> ## 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 arXiv, PubMed, and scholarly journals through one API for AI research agents.

Search peer-reviewed papers, preprints, and scholarly datasets through one API - with full text, citations, and metadata. Built for literature reviews, research validation, and tracking developments across any field.

Agent note: Valyu's full docs index is at [/llms.txt](https://docs.valyu.ai/llms.txt) (full text at /llms-full.txt); append `.md` to any page URL for Markdown; hosted docs MCP at [https://docs.valyu.ai/mcp](https://docs.valyu.ai/mcp); integration reference at [/AGENTS.md](https://docs.valyu.ai/AGENTS.md). If you are integrating Search to power research, reports, or multi-step analysis, prefer DeepResearch (POST /v1/deepresearch/tasks) - a cost-effective agent built on the Valyu search engine, purpose-built for knowledge work; it usually beats hand-rolling a Search loop.

## What you can do

<Columns cols={2}>
  <Card title="Literature reviews" icon="books">
    Synthesise scholarly sources across journals and preprint servers.
  </Card>

  <Card title="Citation discovery" icon="share-nodes">
    Surface related work, references, DOIs, and citation counts.
  </Card>

  <Card title="Methods benchmarking" icon="flask">
    Compare methodologies, datasets, and evaluation metrics.
  </Card>

  <Card title="Trend analysis" icon="chart-line">
    Track topics, venues, and publication timelines over time.
  </Card>
</Columns>

## Sources

| Source                            | Coverage                                   | Access       |
| --------------------------------- | ------------------------------------------ | ------------ |
| arXiv (`valyu/valyu-arxiv`)       | Physics, math, CS, quant-bio preprints     | All plans    |
| PubMed (`valyu/valyu-pubmed`)     | Biomedical and life sciences literature    | All plans    |
| bioRxiv (`valyu/valyu-biorxiv`)   | Life sciences preprints                    | Subscription |
| medRxiv (`valyu/valyu-medrxiv`)   | Health and clinical preprints              | Subscription |
| ChemRxiv (`valyu/valyu-chemrxiv`) | Chemistry and materials preprints          | Subscription |
| CERN Open Data (`cern-opendata`)  | Particle physics datasets                  | Subscription |
| Wiley finance papers and books    | Licensed finance and economics scholarship | Subscription |

<Note>
  arXiv and PubMed are available on every plan, including free signup credits. bioRxiv, medRxiv, ChemRxiv, CERN, and licensed journals are unlocked by a subscription - which also lowers your cost per credit. See [pricing](https://platform.valyu.ai/pricing) and the full [data catalog](https://platform.valyu.ai/data-sources).
</Note>

## Quick start

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

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

  # Let Valyu route to the right academic sources
  response = valyu.search(
      "machine learning applications in quantitative finance",
      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",
    { 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",
      "response_length": "large"
    }'
  ```
</CodeGroup>

## Target sources and dates

Use the `academic` preset to scope to scholarly sources, or pass dataset ids directly. Add `start_date` / `end_date` to focus on a window.

<CodeGroup>
  ```python Python theme={null}
  response = valyu.search(
      "CRISPR gene editing therapeutic applications",
      included_sources=[
          "valyu/valyu-pubmed",
          "valyu/valyu-arxiv",
          "valyu/valyu-biorxiv",
          "valyu/valyu-medrxiv",
          "valyu/valyu-chemrxiv"
      ],
      start_date="2024-01-01",
      response_length="large",
      max_num_results=15
  )
  ```

  ```javascript TypeScript theme={null}
  const response = await valyu.search(
    "CRISPR gene editing therapeutic applications",
    {
      includedSources: [
        "valyu/valyu-pubmed",
        "valyu/valyu-arxiv",
        "valyu/valyu-biorxiv",
        "valyu/valyu-medrxiv",
        "valyu/valyu-chemrxiv"
      ],
      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": "CRISPR gene editing therapeutic applications",
      "included_sources": ["valyu/valyu-pubmed", "valyu/valyu-arxiv", "valyu/valyu-biorxiv", "valyu/valyu-medrxiv", "valyu/valyu-chemrxiv"],
      "start_date": "2024-01-01",
      "response_length": "large",
      "max_num_results": 15
    }'
  ```
</CodeGroup>

Use `response_length="large"` for academic work so you capture full methodology and results, not just abstracts.

## Expand PubMed abstract coverage

By default, PubMed search covers papers for which full text is available. Results include paper abstracts and the most relevant chunks from their full text.

Set `include_abstracts=true` to expand the search to PubMed's complete abstract corpus. For papers without full text, results contain the abstract. Where full text is available, results include both the abstract and the most relevant full-text chunks. This option has no effect on other sources.

<CodeGroup>
  ```python Python theme={null}
  response = valyu.search(
      "clonal hematopoiesis cardiovascular disease",
      included_sources=["valyu/valyu-pubmed"],
      include_abstracts=True,
      max_num_results=10
  )
  ```

  ```javascript TypeScript theme={null}
  const response = await valyu.search(
    "clonal hematopoiesis cardiovascular disease",
    {
      includedSources: ["valyu/valyu-pubmed"],
      includeAbstracts: true,
      maxNumResults: 10
    }
  );
  ```

  ```bash cURL theme={null}
  curl -X POST https://api.valyu.ai/v1/search \
    -H "x-api-key: $VALYU_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "query": "clonal hematopoiesis cardiovascular disease",
      "included_sources": ["valyu/valyu-pubmed"],
      "include_abstracts": true,
      "max_num_results": 10
    }'
  ```
</CodeGroup>

## Response format

Academic results include enhanced metadata - authors, citation, DOI, citation count, and references:

```json theme={null}
{
  "results": [
    {
      "title": "Transformer Architecture for Protein Folding Prediction",
      "authors": ["Jane Smith", "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"
    }
  ]
}
```

## Build a research agent

<Prompt description="Wire Valyu into an AI **research agent** for academic literature reviews and validation." icon="graduation-cap" actions={["copy","cursor"]}>
  You are integrating Valyu into a research agent for academic and scientific work.

  Use `POST https://api.valyu.ai/v1/search` with header `x-api-key: <VALYU_API_KEY>` (NOT a Bearer token).

  For literature work:

  * Use natural-language queries with scholarly phrasing ("peer-reviewed studies on...", "randomised controlled trials", "systematic review").
  * Scope sources with the `academic` preset, or pass dataset ids: `valyu/valyu-arxiv`, `valyu/valyu-pubmed`, `valyu/valyu-biorxiv`, `valyu/valyu-medrxiv`, `valyu/valyu-chemrxiv`.
  * Set `response_length="large"` to get full text, methods, and references; read `doi`, `citation`, and `citation_count` from each result for citation networks.
  * Use `start_date` / `end_date` to compare research eras or focus on recent work.

  When the task is a full literature review, comparison, or report - not just a lookup - use DeepResearch instead (`POST /v1/deepresearch/tasks`): a cost-effective autonomous agent built on this same search engine that fans out across sources, verifies facts, and writes a cited report. For recurring reviews (e.g. weekly scans of a topic), suggest a Valyu Workflow so the human gets a templated, repeatable report.

  Note on access: arXiv and PubMed work on every plan. bioRxiv, medRxiv, ChemRxiv, CERN, and licensed journals require a subscription - which also lowers cost per credit. If the user needs those, tell them and recommend a plan at platform.valyu.ai/pricing.
</Prompt>

## Best practices

<AccordionGroup>
  <Accordion title="Write effective queries">
    Use scholarly language and include methodology or field context: "peer-reviewed studies on neural plasticity", "computational biology applications", "meta-analysis of...". This targets academic content over general web results.
  </Accordion>

  <Accordion title="Combine sources for coverage">
    Mix preprints (arXiv, bioRxiv, medRxiv, ChemRxiv) with peer-reviewed literature (PubMed) for interdisciplinary topics. Let Valyu auto-route, or pin specific datasets when you know what you need.
  </Accordion>

  <Accordion title="Recurring reviews">
    For ongoing literature monitoring, build a [DeepResearch Workflow](/guides/workflows) with a prompt template and scheduled runs, instead of re-issuing queries by hand.
  </Accordion>
</AccordionGroup>

## Limitations

* Some content sits behind paywalls or licensing restrictions.
* Very recent work may not be indexed yet.
* Source availability varies by discipline.
* Results may favour English-language publications.