Here are various open-source libraries and tools for natural language processing tasks, including text classification, sentiment analysis, and entity recognition:

• langchain - A Python framework for integrating LLMs into your app.
• openai - OpenAI SDKs for both Python and Node.
• allennlp - An open-source NLP research library built on PyTorch that provides a set of pre-built models and tools for natural language understanding tasks.
• anago - A Python library for sequence labeling implemented in Keras that can be used for tasks such as named entity recognition and part-of-speech tagging.
• CoreNLP - A suite of core NLP tools developed by Stanford that provides a range of natural language processing capabilities, including sentiment analysis, entity recognition, and dependency parsing.
• dimsum16 - A system for detecting minimal semantic units and their meanings, which can be used for tasks such as word sense disambiguation and lexical substitution.
• finetune - A scikit-learn style library for model fine-tuning in NLP tasks, allowing for more efficient and accurate model training.
• flair - A simple and lightweight framework for state-of-the-art NLP that provides pre-trained models and easy-to-use APIs for common NLP tasks.
• flashtext - A library for extracting keywords from sentences or replacing keywords in sentences, which can be used for tasks such as search engine optimization and text analysis.
• fuzzywuzzy - A Python library for fuzzy string matching that can be used to identify similarities between strings with different degrees of accuracy.
• gensim - A Python library for topic modeling that provides a range of tools for extracting insights and patterns from large collections of texts.
• gluon - A toolkit for easy text preprocessing in NLP research, designed to speed up the process of preparing text data for machine learning models.
• Kashgari - An NLP transfer learning framework for text labeling and classification that provides pre-trained models and easy-to-use APIs for common NLP tasks.
• magnitude - A fast and efficient utility package for working with vector embeddings, which are often used in NLP tasks such as sentiment analysis and document classification.
• mallet - A Java-based package for machine learning applications to text, which provides tools for topic modeling, document classification, and more.
• nltk - A popular Python library for natural language processing that provides a range of tools for text analysis, tokenization, and stemming.
• pattern - A Python library for web mining that provides a range of tools for scraping, NLP, machine learning, network analysis, and visualization.
• polyglot - A multilingual text processing toolkit that provides a range of tools for working with text in multiple languages, including entity recognition, sentiment analysis, and more.
• rasa - An open-source machine learning framework for automating text- and voice-based conversations, which can be used to build chatbots and virtual assistants.