2.1 KiB
How Perplexica Works
This is a high level overview of how Perplexica answers a question.
If you want a component level overview, see README.md.
If you want implementation details, see CONTRIBUTING.md.
What happens when you ask a question
When you send a message in the UI, the app calls POST /api/chat.
At a high level, we do three things:
- Classify the question and decide what to do next.
- Run research and widgets in parallel.
- Write the final answer and include citations.
Classification
Before searching or answering, we run a classification step.
This step decides things like:
- Whether we should do research for this question
- Whether we should show any widgets
- How to rewrite the question into a clearer standalone form
Widgets
Widgets are small, structured helpers that can run alongside research.
Examples include weather, stocks, and simple calculations.
If a widget is relevant, we show it in the UI while the answer is still being generated.
Widgets are helpful context for the answer, but they are not part of what the model should cite.
Research
If research is needed, we gather information in the background while widgets can run.
Depending on configuration, research may include web lookup and searching user uploaded files.
Answer generation
Once we have enough context, the chat model generates the final response.
You can control the tradeoff between speed and quality using optimizationMode:
speedbalancedquality
How citations work
We prompt the model to cite the references it used. The UI then renders those citations alongside the supporting links.
Search API
If you are integrating Perplexica into another product, you can call POST /api/search.
It returns:
message: the generated answersources: supporting references used for the answer
You can also enable streaming by setting stream: true.
Image and video search
Image and video search use separate endpoints (POST /api/images and POST /api/videos). We generate a focused query using the chat model, then fetch matching results from a search backend.