### Retrieve Paper Details by arXiv ID

Source: https://ai4scholar.net/apidoc.md

Fetch detailed information for a paper using its arXiv ID. This example retrieves the title, abstract, authors, year, citation count, and TLDR. Replace YOUR_API_KEY with your actual API key.

```bash
curl "https://ai4scholar.net/graph/v1/paper/ARXIV:2106.15928?fields=title,abstract,authors,year,citationCount,tldr" \
  -H "x-api-key: YOUR_API_KEY"
```

--------------------------------

### Get Recommendations Based on Positive and Negative Samples

Source: https://ai4scholar.net/apidoc.md

Generate paper recommendations based on a list of positively and negatively sampled paper IDs. You can control the number of recommendations and the fields returned.

```bash
curl -X POST "https://ai4scholar.net/recommendations/v1/papers/?fields=title,year,authors&limit=10" \
  -H "x-api-key: YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"positivePaperIds":["649def34f8be52c8b66281af98ae884c09aef38b"],"negativePaperIds":["ArXiv:1805.02262"]}'
```

--------------------------------

### Recommendations based on Positive/Negative Samples

Source: https://ai4scholar.net/apidoc.md

Get paper recommendations based on provided positive and negative paper IDs.

```APIDOC
## POST /recommendations/v1/papers/

### Description
Generate paper recommendations based on a list of positive and optionally negative paper IDs.

### Method
POST

### Endpoint
/recommendations/v1/papers/

### Parameters
#### Query Parameters
- **limit** (integer) - Optional - The maximum number of recommendations to return (default: 100, max: 500).
- **fields** (string) - Optional - Specifies the fields to return for each recommended paper (e.g., `paperId,title`).

#### Request Body
- **positivePaperIds** (string[]) - Required - A list of paper IDs that are considered positive examples.
- **negativePaperIds** (string[]) - Optional - A list of paper IDs that are considered negative examples.

### Request Example
```bash
curl -X POST "https://ai4scholar.net/recommendations/v1/papers/?fields=title,year,authors&limit=10" \
  -H "x-api-key: YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"positivePaperIds":["649def34f8be52c8b66281af98ae884c09aef38b"],"negativePaperIds":["ArXiv:1805.02262"]}'
```
```

--------------------------------

### Dataset Download URL

Source: https://ai4scholar.net/apidoc.md

Get a pre-signed URL to download a specific dataset.

```APIDOC
## GET /datasets/v1/release/{release_id}/dataset/{dataset_name}

### Description
Obtain a pre-signed URL for downloading a specific dataset from a given release version.

### Method
GET

### Endpoint
/datasets/v1/release/{release_id}/dataset/{dataset_name}

### Parameters
#### Path Parameters
- **release_id** (string) - Required - The ID of the release version.
- **dataset_name** (string) - Required - The name of the dataset.
```

--------------------------------

### Batch Get Author Details

Source: https://ai4scholar.net/apidoc.md

Retrieve details for up to 1000 authors simultaneously using their IDs. You can specify the fields to be returned.

```bash
curl -X POST "https://ai4scholar.net/graph/v1/author/batch?fields=name,hIndex,citationCount" \
  -H "x-api-key: YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"ids":["1741101","1780531"]}'
```

--------------------------------

### Get Paper Details with curl

Source: https://ai4scholar.net/apidoc.md

Retrieve detailed information about a specific paper using its identifier (DOI, arXiv ID, PMID, etc.). Replace YOUR_API_KEY with your actual API key.

```bash
curl "https://ai4scholar.net/graph/v1/paper/DOI:10.1038/s41586-020-2008-3?fields=title,abstract,authors" \
  -H "x-api-key: YOUR_API_KEY"
```

--------------------------------

### Recommendations for a Single Paper

Source: https://ai4scholar.net/apidoc.md

Get paper recommendations based on a single paper.

```APIDOC
## GET /recommendations/v1/papers/forpaper/{paper_id}

### Description
Get paper recommendations similar to a given paper.

### Method
GET

### Endpoint
/recommendations/v1/papers/forpaper/{paper_id}

### Parameters
#### Path Parameters
- **paper_id** (string) - Required - The ID of the paper for which to get recommendations.

#### Query Parameters
- **from** (string) - Optional - The pool of papers to recommend from (`recent` or `all-cs`, default: `recent`).
- **limit** (integer) - Optional - The maximum number of recommendations to return (default: 100, max: 500).
- **fields** (string) - Optional - Specifies the fields to return for each recommended paper (e.g., `paperId,title`).
```

--------------------------------

### Batch Get Paper Details

Source: https://ai4scholar.net/apidoc.md

Retrieve details for up to 500 papers at once by providing a list of paper IDs. Supports various ID formats.

```bash
curl -X POST "https://ai4scholar.net/graph/v1/paper/batch?fields=title,year,authors" \
  -H "x-api-key: YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"ids":["649def34f8be52c8b66281af98ae884c09aef38b","ARXIV:2106.15928"]}'
```

--------------------------------

### Category List

Source: https://ai4scholar.net/apidoc.md

Get a list of journal categories with sorting options.

```APIDOC
## GET /jcr/v1/categories

### Description
Retrieves a list of journal categories.

### Method
GET

### Endpoint
/jcr/v1/categories

### Parameters
#### Query Parameters
- **sort** (string) - Optional - Sorting order: `journal_count_desc`, `avg_if_desc`, `name_asc`, etc.
- **limit** (integer) - Optional - Number of results to return, 0 means all, defaults to 0

### Response
(Response details not provided in the source text)
```

--------------------------------

### Dataset Incremental Diffs

Source: https://ai4scholar.net/apidoc.md

Get incremental updates for a dataset between two release versions.

```APIDOC
## GET /datasets/v1/diffs/{start_release_id}/to/{end_release_id}/{dataset_name}

### Description
Retrieve incremental changes for a specific dataset between two specified release versions.

### Method
GET

### Endpoint
/datasets/v1/diffs/{start_release_id}/to/{end_release_id}/{dataset_name}

### Parameters
#### Path Parameters
- **start_release_id** (string) - Required - The ID of the starting release version.
- **end_release_id** (string) - Required - The ID of the ending release version.
- **dataset_name** (string) - Required - The name of the dataset.
```

--------------------------------

### Paper Authors List

Source: https://ai4scholar.net/apidoc.md

Get a list of authors for a specific paper.

```APIDOC
## GET /graph/v1/paper/{paper_id}/authors

### Description
Retrieve a list of authors associated with a specific paper.

### Method
GET

### Endpoint
/graph/v1/paper/{paper_id}/authors

### Parameters
#### Path Parameters
- **paper_id** (string) - Required - The ID of the paper.

#### Query Parameters
- **fields** (string) - Optional - Specifies the fields to return for each author (e.g., `affiliations,papers.title`).
- **offset** (integer) - Optional - The number of results to skip (default: 0).
- **limit** (integer) - Optional - The maximum number of results to return (default: 100, max: 1000).
```

--------------------------------

### Smart Image Generation with Nano Banana API

Source: https://ai4scholar.net/apidoc.md

Use the 'smart' action for intelligent image generation based on a prompt. Specify the model, image size, and language for customized output. Requires an API Key for authentication.

```bash
curl -X POST "https://ai4scholar.net/api/proxy/nano/generate" \
  -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"action":"smart","prompt":"PI3K-AKT-mTOR signaling pathway","model":"flash","imageSize":"2K","lang":"en"}'
```

--------------------------------

### Nano Banana Image Generation

Source: https://ai4scholar.net/apidoc.md

This endpoint allows users to generate, edit, style, compose, iterate, critique, or vectorize images using various AI models. Authentication is required via an API Key.

```APIDOC
## POST /api/proxy/nano/generate

### Description
Generates, edits, styles, composes, iterates, critiques, or vectorizes images using AI models. Requires `Authorization` header with an API Key.

### Method
POST

### Endpoint
`/api/proxy/nano/generate`

### Parameters
#### Query Parameters
- **action** (string) - Required - Specifies the operation: `smart`, `generate`, `edit`, `style`, `compose`, `iterate`, `critic`, `vectorize`.
- **prompt** (string) - Conditional - Image description. Not required for `critic` or `vectorize` actions.
- **model** (string) - Optional - AI model to use. Defaults to `flash`. Options: `flash`, `flash31`, `pro`, `gptimage`.
- **imageSize** (string) - Optional - Desired image resolution. Defaults to `2K`. Options: `512px`, `1K`, `2K`, `4K`.
- **aspectRatio** (string) - Optional - Aspect ratio of the image. Defaults to `1:1`. Examples: `1:1`, `16:9`, `9:16`, `4:3`, `3:4`, `3:2`, `2:3`.
- **images** (string[]) - Optional - URLs of reference images. Used for `edit`, `style`, `compose`, `iterate`, `critic`, `vectorize` actions.
- **stylePreset** (string) - Optional - A predefined style to apply to the image. Examples: `biorender`, `nature`, `textbook`, `threed`, `infograph`, `schematic`, `electron`.
- **lang** (string) - Optional - Language for the `smart` mode. Defaults to `en`. Options: `en`, `zh`.
- **vectorizeMode** (string) - Optional - Mode for vector conversion. Defaults to `fast`. Options: `fast`, `standard`, `premium`.

### Request Example
```json
{
  "action": "smart",
  "prompt": "PI3K-AKT-mTOR signaling pathway",
  "model": "flash",
  "imageSize": "2K",
  "lang": "en"
}
```

### Response
#### Success Response (200)
- **success** (boolean) - Indicates if the operation was successful.
- **imageUrl** (string) - URL of the generated or processed image.
- **optimizedPrompt** (string) - The optimized prompt used for generation.
- **creditCost** (integer) - The cost in credits for the operation.

For `vectorize` action, additional fields `pdfUrl` and `pptxUrl` are included.

#### Response Example
```json
{
  "success": true,
  "imageUrl": "https://...",
  "optimizedPrompt": "...",
  "creditCost": 3
}
```
```

--------------------------------

### Vectorize Image with Nano Banana API

Source: https://ai4scholar.net/apidoc.md

Convert an image to a vector format using the 'vectorize' action. This is useful for creating scalable diagrams. Specify the image URL and the desired vectorization mode. Requires an API Key for authentication.

```bash
curl -X POST "https://ai4scholar.net/api/proxy/nano/generate" \
  -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"action":"vectorize","images":["https://example.com/diagram.png"],"vectorizeMode":"standard"}'
```

--------------------------------

### Recommend Journals Based on Paper Details

Source: https://ai4scholar.net/apidoc.md

Submit a paper's title and abstract to receive journal recommendations. You can specify filters like impact factor, JCR quartiles, and categories. Authentication with your API key is necessary.

```bash
curl -X POST "https://ai4scholar.net/jrec/v1/recommend" \
  -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"title":"Deep Learning for Medical Image Analysis","abstract":"This paper proposes...","top_n":5,"filters":{"min_impact_factor":3,"jcr_quartiles":["Q1","Q2"]}}'
```

--------------------------------

### Search Patents with Specific Criteria

Source: https://ai4scholar.net/apidoc.md

Use this endpoint to search for patents using keywords, country, status, and sorting preferences. Ensure your API key is included in the Authorization header.

```bash
curl -X POST "https://ai4scholar.net/google-scholar/v1/patents" \
  -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"query":"artificial intelligence","country":"US,CN","status":"GRANT","sort":"new"}'
```

--------------------------------

### Search Papers with curl

Source: https://ai4scholar.net/apidoc.md

Use this command to search for papers using keywords and specify fields, limits, and other parameters. Replace YOUR_API_KEY with your actual API key.

```bash
curl "https://ai4scholar.net/graph/v1/paper/search?query=CRISPR&fields=title,year,authors&limit=5" \
  -H "x-api-key: YOUR_API_KEY"
```

--------------------------------

### Dataset Release Details

Source: https://ai4scholar.net/apidoc.md

Retrieve a list of datasets for a specific release version.

```APIDOC
## GET /datasets/v1/release/{release_id}

### Description
Get a list of datasets available within a specific release version.

### Method
GET

### Endpoint
/datasets/v1/release/{release_id}

### Parameters
#### Path Parameters
- **release_id** (string) - Required - The ID of the release version.
```

--------------------------------

### Dataset Release Versions

Source: https://ai4scholar.net/apidoc.md

Retrieve a list of all available dataset release versions.

```APIDOC
## GET /datasets/v1/release/

### Description
Get a list of all available dataset release versions.

### Method
GET

### Endpoint
/datasets/v1/release/
```

--------------------------------

### Scientific Graph Generation with curl

Source: https://ai4scholar.net/apidoc.md

Generate scientific graphs using a POST request with form data. Specify the action, prompt, and model. Replace YOUR_API_KEY with your actual API key.

```bash
curl -X POST "https://ai4scholar.net/api/proxy/nano/generate" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "action=smart" -F "prompt=PI3K-AKT-mTOR signaling pathway" -F "model=flash"
```

--------------------------------

### Search for Authors

Source: https://ai4scholar.net/apidoc.md

Search for authors by name. You can specify which fields to return and control the pagination.

```bash
curl "https://ai4scholar.net/graph/v1/author/search?query=Yoshua+Bengio&fields=name,affiliations,hIndex,paperCount&limit=5" \
  -H "x-api-key: YOUR_API_KEY"
```

--------------------------------

### Paper Autocomplete

Source: https://ai4scholar.net/apidoc.md

Provides autocomplete suggestions for paper titles based on a partial query string.

```APIDOC
## GET /graph/v1/paper/autocomplete

### Description
Provides autocomplete suggestions for paper titles based on a partial query string. The query is truncated to the first 100 characters. Returns a `matches` array, where each item contains `id`, `title`, and `authorsYear`.

### Method
GET

### Endpoint
/graph/v1/paper/autocomplete

### Parameters
#### Query Parameters
- **query** (string) - Required - Partial query string for autocomplete suggestions.
```

--------------------------------

### Scientific Plotting (Nano API Proxy)

Source: https://ai4scholar.net/apidoc.md

Generates scientific plots via a proxy to the Nano API. This POST request accepts form data for the action, prompt, and model.

```APIDOC
## POST /api/proxy/nano/generate

### Description
Generates scientific plots via a proxy to the Nano API. This POST request accepts form data for the action, prompt, and model.

### Method
POST

### Endpoint
/api/proxy/nano/generate

### Parameters
#### Form Data
- **action** (string) - Required - The action to perform (e.g., `smart`).
- **prompt** (string) - Required - The prompt describing the scientific concept for the plot (e.g., `PI3K-AKT-mTOR signaling pathway`).
- **model** (string) - Optional - The model to use for generation (e.g., `flash`).

### Request Example (curl)
```bash
curl -X POST "https://ai4scholar.net/api/proxy/nano/generate" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "action=smart" -F "prompt=PI3K-AKT-mTOR signaling pathway" -F "model=flash"
```
```

--------------------------------

### Successful API Response for Nano Banana

Source: https://ai4scholar.net/apidoc.md

A successful response from the Nano Banana API typically includes a success status, the generated image URL, an optimized prompt, and the credit cost. For vectorization, PDF and PPTX URLs are also provided.

```json
{
  "success": true,
  "imageUrl": "https://...",
  "optimizedPrompt": "...",
  "creditCost": 3
}
```

--------------------------------

### Automatically Cite References in Text

Source: https://ai4scholar.net/apidoc.md

This endpoint processes academic text to automatically identify and cite references. It supports various citation styles and allows for manual citation marking. The API key is required, and the response is streamed via Server-Sent Events.

```bash
curl -N -X POST "https://ai4scholar.net/api/proxy/auto-cite" \
  -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"text":"Deep learning has revolutionized many fields...","mode":"auto","minCitations":5,"citationStyle":"ieee"}'
```

--------------------------------

### Query Journals by Category and Impact Factor

Source: https://ai4scholar.net/apidoc.md

Retrieve a list of journals filtered by category, JCR quartile, and minimum impact factor. The API key is required for authentication.

```bash
curl "https://ai4scholar.net/jcr/v1/journals?category=Oncology&jcr_quartile=Q1&min_if=5&limit=10" \
  -H "Authorization: Bearer YOUR_API_KEY"
```

--------------------------------

### Batch Paper Details

Source: https://ai4scholar.net/apidoc.md

Retrieve details for multiple papers at once. Supports up to 500 papers per request.

```APIDOC
## POST /graph/v1/paper/batch

### Description
Retrieve details for multiple papers at once. Supports up to 500 papers per request.

### Method
POST

### Endpoint
/graph/v1/paper/batch

### Parameters
#### Query Parameters
- **fields** (string) - Optional - Specifies the fields to return.

#### Request Body
- **ids** (string[]) - Required - An array of paper IDs in various supported formats.

### Request Example
```bash
curl -X POST "https://ai4scholar.net/graph/v1/paper/batch?fields=title,year,authors" \
  -H "x-api-key: YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"ids":["649def34f8be52c8b66281af98ae884c09aef38b","ARXIV:2106.15928"]}'
```
```

--------------------------------

### Batch Author Details

Source: https://ai4scholar.net/apidoc.md

Retrieve details for multiple authors at once. Supports up to 1000 authors per request.

```APIDOC
## POST /graph/v1/author/batch

### Description
Retrieve details for multiple authors simultaneously. Supports up to 1000 authors per request.

### Method
POST

### Endpoint
/graph/v1/author/batch

### Parameters
#### Query Parameters
- **fields** (string) - Optional - Specifies the fields to return for each author (e.g., `name,hIndex,citationCount,papers.title`).

#### Request Body
- **ids** (string[]) - Required - An array of author IDs.

### Request Example
```bash
curl -X POST "https://ai4scholar.net/graph/v1/author/batch?fields=name,hIndex,citationCount" \
  -H "x-api-key: YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"ids":["1741101","1780531"]}'
```
```

--------------------------------

### Paper Bulk Search

Source: https://ai4scholar.net/apidoc.md

Performs a bulk search for papers using advanced query syntax. Supports pagination via a token and filtering by various criteria.

```APIDOC
## GET /graph/v1/paper/search/bulk

### Description
Performs a bulk search for papers using advanced query syntax. Supports pagination via a token and filtering by various criteria. Each request can return up to 1000 papers, and up to 10,000,000 papers can be retrieved using the token for pagination. Does not support nested citation or reference data.

### Method
GET

### Endpoint
/graph/v1/paper/search/bulk

### Parameters
#### Query Parameters
- **query** (string) - Required - Search query supporting boolean operators: `+` AND, `|` OR, `-` NOT, `""` phrase, `*` prefix, `~N` fuzzy matching.
- **token** (string) - Optional - Pagination token obtained from a previous response.
- **fields** (string) - Optional - Comma-separated list of fields to return (e.g., `paperId,title`).
- **sort** (string) - Optional - Field to sort by (e.g., `citationCount:desc`).
- **publicationTypes** (string) - Optional - Publication types (e.g., `Review,JournalArticle`).
- **openAccessPdf** (string) - Optional - Filter for papers with open access PDFs.
- **minCitationCount** (string) - Optional - Minimum citation count.
- **publicationDateOrYear** (string) - Optional - Date range (e.g., `2020-01-01:2024-12-31`).
- **year** (string) - Optional - Year range (e.g., `2020-2024`).
- **venue** (string) - Optional - Journal or conference name (e.g., `Nature,Science`).
- **fieldsOfStudy** (string) - Optional - Fields of study (e.g., `Computer Science,Medicine`).
```

--------------------------------

### Google Scholar Search with curl

Source: https://ai4scholar.net/apidoc.md

Search Google Scholar using a POST request. You can specify the query, page number, and year range. Replace YOUR_API_KEY with your actual API key.

```bash
curl -X POST "https://ai4scholar.net/google-scholar/v1/search" \
  -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"query":"deep learning","page":1,"yearFrom":2023}'
```

--------------------------------

### Patent Search

Source: https://ai4scholar.net/apidoc.md

Search for patents using various criteria such as keywords, status, country, and dates.

```APIDOC
## POST /google-scholar/v1/patents

### Description
Searches for patents based on a given query and various filters.

### Method
POST

### Endpoint
/google-scholar/v1/patents

### Parameters
#### Query Parameters
- **query** (string) - Required - Search keywords, supports boolean syntax like `(Coffee) OR (Tea)`
- **page** (integer) - Optional - Page number, defaults to 1
- **num** (integer) - Optional - Number of items per page, maximum 100, defaults to 10
- **sort** (string) - Optional - Sorting order: `new` (latest) or `old` (earliest)
- **status** (string) - Optional - Patent status: `GRANT` (granted) or `APPLICATION` (in progress)
- **type** (string) - Optional - Patent type: `PATENT` (invention) or `DESIGN` (design)
- **country** (string) - Optional - Comma-separated country codes, e.g., `US,CN,WO`
- **language** (string) - Optional - Comma-separated languages, e.g., `ENGLISH,CHINESE`
- **inventor** (string) - Optional - Comma-separated inventor names
- **assignee** (string) - Optional - Comma-separated assignee/company names
- **before** (string) - Optional - Deadline date, format `type:YYYYMMDD`, e.g., `publication:20231231`
- **after** (string) - Optional - Start date, format `type:YYYYMMDD`, e.g., `filing:20200101`

### Request Example
```json
{
  "query": "artificial intelligence",
  "country": "US,CN",
  "status": "GRANT",
  "sort": "new"
}
```

### Response
(Response details not provided in the source text)
```

--------------------------------

### Auto-Cite

Source: https://ai4scholar.net/apidoc.md

Automatically cite academic literature within a given text.

```APIDOC
## POST /api/proxy/auto-cite

### Description
Automatically identifies and formats citations within a given academic text. Returns results as a Server-Sent Events (SSE) stream.

### Method
POST

### Endpoint
/api/proxy/auto-cite

### Parameters
#### Request Body
- **text** (string) - Required - Academic text, between 100 and 10000 characters
- **mode** (string) - Optional - Mode of operation: `auto` (automatic citation detection) or `manual` (using `[CITE]` markers), defaults to `auto`
- **minCitations** (number) - Optional - Minimum number of citations to detect in `auto` mode, defaults to 10
- **maxReferences** (number) - Optional - Maximum number of references to return
- **preferredVenues** (string[]) - Optional - Preferred venues (journals, conferences) for citation matching, e.g., `["Nature","Science","CVPR"]`
- **field** (string) - Optional - Subject field, e.g., `computer science`
- **yearPreference** (number) - Optional - Preferred year for citation matching
- **excludePreprints** (boolean) - Optional - Whether to exclude preprints, defaults to `false`
- **excludeConferences** (boolean) - Optional - Whether to exclude conference papers, defaults to `false`
- **citationStyle** (string) - Optional - Citation style, defaults to `ieee`. Supported styles: `ieee`, `apa`, `apa6`, `nature`, `vancouver`, `mla`, `chicago`, `harvard`, `acs`, `ama`, `acm`, `turabian`, `cse`, `asce`, `gbt7714`

### Manual Mode Markers
- `[CITE]`: Automatically select a reference.
- `[CITE:keyword]`: Prompt to search for references related to a specific keyword.

### SSE Response Events
- **progress**: Progress update `{step, message, percent}`
- **result**: Final result `{annotatedText, references[], candidates}`
- **error**: Error information `{code, message}`

### Request Example
```bash
curl -N -X POST "https://ai4scholar.net/api/proxy/auto-cite" \
  -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"text":"Deep learning has revolutionized many fields...","mode":"auto","minCitations":5,"citationStyle":"ieee"}'
```
```

--------------------------------

### Paper References

Source: https://ai4scholar.net/apidoc.md

Retrieve a list of papers cited by a given paper.

```APIDOC
## GET /graph/v1/paper/{paper_id}/references

### Description
Get a list of papers that are cited by the specified paper.

### Method
GET

### Endpoint
/graph/v1/paper/{paper_id}/references

### Parameters
#### Path Parameters
- **paper_id** (string) - Required - The ID of the paper.

#### Query Parameters
- **fields** (string) - Optional - Specifies the fields to return for each cited paper (e.g., `paperId,title`).
- **offset** (integer) - Optional - The number of results to skip (default: 0).
- **limit** (integer) - Optional - The maximum number of results to return (default: 100, max: 1000).

### Response
#### Success Response (200)
- **contexts** (string) - The citation context text.
- **intents** (string) - The intent of the citation.
- **isInfluential** (boolean) - Indicates if the citation is influential.
- **citedPaper** (object) - Details of the cited paper.
```

--------------------------------

### Journal Recommendation

Source: https://ai4scholar.net/apidoc.md

Recommend journals based on a paper's title and abstract.

```APIDOC
## POST /jrec/v1/recommend

### Description
Recommends journals based on the semantic similarity of a paper's title and abstract.

### Method
POST

### Endpoint
/jrec/v1/recommend

### Parameters
#### Request Body
- **title** (string) - Required - Paper title (minimum 5 characters)
- **abstract** (string) - Optional - Paper abstract
- **top_n** (integer) - Optional - Number of recommendations to return, maximum 50, defaults to 10
- **filters** (object) - Optional - Filtering conditions for recommendations
- **fields** (array) - Optional - Fieldsets to return

#### Filters (Object)
- **min_impact_factor** (float) - Minimum impact factor
- **max_impact_factor** (float) - Maximum impact factor
- **jcr_quartiles** (array) - JCR quartiles, e.g., `["Q1","Q2"]`
- **cas_quartiles** (array) - CAS quartiles, e.g., `["1区","2区"]`
- **is_oa** (boolean) - Whether to include open access journals
- **categories** (array) - Subject category keywords

### Request Example
```json
{
  "title": "Deep Learning for Medical Image Analysis",
  "abstract": "This paper proposes...",
  "top_n": 5,
  "filters": {
    "min_impact_factor": 3,
    "jcr_quartiles": ["Q1","Q2"]
  }
}
```

### Response
(Response details not provided in the source text)
```

--------------------------------

### Author Details

Source: https://ai4scholar.net/apidoc.md

Retrieve detailed information for a specific author.

```APIDOC
## GET /graph/v1/author/{author_id}

### Description
Get detailed information about a specific author using their ID.

### Method
GET

### Endpoint
/graph/v1/author/{author_id}

### Parameters
#### Path Parameters
- **author_id** (string) - Required - The Semantic Scholar author ID.

#### Query Parameters
- **fields** (string) - Optional - Specifies the fields to return (e.g., `name,affiliations,homepage,paperCount,citationCount,hIndex,papers`).
```

--------------------------------

### Paper Citations

Source: https://ai4scholar.net/apidoc.md

Retrieve a list of papers that cite a given paper.

```APIDOC
## GET /graph/v1/paper/{paper_id}/citations

### Description
Get a list of papers that cite the specified paper.

### Method
GET

### Endpoint
/graph/v1/paper/{paper_id}/citations

### Parameters
#### Path Parameters
- **paper_id** (string) - Required - The ID of the paper.

#### Query Parameters
- **fields** (string) - Optional - Specifies the fields to return for each citing paper (e.g., `contexts,intents,isInfluential,abstract,authors`).
- **publicationDateOrYear** (string) - Optional - Filters results by publication date or year.
- **offset** (integer) - Optional - The number of results to skip (default: 0).
- **limit** (integer) - Optional - The maximum number of results to return (default: 100, max: 1000).

### Response
#### Success Response (200)
- **contexts** (string) - The citation context text.
- **intents** (string) - The intent of the citation (e.g., methodology, background, result).
- **isInfluential** (boolean) - Indicates if the citation is influential.
- **citingPaper** (object) - Details of the citing paper.
```

--------------------------------

### Search Authors

Source: https://ai4scholar.net/apidoc.md

Search for authors based on a query string.

```APIDOC
## GET /graph/v1/author/search

### Description
Search for authors by name.

### Method
GET

### Endpoint
/graph/v1/author/search

### Parameters
#### Query Parameters
- **query** (string) - Required - The author's name to search for.
- **fields** (string) - Optional - Specifies the fields to return for each author (e.g., `affiliations,hIndex,papers.title`).
- **offset** (integer) - Optional - The number of results to skip (default: 0).
- **limit** (integer) - Optional - The maximum number of results to return (default: 100, max: 1000).

### Request Example
```bash
curl "https://ai4scholar.net/graph/v1/author/search?query=Yoshua+Bengio&fields=name,affiliations,hIndex,paperCount&limit=5" \
  -H "x-api-key: YOUR_API_KEY"
```
```

--------------------------------

### Semantic Scholar Paper Search with Specific Fields

Source: https://ai4scholar.net/apidoc.md

Search for papers within Semantic Scholar, specifying the query, desired fields, year range, and limit. Replace YOUR_API_KEY with your actual API key.

```bash
curl "https://ai4scholar.net/graph/v1/paper/search?query=transformer+attention&fields=title,year,citationCount&year=2020-2024&limit=10" \
  -H "x-api-key: YOUR_API_KEY"
```

--------------------------------

### Paper Details

Source: https://ai4scholar.net/apidoc.md

Retrieves detailed information for a specific paper using its unique identifier. Supports various ID formats including SHA, CorpusId, DOI, arXiv, MAG, ACL, PubMed, PMCID, and URL.

```APIDOC
## GET /graph/v1/paper/{paper_id}

### Description
Retrieves detailed information for a specific paper using its unique identifier. Supports various ID formats including SHA, CorpusId, DOI, arXiv, MAG, ACL, PubMed, PMCID, and URL.

### Method
GET

### Endpoint
/graph/v1/paper/{paper_id}

### Parameters
#### Path Parameters
- **paper_id** (string) - Required - The unique identifier of the paper. Supported formats:
  - SHA: `649def34f8be52c8b66281af98ae884c09aef38b`
  - CorpusId: `CorpusId:215416146`
  - DOI: `DOI:10.18653/v1/N18-3011`
  - arXiv: `ARXIV:2106.15928`
  - MAG: `MAG:112218234`
  - ACL: `ACL:W12-3903`
  - PubMed: `PMID:19872477`
  - PubMed Central: `PMCID:2323736`
  - URL: `URL:https://arxiv.org/abs/2106.15928v1`

#### Query Parameters
- **fields** (string) - Optional - Comma-separated list of fields to return (e.g., `title,abstract,authors,year,citationCount,tldr`).

### Request Example
```bash
curl "https://ai4scholar.net/graph/v1/paper/ARXIV:2106.15928?fields=title,abstract,authors,year,citationCount,tldr" \
  -H "x-api-key: YOUR_API_KEY"
```
```

--------------------------------

### Text Snippet Search

Source: https://ai4scholar.net/apidoc.md

Searches for matching text snippets from the body of papers. Returns excerpts of approximately 500 words. Supports filtering by paper IDs, authors, citation count, date, year, venue, and fields of study.

```APIDOC
## GET /graph/v1/snippet/search

### Description
Returns matching text snippets from the body of papers (approximately 500-word excerpts). Supports filtering by paper IDs, authors, citation count, date, year, venue, and fields of study.

### Method
GET

### Endpoint
/graph/v1/snippet/search

### Parameters
#### Query Parameters
- **query** (string) - Required - The text to search for.
- **fields** (string) - Optional - Fields to return for the snippet, such as `snippet.text,snippet.snippetKind`.
- **paperIds** (string) - Optional - Comma-separated list of paper IDs to limit the search within.
- **authors** (string) - Optional - Comma-separated list of author names to limit the search.
- **minCitationCount** (string) - Optional - Minimum citation count.
- **publicationDateOrYear** (string) - Optional - Date range (e.g., `2020-01-01:2024-12-31`).
- **year** (string) - Optional - Year range (e.g., `2020-2024`).
- **venue** (string) - Optional - Journal or conference name (e.g., `Nature,Science`).
- **fieldsOfStudy** (string) - Optional - Fields of study (e.g., `Computer Science,Medicine`).
- **limit** (integer) - Optional - Number of results to return (max: 1000, default: 10).
```

--------------------------------

### PubMed Paper Search with curl

Source: https://ai4scholar.net/apidoc.md

Perform a search on PubMed data using a POST request. Specify the query and limit in the JSON payload. Replace YOUR_API_KEY with your actual API key.

```bash
curl -X POST "https://ai4scholar.net/pubmed/v1/paper/search" \
  -H "x-api-key: YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"query":"COVID-19 vaccine","limit":5}'
```

--------------------------------

### Author Papers

Source: https://ai4scholar.net/apidoc.md

Retrieve a list of papers authored by a specific author.

```APIDOC
## GET /graph/v1/author/{author_id}/papers

### Description
Get a list of papers written by a specific author.

### Method
GET

### Endpoint
/graph/v1/author/{author_id}/papers

### Parameters
#### Path Parameters
- **author_id** (string) - Required - The ID of the author.

#### Query Parameters
- **fields** (string) - Optional - Specifies the fields to return for each paper (e.g., `abstract,year,citations.title,references`).
- **publicationDateOrYear** (string) - Optional - Filters results by publication date or year.
- **offset** (integer) - Optional - The number of results to skip (default: 0).
- **limit** (integer) - Optional - The maximum number of results to return (default: 100, max: 1000).
```

--------------------------------

### Journal Search

Source: https://ai4scholar.net/apidoc.md

Query journals based on name, category, impact factor, and other metrics.

```APIDOC
## GET /jcr/v1/journals

### Description
Searches for journals based on various criteria including name, category, and impact factor.

### Method
GET

### Endpoint
/jcr/v1/journals

### Parameters
#### Query Parameters
- **query** (string) - Optional - Journal name fuzzy match
- **category** (string) - Optional - Subject category keyword, e.g., `Oncology`
- **jcr_quartile** (string) - Optional - JCR quartile, e.g., `Q1,Q2`
- **cas_quartile** (string) - Optional - CAS quartile, e.g., `1区,2区`
- **min_if** (float) - Optional - Minimum impact factor
- **max_if** (float) - Optional - Maximum impact factor
- **is_oa** (boolean) - Optional - Whether to include open access journals
- **sort** (string) - Optional - Sorting order: `if_desc`/`if_asc`/`name_asc`/`name_desc`, defaults to `if_desc`
- **limit** (integer) - Optional - Number of results to return, maximum 100, defaults to 20
- **offset** (integer) - Optional - Pagination offset, defaults to 0
- **fields** (string) - Optional - Fieldset to return: `basic`, `metrics`, `history`, etc.

### Request Example
```bash
curl "https://ai4scholar.net/jcr/v1/journals?category=Oncology&jcr_quartile=Q1&min_if=5&limit=10" \
  -H "Authorization: Bearer YOUR_API_KEY"
```

### Response
(Response details not provided in the source text)
```

--------------------------------

### Journal Details

Source: https://ai4scholar.net/apidoc.md

Retrieve detailed information for a specific journal using its ID.

```APIDOC
## GET /jcr/v1/journals/{id}

### Description
Retrieves detailed information for a specific journal.

### Method
GET

### Endpoint
/jcr/v1/journals/{id}

### Parameters
#### Path Parameters
- **id** (string) - Required - Journal identifier (ISSN or eISSN)

#### Query Parameters
- **fields** (string) - Optional - Fieldset to return, defaults to `all`, options include `basic`, `metrics`, `history`

### Response
(Response details not provided in the source text)
```

--------------------------------

### Google Scholar Search

Source: https://ai4scholar.net/apidoc.md

Searches for papers on Google Scholar. This is a POST request that accepts a JSON payload for the search query, including options for pagination and year range.

```APIDOC
## POST /google-scholar/v1/search

### Description
Searches for papers on Google Scholar. This is a POST request that accepts a JSON payload for the search query, including options for pagination and year range.

### Method
POST

### Endpoint
/google-scholar/v1/search

### Parameters
#### Request Body
- **query** (string) - Required - The search query for Google Scholar.
- **page** (integer) - Optional - The page number for search results (default: 1).
- **yearFrom** (integer) - Optional - The starting year for the search.

### Request Example
```json
{
  "query": "deep learning",
  "page": 1,
  "yearFrom": 2023
}
```

### Request Example (curl)
```bash
curl -X POST "https://ai4scholar.net/google-scholar/v1/search" \
  -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" \
  -d '{"query":"deep learning","page":1,"yearFrom":2023}'
```
```

--------------------------------

### Paper Relevance Search

Source: https://ai4scholar.net/apidoc.md

Searches for papers based on relevance to a given query. Supports filtering by publication type, open access status, citation count, publication date, year, venue, and fields of study.

```APIDOC
## GET /graph/v1/paper/search

### Description
Searches for papers based on relevance to a given query. Supports filtering by publication type, open access status, citation count, publication date, year, venue, and fields of study.

### Method
GET

### Endpoint
/graph/v1/paper/search

### Parameters
#### Query Parameters
- **query** (string) - Required - Search keywords
- **fields** (string) - Optional - Comma-separated list of fields to return (e.g., `paperId,title`)
- **publicationTypes** (string) - Optional - Publication types (e.g., `Review,JournalArticle,Conference,ClinicalTrial`)
- **openAccessPdf** (-) - Optional - Filter for papers with open access PDFs
- **minCitationCount** (string) - Optional - Minimum citation count
- **publicationDateOrYear** (string) - Optional - Date range (e.g., `2020-01-01:2024-12-31`)
- **year** (string) - Optional - Year range (e.g., `2020-2024`)
- **venue** (string) - Optional - Journal or conference name (e.g., `Nature,Science`)
- **fieldsOfStudy** (string) - Optional - Fields of study (e.g., `Computer Science,Medicine,Biology`)
- **offset** (integer) - Optional - Pagination offset (default: 0)
- **limit** (integer) - Optional - Number of results to return (max: 100, default: 100)

### Request Example
```bash
curl "https://ai4scholar.net/graph/v1/paper/search?query=transformer+attention&fields=title,year,citationCount&year=2020-2024&limit=10" \
  -H "x-api-key: YOUR_API_KEY"
```
```

--------------------------------

### Paper Title Search

Source: https://ai4scholar.net/apidoc.md

Searches for a single paper whose title best matches the provided query. Supports filtering by publication type, open access status, citation count, date, year, venue, and fields of study.

```APIDOC
## GET /graph/v1/paper/search/match

### Description
Returns the single paper whose title best matches the provided query. Supports filtering by publication type, open access status, citation count, date, year, venue, and fields of study.

### Method
GET

### Endpoint
/graph/v1/paper/search/match

### Parameters
#### Query Parameters
- **query** (string) - Required - The paper title to search for.
- **fields** (string) - Optional - Comma-separated list of fields to return.
- **publicationTypes** (string) - Optional - Publication types (e.g., `Review,JournalArticle`).
- **openAccessPdf** (string) - Optional - Filter for papers with open access PDFs.
- **minCitationCount** (string) - Optional - Minimum citation count.
- **publicationDateOrYear** (string) - Optional - Date range (e.g., `2020-01-01:2024-12-31`).
- **year** (string) - Optional - Year range (e.g., `2020-2024`).
- **venue** (string) - Optional - Journal or conference name (e.g., `Nature,Science`).
- **fieldsOfStudy** (string) - Optional - Fields of study (e.g., `Computer Science,Medicine`).
```