Get your free Valyu API key
Install Valyu
Install the SDK for your language: Start searching
Basic Search
Run your first search in a few lines of code:from valyu import Valyu
valyu = Valyu("your-api-key-here")
response = valyu.search("What is quantum computing?")
for result in response.results:
print(f"Title: {result.title}")
print(f"Content preview: {result.content[:200]}...")
print(f"URL: {result.url}")
Advanced Search
Add parameters to improve or filter results:from valyu import Valyu
valyu = Valyu("your-api-key-here")
response = valyu.search(
"Implementation details of agentic search-enhanced large reasoning models",
search_type="proprietary",
max_num_results=10,
max_price=30,
relevance_threshold=0.5,
category="agentic retrieval-augmented generation",
included_sources=["valyu/valyu-arxiv"],
is_tool_call=True
)
for result in response.results:
print(f" Title: {result.title}")
print(f" URL: {result.url}")
print(f" Content Preview: {result.content[:300]}...")
from valyu import Valyu
valyu = Valyu() # Uses VALYU_API_KEY from env
data = valyu.contents(
urls=[
"https://techcrunch.com/category/artificial-intelligence/",
],
response_length="medium",
extract_effort="auto",
)
print(data["results"][0]["content"][:500])
AI-Powered Answers
Get intelligent responses that combine search with AI processing:from valyu import Valyu
valyu = Valyu() # Uses VALYU_API_KEY from env
data = valyu.answer(
query="latest developments in quantum computing",
)
print(data["contents"])
Use Cases
Academic Research
Search millions of papers with full-text retrieval:
response = valyu.search(
"Extending context window of large language models via positional interpolation",
search_type="proprietary",
max_num_results=5,
max_price=30,
included_sources=["valyu/valyu-arxiv", "valyu/valyu-pubmed"]
)
for result in response.results:
print(f" Title: {result.title}")
print(f" Authors: {', '.join(result.authors) if hasattr(result, 'authors') else 'N/A'}")
print(f" Publication Date: {getattr(result, 'publication_date', 'N/A')}")
print(f" DOI: {getattr(result, 'doi', 'N/A')}")
print(f" Citation: {getattr(result, 'citation', 'N/A')}")
print(f" Citation Count: {getattr(result, 'citation_count', 'N/A')}")
print(f" Content Preview: {result.content[:200]}...")
{
"success": true,
"error": "",
"tx_id": "tx_55e65c6f-3607-4ebe-892b-e964b9c72a8d",
"query": "Extending context window of large language models via positional interpolation",
"results": [
{
"id": "55e65c6f-3607-4ebe-892b-e964b9c72a8d:2306.15595:1",
"title": "Extending Context Window of Large Language Models via Positional Interpolation",
"url": "https://arxiv.org/abs/2306.15595?utm_source=valyu.ai&utm_medium=referral",
"content": "#### 2.3 PROPOSED APPROACH: POSITION INTERPOLATION (PI)\n\n#### 2.1 BACKGROUND: ROTARY POSITION EMBEDDING (ROPE)\n\nTransformer models require explicit positional information...",
"source": "valyu/valyu-arxiv",
"length": 593,
"publication_date": "2023-01-01",
"doi": "https://doi.org/10.48550/arxiv.2306.15595",
"citation": "Shouyuan Chen et al. (2023). Extending Context Window of Large Language Models via Positional Interpolation.",
"citation_count": 25,
"authors": [
"Shouyuan Chen",
"S.H. Wong",
"Liangjian Chen",
"Yuandong Tian"
],
"price": 0.0005,
"data_type": "unstructured",
"source_type": "paper",
"relevance_score": 0.8071867796187081
}
],
"results_by_source": {
"proprietary": 1,
"web": 0
}
}
Financial Market Data
Just ask in plain English:
response = valyu.search(
"Pfizer stock price since COVID-19 outbreak",
search_type="proprietary",
max_num_results=1,
max_price=30
)
for result in response.results:
print(f" Title: {result.title}")
print(f" Content Preview: {str(result.content)[:300]}...")
if result.data_type == "structured" and isinstance(result.content, list):
print(f" Sample Data Points: {len(result.content)} entries")
for item in range(0, 3):
print(f" {result.content[item]}")
{
"success": true,
"error": "",
"tx_id": "tx_6a2568cf-a3f4-4860-9b6e-96b35e398b7f",
"query": "Price of TSLA today?",
"results": [
{
"title": "Price of PFE every 1mo between 2020-01-01 00:00 and 2025-05-26 00:00",
"url": "https://platform.valyu.ai/data-sources/valyu/valyu-stocks/characteristics",
"content": [
{
"datetime": "2025-05-01 04:00:00",
"open": 24,
"high": 24,
"low": 22,
"close": 23,
"volume": 78776482
}
],
"source": "valyu/valyu-stocks",
"price": 0.006,
"length": 8175,
"data_type": "structured",
"source_type": "data",
"relevance_score": 0.6277149030411012
}
],
"results_by_source": {
"proprietary": 1,
"web": 0
}
}
The search can interpret noisy queries like ”$$$$$ of larry and
Sergey brins companie. on fr week commencing 5th hune on the 21st century”
(which maps to “Google stock price for Friday June 5th, 2021”).
Next Steps
