endoc 1.7.0

Endoc SDK: A note-taking app SDK powered by LLMs

Endoc SDK

Endoc SDK is a Python library that provides powerful tools for advanced paper search, summarization, and note management using a GraphQL API. It leverages Pydantic for robust data validation and modeling, so that all responses are returned as easy‐to‐use Python objects. In addition, Endoc SDK offers an extensibility mechanism to allow you to create custom composite services without modifying the core code.

Features

• Document Search: Search and filter papers using ranking variables and keywords.
• Summarize Paper: Generate summaries for individual papers.
• Paginated Search: Retrieve paginated search results.
• Single Paper Search: Get detailed information about a single paper.
• Note Library: Retrieve papers associated with a note.
• Custom Services: Easily extend the client with your own functions.

Installation

Install Endoc SDK via pip:

pip install endoc

Setup

1. Obtain Your API Key:

   • Visit https://endoc.ethz.ch and sign up using your Switch Edu-ID credentials.
   • After logging in, click on the Account option in the side panel.
   • Under the Developer API section, click Generate to create a new API key.
   • Copy the generated API key for later use.

2. Create a .env File:

   • In your project's root directory, create a file named .env.
   • Add your API key to the file using the following format:

     API_KEY=your_api_key_here
     

3. Load Environment Variables:

   • Install python-dotenv if you haven't already:

     pip install python-dotenv
     

   • In your Python script, load the environment variables at the very start:

     from dotenv import load_dotenv
     load_dotenv()
     api_key = os.getenv("API_KEY")
     

4. Instantiate the Endoc client

   • In your Python script, instantiate a new instance of the EndocClient:

    client = EndocClient(api_key)
   

Basic Usage

1) Document Search

To search for papers, call the document_search method. This returns a DocumentSearchData object.

doc_search_result = client.document_search(
    ranking_variable="BERT",
    keywords=["AvailableField:Content.Fullbody_Parsed"]
)

# Accessing properties:
print(doc_search_result.status)
print(doc_search_result.response.search_stats.nMatchingDocuments)
print(doc_search_result.response.paper_list[0].id_value)

2) Summarize Paper

Call the summarize method with a paper ID to get a summary. The result is a SummarizationResponseData object.

summarize_result = client.summarize("221802394")
# Example usage:
print(summarize_result.status)
# You can further inspect summarize_result.response for detailed summary items.

3) Paginated Search

Use the paginated_search method to retrieve paginated results. Prepare a list of paper metadata as input.

example_paper = {
    "collection": "S2AG",
    "id_field": "id_int",
    "id_type": "int",
    "id_value": "221802394"
}
paper_list = [example_paper]
paginated_result = client.paginated_search(paper_list=paper_list)
# Example usage:
print(paginated_result.status)

4) Single Paper Search

To fetch detailed information for a single paper, use the single_paper method. This returns a SinglePaperData object.

single_paper_result = client.single_paper("221802394")
# Example usage:
print(single_paper_result.response.Title)

5) Get Note Library

Retrieve papers related to a note by calling the get_note_library method. This returns a GetNoteLibraryResponse object. To find your note ID, navigate to a note on Endoc and copy the last part of the url, e.g. for https://endoc.ethz.ch/note/679a1e2e5b25cf001a7c7157, the note's ID is 679a1e2e5b25cf001a7c7157.

note_library_result = client.get_note_library("679a1e2e5b25cf001a7c7157")
if note_library_result.response:
    print(note_library_result.response[0].id_value)

Extending the Client with Custom Services

Endoc SDK allows you to add your own composite services without modifying the core code. You have two options:

Option 1: Using the register_service Decorator

Endoc SDK re-exports the register_service decorator, so you can define custom methods that become part of the client interface. For example:

from endoc import register_service

@register_service("combined_search")
def combined_search(self, paper_list, id_value):
    paginated = self.paginated_search(paper_list, keywords=["example"])
    single = self.single_paper(id_value)
    return {"paginated": paginated, "single": single}

result = client.combined_search(paper_list, "221802394")
print("Combined Search Result:", result)

Option 2: Using the register_service Method

Alternatively, you can register a custom service function directly on the client instance:

def my_custom_service(paper_list, id_value):
    paginated = client.paginated_search(paper_list, keywords=["custom"])
    single = client.single_paper(id_value)
    return {"paginated": paginated, "single": single}

client.register_service("my_custom_service", my_custom_service)

result = client.my_custom_service(paper_list, "221802394")
print("My Custom Service Result:", result)

Package Structure

The package is organized as follows:

endoc/
├── __init__.py
├── client.py
├── endoc_client.py
├── decorators.py
├── queries/
│   ├── document_search_query.py
│   ├── get_note_library_query.py
│   ├── paginated_search_query.py
│   ├── single_paper_query.py
│   └── summarize_paper_query.py
├── models/
│   ├── document_search.py
│   ├── note_library.py
│   ├── paginated_search.py
│   ├── single_paper.py
│   └── summarization.py
└── services/
    ├── document_search.py
    ├── get_note_library.py
    ├── paginated_search.py
    ├── single_paper_search.py
    └── summarization.py
tests/
├── __init__.py
├── conftest.py
├── fixtures/
│   ├── __init__.py
│   ├── dummy_api.py
│   └── document_search_fixtures.py
├── integration/
│   └── __init__.py
└── unit/
    ├── __init__.py
    ├── test_document_search.py
    └── test_custom_services.py

Environment Variables

The SDK expects your API key as the environment variable API_KEY. Use a .env file and python-dotenv to load the variable:

from dotenv import load_dotenv
load_dotenv()

Testing

Endoc SDK includes a test suite to ensure quality and maintain high coverage. The tests are organized by functionality, making it easy to add new tests or modify existing ones.

• Make sure you have installed pytest and any other test dependencies:

   pip install pytest
  

Running the Tests

In the root of your project (the same directory containing tests/), run: pytest.

Test Organization

Fixtures

The tests/fixtures folder holds reusable components like mock responses and dummy clients (e.g., dummy_api.py).

A document_search_fixtures.py file might contain fixtures that set up data or patch classes for document search tests.

Unit Tests

Located in tests/unit, these tests focus on individual modules or classes, mocking external calls.

For example, test_document_search.py might ensure the DocumentSearchService parses JSON correctly.

Integration Tests

Placed in tests/integration, these tests cover how multiple parts of the SDK interact. They may call real endpoints in a staging environment or use more extensive mocks that simulate multi-step workflows.

conftest.py

Pytest automatically discovers and uses any fixtures defined in conftest.py. You can place shared fixtures here (like a global mock of your API client or environment setup).

Contributing

Contributions are welcome! Please open issues or submit pull requests on the GitHub repository. Ensure that any contributions adhere to the existing code style and include tests where applicable.

License

This project is licensed under the MIT license.