๐ Meet LearningCircuit/local-deep-research: a gem from today's GitHub trending list.
๐ https://github.com/LearningCircuit/local-deep-research
๐ ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.
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Local Deep Research is an AI-powered research assistant that runs locally for privacy, allowing you to use any Large Language Model (LLM) and build your own searchable knowledge base. With multiple research strategies and proper citations, it helps you perform deep, agentic research across the web, academic papers, and your own documents.
The
The tool builds your knowledge base by downloading sources, extracting text, indexing, and making them searchable. It features SQLCipher encryption with AES-256, ensuring your data stays private.
Security is a top priority, with static analysis, dependency scanning, and container security measures in place. The repository includes a Security Policy and a Security Review Process to ensure transparency.
In short, Local Deep Research is a powerful, private, and secure research assistant that helps you take control of your data and research. You own your data and can see exactly how it works, making it an ideal solution for anyone looking for a reliable and trustworthy research tool - Empowering your research, one query at a time.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/LearningCircuit/local-deep-research
๐ ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.
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Local Deep Research is an AI-powered research assistant that runs locally for privacy, allowing you to use any Large Language Model (LLM) and build your own searchable knowledge base. With multiple research strategies and proper citations, it helps you perform deep, agentic research across the web, academic papers, and your own documents.
The
local-deep-research repository provides a Docker-based solution, with options for Docker Run and Docker Compose, as well as a pip install method for Windows, macOS, and Linux. You can choose from 20+ research strategies, including the new LangGraph Agent Strategy, which adaptively switches between search engines.The tool builds your knowledge base by downloading sources, extracting text, indexing, and making them searchable. It features SQLCipher encryption with AES-256, ensuring your data stays private.
Security is a top priority, with static analysis, dependency scanning, and container security measures in place. The repository includes a Security Policy and a Security Review Process to ensure transparency.
In short, Local Deep Research is a powerful, private, and secure research assistant that helps you take control of your data and research. You own your data and can see exactly how it works, making it an ideal solution for anyone looking for a reliable and trustworthy research tool - Empowering your research, one query at a time.
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๐ง Channel: https://t.me/GithubRe
Github Top Repositories
Photo
๐ฏ lobehub/lobehub landed on trending. Worth a proper look.
๐ https://github.com/lobehub/lobehub
๐ The ultimate space for work and life โ to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level โ enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.
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LobeHub is a revolutionary platform that enables humans and agents to co-evolve, transforming the way we work and interact with AI. The platform offers a range of key features, including the ability to create, collaborate, and evolve with agent teammates that grow with you.
To get started, users can join the LobeHub community and explore the various features and tools available. The platform provides a
Some of the technical highlights of LobeHub include its
LobeHub is designed for a wide range of users, from professional developers to enthusiastic users, and offers a user-friendly product ecosystem that is open, transparent, and constantly evolving.
In a nutshell, LobeHub is the future of human-AI collaboration - and it's here to revolutionize the way we work and interact with AI.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/lobehub/lobehub
๐ The ultimate space for work and life โ to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level โ enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.
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LobeHub is a revolutionary platform that enables humans and agents to co-evolve, transforming the way we work and interact with AI. The platform offers a range of key features, including the ability to create, collaborate, and evolve with agent teammates that grow with you.
To get started, users can join the LobeHub community and explore the various features and tools available. The platform provides a
unified intelligence system, allowing users to access any model and modality, and a library of over 10,000+ skills and MCP-compatible plugins.Some of the technical highlights of LobeHub include its
Agent Builder, Agent Groups, and Personal Memory features, which enable users to build, collaborate, and learn with their agent teammates. The platform also supports local large language model (LLM) support, model visual recognition, and TTS & STT voice conversation.LobeHub is designed for a wide range of users, from professional developers to enthusiastic users, and offers a user-friendly product ecosystem that is open, transparent, and constantly evolving.
In a nutshell, LobeHub is the future of human-AI collaboration - and it's here to revolutionize the way we work and interact with AI.
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๐ง Channel: https://t.me/GithubRe
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Github Top Repositories
Photo
๐ Meet datawhalechina/hello-agents: a gem from today's GitHub trending list.
๐ https://github.com/datawhalechina/hello-agents
๐ ๐ ใไป้ถๅผๅงๆๅปบๆบ่ฝไฝใโโไป้ถๅผๅง็ๆบ่ฝไฝๅ็ไธๅฎ่ทตๆ็จ
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Hello-Agents is a comprehensive open-source tutorial on building AI agents from scratch. The project aims to provide a systematic guide to constructing intelligent systems, from basic theories to practical applications.
Key features of the project include:
- A structured approach to learning, covering the fundamentals of AI agents, language models, and their applications
-
- A community-driven approach, with opportunities for contributors to share their knowledge and experiences
The project is suitable for AI developers, software engineers, students, and self-learners with basic Python programming skills and a conceptual understanding of large language models.
The project's technical highlights include:
-
- Implementing memory and retrieval systems, context engineering, and communication protocols
- Training and evaluating AI models using Agentic-RL and other advanced techniques
By following the tutorial, learners can gain a deep understanding of AI agents and their applications, and develop the skills to construct their own intelligent systems.
In short, Hello-Agents is your one-stop-shop for learning AI agent development - so get building, and become an AI agent master!
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/datawhalechina/hello-agents
๐ ๐ ใไป้ถๅผๅงๆๅปบๆบ่ฝไฝใโโไป้ถๅผๅง็ๆบ่ฝไฝๅ็ไธๅฎ่ทตๆ็จ
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Hello-Agents is a comprehensive open-source tutorial on building AI agents from scratch. The project aims to provide a systematic guide to constructing intelligent systems, from basic theories to practical applications.
Key features of the project include:
- A structured approach to learning, covering the fundamentals of AI agents, language models, and their applications
-
hands-on exercises and projects to help learners gain practical experience- A community-driven approach, with opportunities for contributors to share their knowledge and experiences
The project is suitable for AI developers, software engineers, students, and self-learners with basic Python programming skills and a conceptual understanding of large language models.
The project's technical highlights include:
-
constructing AI agents using popular frameworks and tools
- Implementing memory and retrieval systems, context engineering, and communication protocols
- Training and evaluating AI models using Agentic-RL and other advanced techniques
By following the tutorial, learners can gain a deep understanding of AI agents and their applications, and develop the skills to construct their own intelligent systems.
In short, Hello-Agents is your one-stop-shop for learning AI agent development - so get building, and become an AI agent master!
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๐ง Channel: https://t.me/GithubRe
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๐ flutter/skills caught my eye on GitHub Trending today.
๐ https://github.com/flutter/skills
๐ No description.
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The Flutter Skills repository provides a collection of skills for happy path Flutter app development workflows. These skills offer tailored instructions to reduce mistakes and ensure agents complete tasks following best practices. You can install all skills into your project using the command
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/flutter/skills
๐ No description.
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The Flutter Skills repository provides a collection of skills for happy path Flutter app development workflows. These skills offer tailored instructions to reduce mistakes and ensure agents complete tasks following best practices. You can install all skills into your project using the command
npx skills add flutter/skills --skill '*' --agent universal. The available skills include flutter-add-integration-test, flutter-add-widget-preview, and flutter-apply-architecture-best-practices, among others. Each skill has a specific use case, such as adding integration tests or creating interactive widget previews. To update the skills, run the command npx skills update. The repository is maintained by the Flutter team and is suitable for developers looking to streamline their workflow. Take your Flutter development to the next level with these skills - automate repetitive tasks and focus on what matters.โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
๐ง Channel: https://t.me/GithubRe
โค2
๐ Augani/openreel-video caught my eye on GitHub Trending today.
๐ https://github.com/Augani/openreel-video
๐ OpenReel Video - Professional browser-based video editor. Open source CapCut alternative. 100% browser-based, no installation, no cloud uploads, no watermarks.
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OpenReel Video is a free, open-source, browser-based video editor that runs entirely client-side, offering professional-grade video editing without the need for expensive software or cloud processing. With key features like a multi-track timeline, keyframe animations, color grading, and audio effects, it's an alternative to popular video editing software.
The editor is built with
Takeaway: OpenReel Video is revolutionizing video editing by making it free, open-source, and accessible to everyone, forever.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/Augani/openreel-video
๐ OpenReel Video - Professional browser-based video editor. Open source CapCut alternative. 100% browser-based, no installation, no cloud uploads, no watermarks.
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OpenReel Video is a free, open-source, browser-based video editor that runs entirely client-side, offering professional-grade video editing without the need for expensive software or cloud processing. With key features like a multi-track timeline, keyframe animations, color grading, and audio effects, it's an alternative to popular video editing software.
Try it live at openreel.video or run it locally by cloning the repository and installing dependencies. The editor is built with
React, TypeScript, WebCodecs, and WebGPU for smooth 4K editing and fast exports. It's suitable for anyone looking for a free, user-friendly, and feature-rich video editing solution.Takeaway: OpenReel Video is revolutionizing video editing by making it free, open-source, and accessible to everyone, forever.
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๐ง Channel: https://t.me/GithubRe
โค1
๐ฅ anthropics/financial-services is trending โ and it deserves your attention.
๐ https://github.com/anthropics/financial-services
๐ No description.
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The Claude for Financial Services GitHub repository provides a comprehensive set of tools and templates for financial services workflows, including investment banking, equity research, private equity, and wealth management. The repository offers reference agents, skills, and data connectors that can be installed as
Key features include:
- Agents: named, end-to-end workflow agents (e.g., Pitch Agent, Market Researcher) that can be installed and tuned to a firm's specific needs
- Vertical plugins: skill and command bundles for specific financial services verticals (e.g., investment banking, equity research)
- Data connectors: integrations with various data providers (e.g., Daloopa, Morningstar, S&P Global) via the Model Context Protocol (MCP)
To get started, users can install the repository as a
The target audience for this repository includes financial services professionals, developers, and IT administrators looking to automate and streamline their workflows using AI-powered tools.
In short, the Claude for Financial Services repository is a powerful toolkit for financial services firms looking to leverage AI and automation to boost productivity and efficiency - and the best part is, it's all customizable to how your firm works.
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๐ง Channel: https://t.me/GithubRe
๐ https://github.com/anthropics/financial-services
๐ No description.
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The Claude for Financial Services GitHub repository provides a comprehensive set of tools and templates for financial services workflows, including investment banking, equity research, private equity, and wealth management. The repository offers reference agents, skills, and data connectors that can be installed as
Claude Cowork plugins or deployed via the Claude Managed Agents API. Key features include:
- Agents: named, end-to-end workflow agents (e.g., Pitch Agent, Market Researcher) that can be installed and tuned to a firm's specific needs
- Vertical plugins: skill and command bundles for specific financial services verticals (e.g., investment banking, equity research)
- Data connectors: integrations with various data providers (e.g., Daloopa, Morningstar, S&P Global) via the Model Context Protocol (MCP)
To get started, users can install the repository as a
Claude Cowork plugin or deploy it via the Claude Managed Agents API. The repository also includes a Claude for Microsoft 365 install tool for provisioning the Claude add-in in a customized Microsoft 365 environment.The target audience for this repository includes financial services professionals, developers, and IT administrators looking to automate and streamline their workflows using AI-powered tools.
In short, the Claude for Financial Services repository is a powerful toolkit for financial services firms looking to leverage AI and automation to boost productivity and efficiency - and the best part is, it's all customizable to how your firm works.
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๐ง Channel: https://t.me/GithubRe
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