Maintained by deepset

Integration: Brave Search

Search the web using the Brave Search API with Haystack

Authors

deepset

GitHub Repo PyPI Package

Overview
Installation
Usage
- BraveWebSearch
License

Overview

Brave Search is an independent search engine with its own web index. Unlike most search APIs, it does not rely on Google or Bing, making it a great choice for privacy-conscious applications.

This integration provides:

BraveWebSearch: Searches the web using the Brave Search API and returns results as Haystack Document objects along with source URLs.

You need a Brave Search API key to use this integration. You can get one at brave.com/search/api.

Installation

pip install brave-search-haystack

Usage

BraveWebSearch

BraveWebSearch queries the Brave Search API and returns results as Haystack Document objects containing the content snippets and metadata (title, URL). Source URLs are also returned separately.

Basic Example

from haystack_integrations.components.websearch.brave import BraveWebSearch

web_search = BraveWebSearch(top_k=5)

result = web_search.run(query="What is Haystack by deepset?")
documents = result["documents"]
links = result["links"]

In a Pipeline

Here is an example of a RAG pipeline that uses BraveWebSearch to retrieve web content and answer a question:

from haystack import Pipeline
from haystack.utils import Secret
from haystack.components.builders.chat_prompt_builder import ChatPromptBuilder
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.dataclasses import ChatMessage
from haystack_integrations.components.websearch.brave import BraveWebSearch

web_search = BraveWebSearch(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 = OpenAIChatGenerator(
    api_key=Secret.from_env_var("OPENAI_API_KEY"),
    model="gpt-4o-mini",
)

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)

Async Support

The component supports asynchronous execution via run_async:

import asyncio
from haystack_integrations.components.websearch.brave import BraveWebSearch

async def main():
    web_search = BraveWebSearch(top_k=3)
    result = await web_search.run_async(query="What is Haystack by deepset?")
    print(f"Found {len(result['documents'])} documents")

asyncio.run(main())

Parameters

api_key: API key for Brave Search. Defaults to the BRAVE_API_KEY environment variable.
top_k: Maximum number of results to return. Defaults to 10.
country: 2-letter country code to bias search results (e.g. "US", "DE").
search_lang: Language code for search results (e.g. "en", "de").
extra_params: Additional query parameters passed directly to the Brave Search API.
timeout: Timeout in seconds for the HTTP request. Defaults to 10.
max_retries: Maximum number of retry attempts on transient failures. Defaults to 3.

License

brave-search-haystack is distributed under the terms of the Apache-2.0 license.