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Source channel @githubtrending · Post #15168 · Sep 25

#python#ai#context#embedded#faiss#knowledge_base#knowledge_graph#llm#machine_learning#memory#nlp#offline_first#opencv#python#rag#retrieval_augmented_generation#semantic_search#vector_database#video_processing Memvid lets you store millions of text pieces inside a single MP4 video file using QR codes, making your data 50-100 times smaller than usual databases. You can search this video instantly in under 100 milliseconds without needing servers or internet after setup. It works offline, is easy to use with simple Python code, and supports PDFs and chat with your data. The upcoming version 2 will add features like continuous memory updates, shareable capsules, fast local caching, and better video compression, making your AI memory smarter, faster, and more flexible. This means you get a powerful, portable, and efficient way to manage and search huge knowledge bases quickly and easily. https://github.com/Olow304/memvid

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Data Science Jobs

@datasciencejobs · Post #2701 · 04/28/2025, 03:03 PM

#LangChain#LangGraph#LLM#AI#вакансии Друзья, всем привет! Ищем Автора для разработки текстового асинхронного курса по фреймворкам LangChain и LangGraph для действующих специалистов DS уровня Jun+. О нас: Standard Data – проектируем и реализуем образовательные решения под заказ крупных компаний в сферах ИИ, дата-инжиниринга и веб-разработки. Кого ищем: Data Scientist уровней middle и senior для создания текстового курса. Ожидания от кандидата: • Опыт работы с LLM в коммерческих проектах от 1 года; • Опыт работы в Data Science от 1,5 лет; • Высшее профильное образование; • Глубокое знание Python и интересуешься языковыми моделями и машинным обучением; • Желание делиться знаниями. Что нужно делать: • Разрабатывать уроки для курса по фреймворкам LangChain и LangGraph; • Писать текстовые материалы; • Работать в команде с тех-лидом, редактором и дизайнером. Что мы предлагаем: • Вознаграждение за один урок (3-5 страниц текста в Google Документах): 7к - 12к; • Гибкий график; • Сумма вознаграждения возможна и больше, всё зависит от опыта, публикаций и результатов собеседования; • Классную команду единомышленников. Ждем тебя в нашей команде, пишите в тг, или сразу кидайте резюме: @KaterinkaGl _____ За успешную рекомендацию по традиции бонус! Суммарно 15к: при прохождении тестового 5к, еще 10к. после 2 месяцев хорошей работы. Если у тебя классный кандидат с большим опытом, то пишите в ЛС, согласуем другой бонус!

GitHub Trends

@githubtrending · Post #15565 · 03/16/2026, 11:30 AM

#python#ai#deepagents#langchain#langgraph Deep Agents is a ready-to-use AI agent framework that comes with built-in planning, file management, and task delegation tools. It breaks down complex tasks into manageable steps, maintains context across conversations, and can spawn specialized sub-agents to handle focused work independently. You benefit from getting a working agent immediately without building from scratch, while retaining full customization options for your specific needs. The framework handles context management automatically, making it ideal for multi-step projects that traditional agents struggle with. https://github.com/langchain-ai/deepagents

GitHub Trends

@githubtrending · Post #15419 · 01/17/2026, 09:30 AM

#python#agent#ai#aippt#editable_pptx#langgraph#paper2slides#ppt_generator Paper2Any turns paper PDFs, images, or text into editable diagrams, technical roadmaps, experiment plots, PPT slides, and more with one click. Key tools include Paper2Figure for scientific visuals, Paper2PPT for custom decks with table extraction, PDF2PPT for layout-perfect conversions, and AI beautification. Install via GitHub on Python 3.11+, Linux preferred; try online demo or scripts. You save hours recreating figures or slides for research, talks, or reports, getting pro-quality, customizable outputs fast. https://github.com/OpenDCAI/Paper2Any

GitHub Trends

@githubtrending · Post #15523 · 02/25/2026, 12:30 PM

#typescript#agent#agentic#agentic_framework#agentic_workflow#ai#ai_agents#bytedance#deep_research#harness#langchain#langgraph#langmanus#llm#multi_agent#nodejs#podcast#python#superagent#typescript DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge. https://github.com/bytedance/deer-flow

GitHub Trends

@githubtrending · Post #14662 · 05/02/2025, 12:00 PM

#typescript#aceternity_ui#agent#agents#ai#chrome_extension#extension#fastapi#glean#langchain#langgraph#nextjs#nextjs15#notebooklm#notion#ollama#perplexity#python#rag#slack#typescript SurfSense is a highly customizable AI research tool that helps you organize and search your personal knowledge base. It connects to many external sources like search engines, Slack, Notion, YouTube, and GitHub. You can upload various file types and interact with your saved content using natural language. SurfSense provides cited answers and supports local AI models, making it a powerful tool for research. It's also self-hostable and open-source, allowing you to control your data and customize it as needed. This helps you manage information more efficiently and privately. https://github.com/MODSetter/SurfSense