Awesome GitHub RepositoriesSentiment Analysis Tools

HanLP is a natural language processing library and deep learning framework specifically optimized for the Chinese language, while also functioning as a multilingual text processor. It serves as a toolkit for performing linguistic analysis, semantic understanding, and script conversion. The project distinguishes itself through a dedicated focus on Chinese linguistic structures, including a specialized script converter for transforming text between Simplified Chinese, Traditional Chinese, and Pinyin. It further supports domain-specific model training to improve the recognition of professional t

This project is an educational platform and research toolkit designed to teach deep learning through a combination of mathematical theory, visual diagrams, and executable code. It provides a comprehensive environment for building, training, and evaluating neural networks, grounding complex concepts in interactive computational notebooks that allow for hands-on experimentation. The framework distinguishes itself by interleaving theoretical foundations—including linear algebra, calculus, and probability—with practical implementations across multiple industry-standard libraries. It supports flex

AiToEarn is an artificial intelligence-driven social media management platform designed to centralize content orchestration, audience engagement, and performance analytics. It provides a unified workspace where users can generate, optimize, and schedule content across multiple social networks while automating interactions through intelligent language and media models. The platform distinguishes itself by integrating sentiment analysis to categorize audience engagement and identify purchase intent, allowing for personalized automated responses. It utilizes a credit-based accounting system to m

FinGPT is a suite of specialized financial tools and a framework for adapting large language models to the financial domain. It provides a set of pipelines for financial entity extraction, sentiment analysis, and retrieval-augmented generation to improve the accuracy of financial information systems. The project distinguishes itself through efficient training workflows, utilizing low-rank adaptation and quantized low-rank adaptation to fine-tune models on consumer-grade hardware. It employs market-labeled datasets and reinforcement learning that uses actual stock price movements as reward sig

Claude Quickstarts is a development framework and collection of reference implementations designed for building autonomous agents. It provides the foundational patterns necessary to orchestrate multi-agent workflows, enabling models to perform complex, multi-step tasks across software engineering, customer support, and computer-use domains. The platform distinguishes itself through specialized capabilities for desktop and browser automation, allowing agents to interact with graphical interfaces by capturing visual context and executing precise mouse and keyboard inputs. It includes robust inf

llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model workflows and autonomous agents. It provides a unified model catalog and standardized interface to execute specialized language models for complex research, analysis, and structured data generation. The project distinguishes itself through its heavy emphasis on local execution and quantized inference, allowing models to run on private infrastructure using CPU, GPU, and NPU acceleration via runtimes like ONNX and OpenVino. It features a specialized ability to translate natural lang

This project is a collection of Python scripts and tools designed for web scraping, browser automation, and large-scale data extraction. It provides a set of implementations for retrieving information from websites and private APIs, including tools for multimedia downloading and social media data archiving. The toolset includes specialized mechanisms for bypassing anti-scraping measures through IP proxy pool rotation and multi-threaded crawlers. It also features capabilities for simulating browser sessions to handle authentication, intercepting session cookies, and decrypting network payloads

Flair is a transformer-based natural language processing framework used to build and train models for text classification and sequence tagging. It provides a specialized library for generating contextual text embeddings and performing linguistic analysis. The framework includes dedicated tools for named entity recognition, including the identification of specialized biomedical entities across multiple languages. It further supports entity linking to map identified text mentions to unique entries within general or biomedical knowledge bases. The project covers a broad range of language analys

Flair is a natural language processing framework for training and applying models for sequence labeling and text classification. It provides a system for generating word embeddings and identifying semantic entities within text. The framework includes a dedicated system for zero and few-shot learning, enabling text classification and entity extraction using minimal training examples by leveraging pre-trained knowledge. Its capabilities cover named entity recognition, sentiment analysis, and the training of specialized models using custom datasets. It also includes tooling for the visual highl

This project is an automated machine learning framework and toolkit designed for training and tuning custom models for classification, regression, and recommendations. It functions as a multimodal machine learning toolkit capable of processing and training models using a combination of text, image, audio, and sensor data. The framework distinguishes itself as a multimodal data processor that can handle and visualize large datasets on a single machine using column-oriented disk storage. It includes a core machine learning model generator that converts trained models into formats compatible wit

CoreNLP es una biblioteca de procesamiento de lenguaje natural en Java diseñada para convertir texto en lenguaje humano sin procesar en datos estructurados. Utiliza un conjunto de anotadores lingüísticos para analizar el texto a través de un pipeline, extrayendo estructuras gramaticales, sentimiento y patrones lingüísticos. El proyecto incluye un motor de resolución de correferencia que vincula múltiples menciones de la misma entidad para mantener la coherencia contextual en los documentos. También proporciona herramientas para el reconocimiento de entidades nombradas con el fin de categorizar personas, empresas y ubicaciones, así como un etiquetador de partes de la oración para asignar categorías gramaticales y formas base a las palabras. La biblioteca también cubre el análisis de sentimiento de texto para evaluar el tono emocional y admite la serialización de datos lingüísticos procesados en formatos estandarizados para su almacenamiento o intercambio externo.

TextBlob is a natural language processing library that provides a unified interface for common linguistic tasks. It operates as a wrapper-based API, simplifying the use of complex processing libraries by delegating core operations to specialized external frameworks. The project features a pluggable processing pipeline that allows for the integration of custom logic and alternative language engines. It supports the extension of processing models through plugins to add specific language support or custom data processing. The library covers a broad range of linguistic capabilities, including se

This project is a quantitative trading platform and algorithmic trading bot designed for market data aggregation, strategy backtesting, and trade execution. It functions as a comprehensive system for collecting financial data via APIs and web sources, simulating investment strategies against historical records, and programmatically managing investment positions through brokerage interfaces. The platform distinguishes itself through institutional sentiment analysis and market intelligence tools. It monitors institutional fund activity, tracks corporate actions like equity pledges, and crawls f

This project is a plugin framework and agentic workflow library designed to connect large language models to professional toolstacks. It provides a system for integrating language models with external data warehouses, CRMs, and other enterprise software to retrieve and manipulate real-time business data. The framework enables the automation of specialized professional tasks through a file-based plugin definition system. It allows for the customization of domain expertise and plugin behavior to align with internal company processes, supported by an enterprise data connector that links models t

Rig is a framework for building large language model applications, featuring a multi-provider client and a workflow builder for retrieval-augmented generation systems. It serves as an orchestrator for creating autonomous agents that can maintain conversation state and execute complex tasks through custom prompting and plugins. The project provides standardized interfaces for both completion and embedding model providers, allowing for unified request and response patterns across different engines. It also includes a vector database integration layer that defines a common interface for indexing

This project serves as a comprehensive educational repository and technical reference collection, documenting a wide range of software engineering practices and modern development technologies. It provides a structured learning path for developers, curating tutorials and practical examples that cover the full lifecycle of application development, from initial project scaffolding to deployment and maintenance. The repository distinguishes itself by offering deep technical insights into complex architectural patterns, including actor-based concurrency models for managing parallel tasks and cont

HuLa is an open-source communication suite and cross-platform chat client designed for real-time instant messaging, voice, and video calls. It functions as an LLM-integrated messaging platform and an AI-powered social manager that synchronizes user data and settings across different operating systems. The platform integrates large language models to provide automated AI assistants, real-time message translation, and chat log summarization. It further utilizes artificial intelligence for user sentiment analysis to assist with social matching and risk management. The system includes a high-per

SnowNLP is a Python library for Chinese natural language processing. It provides tools for text segmentation, sentiment analysis, document classification, and phonetic transliteration. The library includes capabilities for training and saving custom machine learning models for tokenization and sentiment analysis using raw training datasets. It covers a range of linguistic processing areas, including parts of speech tagging, sentence splitting, and text similarity measurement. The toolkit also provides utilities for extracting key information through text summarization and calculating word im

nlp.js is a JavaScript natural language processing library and development framework used to build natural language understanding engines. It provides a toolkit for creating local machine learning models for intent classification and acts as a multilingual text processor that detects languages and normalizes text across various dialects. The framework distinguishes itself by supporting local execution on both servers and mobile devices, enabling chatbot functionality without an internet connection. It features a specialized system for conversational slot filling to collect mandatory informati

trump2cash is a sentiment-based stock trading bot and social media market monitor. It uses a natural language processing sentiment analysis tool to scan real-time social media feeds for mentions of publicly traded companies and translates the emotional tone of that text into automated buy or short stock market orders. The system utilizes a ticker mapping utility to resolve company names, subsidiaries, and brands into valid public stock market ticker symbols. To verify the efficacy of these sentiment-driven signals, it includes an algorithmic trading backtester that evaluates trading strategie