Google Patents Details API Documentation

The Google Patents Details API, accessible via the /api/v1/search?engine=google_patents_details endpoint, provides data on patents in a structured JSON format. This API enables the retrieval of detailed information on patents, including publication numbers, application numbers, inventors, assignees, classifications, and patent events, among others.

The API can be utilized for a variety of purposes, such as:

  • Retrieving detailed information on specific patents by publication number or application number.
  • Exploring patent classifications to understand the technological fields of inventions.
  • Monitoring patent legal events and status changes over time.
  • Accessing patent citations and similar documents for research and analysis.

API Parameters

Search Query

  • Name
    patent_id
    Required
    Required
    Description

    Parameter defines the patent or scholar id. For example: patent/US20240003950A1/en or scholar/5943115021336935230. Ids can be found in the URL of the Google Patents (https://patents.google.com/patent_id?) or in the Google Patents API response.

Engine

  • Name
    engine
    Required
    Required
    Description

    Parameter defines an engine that will be used to retrieve real-time data. It must be set to google_patents_details.

API key

  • Name
    api_key
    Required
    Required
    Description

    The api_key authenticates your requests. Use it as a query parameter (https://www.searchapi.io/api/v1/search?api_key=YOUR_API_KEY) or in the Authorization header (Bearer YOUR_API_KEY).

API Examples

Patent

Patent
GET
https://www.searchapi.io/api/v1/search?engine=google_patents_details&patent_id=patent%2FCN116401354A%2Fen
Request
import requests

url = "https://www.searchapi.io/api/v1/search"
params = {
  "engine": "google_patents_details",
  "patent_id": "patent/CN116401354A/en"
}

response = requests.get(url, params=params)
print(response.text)
Response
{
  "search_metadata": {
    "id": "search_8qWVwGvboYPYTGAgmDQJaN4d",
    "status": "Success",
    "created_at": "2024-02-27T13:30:10Z",
    "request_time_taken": 1.69,
    "parsing_time_taken": 0.09,
    "total_time_taken": 1.78,
    "request_url": "https://patents.google.com/patent/CN116401354A/en",
    "html_url": "http://www.seachapi.io/api/v1/searches/search_8qWVwGvboYPYTGAgmDQJaN4d.html",
    "json_url": "http://www.seachapi.io/api/v1/searches/search_8qWVwGvboYPYTGAgmDQJaN4d"
  },
  "search_parameters": {
    "engine": "google_patents_details",
    "patent_id": "patent/CN116401354A/en"
  },
  "title": "Text processing method, device, storage medium and equipment",
  "type": "patent",
  "pdf": "https://patentimages.storage.googleapis.com/9e/e5/6f/d5646159d5b3b3/CN116401354A.pdf",
  "publication_number": "CN116401354A",
  "country": "China",
  "prior_art_keywords": [
    "text",
    "target",
    "information",
    "question",
    "target problem"
  ],
  "prior_art_date": "2023-04-28",
  "application_number": "CN202310491406.3A",
  "inventors": [
    {
      "name": "刘权",
      "link": "https://patents.google.com/?inventor=刘权"
    },
    ...
  ],
  "assignees": ["iFlytek Co Ltd"],
  "priority_date": "2023-04-28",
  "filing_date": "2023-04-28",
  "publication_date": "2023-07-07",
  "worldwide_applications": [
    {
      "year": "2023",
      "applications": [
        {
          "filing_date": "2023-04-28",
          "country_code": "CN",
          "application_number": "CN202310491406.3A",
          "document_id": "patent/CN116401354A/en",
          "legal_status_cat": "active",
          "legal_status": "Pending",
          "link": "https://patents.google.com/patent/CN116401354A/en"
        }
      ]
    }
  ],
  "events": [
    {
      "date": "2023-04-28",
      "title": "Application filed by iFlytek Co Ltd",
      "type": "filed",
      "critical": true,
      "assignee_search": "iFlytek Co Ltd"
    },
    ...
  ],
  "external_links": [
    {
      "text": "Espacenet",
      "link": "https://worldwide.espacenet.com/publicationDetails/biblio?CC=CN&NR=116401354A&KC=A&FT=D"
    },
    ...
  ],
  "images": [
    "https://patentimages.storage.googleapis.com/ba/4b/56/4ea26c2212a550/HDA0004210520700000011.png",
    "https://patentimages.storage.googleapis.com/02/15/4d/c64a612b857baa/HDA0004210520700000021.png"
  ],
  "classifications": [
    {
      "code": "G06F16/3329",
      "description": "Natural language query formulation or dialogue systems",
      "leaf": true,
      "first_code": true
    },
    ...
  ],
  "abstract": "Abstract The application discloses a text processing method, a text processing device, a storage medium and a text processing device, wherein the method comprises the following steps: firstly, acquiring a target question text to be answered, which is input by a target user; then calculating the definition of the target problem text, and judging whether the definition is not lower than a preset threshold value; if yes, directly generating a reply text; if not, carrying out importance analysis processing on the target problem text, carrying out information supplementation on the target problem text according to an analysis result, taking the target problem text after information supplementation as the target problem text again, repeatedly and iteratively executing the steps of calculating the definition and follow-up steps of the target problem text until a preset stopping condition is reached, taking the target problem text after information supplementation obtained at the moment as a final target problem text, thereby being capable of more accurately identifying the real intention of a target user based on the final target problem text, further generating reply information really wanted by the target user and improving the interactive experience of the target user.",
  "description": "Description Text processing method, device, storage medium and equipment Technical Field The present disclosure relates to the field of natural language processing technologies, and in particular, to a text processing method, a device, a storage medium, and a device. Background With the rapid development of information technologies such as artificial intelligence and the Internet of things, application scenes of human-computer interaction are wider and wider. Various intelligent interaction software and devices appear in life and work of people, such as chat generation pretraining converters (Chat Generative Pre-trained Transformer, chatGPT for short), intelligent sound boxes, intelligent televisions and the like, and can provide intelligent interaction functions of numerous application scenes such as information inquiry and the like for people so as to assist users to complete various behavior intentions. At present, aiming at voice or text information input by a user into intelligent interaction software or equipment...",
  "claims": [
    "1. A text processing method, comprising: acquiring a target question text to be answered, which is input by a target user; calculating the definition of the target problem text, and judging whether the definition is not lower than a preset threshold value; if yes, generating a reply text according to the target question text; if not, carrying out importance analysis processing on the target problem text, and carrying out information supplementation on the target problem text according to an analysis result to obtain an information-supplemented target problem text; and taking the target problem text after the information supplementation as a target problem text again, repeatedly and iteratively executing the steps of calculating the definition of the target problem text and the follow-up steps until a preset stop condition is reached, and taking the target problem text after the information supplementation obtained after the iteration when the preset stop condition is reached as a final target problem text so as to generate a final reply text according to the final target problem text.",
    "2. The method of claim 1, wherein said calculating the clarity of the target question text comprises: preprocessing the target problem text by using a preset prompt word, inputting the preprocessed target problem text into a pre-constructed large voice model LLM, and predicting the definition of the target problem text; The large voice model LLM is obtained by utilizing a large-scale language data set and performing language rules and mode training in an autoregressive generation mode, and when new text data are generated, the possibility of the next language unit is predicted based on the content which is generated before until complete text data are generated.",
    ...
  ],
  "priority_applications": [
    {
      "application_number": "CN202310491406.3A",
      "representative_publication": "CN116401354A",
      "primary_language": "en",
      "priority_date": "2023-04-28",
      "filing_date": "2023-04-28",
      "title": "Text processing method, device, storage medium and equipment",
      "link": "https://patents.google.com//patent/CN116401354A/en"
    }
  ],
  "applications_claiming_priority": [
    {
      "application_number": "CN202310491406.3A",
      "representative_publication": "CN116401354A",
      "primary_language": "en",
      "priority_date": "2023-04-28",
      "filing_date": "2023-04-28",
      "title": "Text processing method, device, storage medium and equipment",
      "link": "https://patents.google.com//patent/CN116401354A/en"
    }
  ],
  "cited_by": {
    "family_to_family": [
      {
        "publication_number": "CN117034958A",
        "primary_language": "en",
        "examiner_cited": "*",
        "priority_date": "2023-07-21",
        "publication_date": "2023-11-10",
        "assignee_original": "南京领行科技股份有限公司",
        "title": "User intention recognition method, reply generation method and server",
        "patent_id": "patent/CN117034958A/en",
        "link": "https://patents.google.com/patent/CN117034958A/en"
      },
      ...
    ]
  },
  "similar_documents": [
    {
      "is_patent": true,
      "publication_number": "CN108536802B",
      "primary_language": "en",
      "publication_date": "2020-01-14",
      "title": "Interaction method and device based on child emotion",
      "patent_id": "patent/CN108536802B/en",
      "link": "https://patents.google.com/patent/CN108536802B/en"
    },
    ...
  ],
  "legal_events": [
    {
      "date": "2023-07-07",
      "code": "PB01",
      "title": "Publication"
    },
    ...
  ]
}

Scholar

Scholar
GET
https://www.searchapi.io/api/v1/search?engine=google_patents_details&patent_id=scholar%2F5943115021336935230
Request
import requests

url = "https://www.searchapi.io/api/v1/search"
params = {
  "engine": "google_patents_details",
  "patent_id": "scholar/5943115021336935230"
}

response = requests.get(url, params=params)
print(response.text)
Response
{
  "search_metadata": {
    "id": "search_vxbn58j7pJdLFkjoDeN0V2da",
    "status": "Success",
    "created_at": "2024-02-27T13:38:42Z",
    "request_time_taken": 1.59,
    "parsing_time_taken": 0.07,
    "total_time_taken": 1.66,
    "request_url": "https://patents.google.com/scholar/5943115021336935230",
    "html_url": "http://www.seachapi.io/api/v1/searches/search_vxbn58j7pJdLFkjoDeN0V2da.html",
    "json_url": "http://www.seachapi.io/api/v1/searches/search_vxbn58j7pJdLFkjoDeN0V2da"
  },
  "search_parameters": {
    "engine": "google_patents_details",
    "patent_id": "scholar/5943115021336935230"
  },
  "title": "Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models",
  "type": "scholar",
  "publication_year": "2023",
  "publication_venue": "PLoS digital health",
  "full_view_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000198&fbclid=IwAR3U9R0A5QwAVMACFfgA79EFYWu32uFE8upittW5ZEb9qaNSZyWXpxdnJU4",
  "cited_by_url": "https://scholar.google.com/scholar?cites=5943115021336935230&hl=en",
  "main_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000198&fbclid=IwAR3U9R0A5QwAVMACFfgA79EFYWu32uFE8upittW5ZEb9qaNSZyWXpxdnJU4",
  "other_versions_url": "https://scholar.google.com/scholar?cluster=5943115021336935230&hl=en",
  "publication_date": "2023",
  "classifications": [
    {
      "code": "G06F19/345",
      "description": "Medical expert systems, neural networks or other automated diagnosis",
      "leaf": true
    },
    ...
  ],
  "snippet": "Snippet We evaluated the performance of a large language model called ChatGPT on the United States Medical Licensing Exam (USMLE), which consists of three exams: Step 1, Step 2CK, and Step 3. ChatGPT performed at or near the passing threshold for all three exams without …",
  "similar_documents": [
    {
      "publication_date": "2023",
      "title": "Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models",
      "patent_id": "scholar/5943115021336935230",
      "link": "https://patents.google.com/scholar/5943115021336935230"
    },
    ...
  ]
}

Concepts

Concepts
GET
https://www.searchapi.io/api/v1/search?engine=google_patents_details&patent_id=patent%2FUS3807170A%2Fen
Request
import requests

url = "https://www.searchapi.io/api/v1/search"
params = {
  "engine": "google_patents_details",
  "patent_id": "patent/US3807170A/en"
}

response = requests.get(url, params=params)
print(response.text)
Response
{
  "concepts": {
    "match": [
      {
        "id": "238000002347",
        "name": "injection",
        "domain": "Methods",
        "similarity": 0,
        "sections": ["title", "claims", "abstract", "description"],
        "count": 39
      },
      }
      ...
    ]
  }
}