> ## Documentation Index
> Fetch the complete documentation index at: https://docs.valyu.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Academic Search API for AI - arXiv, PubMed, Scholarly Papers

> Search millions of academic papers through one API. Access arXiv, PubMed, bioRxiv, and licensed journals with full-text retrieval for AI agents and research applications.

Search peer-reviewed papers, academic journals, and scholarly datasets. Useful for literature reviews, research validation, and exploring developments in any field.

## What You Can Do

* **Literature reviews** - Gather scholarly sources on specific topics
* **Research validation** - Cross-reference findings across sources
* **Citation discovery** - Find related papers and citation networks
* **Trend analysis** - Track research developments over time

## Features

<CardGroup cols={2}>
  <Card title="Enhanced Metadata" icon="tags">
    Author info, citation counts, DOIs, and publication dates.
  </Card>

  <Card title="Proprietary Datasets" icon="database">
    Access closed-access journals and books.
  </Card>

  <Card title="Source Prioritisation" icon="star">
    Automatically prioritise scholarly databases and journals.
  </Card>

  <Card title="Citation Networks" icon="share-nodes">
    Discover related work through citations and references.
  </Card>
</CardGroup>

## Available Datasets

| **Dataset**                  | **Content**                                         | **Use Case**                            |
| ---------------------------- | --------------------------------------------------- | --------------------------------------- |
| `valyu/valyu-arxiv`          | ArXiv preprints and papers                          | Latest research across all fields       |
| `valyu/valyu-pubmed`         | Medical and life sciences literature                | Healthcare and biomedical research      |
| `wiley/wiley-finance-papers` | Finance and economics papers                        | Finance and economics research          |
| `valyu/valyu-biorxiv`        | Life sciences preprints from BioRxiv                | Latest life sciences research           |
| `valyu/valyu-medrxiv`        | Health and clinical research preprints from medRxiv | Clinical research and medical preprints |

<Tip>
  Combine multiple datasets for comprehensive coverage. See all available datasets
  [here](https://platform.valyu.ai/data-sources).
</Tip>

## Quick Start

### Basic Academic Search

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")
  response = valyu.search(
      "machine learning applications in quantitative finance research",
      response_length="large"
  )

  print(response)

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  const response = await valyu.search(
    'machine learning applications in quantitative finance research',
    {
      responseLength: 'large'
    }
  );

  console.log(response);
  ```

  ```bash cURL theme={null}
  curl -X POST https://api.valyu.ai/v1/search \
    -H "x-api-key: your-valyu-api-key" \
    -H "Content-Type: application/json" \
    -d '{
      "query": "machine learning applications in quantitative finance research",
      "response_length": "large"
    }'
  ```
</CodeGroup>

### Target Specific Sources

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")
  response = valyu.search(
      "CRISPR gene editing therapeutic applications",
      included_sources=[
          "valyu/valyu-pubmed",
          "valyu/valyu-arxiv",
          "valyu/valyu-biorxiv",
          "valyu/valyu-medrxiv"
      ],
  )

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  const response = await valyu.search(
    'CRISPR gene editing therapeutic applications',
    {
      includedSources: [
        'valyu/valyu-pubmed',
        'valyu/valyu-arxiv',
        'valyu/valyu-biorxiv',
        'valyu/valyu-medrxiv'
      ],
    }
  );
  ```

  ```bash cURL theme={null}
  curl -X POST https://api.valyu.ai/v1/search \
    -H "x-api-key: your-valyu-api-key" \
    -H "Content-Type: application/json" \
    -d '{
      "query": "CRISPR gene editing therapeutic applications",
      "included_sources": [
        "valyu/valyu-pubmed",
        "valyu/valyu-arxiv",
        "valyu/valyu-biorxiv",
        "valyu/valyu-medrxiv"
      ]
    }'
  ```
</CodeGroup>

### Filter by Date

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")
  response = valyu.search(
      "peer-reviewed studies on climate change mitigation strategies",
      included_sources=[
          "valyu/valyu-arxiv",
          "valyu/valyu-pubmed"
      ],
      start_date="2024-01-01",
      response_length="large",
      max_num_results=15
  )

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  const response = await valyu.search(
    'peer-reviewed studies on climate change mitigation strategies',
    {
      includedSources: [
        'valyu/valyu-arxiv',
        'valyu/valyu-pubmed'
      ],
      startDate: '2024-01-01',
      responseLength: 'large',
      maxNumResults: 15
    }
  );
  ```

  ```bash cURL theme={null}
  curl -X POST https://api.valyu.ai/v1/search \
    -H "x-api-key: your-valyu-api-key" \
    -H "Content-Type: application/json" \
    -d '{
      "query": "peer-reviewed studies on climate change mitigation strategies",
      "included_sources": ["valyu/valyu-arxiv", "valyu/valyu-pubmed"],
      "start_date": "2024-01-01",
      "response_length": "large",
      "max_num_results": 15
    }'
  ```
</CodeGroup>

## Common Use Cases

* **Literature review**: Synthesise research across journals and preprints
* **Citation discovery**: Find related work, references, DOIs, citation counts
* **Methods benchmarking**: Compare methodologies, datasets, evaluation metrics
* **Trend analysis**: Track topics, venues, publication timelines
* **Interdisciplinary research**: Combine CS, medical, engineering sources

## Examples

### Interdisciplinary Research

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")
  response = valyu.search(
      "artificial intelligence applications in medical diagnosis research",
      included_sources=[
          "valyu/valyu-arxiv",
          "valyu/valyu-pubmed",
          "valyu/valyu-biorxiv",
          "valyu/valyu-medrxiv"
      ],
      response_length="large"
  )

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  const response = await valyu.search(
    'artificial intelligence applications in medical diagnosis research',
    {
      includedSources: [
        'valyu/valyu-arxiv',
        'valyu/valyu-pubmed',
        'valyu/valyu-biorxiv',
        'valyu/valyu-medrxiv'
      ],
      responseLength: 'large'
    }
  );
  ```
</CodeGroup>

### Compare Research Periods

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")

  # Early research
  early_research = valyu.search(
      "neural network architectures and applications",
      included_sources=["valyu/valyu-arxiv"],
      start_date="1990-01-01",
      end_date="2005-12-31"
  )

  # Modern research
  modern_research = valyu.search(
      "neural network architectures and applications",
      included_sources=["valyu/valyu-arxiv"],
      start_date="2020-01-01"
  )

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  // Early research
  const earlyResearch = await valyu.search(
    'neural network architectures and applications',
    {
      includedSources: ['valyu/valyu-arxiv'],
      startDate: '1990-01-01',
      endDate: '2005-12-31'
    }
  );

  // Modern research
  const modernResearch = await valyu.search(
    'neural network architectures and applications',
    {
      includedSources: ['valyu/valyu-arxiv'],
      startDate: '2020-01-01'
    }
  );
  ```
</CodeGroup>

### Medical Research

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")
  response = valyu.search(
      "immunotherapy cancer treatment efficacy clinical trials",
      included_sources=[
          "valyu/valyu-pubmed",
          "valyu/valyu-medrxiv",
          "valyu/valyu-clinical-trials"
      ],
      start_date="2023-01-01",
      response_length="large"
  )

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  const response = await valyu.search(
    'immunotherapy cancer treatment efficacy clinical trials',
    {
      includedSources: [
        'valyu/valyu-pubmed',
        'valyu/valyu-medrxiv',
        'valyu/valyu-clinical-trials'
      ],
      startDate: '2023-01-01',
      responseLength: 'large'
    }
  );
  ```
</CodeGroup>

### Computer Science

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")
  response = valyu.search(
      "transformer architecture improvements large language models",
      included_sources=[
          "valyu/valyu-arxiv"
      ],
      start_date="2024-01-01",
      search_type="proprietary"
  )

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  const response = await valyu.search(
    'transformer architecture improvements large language models',
    {
      includedSources: [
        'valyu/valyu-arxiv'
      ],
      startDate: '2024-01-01',
      searchType: 'proprietary'
    }
  );
  ```
</CodeGroup>

### Environmental Science

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")
  response = valyu.search(
      "carbon capture technology effectiveness peer-reviewed studies",
      included_sources=[
          "valyu/valyu-arxiv",
          "valyu/valyu-biorxiv"
      ],
      response_length="large",
      max_num_results=20
  )

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  const response = await valyu.search(
    'carbon capture technology effectiveness peer-reviewed studies',
    {
      includedSources: [
        'valyu/valyu-arxiv',
        'valyu/valyu-biorxiv'
      ],
      responseLength: 'large',
      maxNumResults: 20
    }
  );
  ```
</CodeGroup>

### Social Sciences

<CodeGroup>
  ```python Python theme={null}
  from valyu import Valyu

  valyu = Valyu("your-api-key-here")
  response = valyu.search(
      "remote work productivity psychological wellbeing studies",
      included_sources=[
          "valyu/valyu-pubmed",
          "valyu/valyu-medrxiv"
      ],
      start_date="2020-01-01",
      response_length="large"
  )

  ```

  ```javascript TypeScript theme={null}
  import { Valyu } from 'valyu-js';

  const valyu = new Valyu("your-api-key-here");

  const response = await valyu.search(
    'remote work productivity psychological wellbeing studies',
    {
      includedSources: [
        'valyu/valyu-pubmed',
        'valyu/valyu-medrxiv'
      ],
      startDate: '2020-01-01',
      responseLength: 'large'
    }
  );
  ```
</CodeGroup>

## Response Format

Academic searches return enhanced metadata:

```json theme={null}
{
  "results": [
    {
      "title": "Transformer Architecture for Protein Folding Prediction",
      "authors": ["Dr. Jane Smith", "Dr. John Doe"],
      "citation": "Smith, J., Doe, J. (2024). Nature Biotechnology, 42(3), 123-135",
      "citation_count": 45,
      "doi": "10.1038/s41587-024-12345",
      "publication_date": "2024-03-15",
      "content": "Detailed research content...",
      "references": "1. Previous work citation...",
      "source": "valyu/valyu-arxiv"
    }
  ]
}
```

## Best Practices

<Tip>
  Use `response_length="large"` for academic searches to capture full research
  context and methodology details.
</Tip>

### Writing Effective Queries

| **Strategy**              | **Example**                                       | **Why It Works**              |
| ------------------------- | ------------------------------------------------- | ----------------------------- |
| **Scholarly language**    | "peer-reviewed studies on neural plasticity"      | Targets academic content      |
| **Include methodology**   | "randomised controlled trials" or "meta-analysis" | Finds specific research types |
| **Specify research type** | "empirical studies" or "systematic review"        | Focuses on particular designs |
| **Add field context**     | "computational biology applications"              | Narrows to relevant domains   |

### Tips

1. **Date filtering**: Add date ranges to focus on recent or historical research
2. **Response length**: Use `response_length="large"` for comprehensive context
3. **Source targeting**: Use `included_sources` to focus on specific publishers

## Limitations

* **Access restrictions**: Some content may be behind paywalls
* **Publication lag**: Very recent research may not be indexed yet
* **Field coverage**: Source availability varies by discipline
* **Language bias**: Results may favour English-language publications