Python SDK

from exa_py import Exa

exa = Exa()  # reads EXA_API_KEY from environment

results = exa.search(
    "blog post about artificial intelligence",
    contents={"text": True}
)

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

results = exa.get_contents(
    ["https://openai.com/research"],
    text=True
)

results = exa.get_contents(
    ["https://stripe.com/docs/api"],
    summary=True
)

results = exa.get_contents(
    ["https://arxiv.org/abs/2303.08774"],
    highlights={"num_sentences": 3}
)

results = exa.find_similar(
    "https://paulgraham.com/greatwork.html",
    contents={"text": True}
)

results = exa.find_similar(
    "https://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html",
    exclude_source_domain=True,
    contents={"text": True}
)

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)

from exa_py import AsyncExa

exa = AsyncExa()

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

task = exa.research.create(
    instructions="Summarize recent advances in fusion energy",
    output_schema={
        "type": "object",
        "properties": {
            "summary": {"type": "string"},
            "key_developments": {"type": "array", "items": {"type": "string"}}
        }
    }
)

result = exa.research.poll_until_finished(task.research_id)