntegrationIt supports developers in integrating Perplexica into their own applications and using the search function.
  • Real-time information updatesUse the SearchNG meta-search engine to ensure you get the latest information.

Perplexica's technical principles

  • User InteractionThe user sends a message to the backend server via WebSocket, triggering the processing chain.
  • Query processingThe message is passed to a chain that predicts whether a network search is needed based on the chat history and the question. If so, a query is generated.
  • Web search: Query based on SearchXNG to retrieve information from the web.
  • Similarity searchThe search results are based on the conversion into embeddings and similarity searches to find the most relevant resources.
  • Response generationResources are passed to the response generator, which combines chat history, queries, and resources to generate a response.
  • User interface displayThe final response is displayed to the user through the user interface, completing the entire search and response process.

Perplexica's project address

Applications of Perplexica

  • Personal search engineAs a personal search engine for users, we protect privacy and customize the search experience.
  • academic researchResearchers use it to find academic papers and articles to support their research efforts.
  • Internal Enterprise SearchEnterprises build internal knowledge base search engines to help employees quickly find the information they need.
  • Developer toolsDevelopers can integrate Perplexica's API into their applications to enhance their search capabilities.
  • Educational purposesEducational institutions help students and teachers quickly access educational resources and academic materials.
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