Python SDK for Exa API.
Project description
Exa
Exa API in Python
Installation
pip install exa_py
Usage
Import the package and initialize the Exa client with your API key:
from exa_py import Exa
exa = Exa(api_key="your-api-key")
Search Request
response = exa.search("funny article about silicon valley tech culture",
num_results=5,
include_domains=["nytimes.com", "wsj.com"],
start_published_date="2023-06-12"
)
for result in response.results:
print(result.title, result.url)
Find Similar
response = exa.find_similar("https://waitbutwhy.com/2014/05/fermi-paradox.html", num_results=5)
for result in response.results:
print(result.title, result.url)
Retrieve Document Contents
ids = ["8U71IlQ5DUTdsZFherhhYA", "X3wd0PbJmAvhu_DQjDKA7A"]
response = exa.get_contents(ids)
for content in response.contents:
print(content.title, content.url)
Reference
exa.search()
This function performs a search on the Exa API.
Args
- query (str): The search query.
- options: Additional search options. Valid options are:
num_results(int): The number of search results to return.include_domains(list): A list of domains to include in the search.exclude_domains(list): A list of domains to exclude from the search.start_crawl_date(str): The start date for the crawl (in YYYY-MM-DD format).end_crawl_date(str): The end date for the crawl (in YYYY-MM-DD format).start_published_date(str): The start date for when the document was published (in YYYY-MM-DD format).end_published_date(str): The end date for when the document was published (in YYYY-MM-DD format).use_autoprompt(bool): Whether to use autoprompt for the search.type(str): The type of search, 'keyword' or 'neural'. Default: neural
Returns
SearchResponse: A dataclass containing the search results.
exa.find_similar()
Args:
- url (str): The base url to find similar links with.
- options: Additional search options. Valid options are:
num_results(int): The number of search results to return.include_domains(list): A list of domains to include in the search.exclude_domains(list): A list of domains to exclude from the search.start_crawl_date(str): The start date for the crawl (in YYYY-MM-DD format).end_crawl_date(str): The end date for the crawl (in YYYY-MM-DD format).start_published_date(str): The start date for when the document was published (in YYYY-MM-DD format).end_published_date(str): The end date for when the document was published (in YYYY-MM-DD format).
Returns
SearchResponse: A dataclass containing the search results.
Contribution
Contributions to exa-py are very welcome! Feel free to submit pull requests or raise issues.
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