Exa Python SDK


The official Python SDK for Exa, the web search API for AI.

Documentation | Dashboard

Install

pip install exa-py

Requires Python 3.9+

Quick Start

from exa_py import Exa
exa = Exa(api_key="your-api-key")
Search the web

results = exa.search(
    "blog post about artificial intelligence",
    type="auto",
    contents={"highlights": True}
)
Ask a question

response = exa.answer("What is the capital of France?")

Search

results = exa.search(
    "machine learning startups",
    contents={"highlights": True}
)

results = exa.search(
    "climate tech news",
    num_results=20,
    start_published_date="2024-01-01",
    include_domains=["techcrunch.com", "wired.com"],
    contents={"highlights": True}
)

results = exa.search(
    "What are the latest battery breakthroughs?",
    type="deep",
    system_prompt="Prefer official sources and avoid duplicate results",
    output_schema={
        "type": "object",
        "properties": {
            "summary": {"type": "string"},
            "key_companies": {"type": "array", "items": {"type": "string"}},
        },
        "required": ["summary", "key_companies"],
    },
)
print(results.output.content if results.output else None)

Deep output_schema modes:

{"type": "text", "description": "..."}: return plain text in output.content

{"type": "object", ...}: return structured JSON in output.content

Deep search also supports system_prompt to guide both the search process and the final returned result, for example by preferring certain sources, emphasizing novel findings, avoiding duplicates, or constraining output style.

For type: "object", deep search currently enforces:

max nesting depth: 2

max total properties: 10

Deep search variants:

deep: light mode

deep-reasoning: base reasoning mode

Contents

results = exa.get_contents(
    ["https://docs.exa.ai"],
    text=True
)

results = exa.get_contents(
    ["https://arxiv.org/abs/2303.08774"],
    highlights=True
)

Answer

response = exa.answer("What caused the 2008 financial crisis?")
print(response.answer)

for chunk in exa.stream_answer("Explain quantum computing"):
    print(chunk, end="", flush=True)

Async

from exa_py import AsyncExa
exa = AsyncExa(api_key="your-api-key")
results = await exa.search("async search example", contents={"highlights": True})

More

See the full documentation for all features including websets, filters, and advanced options.