Search Results for "summarize"
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Showing 90 open source projects for "summarize"
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1
Summarize
Point at any URL/YouTube/Podcast or file
Summarize is a toolset that lets you point at almost any content and quickly extract the gist, whether that content is a webpage, a YouTube video, a podcast, or a local file. It’s built around a CLI workflow so you can summarize from the terminal, but it also includes a Chrome extension so you can do the same thing directly while browsing. -
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dplyr
dplyr: A grammar of data manipulation
dplyr is an R package that provides a consistent and intuitive grammar for data manipulation, enabling users to filter, arrange, summarize, and transform data efficiently. Part of the tidyverse ecosystem, dplyr simplifies complex data operations through a clear and readable syntax, whether working with data frames, tibbles, or databases. It is widely used in data science and statistical analysis workflows. -
3
ChatPaper
Use ChatGPT to summarize the arXiv papers
ChatPaper is an AI-assisted research toolkit designed to accelerate academic reading and writing workflows. It uses language models to summarize papers and help researchers screen literature more efficiently. The project also supports full-paper translation, writing improvement, peer-review analysis, and responses to reviewer comments. It can retrieve recent arXiv papers based on keywords and time ranges for topic-focused research. Related tools can generate literature reviews, suggest paper titles, and turn papers into structured notes. ... -
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S5CMD
Parallel S3 and local filesystem execution tool
...Set Access Control List (ACL) for objects/files on the upload, copy, move. Print object contents to stdout. Select JSON records from objects using SQL expressions. Create or remove buckets. Summarize objects sizes, grouping by storage class. Wildcard support for all operations. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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MCP YouTube
A Model-Context Protocol Server for YouTube
The YouTube MCP Server uses yt-dlp to download subtitles from YouTube videos and connects to claude.ai via the Model Context Protocol. It enables AI assistants to summarize YouTube videos by accessing their subtitles. -
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WikiChat
WikiChat is an improved RAG
WikiChat is a chatbot framework designed to interactively retrieve and summarize Wikipedia information, allowing users to ask questions and get context-aware responses? -
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SillyTavern
LLM Frontend for Power Users
Mobile-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI, OpenRouter, Claude, Scale), VN-like Waifu Mode, Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters you or the community create. SillyTavern is a fork of TavernAI 1.2.8 which is under more active development and has added many major features. At this point, they can be thought of as completely independent programs. -
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DataFramesMeta.jl
Metaprogramming tools for DataFrames
Metaprogramming tools for DataFrames.jl objects to provide more convenient syntax. DataFrames.jl has the functions select, transform, and combine, as well as the in-place select! and transform! for manipulating data frames. DataFramesMeta.jl provides the macros @select, @transform, @combine, @select!, and @transform! to mirror these functions with more convenient syntax. Inspired by dplyr in R and LINQ in C#. -
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Shapash
Explainability and Interpretability to Develop Reliable ML models
Shapash is a Python library dedicated to the interpretability of Data Science models. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria. -
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10
Coverage.jl
Take Julia code coverage and memory allocation results, do useful thin
...This is useful for measuring how much of your code base your tests actually test, and can reveal the parts of your code that are not tested and might be hiding a bug. You can use Coverage.jl to summarize the results of this tracking or to send them to a service like Coveralls.io or Codecov.io. Julia can track how much memory is allocated by each line of your code. This can reveal problems like type instability, or operations that you might have thought were cheap (in terms of memory allocated) but aren't (i.e. accidental copying). -
11
book-to-skill
Turn any technical book PDF into a Claude Code skill
...The project is useful for transforming dense manuals, textbooks, internal documentation, or technical guides into practical agent-accessible knowledge. It includes an extraction script and a SKILL.md workflow that guides how the resulting content should be used. The goal is not simply to summarize a book, but to make its knowledge available during problem solving and implementation. book-to-skill is best suited for developers and researchers who want AI assistants to work from specific long-form source material. -
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Metabase
The simplest, fastest way to share business intelligence and analytics
Metabase is the easiest way to let everyone in your company access business data and analytics, learn from it and ask questions. Even if you or your colleagues have no experience in SQL, you can easily summarize and visualize your data, share it and let your team ask questions about it. Metabase creates beautiful graphs and charts, with an easy-to-use dashboard where everyone can create, organize and share exceptionally visualized data. It supports a great number of databases, including Postgres, MySQL, Druid, MongoDB, SQLite and more. ... -
13
HiClaw
An open source collaborative multi-agent OS
HiClaw is an AI-powered legal assistant framework developed within the AgentScope ecosystem to support intelligent legal reasoning, document analysis, and workflow automation for legal research and compliance tasks. The project combines large language models with agent orchestration systems to process legal documents, interpret regulations, summarize contracts, and assist with legal knowledge retrieval. It is designed to provide structured, explainable workflows that help legal professionals interact with AI systems more transparently and efficiently. hiclaw emphasizes modularity and integration with external legal databases, retrieval systems, and enterprise tooling, enabling customization for different legal domains and operational requirements. ... -
14
VisiData
A terminal spreadsheet multitool for discovering and arranging data
...Code in the stable branch of this repository, including the main vd application, loaders, and plugins, is available for use and redistribution under GPLv3. VisiData is a free, open-source tool that lets you quickly open, explore, summarize, and analyze datasets in your computer’s terminal. VisiData works with CSV files, Excel spreadsheets, SQL databases, and many other data sources. -
15
Robin
AI-powered tool for dark web OSINT search and investigation
Robin is an AI-powered open source tool designed to assist investigators and researchers in conducting dark web OSINT (Open Source Intelligence) investigations. It combines automated dark web search capabilities with large language models (LLMs) to analyze and summarize information discovered across hidden services and Tor-based search engines. The tool helps refine investigative queries, collect results from multiple dark web sources, and filter relevant intelligence using AI-driven processing. Robin also performs scraping of discovered pages through Tor sessions, allowing users to gather additional context from dark web sites while maintaining the required network routing. ... -
16
Sidekick
Bare metal to production ready in mins; your own fly server
Sidekick is an open-source assistant application built to act as a specialized productivity companion, integrating AI capabilities into daily workflows like note-taking, task management, and contextual knowledge lookup. It provides a responsive interface where users can interact with AI to draft content, ask questions about projects, summarize lengthy text, and generate ideas or outlines, effectively serving as an intelligent extension of traditional productivity tools. Sidekick also includes structured tools like lists, reminders, and project folders so that users can combine generative assistance with tangible organizational frameworks. It supports connectivity with external data sources or APIs so that information can be pulled in contextually, helping to ground AI responses in user-specific content when available. ... -
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TraceRoot
Find the Root Cause in Your Code's Trace
TraceRoot.AI is an open source, AI-native observability and debugging platform designed to help engineering teams resolve production issues faster. It consolidates telemetry into a single correlated execution tree that provides causal context for failures. AI agents operate over this structured view to summarize issues, pinpoint likely root causes, and even suggest actionable fixes or draft GitHub issues and pull requests. It offers interactive trace exploration with zoomable log clusters, span and latency views, and code-linked insights. Lightweight SDKs for Python and TypeScript enable seamless instrumentation using OpenTelemetry, with support for both self-hosted and cloud deployment. ... -
18
HyperTAG
AI-Generated Tags and Summaries for Telegram Messages
HyperTAG is a Telegram bot that leverages advanced AI models to generate context-aware tags and summaries for your messages. It can also automatically create tags and summaries for channel posts. The bot analyzes the text content of your messages along with any included links, producing relevant tags and summaries based on both the message text and the text from the links. Additionally, it generates summaries for Web pages or YouTube videos using their links. -
19
Copilot for Obsidian
AI assistant plugin that brings chat, search, and agents to Obsidian
Obsidian Copilot is an open source plugin that integrates AI-powered assistance directly into the Obsidian note-taking environment. It enables users to interact with their notes through conversational chat, allowing them to ask questions, summarize information, and generate new content using large language models. It works inside a user’s vault and can analyze notes, documents, and other referenced materials to provide context-aware responses. It supports multiple AI providers and models, giving users the flexibility to choose external APIs or run compatible local models depending on their setup. ... -
20
Folo
Folo is the AI Reader
...The project focuses on reducing information overload by automatically organizing feeds and surfacing the most relevant updates based on user preferences. It incorporates AI features that summarize timelines, label entries, and adapt recommendations over time so the reading experience becomes more personalized. Folo is built as a modern cross-platform application with support for desktop, mobile, and web environments, positioning it as a next-generation alternative to traditional feed readers. The system also emphasizes user control through features like Bring Your Own Key support for AI providers and customizable feed management. ... -
21
Rocketnotes
AI-powered markdown editor - leverage LLMs with your documents
...The project focuses on providing a fast, lightweight environment where users can create structured notes, manage personal knowledge bases, and interact with AI tools to summarize or expand their content. Instead of functioning purely as a document editor, RocketNotes integrates AI capabilities that assist with tasks such as generating insights, organizing ideas, and improving written content. The system is designed with productivity workflows in mind, allowing users to build interconnected notes and maintain organized collections of information. ... -
22
DecryptPrompt
Summarize Prompt & LLM papers, open source data & models
DecryptPrompt is an open-source research repository dedicated to organizing and summarizing academic research related to prompts and large language models. The project collects papers, technical reports, and research materials that explore prompting techniques, model architectures, and reasoning strategies used in modern AI systems. It serves as a structured knowledge base where developers and researchers can quickly find key papers about topics such as chain-of-thought reasoning, prompt... -
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VideoRAG
"VideoRAG: Chat with Your Videos
VideoRAG is a retrieval-augmented generation (RAG) framework tailored for video content that enables AI systems to answer questions, summarize, and reason over long videos by combining visual embeddings with contextual search. The system works by first breaking video into clips, extracting visual and audio-textual features, and indexing them into embeddings, then using an LLM with a retriever to pull relevant segments on demand. When a user query is received, VideoRAG locates semantically relevant moments in the video using the embedding index, retrieves associated clips or transcripts, and feeds them to a generative model to produce accurate, grounded answers or summaries. ... -
24
NG-ALAIN
NG-ZORRO admin panel front-end framework
...Detailing functions to allow users to focus more on business. With the continuous feedback of the "designer", it will continue to iterate, gradually precipitate and summarize more design patterns and corresponding code implementations, and elaborate on the best practices of middle and back-end product templates/components/business scenarios, and I look forward to your participation. and co-build. -
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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
...These examples show how different optimization techniques influence performance on modern GPU hardware and allow readers to experiment with real implementations. The repository also contains extensive learning notes that summarize CUDA programming concepts, GPU architecture details, and performance engineering strategies.
