Search Results for "text analysis" - Page 2
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Showing 574 open source projects for "text analysis"
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LangKit
An open-source toolkit for monitoring Language Learning Models (LLMs)
LangKit is an open-source text metrics toolkit for monitoring language models. It offers an array of methods for extracting relevant signals from the input and/or output text, which are compatible with the open-source data logging library whylogs. Productionizing language models, including LLMs, comes with a range of risks due to the infinite amount of input combinations, which can elicit an infinite amount of outputs. The unstructured nature of text poses a challenge in the ML observability... -
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PDF4QT
Open source PDF editor
PDF4QT is open source PDF editor based on Qt framework. It contains a C++ library, applications for viewing/editing PDF documents, and a command line tool. PDF4QT is an open-source PDF editor for Windows/Linux. It is a modern solution for viewing/editing/rendering PDF documents, for users and developers alike. For developers, there is a C++ library and a command line tool for use in scripts. For users, there are four applications offering many features. The project is hosted on Github and... -
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Ultravox
Fast multimodal LLM for real-time voice interaction and AI apps
Ultravox is an open source multimodal large language model designed specifically for real-time voice-based interactions. It is built to process both text and spoken audio directly, eliminating the need for a separate speech recognition stage and enabling more seamless conversational experiences. Ultravox works by combining text prompts with encoded audio inputs, allowing it to understand spoken language alongside written instructions in a unified pipeline. Internally, it leverages pretrained language models and speech encoders, with a multimodal adapter that integrates both modalities for inference and training. ... -
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RAG Anything
RAG-Anything: All-in-One RAG Framework
...The system uses a multi-stage pipeline (e.g., document parsing, content analysis, knowledge graph construction, intelligent retrieval) so queries can navigate across modalities with deeper understanding and relevance. -
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Awesome Mac
Collect premium software in various categories
Now we have become very big and different from the original idea. Here we collect awesome macOS software in various categories. Feel free to star and fork. Reading and writing tools, text editors, office, markdown tools, note-taking, journaling. Ebooks, RSS, developer tools, IDEs, developer utilities, etc. Regular expression editors, API development and analysis, network analysis, command line tools, frameworks for hybrid applications, version control. Virtualization, databases, design and product, design tools, prototyping and mind-mapping tools, screen capturing software, etc. ... -
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Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. ... -
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NetworkX
Network analysis in Python
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Data structures for graphs, digraphs, and multigraphs. Many standard graph algorithms. Network structure and analysis measures. Generators for classic graphs, random graphs, and synthetic networks. Nodes can be "anything" (e.g., text, images, XML records). Edges can hold arbitrary data (e.g., weights, time-series). Open source 3-clause BSD license. Well tested with over 90% code coverage. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. ... -
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
DeepAnalyze is an open source project that introduces an agentic large language model designed to perform autonomous data science tasks from start to finish. It is built to handle the entire data science pipeline, including data preparation, analysis, modeling, visualization, and report generation without requiring continuous human guidance. DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and unstructured text, enabling flexible and comprehensive analysis workflows. It integrates execution-based reasoning by generating and running code as part of its analysis process, allowing it to iteratively refine results and produce more accurate outputs. ... -
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pprof
pprof is a tool for visualization and analysis of profiling data
pprof is a profiling visualization and analysis tool that ingests profiles in the profile.proto format and generates human-readable and graph-based reports. It supports multiple profile types (CPU, heap, allocations, contention, etc.) and can present data as text tables, call graphs (via Graphviz/dot), flame graphs, and interactive web UIs. The tool helps developers find hot paths, quantify resource usage, and compare profiles across runs to validate performance changes. ... -
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ShieldFont
A typeface that protects written content by poisoning unauthorized AI
...An optional accessibility layer reveals the original text through a browser-side puzzle, but protected blocks are not fully WCAG compliant. The defense raises scraping costs rather than providing encryption and does not stop font analysis, rendered browsers, OCR, or screenshots. -
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deepdoctection
A Repo For Document AI
DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. -
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NLP
Open source NLP guide with models, methods, and real use cases
NLP is an open source introductory resource for natural language processing, presented as a continuously updated book hosted on GitHub. It explains how machines process and understand human language, combining theory with practical examples. Its covers core NLP concepts such as text representation, feature extraction, and model evaluation, alongside hands-on implementations using tools like Word2Vec, TF-IDF, and FastText. It also introduces topic modeling with LDA, keyword extraction techniques, and document similarity methods. NLP extends into real-world applications, including sentiment analysis and text classification, helping readers connect concepts to use cases. ... -
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Semantra
Multi-tool for semantic search
...By relying on semantic embeddings and contextual analysis, the tool can identify passages that are relevant even when the query uses different wording than the source documents. -
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Node.js Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models
This is the Node.js client (with Typescript types) for the NLP Cloud API. NLP Cloud serves high-performance pre-trained or custom models for NER, sentiment analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, text generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. ... -
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Underthesea
Underthesea - Vietnamese NLP Toolkit
Underthesea is a Vietnamese NLP toolkit providing various text processing capabilities, including word segmentation, part-of-speech tagging, and named entity recognition. -
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Python Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models for NER
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. ... -
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Matter AI
Matter AI is open-source AI Code Reviewer Agent
Matter AI is an AI-powered platform designed to enhance productivity through automated content generation, data analysis, and decision support. It leverages machine learning models to process text, analyze patterns, and generate insights, making it suitable for businesses looking to optimize data-driven decision-making. Matter AI integrates with various data sources and provides customizable AI workflows tailored to different industries. -
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GNU Emacs / N Λ N O
Emacs made simple
...The project includes only minimal configuration and essential extensions, enabling users to start editing text comfortably without wrestling with a steep learning curve or bloated init files. This makes it appealing for users who like the power of Emacs (or similar advanced editors) but want a fast, responsive, and easy-to-maintain editor. Nano-Emacs can be especially useful for scripting, quick edits, data-analysis workflows, or writing in scientific/research contexts, especially when you want something more powerful than a simple text editor but lighter than a full IDE. -
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Eliza
Autonomous agents for everyone
Build and deploy autonomous AI agents with consistent personalities across Discord, Twitter, and Telegram. Full support for voice, text, and media interactions. Built-in RAG memory system, document processing, media analysis, and autonomous trading capabilities. Supports multiple AI models including Llama, GPT-4, and Claude. Create custom actions, add new platform integrations, and extend functionality through a modular plugin system. Full TypeScript support. -
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eslint-plugin-unicorn
More than 100 powerful ESLint rules
More than 100 powerful ESLint rules. You might want to check out XO, which includes this plugin. Each rule has emojis denoting if it belongs to the recommended configuration if some problems reported by the rule are automatically fixable by the --fix command line option, or if some problems reported by the rule are manually fixable by editor suggestions. Use a preset config or configure each rules in package.json. -
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ChatGPT Exporter
Export and Share your ChatGPT conversation history
...It integrates directly into the ChatGPT web environment, typically via tools like Tampermonkey, and adds export functionality without requiring backend services or complex setup. The tool supports a wide range of output formats including plain text, HTML, Markdown, JSON, and even image-based exports, making it suitable for documentation, knowledge management, and data analysis workflows. One of its key strengths is its ability to preserve formatting such as code blocks, tables, and structured responses, ensuring that exported content remains usable and readable. It also allows exporting entire conversations or selected portions, giving users flexibility depending on their needs. -
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Shows how a target value (e.g. "Survived" in the Titanic dataset) relates to other features. ... -
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Ollama-Laravel Package
Ollama-Laravel is a Laravel package providing seamless integration
...It abstracts the Ollama API into a developer-friendly facade, allowing Laravel developers to interact with models using familiar patterns such as service containers, configuration files, and fluent method chaining. The package supports a wide range of AI capabilities including text generation, chat-based interactions, embeddings, and multimodal vision analysis, making it suitable for both simple features and complex AI-driven systems. It also includes support for reasoning models and function calling, enabling developers to build more advanced workflows where models can trigger tools or structured actions. Real-time streaming responses are supported, allowing applications to deliver incremental outputs for better user experience. -
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Qwen2-Audio
Repo of Qwen2-Audio chat & pretrained large audio language model
Qwen2-Audio is a large audio-language model by Alibaba Cloud, part of the Qwen series. It is trained to accept various audio signal inputs (including speech, sounds, etc.) and perform both voice chat and audio analysis, producing textual responses. It supports two major modes: Voice Chat (interactive voice only input) and Audio Analysis (audio + text instructions), with both base and instruction-tuned models. It is evaluated on many benchmarks (speech recognition, translation, sound classification, emotion, etc.), and offers pretrained models (e.g. 7B) released via ModelScope and Hugging Face. ... -
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Introduction-NLP
Detailed notes on HanLP's new book, "Introduction to Natural Language"
Introduction NLP is a Chinese-language study-notes repository based on the book Introduction to Natural Language Processing by the author of HanLP. It explains NLP concepts in accessible language while pairing theory with practical implementation notes. The material begins with basic concepts and Chinese word segmentation before progressing into statistical sequence models. Later chapters cover part-of-speech tagging, named entity recognition, information extraction, text clustering, text...
