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Consider using release 1.7.0 instead.
Reason given by maintainers: half-published version

Geneea NLP Client SDK

A Python SDK for the Geneea Interpretor - a Natural Language Processing REST API that extracts linguistic insights from text documents.

Features

The SDK provides access to Geneea's NLP capabilities including language detection, named entity recognition (persons, organizations, locations), semantic tagging, sentiment analysis, and relationship extraction between entities.

Installation

pip install geneea-nlp-client

Supports Python 3.8 - 3.13.

Quick Start

from geneeanlpclient import g3

# Create a request builder with desired analyses
builder = g3.Request.Builder(
    analyses=[g3.AnalysisType.ENTITIES, g3.AnalysisType.SENTIMENT]
)

# Analyze text using the API client
with g3.Client.create(userKey="YOUR_API_KEY") as client:
    analysis = client.analyze(builder.build(
        id="doc1",
        text="Angela Merkel visited Paris last Tuesday."
    ))
    
    # Access results
    for entity in analysis.entities:
        print(f"{entity.type}: {entity.stdForm}")
    
    if analysis.docSentiment:
        print(f"Sentiment: {analysis.docSentiment.label}")

You can also set the API key via the GENEEA_API_KEY environment variable.

Analysis Types

Type	Description
`ENTITIES`	Named entity recognition
`TAGS`	Semantic tagging and topic extraction
`RELATIONS`	Entity relationships and attributes
`SENTIMENT`	Sentiment analysis
`LANGUAGE`	Language detection
`ALL`	All analyses

Advanced Usage

Structured document input:

builder = g3.Request.Builder(analyses=[g3.AnalysisType.ALL])
request = builder.build(
    id="article1",
    paraSpecs=[
        g3.ParaSpec.title("Author Elena Marsh Releases New Historical Novel"),
        g3.ParaSpec.lead("The acclaimed writer returns with a story set in 19th century Prague."),
        g3.ParaSpec.body("First paragraph of the article."),
        g3.ParaSpec.body("Second paragraph of the article.")
    ]
)

Note: The Interpretor (General API) can accept any number of paragraphs, but always returns at most one of each type: title, lead, and body. For title and lead this is usually not a limitation (there is typically only one of each), but if there are multiple body paragraphs in the input, they are concatenated into a single body paragraph with "\n\n" as separator in the output.

Domain-specific analysis:

builder = g3.Request.Builder(
    analyses=[g3.AnalysisType.ENTITIES, g3.AnalysisType.TAGS],
    domain=g3.Domain.NEWS,  # News media articles
    language=g3.LanguageCode.EN
)

With item-level sentiment and mentions:

builder = g3.Request.Builder(
    analyses=[g3.AnalysisType.ENTITIES, g3.AnalysisType.SENTIMENT],
    returnMentions=True,
    returnItemSentiment=True
)

Working with results:

# Iterate through document structure
for paragraph in analysis.paragraphs:
    print(f"Paragraph type: {paragraph.type}")
    for sentence in paragraph.sentences:
        print(f"  Sentence: {sentence.text}")
        print(f"  First word: {sentence.tokens[0].text}")

# Entity mentions with positions
for entity in analysis.entities:
    for mention in entity.mentions:
        print(f"{entity.stdForm} found at: {mention.tokens.charSpan}")

Dependencies

requests~=2.25 - HTTP communication
pandas>=0.22 (optional) - For example scripts with Excel export

Development

The SDK is built using Bitbucket Pipelines. The pipelines are run at least once a month to keep the SonarQube token valid.

Documentation

License

Apache License 2.0

Release files for geneea-nlp-client 1.6.0

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