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Perplexica Search API Documentation

Overview

Perplexica’s Search API makes it easy to use our AI-powered search engine. You can run different types of searches, pick the models you want to use, and get the most recent info. Follow the following headings to learn more about Perplexica's search API.

Endpoint

POST `http://localhost:3001/api/search`

Note: Replace 3001 with any other port if you've changed the default PORT

Request

The API accepts a JSON object in the request body, where you define the focus mode, chat models, embedding models, and your query.

Request Body Structure

{
  "chatModel": {
    "provider": "openai",
    "model": "gpt-4o-mini"
  },
  "embeddingModel": {
    "provider": "openai",
    "model": "text-embedding-3-large"
  },
  "focusMode": "webSearch",
  "query": "What is Perplexica",
  "history": [
    ["human", "Hi, how are you?"],
    ["assistant", "I am doing well, how can I help you today?"]
  ]
}

Request Parameters

chatModel (object, optional): Defines the chat model to be used for the query. For model details you can send a GET request at http://localhost:3001/api/models.
- provider: Specifies the provider for the chat model (e.g., openai, ollama).
- model: The specific model from the chosen provider (e.g., gpt-4o-mini).
- Optional fields for custom OpenAI configuration:
  - customOpenAIBaseURL: If you’re using a custom OpenAI instance, provide the base URL.
  - customOpenAIKey: The API key for a custom OpenAI instance.
embeddingModel (object, optional): Defines the embedding model for similarity-based searching. For model details you can send a GET request at http://localhost:3001/api/models.
- provider: The provider for the embedding model (e.g., openai).
- model: The specific embedding model (e.g., text-embedding-3-large).
focusMode (string, required): Specifies which focus mode to use. Available modes:
- webSearch, academicSearch, writingAssistant, wolframAlphaSearch, youtubeSearch, redditSearch.
query (string, required): The search query or question.
history (array, optional): An array of message pairs representing the conversation history. Each pair consists of a role (either 'human' or 'assistant') and the message content. This allows the system to use the context of the conversation to refine results. Example:
```
[
  ["human", "What is Perplexica?"],
  ["assistant", "Perplexica is an AI-powered search engine..."]
]
```

Response

The response from the API includes both the final message and the sources used to generate that message.

Example Response

{
	"message": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online. Here are some key features and characteristics of Perplexica:\n\n- **AI-Powered Technology**: It utilizes advanced machine learning algorithms to not only retrieve information but also to understand the context and intent behind user queries, providing more relevant results [1][5].\n\n- **Open-Source**: Being open-source, Perplexica offers flexibility and transparency, allowing users to explore its functionalities without the constraints of proprietary software [3][10].",
	"sources": [
		{
			"pageContent": "Perplexica is an innovative, open-source AI-powered search engine designed to enhance the way users search for information online.",
			"metadata": {
				"title": "What is Perplexica, and how does it function as an AI-powered search ...",
				"url": "https://askai.glarity.app/search/What-is-Perplexica--and-how-does-it-function-as-an-AI-powered-search-engine"
			}
		},
		{
			"pageContent": "Perplexica is an open-source AI-powered search tool that dives deep into the internet to find precise answers.",
			"metadata": {
				"title": "Sahar Mor's Post",
				"url": "https://www.linkedin.com/posts/sahar-mor_a-new-open-source-project-called-perplexica-activity-7204489745668694016-ncja"
			}
		}
        ....
	]
}

Fields in the Response

message (string): The search result, generated based on the query and focus mode.
sources (array): A list of sources that were used to generate the search result. Each source includes:
- pageContent: A snippet of the relevant content from the source.
- metadata: Metadata about the source, including:
  - title: The title of the webpage.
  - url: The URL of the webpage.

Error Handling

If an error occurs during the search process, the API will return an appropriate error message with an HTTP status code.

400: If the request is malformed or missing required fields (e.g., no focus mode or query).
500: If an internal server error occurs during the search.

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