deepset-ai--haystack/docs-website/docs/pipeline-components/websearch/perplexitywebsearch.mdx

---
title: "PerplexityWebSearch"
id: perplexitywebsearch
slug: "/perplexitywebsearch"
description: "Search the web using the Perplexity Search API and return results as Haystack Documents."
---

# PerplexityWebSearch

Search the web using the Perplexity Search API.

<div className="key-value-table">

|  |  |
| --- | --- |
| **Most common position in a pipeline** | Before a [`ChatPromptBuilder`](../builders/chatpromptbuilder.mdx) or at the beginning of an indexing pipeline |
| **Mandatory init variables** | `api_key`: A Perplexity API key. Can be set with `PERPLEXITY_API_KEY` env var. |
| **Mandatory run variables** | `query`: A string with your search query. |
| **Output variables** | `documents`: A list of Haystack Documents containing search result content and metadata. <br /> <br />`links`: A list of strings of resulting URLs. |
| **API reference** | [Integrations](/reference/integrations-perplexity) |
| **GitHub link** | https://github.com/deepset-ai/haystack-core-integrations/blob/main/integrations/perplexity/src/haystack_integrations/components/websearch/perplexity/perplexity_websearch.py |
| **Package name** | `perplexity-haystack` |

</div>

## Overview

When you give `PerplexityWebSearch` a query, it uses the [Perplexity Search API](https://docs.perplexity.ai/) to search the web and return relevant content as Haystack `Document` objects. It also returns a list of the source URLs.

Each returned `Document` contains a text snippet as its `content` and a `meta` dictionary with `title`, `url`, `date`, and `last_updated` fields.

`PerplexityWebSearch` requires a Perplexity API key to work. By default, it reads from the `PERPLEXITY_API_KEY` environment variable. You can also pass an `api_key` directly during initialization.

The `top_k` parameter controls the maximum number of results returned (between 1 and 20, default is 10).

You can filter and refine search results using `search_params`, which supports keys such as `country`, `search_recency_filter`, `search_domain_filter`, and date range filters. These can be set at initialization or overridden per `run()` call. See the [Perplexity Search API reference](https://docs.perplexity.ai/api-reference/search-post) for the full list of parameters.

`PerplexityWebSearch` supports both synchronous (`run()`) and asynchronous (`run_async()`) operation.

## Usage

### On its own

```python
from haystack.utils import Secret
from haystack_integrations.components.websearch.perplexity import PerplexityWebSearch

web_search = PerplexityWebSearch(
    api_key=Secret.from_env_var("PERPLEXITY_API_KEY"),
    top_k=5,
)
result = web_search.run(query="What is Haystack by deepset?")

for doc in result["documents"]:
    print(doc.content)
    print(doc.meta["url"])
```

With search filters:

```python
from haystack.utils import Secret
from haystack_integrations.components.websearch.perplexity import PerplexityWebSearch

web_search = PerplexityWebSearch(
    api_key=Secret.from_env_var("PERPLEXITY_API_KEY"),
    top_k=5,
    search_params={"country": "us", "search_recency_filter": "week"},
)
result = web_search.run(query="Latest AI research papers")

for doc in result["documents"]:
    print(doc.meta["title"], doc.meta["url"])
```

### In a pipeline

Here is an example of a RAG pipeline that uses `PerplexityWebSearch` to look up an answer on the web.

```python
from haystack import Pipeline
from haystack.utils import Secret
from haystack.components.builders.chat_prompt_builder import ChatPromptBuilder
from haystack.dataclasses import ChatMessage
from haystack_integrations.components.generators.perplexity import (
    PerplexityChatGenerator,
)
from haystack_integrations.components.websearch.perplexity import PerplexityWebSearch

web_search = PerplexityWebSearch(
    api_key=Secret.from_env_var("PERPLEXITY_API_KEY"),
    top_k=3,
)

prompt_template = [
    ChatMessage.from_system("You are a helpful assistant."),
    ChatMessage.from_user(
        "Given the information below:\n"
        "{% for document in documents %}{{ document.content }}\n{% endfor %}\n"
        "Answer the following question: {{ query }}.\nAnswer:",
    ),
]

prompt_builder = ChatPromptBuilder(
    template=prompt_template,
    required_variables=["query", "documents"],
)

llm = PerplexityChatGenerator(
    api_key=Secret.from_env_var("PERPLEXITY_API_KEY"),
)

pipe = Pipeline()
pipe.add_component("search", web_search)
pipe.add_component("prompt_builder", prompt_builder)
pipe.add_component("llm", llm)

pipe.connect("search.documents", "prompt_builder.documents")
pipe.connect("prompt_builder.prompt", "llm.messages")

query = "What is Haystack by deepset?"
result = pipe.run(data={"search": {"query": query}, "prompt_builder": {"query": query}})
print(result["llm"]["replies"][0].text)
```