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chore(docs): fix Markdown lint issues in the docs

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Damien Laureaux 2024-11-15 07:04:45 +01:00
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docs/architecture/README.md
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## Perplexica's Architecture
# Perplexica's Architecture
Perplexica's architecture consists of the following key components:

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docs/architecture/WORKING.md
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## How does Perplexica work?
# How does Perplexica work?
Curious about how Perplexica works? Don't worry, we'll cover it here. Before we begin, make sure you've read about the architecture of Perplexica to ensure you understand what it's made up of. Haven't read it? You can read it [here](https://github.com/ItzCrazyKns/Perplexica/tree/master/docs/architecture/README.md).
@ -10,10 +10,10 @@ We'll understand how Perplexica works by taking an example of a scenario where a
4. After the information is retrieved, it is based on keyword-based search. We then convert the information into embeddings and the query as well, then we perform a similarity search to find the most relevant sources to answer the query.
5. After all this is done, the sources are passed to the response generator. This chain takes all the chat history, the query, and the sources. It generates a response that is streamed to the UI.
### How are the answers cited?
## How are the answers cited?
The LLMs are prompted to do so. We've prompted them so well that they cite the answers themselves, and using some UI magic, we display it to the user.
### Image and Video Search
## Image and Video Search
Image and video searches are conducted in a similar manner. A query is always generated first, then we search the web for images and videos that match the query. These results are then returned to the user.