Search Results for "content analysis" - Page 2
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Showing 77 open source projects for "content analysis"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Wiseflow
Enhance any agent's browser use skill
Wiseflow is an open-source information extraction and knowledge discovery system designed to collect, filter, and organize valuable information from large volumes of online content. The platform continuously monitors specified sources such as websites, social platforms, and other digital channels to identify relevant data according to user-defined interests or topics. By combining web crawling, content parsing, and large language model analysis, the system extracts concise insights from raw information streams and converts them into structured data that can be stored or analyzed. ... -
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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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DeepWiki Open
AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories
DeepWiki Open is an open-source, AI-powered wiki generator that automatically creates fully navigable, richly structured wiki documentation for GitHub, GitLab, or Bitbucket repositories by combining code analysis, vector embeddings, retrieval-augmented generation (RAG), and visualization tools. Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and... -
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GitMCP
Turn any GitHub repository into an MCP documentation server for AI
...Its architecture retrieves documentation, analyzes code, and provides searchable access to repository information through semantic search and code analysis capabilities. -
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Vidi2
Large Multimodal Models for Video Understanding and Editing
Vidi is a family of large multimodal models developed for deep video understanding and editing tasks, integrating vision, audio, and language to allow sophisticated querying and manipulation of video content. It’s designed to process long-form, real-world videos and answer complex queries such as “when in this clip does X happen?” or “where in the frame is object Y during that moment?” — offering temporal retrieval, spatio-temporal grounding (i.e. locating objects over time + space), and even video question answering. Vidi targets applications like intelligent video editing, automated video search, content analysis, and editing assistance, enabling users to efficiently locate relevant segments and objects in hours-long footage. ... -
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OpenOCR
An Open-Source Toolkit for General-OCR Research and Applications
...Built on advanced OCR technologies such as SVTRv2 and UniRec-0.1B, OpenOCR delivers high accuracy while maintaining efficient inference performance. The toolkit supports both Chinese and English content, making it suitable for multilingual document analysis. OpenOCR includes training, evaluation, fine-tuning, and deployment tools, allowing users to customize models for specific OCR tasks. Its comprehensive ecosystem bridges academic research and industrial applications through reproducible benchmarks and commercial-grade OCR solutions. -
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Gemma 4 Browser Assistant
On-device AI agent Chrome extension powered by Transformers.js
Gemma 4 Browser Assistant is an open-source browser extension that embeds an AI assistant directly into the browsing experience, powered by on-device machine learning models. It uses Transformers.js and Gemma models to run inference locally in the browser, eliminating the need for external servers and preserving user privacy. The extension includes a side panel interface that allows users to interact with the AI while browsing, enabling tasks such as summarizing pages and answering... -
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Docling
Get your documents ready for gen AI
Docling is an open-source document processing toolkit built to prepare diverse content types for modern generative AI and data workflows. The project focuses on converting and parsing many document formats into a unified structured representation that downstream systems can easily consume. It supports advanced PDF understanding, including layout detection, table extraction, and reading order analysis, enabling high-fidelity document intelligence pipelines. -
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Skill Scanner
Security Scanner for Agent Skills
This repository is a public security-focused scanning tool intended to analyze and assess AI agent skills for potential issues, quality concerns, and vulnerabilities. It acts as a scanner that inspects Agent Skills packages to flag structural problems, inconsistencies, or security flaws before they are deployed or integrated into agent workflows. Because agent skills can contain executable instructions and logic, scanning them for risky patterns is essential to prevent inadvertent... -
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yek
Serialize repositories into LLM-ready context w/ smart prioritization
Yek is a Rust-based CLI tool designed to serialize text-based files from a repository or directory into a single structured output for large language model use. It scans projects using .gitignore rules to exclude irrelevant files and automatically filters out binary or oversized content. Yek prioritizes files based on Git history, placing more important content later in the output to align with how language models process context. Yek supports multiple directories, individual files, and glob patterns, making it flexible for different workflows. It can stream output when piped or save results to a temporary file, depending on usage. ... -
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Gitingest
Create prompt-friendly codebase digests from any Git repository URL
Gitingest is a developer utility that converts an entire Git repository into a structured, prompt-friendly text digest suitable for use with large language models. It analyzes a repository and produces a consolidated textual representation that includes the file structure and code content in an organized format. This makes it easier to provide meaningful code context when working with AI systems that require compact, readable inputs. Developers can generate these digests from either a local... -
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Code2Prompt
Convert codebases into structured prompts optimized for LLM analysis
code2prompt is an open source command line tool designed to convert an entire codebase into a structured prompt that can be easily used with large language models. It analyzes a project directory, gathers relevant source files, and formats them into a single prompt that includes the source tree and code content. This approach helps developers quickly provide full project context to AI models without manually copying files or assembling prompts. code2prompt is built in Rust and focuses on... -
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PapersGPT
A powerful Zotero AI and MCP plugin with ChatGPT, Gemini 3.1, Claude
...The plugin supports a wide range of state-of-the-art language models, including GPT, Claude, Gemini, and open-source alternatives, giving users flexibility in choosing performance, cost, and privacy trade-offs. One of its most powerful features is its ability to process large volumes of academic content quickly, enabling tasks such as literature reviews, theoretical analysis, and research synthesis to be completed significantly faster. It also supports multi-document querying, allowing users to compare findings across multiple papers and generate comprehensive overviews of research topics. -
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DeepSeek-OCR
Contexts Optical Compression
DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body... -
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Claude Code Skills & Plugins
232+ Claude Code skills & agent plugins for Claude Code, Codex
...It supports a wide range of use cases, from development to content generation. Overall, Claude Skills acts as a library of reusable expertise modules for AI systems. -
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GLM-4.6V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
GLM-4.6V represents the latest generation of the GLM-V family and marks a major step forward in multimodal AI by combining advanced vision-language understanding with native “tool-call” capabilities, long-context reasoning, and strong generalization across domains. Unlike many vision-language models that treat images and text separately or require intermediate conversions, GLM-4.6V allows inputs such as images, screenshots or document pages directly as part of its reasoning pipeline — and... -
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Dify
One API for plugins and datasets, one interface for prompt engineering
Dify is an easy-to-use LLMOps platform designed to empower more people to create sustainable, AI-native applications. With visual orchestration for various application types, Dify offers out-of-the-box, ready-to-use applications that can also serve as Backend-as-a-Service APIs. Unify your development process with one API for plugins and datasets integration, and streamline your operations using a single interface for prompt engineering, visual analytics, and continuous improvement.... -
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GitDiagram
AI tool that converts GitHub repositories into interactive diagrams
GitDiagram is an open source web application designed to help developers quickly understand the structure and architecture of GitHub repositories by automatically generating interactive diagrams. It analyzes repository metadata such as the file tree and project documentation to build a visual representation of how different components of a project relate to one another. It uses an AI-powered pipeline to interpret repository structure and transform that information into system design diagrams... -
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QAnything
Question and Answer based on Anything
QAnything is a local knowledge-base question-answering system designed to let users ask questions over many kinds of files and databases. It supports offline installation, making it useful for organizations that need private document analysis without sending data to external services. Users can upload local files and receive fast, reliable answers based on the indexed content. The system supports formats such as PDF, Word, PowerPoint, Excel, Markdown, email, text, images, CSV, and web links. Its retrieval process uses a two-stage vector and reranking approach to maintain answer quality as the knowledge base grows. ... -
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OpenSwarm
Claude code for everything except coding
...Instead of relying on one general-purpose assistant, it coordinates a team of specialized agents through an orchestrator. The included agents can handle research, data analysis, slide decks, documents, images, videos, scheduling, messaging, and other productivity tasks. It is designed for outputs like pitch decks, market research, SEO content, quarterly reports, launch campaigns, visual assets, and multimedia projects. The project can connect to external services through integrations and can be customized into purpose-specific swarms for areas such as SEO, sales, marketing, finance, customer support, or research. ... -
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Ultravox
Fast multimodal LLM for real-time voice interaction and AI apps
...Ultravox is optimized for low latency, achieving fast response times suitable for interactive voice agents and real-time applications. It supports use cases such as conversational AI agents, speech-to-speech translation, and analysis of spoken audio content. Ultravox also includes tooling and configuration systems for training, evaluation, and dataset integration. -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
...The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis. The repository integrates numerous popular machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, XGBoost, and Hugging Face. It aims to strike a balance between theoretical explanation and practical coding by demonstrating algorithms both from scratch and using established libraries. The content is organized into multiple sections covering topics such as clustering, regression, dimensionality reduction, recommender systems, and model evaluation. -
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ILLA Builder
Low-code platform allows you to build business apps
...Connect to your own data sources, including MySQL, PostgreSQL, and other databases, REST APIs, GraphQL, etc. Build CRUD apps in just one minute. Integrating AI agents into your app and empowering it with AI capabilities such as intelligent analysis, content generation, and more, without AI development skills. Use ILLA Flow to automate your workflow to ensure you always have the latest data and reduce repetitive tasks. -
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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
...These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence. The framework supports a wide range of use cases, including software development, machine learning research, financial analysis, and content production. It is designed to work with various AI tools and command-line agents, making it highly flexible and extensible. ClawTeam also includes monitoring tools such as dashboards and tmux-based views to observe agent activity and progress. -
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LLM Vision
Visual intelligence for your home.
LLM Vision is an open-source integration for Home Assistant that adds multimodal large language model capabilities to smart home environments. The project enables Home Assistant to analyze images, video files, and live camera feeds using vision-capable AI models. Instead of relying only on traditional object detection pipelines, it allows users to send prompts about visual content and receive contextual descriptions or answers about what is happening in camera footage. The system can process...
