ContextGem: Effortless LLM extraction from documents
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Updated
Sep 9, 2025 - Python
ContextGem: Effortless LLM extraction from documents
Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .
Homer, a text analyser in Python, can help make your text more clear, simple and useful for your readers.
Language, Knowledge, Cognition
中文情感分析库(Chinese Sentiment))可对文本进行情绪分析、正负情感分析。Text analysis, supporting multiple methods including word count, readability, document similarity, sentiment analysis, Word2Vec .
Official PyTorch implementation of the paper "TEMOS: Generating diverse human motions from textual descriptions", ECCV 2022 (Oral)
🗣️ Tool to generate adversarial text examples and test machine learning models against them
text analysis, supporting multiple methods including word count, readability, document similarity, sentiment analysis, Word2Vec/GloVe, and Large Language Models (LLMs).文本分析包,支持字数统计、可读性、文档相似度、情感分析在内的多种文本分析方法。
A Python library to parse MediaWiki WikiText
Textpipe: clean and extract metadata from text
Text analysis with networks.
Interpretable data visualizations for understanding how texts differ at the word level
Text vectorization tool to outperform TFIDF for classification tasks
This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en
A neural network intent parser
[BEA @ ACL 2023] General-purpose tool for linguistic features extraction; Tested on readability assessment, essay scoring, fake news detection, hate speech detection, etc.
Stanford NLP group's shared Python tools.
A simple text reuse detection CLI tool.
🍊 📄 Text Mining add-on for Orange3
This Python module can be used to obtain antonyms, synonyms, hypernyms, hyponyms, homophones and definitions.
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