chatnoir-api 2.1.5

Simple, type-safe access to the ChatNoir search API.

🔍 chatnoir-api

Simple, type-safe access to the ChatNoir search API.

Working with PyTerrier? Check out the chatnoir-pyterrier package.

Installation

Install the package from PyPI:

pip install chatnoir-api

Usage

The ChatNoir API offers two main features: search with BM25F and retrieving document contents.

Search

To search with the ChatNoir API you need to request an API key. Then you can use our Python client to search for documents. The results object is an iterable wrapper of the search results which handles pagination for you. List-style indexing is supported to access individual results or sub-lists of results:

from chatnoir_api.v1 import search

api_key: str = "<API_KEY>"
results = search(api_key, "python library")

top10_results = results[:10]
print(top10_results)

result_1234 = results[1234]
print(result_1234)

Search the new ChatNoir

There's a new ChatNoir version with the same API interface. To run your search requests against the new API (e.g., if you want to search the ClueWeb22), set staging=True like this:

from chatnoir_api import Index
from chatnoir_api.v1 import search

api_key: str = "<API_KEY>"
results = search(api_key, "python library", staging=True, index=Index.ClueWeb22)

Note for Touché 2023 participants: Set index=Index.ClueWeb22 to search the ClueWeb22 index. (Otherwise, results from the ClueWeb09 and ClueWeb12 indices will be included.)

Phrase Search

To search for phrases, use the search_phrases method in the same way as normal search:

from chatnoir_api.v1 import search_phrases

api_key: str = "<API_KEY>"
results = search_phrases(api_key, "python library", staging=True)

Chat

To generate text with the ChatNoir Chat API you need to request an API key from the admins. With your API key, you can chat with the cat, like this:

from chatnoir_api.chat import chat

api_key: str = "<API_KEY>"
response = chat(api_key, "how are you?")

Retrieve Document Contents

Often the title and ID of a document is not enough to effectively re-rank a list of search results. To retrieve the full content or plain text for a given document you can use the html_contents helper function. The html_contents function expects a ChatNoir-internal UUID, shorthand UUID, or a TREC ID and the index from which to retrieve the document.

Retrieve by TREC ID

You can retrieve a document by its TREC ID like this:

from chatnoir_api import cache_contents, Index

contents = cache_contents(
    "clueweb09-en0051-90-00849",
    Index.ClueWeb09,
)
print(contents)

plain_contents = cache_contents(
    "clueweb09-en0051-90-00849",
    Index.ClueWeb09,
    plain=True,
)
print(plain_contents)

Retrieve by ChatNoir-internal UUID

You can also retrieve a document by its ChatNoir-internal UUID like this:

from uuid import UUID

from chatnoir_api import cache_contents, Index

contents = cache_contents(
    UUID("e635baa8-7341-596a-b3cf-b33c05954361"),
    Index.CommonCrawl1511,
)
print(contents)

plain_contents = cache_contents(
    UUID("e635baa8-7341-596a-b3cf-b33c05954361"),
    Index.CommonCrawl1511,
    plain=True,
)
print(plain_contents)

Retrieve by ChatNoir-internal short UUID

For newer ChatNoir versions, you can also retrieve a document by its ChatNoir-internal short UUID like this:

from chatnoir_api import cache_contents, Index, ShortUUID

contents = cache_contents(
    ShortUUID("6svePe3PXteDeGPk1XqTLA"),
    Index.ClueWeb22,
    staging=True,
)
print(contents)

plain_contents = cache_contents(
    ShortUUID("6svePe3PXteDeGPk1XqTLA"),
    Index.ClueWeb22,
    plain=True,
    staging=True,
)
print(plain_contents)

Citation

If you use this package, please cite the paper from the ChatNoir authors. You can use the following BibTeX information for citation:

@InProceedings{bevendorff:2018,
  address =               {Berlin Heidelberg New York},
  author =                {Janek Bevendorff and Benno Stein and Matthias Hagen and Martin Potthast},
  booktitle =             {Advances in Information Retrieval. 40th European Conference on IR Research (ECIR 2018)},
  editor =                {Leif Azzopardi and Allan Hanbury and Gabriella Pasi and Benjamin Piwowarski},
  month =                 mar,
  publisher =             {Springer},
  series =                {Lecture Notes in Computer Science},
  site =                  {Grenoble, France},
  title =                 {{Elastic ChatNoir: Search Engine for the ClueWeb and the Common Crawl}},
  year =                  2018
}

Development

To build this package and contribute to its development you need to install the build, and setuptools and wheel packages:

pip install build setuptools wheel

(On most systems, these packages are already pre-installed.)

Installation

Install package and test dependencies:

pip install -e .[test]

Testing

Configure the API keys for testing:

export CHATNOIR_API_KEY="<API_KEY>"
export CHATNOIR_API_KEY_STAGING="<API_KEY>"
export CHATNOIR_API_KEY_CHAT="<API_KEY>"

Verify your changes against the test suite to verify.

flake8 chatnoir_api tests examples
pylint -E chatnoir_api tests examples
pytest chatnoir_api tests examples

Please also add tests for your newly developed code.

Build wheels

Wheels for this package can be built with:

python -m build

Support

If you hit any problems using this package, please file an issue. We're happy to help!

License

This repository is released under the MIT license.