Skip to main content

Sentiment Analysis Tool

Project description

Swarmauri Logo

PyPI - Downloads PyPI - Python Version PyPI - License PyPI - Version


Sentiment Analysis Tool

A tool for analyzing the sentiment of text using Hugging Face's transformers library. This tool provides simple sentiment analysis capabilities, classifying text as POSITIVE, NEGATIVE, or NEUTRAL.

Installation

pip install swarmauri_tool_sentimentanalysis

Usage

Here's a basic example of how to use the Sentiment Analysis Tool:

from swarmauri.tools.SentimentAnalysisTool import SentimentAnalysisTool

# Initialize the tool
tool = SentimentAnalysisTool()

# Analyze sentiment
result = tool("I love this product!")
print(result)  # {'sentiment': 'POSITIVE'}

# Another example
result = tool("This product is okay.")
print(result)  # {'sentiment': 'NEUTRAL'}

Want to help?

If you want to contribute to swarmauri-sdk, read up on our guidelines for contributing that will help you get started.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

swarmauri_tool_sentimentanalysis-0.6.1.tar.gz (6.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file swarmauri_tool_sentimentanalysis-0.6.1.tar.gz.

File metadata

File hashes

Hashes for swarmauri_tool_sentimentanalysis-0.6.1.tar.gz
Algorithm Hash digest
SHA256 c52019b34aef4c53af16709cc286ec8dfa8447c077ce96bdbdbda4f872026a78
MD5 a9e3d4c0afb3765c5eea38e7c1434833
BLAKE2b-256 d4c739e30e7e8046616bee57dec33a84f31198b664228fbe7bb94a736d40c47a

See more details on using hashes here.

File details

Details for the file swarmauri_tool_sentimentanalysis-0.6.1-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_tool_sentimentanalysis-0.6.1-py3-none-any.whl
Algorithm Hash digest
SHA256 dad10b3f9eb79fb74935d774df1bd6d77667c2aad807b6db38e5002e2401bb5a
MD5 12cd47cf118f80477ed6feebd40f061e
BLAKE2b-256 7487a922418f84e1646b0be046d02dd1fec0d1ec1fe421d55c4e154c12cbfd5c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page