22 lines
2 KiB
Markdown
22 lines
2 KiB
Markdown
# Perplexica's Architecture
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Perplexica's architecture consists of the following key components:
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1. **User Interface**: A web-based interface that allows users to interact with Perplexica for searching images, videos, and much more.
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2. **Agent/Chains**: These components predict Perplexica's next actions, understand user queries, and decide whether a web search is necessary.
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3. **SearXNG**: A metadata search engine used by Perplexica to search the web for sources.
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4. **LLMs (Large Language Models)**: Utilized by agents and chains for tasks like understanding content, writing responses, and citing sources. Examples include Claude, GPTs, etc.
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5. **Embedding Models**: To improve the accuracy of search results, embedding models re-rank the results using similarity search algorithms such as cosine similarity and dot product distance.
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6. **Web Content**
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- In Quality mode the application uses Crawlee, Playwright, and Chromium to load web content into a real full browser
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- This significantly increases the size of the docker image and also means it can only run on x64 architectures
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- The docker build has been updated to restrict images to linux/amd64 architecture
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- In Balanced mode, the application uses JSDoc and Mozilla's Readability to retrieve and rank relevant segments of web content
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- This approach is less successful than Quality as it doesn't use a full web browser and can't load dynamic content
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- It is also more prone to being blocked by ads or scraping detection
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- Because it only uses segments of web content, it can be less accurate than Quality mode
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- In Speed mode, the application only uses the preview content returned by SearXNG
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- This content is provided by the search engines and contains minimal context from the actual web page
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- This mode is the least accurate and is often prone to hallucination
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For a more detailed explanation of how these components work together, see [WORKING.md](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/architecture/WORKING.md).
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