🎉 Tavily raises $25M to power the Internet of AgentsRead more
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from tavily import TavilyClient
tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")
response = tavily_client.search("Who is Leo Messi?")
print(response)
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const { tavily } = require('@tavily/core');
const tvly = tavily({ apiKey: "tvly-YOUR_API_KEY" });
tvly.search("Who is Leo Messi?")
.then(results => console.log(results));
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curl -X POST 'https://api.tavily.com/search' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer tvly-YOUR_API_KEY' \
-d '{"query": "Who is Leo Messi?"}'
OpenAI’s SimpleQA benchmark measures the ability of language models to answer short, fact-seeking questions. It uses a curated set of factual queries designed to test how accurately a model can retrieve and synthesize factual information. Read more about the SimpleQA benchmark here.
To maintain fairness and ensure documents of similar length were compared across providers, we set include_raw_content=False
(default), contents.highlights=True
, and max_tokens_per_page=512
for Tavily, Exa, and Perplexity Search, respectively. In addition, we retrieved a maximum of 10 documents per query across all providers.