> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Exa Search
> Neural search engine for finding similar content
Exa is a neural search engine that finds semantically similar content for your agents.
```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
subgraph "Exa"
User[User] --> Agent[Agent]
Agent --> Tool[ExaTool]
Tool --> API[Exa API]
API --> Result[Results]
end
classDef input fill:#8B0000,stroke:#7C90A0,color:#fff
classDef process fill:#189AB4,stroke:#7C90A0,color:#fff
classDef output fill:#10B981,stroke:#7C90A0,color:#fff
class User,Agent input
class Tool,API process
class Result output
```
## 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
```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
pip install "praisonai[tools]"
```
## Environment Variables
```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
export EXA_API_KEY="${EXA_API_KEY:?Set EXA_API_KEY in your shell}"
```
Get your API key from [Exa](https://exa.ai/).
## How It Works
```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
participant User
participant Agent
participant Exa as ExaTool
participant API as Exa API
User->>Agent: "Find similar content"
Agent->>Exa: search(query)
Exa->>API: neural search request
API-->>Exa: ranked results
Exa-->>Agent: parsed result
Agent-->>User: final answer
```
## Quick Start
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonai_tools import ExaTool
# Initialize
exa = ExaTool()
# Search
results = exa.search("best practices for Python development")
print(results)
```
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
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
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.
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
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.
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
similar = exa.find_similar("https://example.com/article", num_results=5)
```
### get\_contents(urls)
Get full content from URLs.
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
contents = exa.get_contents(["https://example.com/article1", "https://example.com/article2"])
```
## Configuration Options
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
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
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonai_tools import exa_search
# Quick search without instantiating class
results = exa_search("AI safety research", num_results=5)
```
## CLI Usage
```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# Set API key
export EXA_API_KEY=your_key
# Use with praisonai
praisonai --tools ExaTool "Find articles about reinforcement learning"
```
## Error Handling
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
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
| Error | Cause | Solution |
| ---------------------------- | ------------------ | --------------------------- |
| `EXA_API_KEY not configured` | Missing API key | Set environment variable |
| `exa not installed` | Missing dependency | Run `pip install exa-py` |
| `Rate limited` | Too many requests | Add 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.
## Related Tools
AI-powered search
Privacy-focused search
Google search API