Search and Summarize Web Content with Exa
LlamaIndex tool integration that connects AI agents to Exa web search API for searching the web and retrieving HTML content from the internet.
Why it matters
Leverage the Exa web search API to enable AI agents to search the internet, retrieve HTML content, and summarize findings. This integration allows for efficient information gathering and processing for complex queries.
Outcomes
What it gets done
Search the web using natural language queries via Exa.
Retrieve and process HTML content from search results.
Find similar documents based on provided URLs.
Summarize news and web content for agent consumption.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/li-tool-tools-exa | bash Capabilities
What this skill does
Searches the web and retrieves relevant sources.
Fetches and parses content from web pages.
Condenses long documents or threads into key takeaways.
Chunks, embeds, and indexes documents for semantic retrieval.
Overview
LlamaIndex Tools Integration: Exa
What it does
This tool connects your LlamaIndex agent to Exa, a web search API for AI. It enables web search using natural language queries, retrieval of HTML content from the internet, and finding similar documents to a given URL.
How it connects
Use this tool when your agent needs to search the web, retrieve HTML documents from search results, or find pages similar to a specific URL. Requires an Exa API key from their developer dashboard.
Source README
LlamaIndex Tools Integration: Exa
This tool connects to Exa, one of the best web search APIs for AI, to easily enable
your agent to search and get HTML content from the Internet.
To begin, you need to obtain an API key on the Exa developer dashboard.
Usage
This tool has more a extensive example usage documented in a Jupyter notebook here
Here's an example usage of the ExaToolSpec.
# %pip install llama-index llama-index-core llama-index-tools-exa
from llama_index.tools.exa import ExaToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
exa_tool = ExaToolSpec(
api_key=os.environ["EXA_API_KEY"],
)
agent = FunctionAgent(
tools=exa_tool.to_tool_list(),
llm=OpenAI(model="gpt-4.1"),
)
print(
await agent.run(
"Can you summarize the news published in the last month on superconductors"
)
)
search: Search the web using Exa for a list of articles relating to a natural language query
retrieve_documents: Retrieve a list of documents returned from exa_search.
search_and_retrieve_highlights: Search and retrieve query-relevant highlights from results.
search_and_retrieve_documents: Combines search and retrieve_documents to directly return a list of documents related to a search
current_date: Utility for the Agent to get todays date
This loader is designed to be used as a way to load data as a Tool in a Agent.
Discussion
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