Valyu Best Practices

Valyu Best Practices

This skill provides instructions for using the Valyu API to perform search, content extraction, AI-powered answers, and deep research tasks.

Quick Reference: Choosing the Right API

Use this decision tree to select the appropriate Valyu API:

What do you need?

├─ Find information across multiple sources
│  └─ Use Search API
│
├─ Extract content from specific URLs
│  └─ Use Contents API
│
├─ Get an AI-synthesized answer with citations
│  └─ Use Answer API
│
├─ Generate a comprehensive research report
│  └─ Use DeepResearch API
│
└─ Discover available data sources
   └─ Use Datasources API

---

⚠️ MANDATORY: Use Official Valyu SDK Libraries

CRITICAL: When writing code that uses the Valyu API, you MUST use the official SDK libraries. NEVER make raw HTTP/fetch calls to the Valyu API endpoints.

JavaScript/TypeScript: valyu-js

npm install valyu-js
## or
pnpm add valyu-js

import { Valyu } from 'valyu-js';

const valyu = new Valyu(process.env.VALYU_API_KEY);

// Now use valyu.search(), valyu.contents(), valyu.answer(), valyu.deepResearch

Python: valyu

pip install valyu
## or
uv add valyu

from valyu import Valyu

valyu = Valyu(api_key=os.environ.get("VALYU_API_KEY"))

## Now use valyu.search(), valyu.contents(), valyu.answer(), valyu.deep_research

Why SDK Over Raw API Calls?

1. Type safety - Full TypeScript/Python type hints for all parameters and responses
2. Automatic retries - Built-in retry logic for transient failures
3. Streaming support - Proper async iterator support for streaming responses
4. Error handling - Structured error types with helpful messages
5. Future compatibility - SDK updates handle API changes automatically

❌ NEVER Do This

// DON'T make raw fetch calls
const response = await fetch('https://api.valyu.ai/v1/search', {
  method: 'POST',
  headers: {
    'x-api-key': apiKey,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({ query: '...' })
});

✅ Always Do This

// DO use the SDK
import { Valyu } from 'valyu-js';

const valyu = new Valyu(process.env.VALYU_API_KEY);
const response = await valyu.search({ query: '...' });

---

1. Search API

Purpose: Find information across web, academic, medical, transportation, financial, news, and proprietary sources.

When to Use

• Finding recent information on any topic
• Academic research (arXiv, PubMed, bioRxiv, medRxiv)
• Financial data (SEC filings, earnings reports, stock data)
• News monitoring and current events
• Healthcare data (clinical trials, drug labels)
• Prediction markets (Polymarket, Kalshi)
• Transportation (UK National Rail, Global Shipping)

Basic Usage

const response = await valyu.search({
  query: "transformer architecture attention mechanism 2024",
  searchType: "all",
  maxNumResults: 10
});

Search Types

Type	Use For
all	Everything - web, academic, financial, proprietary
web	General internet content only
proprietary	Licensed academic papers and research
news	News articles and current events

Key Parameters

Parameter (TS/JS)	Parameter (Python)	Purpose	Example
query	query	Search query (under 400 chars)	"CRISPR gene editing 2024"
searchType	search_type	Source scope	"all", "web", "proprietary", "news"
maxNumResults	max_num_results	Number of results (1-20)	10
includedSources	included_sources	Limit to specific sources	["valyu/valyu-arxiv", "valyu/valyu-pubmed"]
startDate / endDate	start_date / end_date	Date filtering	"2024-01-01"
relevanceThreshold	relevance_threshold	Minimum relevance (0-1)	0.7

Domain-Specific Search Patterns

Academic Research:

await valyu.search({
  query: "CRISPR therapeutic applications clinical trials",
  searchType: "proprietary",
  includedSources: ["valyu/valyu-arxiv", "valyu/valyu-pubmed", "valyu/valyu-biorxiv"],
  startDate: "2024-01-01"
});

Financial Analysis:

await valyu.search({
  query: "Apple revenue Q4 2024 earnings",
  searchType: "all",
  includedSources: ["valyu/valyu-sec-filings", "valyu/valyu-earnings-US"]
});

News Monitoring:

await valyu.search({
  query: "AI regulation EU",
  searchType: "news",
  startDate: "2024-06-01",
  countryCode: "EU"
});

Search Recipes

For detailed patterns, see:

• Basic Search Patterns
• Academic Search
• Finance Search
• News Search
• Healthcare Search

---

2. Contents API

Purpose: Extract clean, structured content from web pages optimized for LLM processing.

When to Use

• Converting web pages to clean markdown
• Extracting article text for summarization
• Parsing documentation for RAG systems
• Structured data extraction from product pages
• Processing academic papers

Basic Usage

const response = await valyu.contents({
  urls: ["https://example.com/article"]
});

With Summarization

const response = await valyu.contents({
  urls: ["https://arxiv.org/abs/2401.12345"],
  summary: "Extract key findings in 3 bullet points"
});

Structured Extraction (JSON Schema)

const response = await valyu.contents({
  urls: ["https://example.com/product"],
  summary: {
    type: "object",
    properties: {
      product_name: { type: "string" },
      price: { type: "number" },
      features: { type: "array", items: { type: "string" } }
    },
    required: ["product_name", "price"]
  }
});

Key Parameters

Parameter (TS/JS)	Parameter (Python)	Purpose	Example
urls	urls	URLs to process (1-10)	["https://example.com"]
responseLength	response_length	Content length	"short", "medium", "large", "max"
extractEffort	extract_effort	Extraction quality	"normal", "high", "auto"
summary	summary	AI summarization	true, "instructions", or JSON schema
screenshot	screenshot	Capture screenshots	true

Content Recipes

For detailed patterns, see:

• Basic Content Extraction
• Extraction with Summary
• Structured Extraction
• Research Paper Extraction

---

3. Answer API

Purpose: Get AI-powered answers grounded in real-time search results with citations.

When to Use

• Questions requiring current information synthesis
• Multi-source fact verification
• Technical documentation questions
• Research requiring cited sources
• Structured data extraction from search results

Basic Usage

const response = await valyu.answer({
  query: "What are the latest developments in quantum computing?"
});

With Fast Mode (Lower Latency)

const response = await valyu.answer({
  query: "Current Bitcoin price and 24h change",
  fastMode: true
});

With Custom Instructions

const response = await valyu.answer({
  query: "Compare React and Vue for enterprise applications",
  systemInstructions: "Provide a balanced comparison with pros and cons. Format as a comparison table."
});

With Streaming

const stream = await valyu.answer({
  query: "Explain transformer architecture",
  streaming: true
});

for await (const chunk of stream) {
  // Handle: search_results, content, metadata, done, error
  console.log(chunk);
}

Structured Output

const response = await valyu.answer({
  query: "Apple Q4 2024 financial highlights",
  structuredOutput: {
    type: "object",
    properties: {
      revenue: { type: "string" },
      growthRate: { type: "string" },
      keyHighlights: { type: "array", items: { type: "string" } }
    }
  }
});

Key Parameters

Parameter (TS/JS)	Parameter (Python)	Purpose	Example
query	query	Question to answer	"What is quantum computing?"
fastMode	fast_mode	Lower latency	true
systemInstructions	system_instructions	AI directives	"Be concise"
structuredOutput	structured_output	JSON schema	{type: "object", ...}
streaming	streaming	Enable SSE streaming	true
dataMaxPrice	data_max_price	Dollar limit	1.0

Answer Recipes

For detailed patterns, see:

• Basic Answer
• Fast Mode
• Streaming
• Custom Instructions

---

4. DeepResearch API

Purpose: Generate comprehensive research reports with detailed analysis and citations.

When to Use

• Comprehensive market analysis
• Literature reviews
• Competitive intelligence
• Technical deep dives
• Topics requiring multi-source synthesis

Research Modes

Mode	Duration	Best For
fast	~5 minutes	Quick lookups, simple questions
standard	~10-20 minutes	Balanced research (most common)
heavy	~90 minutes	Comprehensive analysis, complex topics

Create Research Task

const task = await valyu.deepResearch.create({
  query: "AI chip market competitive landscape 2024",
  model: "standard"
});
// Returns: { deepresearch_id: "abc123", status: "queued" }

Poll for Completion

const status = await valyu.deepResearch.getStatus(task.deepresearch_id);
// status: "queued" | "running" | "completed" | "failed" | "cancelled"

if (status.status === "completed") {
  console.log(status.output);  // Markdown report
  console.log(status.sources); // Cited sources
  console.log(status.pdf_url); // PDF download link
}

Key Parameters

Parameter (TS/JS)	Parameter (Python)	Purpose	Example
query	query	Research question	"AI market trends 2024"
model	model	Research depth	"fast", "standard", "heavy"
outputFormat	output_format	Report format	"markdown", "pdf"
includedSources	included_sources	Source filtering	["valyu/valyu-arxiv", "techcrunch.com"]
startDate / endDate	start_date / end_date	Date range	"2024-01-01"

DeepResearch Recipes

For detailed patterns, see:

• Fast Research
• Standard Research
• Heavy Research

---

5. Query Writing Best Practices

Core Principles

1. Be specific - Use domain terminology
2. Be concise - Keep queries under 400 characters
3. Be focused - One topic per query
4. Add constraints - Include timeframes, source types

Query Anatomy

Element	Description	Example
Intent	What you need	"latest advancements" vs "overview"
Domain	Topic terminology	"transformer architecture"
Constraints	Filters	"2024", "peer-reviewed"
Source type	Where to look	academic papers, SEC filings

Good vs Bad Queries

BAD:  "I want to know about AI"
GOOD: "transformer attention mechanism survey 2024"

BAD:  "Apple financial information"
GOOD: "Apple revenue growth Q4 2024 earnings SEC filing"

BAD:  "gene editing research"
GOOD: "CRISPR off-target effects therapeutic applications 2024"

Split Complex Requests

## Don't do this
"Tesla stock performance, new products, and Elon Musk statements"

## Do this instead
Query 1: "Tesla stock performance Q4 2024"
Query 2: "Tesla Cybertruck production updates 2024"
Query 3: "Tesla FSD autonomous driving progress"

Source Filtering

Use includedSources for domain authority: ​ Financial Research Collection. Some sources to include:

• valyu/valyu-sec-filings - SEC regulatory filings
• valyu/valyu-stocks - Stock market data
• valyu/valyu-earnings-US - Earnings reports
• reuters.com - Financial news
• bloomberg.com - Market analysis ​ Medical Research Collection. Some sources to include:
• valyu/valyu-pubmed - Medical literature
• valyu/valyu-clinical-trials - Clinical trial data
• valyu/valyu-drug-labels - FDA drug information
• nejm.org - New England Journal of Medicine
• thelancet.com - The Lancet ​ Tech Documentation Collection. Some sources to include:
• docs.aws.amazon.com - AWS documentation
• cloud.google.com/docs - Google Cloud docs
• learn.microsoft.com - Microsoft docs
• kubernetes.io/docs - Kubernetes docs
• developer.mozilla.org - MDN Web Docs

// Academic
includedSources: ["valyu/valyu-arxiv", "valyu/valyu-pubmed", "nature"]

// Financial
includedSources: ["valyu/valyu-sec-filings", "bloomberg.com", "reuters.com"]

// Tech news
includedSources: ["techcrunch.com", "theverge.com", "arstechnica.com"]

For complete prompting guide, see references/prompting.md.

---

6. Common Workflows

Research Workflow

// 1. Quick search to find sources
const searchResults = await valyu.search({
  query: "CRISPR therapeutic applications",
  searchType: "proprietary",
  maxNumResults: 20
});

// 2. Extract key content from top results
const contents = await valyu.contents({
  urls: searchResults.results.slice(0, 3).map(r => r.url),
  summary: "Extract key findings"
});

// 3. Deep analysis for comprehensive report
const research = await valyu.deepResearch.create({
  query: "CRISPR therapeutic applications comprehensive review",
  model: "heavy"
});

Financial Analysis Workflow

// 1. Get SEC filings
const filings = await valyu.search({
  query: "Apple 10-K 2024",
  includedSources: ["valyu/valyu-sec-filings"]
});

// 2. Quick synthesis
const summary = await valyu.answer({
  query: "Apple Q4 2024 financial highlights",
  fastMode: true
});

// 3. Structured extraction
const metrics = await valyu.answer({
  query: "Apple financial metrics 2024",
  structuredOutput: {
    type: "object",
    properties: {
      revenue: { type: "string" },
      netIncome: { type: "string" },
      growthRate: { type: "string" }
    }
  }
});

---

7. Available Data Sources

Valyu provides access to 25+ specialized datasets:

Category	Examples
Academic	arXiv (2.5M+ papers), PubMed (37M+), bioRxiv, medRxiv
Financial	SEC filings, earnings transcripts, stock data, crypto
Healthcare	Clinical trials, DailyMed, PubChem, drug labels, ChEMBL, DrugBank, Open Target, WHO ICD
Economic	FRED, BLS, World Bank, US Treasury, Destatis
Predictions	Polymarket, Kalshi
Patents	US patent database
Transportation	UK Rail, Ship Tracking

For complete datasource reference, see references/datasources.md.

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8. API Reference

For complete API documentation including all parameters, response structures, and error codes, see references/api-guide.md.

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9. Integration Guides

Platform-specific integration documentation:

• Anthropic Claude
• OpenAI
• Vercel AI SDK
• LangChain
• LlamaIndex
• MCP Server

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Additional Resources

• All Recipes Index
• Design Philosophy
• Prompting Guide
• Full API Reference