Skip to main content
Exa is a neural search engine that finds semantically similar content for your agents.

​
Overview

Exa is a neural search engine that uses embeddings to find semantically similar content. It’s particularly good at finding content that matches the meaning of your query.

​
Installation

pip install "praisonai[tools]"

​
Environment Variables

export EXA_API_KEY="${EXA_API_KEY:?Set EXA_API_KEY in your shell}"
Get your API key from Exa.

​
How It Works

​
Quick Start

1

Simple Usage

from praisonai_tools import ExaTool

# Initialize
exa = ExaTool()

# Search
results = exa.search("best practices for Python development")
print(results)
2

With Configuration

Use the same tool with an agent — see Usage with Agent below, or pass env vars and options from the sections above.

​
Usage with Agent

from praisonaiagents import Agent
from praisonai_tools import ExaTool

agent = Agent(
    name="Researcher",
    instructions="You are a research assistant. Use Exa to find relevant content.",
    tools=[ExaTool()]
)

response = agent.chat("Find articles about machine learning best practices")
print(response)

​
Available Methods

​
search(query, num_results=10)

Search for content using neural search. 
from praisonai_tools import ExaTool

exa = ExaTool()
results = exa.search("transformer architecture explained", num_results=5)

# Returns:
# [
#     {"title": "...", "url": "...", "snippet": "...", "score": 0.95},
#     ...
# ]

​
find_similar(url, num_results=10)

Find content similar to a given URL. 
similar = exa.find_similar("https://example.com/article", num_results=5)

​
get_contents(urls)

Get full content from URLs. 
contents = exa.get_contents(["https://example.com/article1", "https://example.com/article2"])

​
Configuration Options

exa = ExaTool(
    api_key="your_key",           # Optional: defaults to EXA_API_KEY
    use_autoprompt=True,          # Auto-optimize queries
    type="neural"                 # "neural" or "keyword"
)

​
Function-Based Usage

from praisonai_tools import exa_search

# Quick search without instantiating class
results = exa_search("AI safety research", num_results=5)

​
CLI Usage

# Set API key
export EXA_API_KEY=your_key

# Use with praisonai
praisonai --tools ExaTool "Find articles about reinforcement learning"

​
Error Handling

from praisonai_tools import ExaTool

exa = ExaTool()
results = exa.search("my query")

if results and "error" in results[0]:
    print(f"Error: {results[0]['error']}")
else:
    for r in results:
        print(f"- {r['title']}: {r['url']}")

​
Common Errors

ErrorCauseSolution
EXA_API_KEY not configuredMissing API keySet environment variable
exa not installedMissing dependencyRun pip install exa-py
Rate limitedToo many requestsAdd delays between requests

​
Best Practices

ExaTool() defaults to the EXA_API_KEY env var. Set it in your shell or .env instead of passing api_key= inline.
search(query, num_results=10) defaults to 10. Lower it for faster, cheaper agent loops when you only need the top matches.
Exa returns a rate-limited response under heavy use. Check for an error key in results and fall back to another search tool so the agent degrades gracefully.

Tavily

AI-powered search

DuckDuckGo

Privacy-focused search

Serper

Google search API