MineContext

volcengineApache-2.0更新放缓

主动感知上下文的 AI 助手,结合上下文工程与 ChatGPT Pulse 思路,自动收集并组织相关信息,为对话提供持续记忆和主动提醒。

MineContext is your proactive context-aware AI partner(Context-Engineering+ChatGPT Pulse)

v0.1.8发布于 2026-01-28 09:51 UTC5,546star414fork同步于 2026-11-10 11:35 UTC

怎么上手

由 README 提炼,执行前请确认
git clone https://github.com/volcengine/MineContext.git
cd MineContext
uv sync
uv run opencontext start
硬件要求按 README 说明

README 未说明具体显存或 GPU 型号要求;支持通过 LMStudio 运行本地模型,也可使用豆包、OpenAI 等云端 API。

下载:源码 zip·GitHub Releases(安装包)本站不镜像安装包

项目说明

由 README 自动翻译提炼

开源主动式上下文感知 AI 伙伴,通过截屏理解你的数字世界并主动推送洞察与总结

主动感知上下文的 AI 助手,结合上下文工程与 ChatGPT Pulse 思路,自动收集并组织相关信息,为对话提供持续记忆和主动提醒。

核心能力

  • 截屏采集并理解屏幕内容作为上下文来源
  • 主动推送日报周报、提示与待办到首页
  • 按需智能浮现相关上下文辅助创作
  • 覆盖多模态数据采集处理存储检索全生命周期
  • 本地优先存储,支持 OpenAI 协议本地模型

容易踩的坑

首次运行需安装后端环境,约需两分钟;前端依赖安装不支持国内 PyPI 镜像,需先执行 pip config unset global.index-url;需自行准备豆包或 OpenAI 兼容的 API Key 并激活视觉语言模型。

内容由模型根据 README 生成,可能不完整或不准确,以官方文档为准。看原文 README

最近发版

5 个版本v0.1.8
  1. v0.1.8最新正式版2026-01-28 · 2026-01-28 09:51 UTC

    fix

    modify doubao embedding model

  2. v0.1.72025-12-25 · 2025-12-25 06:53 UTC
    查看更新说明

    fix

    Model validation pop-up issue

    feat

    Using minecontext heatmaps

  3. 0.1.6v0.1.62025-11-18 · 2025-11-18 07:26 UTC
    查看更新说明

    fixed

    After modifying the prompt in version 0.1.5, some models performed poorly, so this modification was rolled back in version 0.1.6.

  4. 0.1.5v0.1.5:Granite2025-11-14 · 2025-11-14 10:27 UTC
    查看更新说明

    What's Changed in Version Granite

    Release Period: November 1, 2025 - November 14, 2025

    Just as Granite is renowned for its immense durability and enduring presence, this update establishes a new foundation of stability and seamless experience for our product.

    Stability & Trust: The exceptional hardness of Granite symbolizes the robust security and trust brought by Apple Notarization, eliminating the need for command-line workarounds and ensuring a solid, reliable installation.

    Seamless Continuity: The enduring nature of Granite reflects the Automatic Updates and Chat History Saving features. They work together as the persistent bedrock, ensuring your workflow and creative conversations are maintained effortlessly across versions, without interruption or loss.


    ✨ New Features

    feat: Build is now notarized by Apple, eliminating the need for command-line permission overrides in subsequent versions.

    feat: Introduced automatic update checks, enabling seamless version upgrades without requiring full re-downloads. img_v3_02s1_ecc8c70f-98f0-46c8-842d-d76815514b0g

    feat: Conversation history is now preserved across both Home and Creation pages.

    feat: Debug information is automatically saved in the background during operations.

  5. 0.1.4v0.1.4:Opal2025-11-01 · 2025-11-01 01:11 UTC
    查看更新说明

    What's Changed in Version Opal

    Release Period: October 24, 2025 - October 31, 2025

    Just like the Opal gemstone reveals a dazzling play of colors from different angles, this update brings the internal processes of our product to life with clarity and brilliance.

    Visualization: The "play-of-color" in Opal symbolizes how we transform the previously hidden, complex intermediate processes into dynamic, intuitive, and easily understandable visual information.

    Background Operation: The inherent body color of the Opal represents the stable, continuous background services (like MineContext), which serve as the essential foundation that makes all the brilliant visual effects possible.


    ✨ New Features

    • feat: Added tray icon controls on Windows and macOS. You can choose to continue or stop recording, and recording persists even after closing the window.

    • feat: Recording UI now shows real-time recording status, including how many images have been processed.

    • refactor: Rebuilt the screenshot processing module. Switched from parsing multiple images in a single pass to coroutine-based concurrent parsing of single images with merging, improving parsing accuracy.

    • feat: Improved the content quality of daily reports.

    • feat: On Windows, added support for choosing a custom installation data directory.

      🐛 Bug Fixes

      • bug: fix settings page API
      • bug: fix screen process and add log

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    README 原文

    未翻译

    MineContext: Create with Context, Clarity from Chaos

    An open-source, proactive context-aware AI partner, dedicated to bringing clarity and efficiency to your work, study and creation.

    中文 / English

    Community Best Practice · Report Issues · Feedback


    👋 Join our WeChat / Lark / Red Note Group

    🌍 Join our Discord Group

    🖥️ Download for Mac · 💻 Download for Windows

    Table of Contents

    🔗 Related Project: Check out OpenViking - An open-source Context Database designed for AI Agents. OpenViking unifies Memories, Resources, and Skills through a "file system paradigm", providing the infrastructure layer for sophisticated context management.

    👋🏻 What is MineContext

    MineContext is a proactive context-aware AI partner. By utilizing screenshots and content comprehension (with future support for multi-source multimodal information including documents, images, videos, code, and external application data), it can see and understand the user's digital world context. Based on an underlying contextual engineering framework, it actively delivers high-quality information such as insights, daily/weekly summaries, to-do lists, and activity records.

    feature.gif

    🚀 Key Features

    MineContext focuses on four key features: effortless collection, intelligent resurfacing, proactive delivery, and a context engineering architecture.

    1. 📥 Effortless Collection Capable of gathering and processing massive amounts of context. Designed storage management enables extensive collection without adding mental burden.
    2. 🚀 Proactive Delivery Delivers key information and insights proactively in daily use. It extracts summarized content from your context—such as daily/weekly summaries, tips, and todos—and pushes them directly to your homepage.
    3. 💡 Intelligent Resurfacing Surfaces relevant and useful context intelligently during creation. Ensures assisted creativity without overwhelming you with information.
    4. 🎯 Context Engineering Architecture Supports the complete lifecycle of multimodal, multi-source data—from capture, processing, and storage to management, retrieval, and consumption—enabling the generation of six types of intelligent context.

    🔏 Privacy Protection

    Local-First

    MineContext places a high priority on user privacy. By default, all data is stored locally in the following path to ensure your privacy and security.

    ~/Library/Application Support/MineContext/Data
    

    Local AI model

    In addition, we support custom model services based on the OpenAI API protocol. You can use fully local models in MineContext, ensuring that any data does not leave your local environment.

    🏁 Quick Start

    1. Installation

    Click Github Latest Release to Download

    Download APP

    Note: Starting from v0.1.5, MineContext supports Apple notarization, so you no longer need to disable the quarantine attribute. If you're using an older version, please refer to the previous documentation for instructions.

    2. Enter Your API Key

    After the application launches, please follow the prompts to enter your API key. (Note: On the first run, the application needs to install the backend environment, which may take about two minutes).

    We currently support services from Doubao, OpenAI, and custom models. This includes any local models or third-party model services that are compatible with the OpenAI API format.

    We recommend using LMStudio to run local models. It provides a simple interface and powerful features to help you quickly deploy and manage them.

    Considering both cost and performance, we recommend using the Doubao model. The Doubao API Key can be generated in the API Management Interface.

    After obtaining the Doubao API Key, you need to activate two models in the Model Activation Management Interface: the Visual Language Model and the Embedding Model.

    • Visual Language Model: Doubao-Seed-1.6-flash doubao-vlm-model

    • Embedding Model: Doubao-embedding-vision doubao-emb-model

    The following is the filling process after obtaining the API Key:

    Enter API Key

    3. Start Recording

    Enter [Screen Monitor] to enable the system permissions for screen sharing. After completing the setup, you need to restart the application for the changes to take effect. Enable-Permissions

    After restarting the application, please first set your screen sharing area in [Settings], then click [Start Recording] to begin taking screenshots. Screen-Settings

    4. Forget it

    After starting the recording, your context will gradually be collected. It will take some time to generate value. So, forget about it and focus on other tasks with peace of mind. MineContext will generate to-dos, prompts, summaries, and activities for you in the background. Of course, you can also engage in proactive Q&A through [Chat with AI].

    5. Backend Debugging

    MineContext supports backend debugging, which can be accessed at http://localhost:1733.

    1.View Token Consumption and Usage 后台调试1

    2.Configure Interval for Automated Tasks 后台调试2

    3.Adjust System Prompt for Automated Tasks 后台调试3

    🎃 Contribution Guide

    🎨 Frontend Architecture

    The MineContext frontend is a cross-platform desktop application built with Electron, React, and TypeScript, providing a modular, maintainable, and high-performance foundation for desktop development.

    Core Tech Stack

    TechnologyDescription
    ElectronAllows for the development of cross-platform desktop applications using web technologies.
    ReactA component-based UI library for building dynamic user interfaces.
    TypeScriptProvides static type checking to enhance code maintainability.
    ViteA modern frontend build tool optimized for Electron.
    Tailwind CSSA utility-first CSS framework for rapid and consistent UI styling.
    pnpmA fast and efficient package manager suitable for monorepo projects.

    Core Architecture

    The project follows a standard Electron architectural design, clearly separating the code for the main process, preload scripts, and renderer process to ensure security and maintainability.

    frontend/
    ├── src/
    │ ├── main/     # Electron main process (window management, lifecycle, IPC)
    │ ├── preload/  # Preload script, securely bridging Node APIs and the renderer process
    │ └── renderer/ # React frontend interface (renderer process)
    │
    ├── packages/
    │ └── shared/   # Common utilities, IPC channels, logging, and constant definitions
    │
    ├── build/      # Build resources (icons, platform configurations)
    ├── dist/       # Build artifacts generated by electron-builder
    ├── externals/  # External dependencies (Python scripts, binaries, etc.)
    ├── resources/  # Static assets (icons, templates, images)
    └── scripts/    # Development and build helper scripts
    
    1. Main Process (src/main/) is responsible for:

      • Managing application windows
      • Handling lifecycle events (startup, quit, activate)
      • Establishing secure IPC communication
      • Integrating with backend services (Python and system APIs)
    2. Preload Script (src/preload/) is responsible for:

      • Securely exposing Node.js APIs to the renderer process
      • Handling IPC communication with the main process
      • Implementing cross-process resource access
    3. Renderer Process (src/renderer/) is responsible for:

      • Implementing the user interface with React
      • Managing global state with Jotai and Redux
      • Utilizing an efficient styling system based on Tailwind CSS
      • Implementing dynamic loading and performance optimization mechanisms
    4. Build and Packaging are responsible for:

      • electron-vite.config.ts — Configures the build logic for both the main and renderer processes (aliases, plugins, etc.).
      • electron-builder.yml — Defines packaging and distribution configurations for Windows, macOS, and Linux.

    💻 Frontend Usage

    Build Backend

    Before starting frontend development, you need to build the backend first:

    uv sync
    source .venv/bin/activate
    ./build.sh
    

    Install Dependencies

    Due to package version issues, using a domestic PyPI mirror is not currently supported. Please run the following command to ensure you are using the original PyPI source:

    pip config unset global.index-url
    cd frontend
    pnpm install
    

    Development and Debugging

    During local development, it is normal for the screen capture area selection to be slow. Please wait, as this issue does not exist in the packaged application.

    pnpm dev
    

    Application Packaging

    To build APP for macOS:

    pnpm build:mac
    # Data Path
    # ~/Library/Application\ Support/MineContext
    

    The executable files generated by the packaging process will be stored in the MineContext/frontend/dist directory.

    🏗️ Backend Architecture

    MineContext adopts a modular, layered architecture design with clear separation of concerns and well-defined responsibilities for each component.

    Core Architecture Components

    opencontext/
    ├── server/             # Web server and API layer
    ├── managers/           # Business logic managers
    ├── context_capture/    # Context acquisition modules
    ├── context_processing/ # Context processing pipeline
    ├── context_consumption/# Context consumption and generation
    ├── storage/            # Multi-backend storage layer
    ├── llm/               # LLM integration layer
    ├── tools/             # Tool system
    └── monitoring/        # System monitoring
    

    Layer Responsibilities

    1. Server Layer (server/)

      • FastAPI-based RESTful API
      • WebSocket support for real-time communication
      • Static file serving and template rendering
    2. Manager Layer (managers/)

      • CaptureManager: Manages all context capture sources
      • ProcessorManager: Coordinates context processing pipeline
      • ConsumptionManager: Handles context consumption and generation
      • EventManager: Event-driven system coordination
    3. Context Capture Layer (context_capture/)

      • Screenshot monitoring
      • Document monitoring
      • Extensible capture interface for future sources
    4. Processing Layer (context_processing/)

      • Document chunking strategies
      • Entity extraction and normalization
      • Context merging and deduplication
      • Multi-modal content processing (text, images)
    5. Storage Layer (storage/)

      • Multi-backend support (SQLite, ChromaDB)
      • Vector storage for similarity search
      • Unified storage interface
    6. LLM Integration (llm/)

      • Support for multiple LLM providers (OpenAI, Doubao)
      • VLM (Vision-Language Model) integration
      • Embedding generation services

    🚀 Backend Usage

    Installation

    We recommend using uv for fast and reliable package management:

    # Clone repository
    git clone https://github.com/volcengine/MineContext.git
    cd MineContext
    
    # Install uv (if not already installed)
    curl -LsSf https://astral.sh/uv/install.sh | sh
    
    # Sync dependencies (automatically creates virtual environment)
    uv sync
    

    Configuration

    1. Basic Configuration (config/config.yaml):
    server:
      host: 127.0.0.1
      port: 8765
      debug: false
    
    embedding_model:
      provider: doubao # options: openai, doubao
      api_key: your-api-key
      model: doubao-embedding-vision-250615
    
    vlm_model:
      provider: doubao # options: openai, doubao
      api_key: your-api-key
      model: doubao-seed-1-6-flash-250828
    
    capture:
      enabled: true
      screenshot:
        enabled: true # enable screenshot capture
        capture_interval: 5 # capture interval in seconds
    
    1. Prompt Templates (config/prompts_*.yaml):
      • prompts_en.yaml: English prompt templates
      • prompts_zh.yaml: Chinese prompt templates

    Running the Server

    # Start with default configuration
    uv run opencontext start
    
    # Start with custom config
    uv run opencontext start --config /path/to/config.yaml
    
    # Start with custom port (useful for avoiding conflicts)
    uv run opencontext start --port 1733
    

    Available Options:

    • --config: Path to configuration file
    • --host: Host address (default: from config or localhost)
    • --port: Port number (default: from config or 1733)

    Priority: Command-line arguments > Config file > Default values

    Alternatively, you can activate the virtual environment manually:

    source .venv/bin/activate  # On Windows: .venv\Scripts\activate
    pip install -e .
    opencontext start --port 1733
    

    💎 The Philosophy Behind the Name

    The naming of MineContext also reflects the team's ingenuity. It signifies both "my context" and "mining context." It draws inspiration from the core philosophy of Minecraft—openness, creativity, and exploration.

    If vast amounts of context are like scattered "blocks," then MineContext provides a "world" where you can freely build, combine, and create. Users can reimagine and create new content based on the collected massive context and generate high-quality information.

    🎯 Target User

    Target User CategorySpecific Roles/IdentitiesCore Needs/Pain Points
    Knowledge WorkersResearchers, AnalystsNavigating vast amounts of information, improving information processing and analysis efficiency
    Content CreatorsWriters, BloggersCraving endless inspiration, optimizing content creation workflows
    Lifelong LearnersStudents, ResearchersBuilding systematic knowledge systems, efficiently managing and connecting learning materials
    Project ManagersProduct Managers, Project ManagersIntegrating multi-source information and data, ensuring project alignment and decision-making efficiency

    🔌 Context-Source

    We will prioritize the expansion of Context Sources according to the following plan, and we warmly welcome everyone to actively contribute code to our efforts.

    • P0: Digital life and public information loop (PC screen capture and link upload)
    • P1: Personal text context loop (file upload, file tracking)
    • P2: AI and common office context loop (MCP, meeting notes)
    • P3: High-quality information acquisition loop (DeepResearch and RSS)
    • P4: Personal deep context loop (WeChat, QQ chat data acquisition, mobile screenshots)
    • P5: Physical world context loop (smart wearable synchronization, smart glasses synchronization)
    Context Capture CapabilityContext SourcePriorityCompletion Status
    Screen ScreenshotUser PC InformationP0✅
    Note EditingApplication Internal Creation InformationP0✅
    Link UploadInternet InformationP0
    File UploadStructured DocumentsP1
    File UploadUnstructured DocumentsP1
    File UploadImagesP1
    File UploadAudioP4
    File UploadVideoP4
    File UploadCodeP4
    Browser ExtensionAI Conversation RecordsP2
    Browser ExtensionRefined Internet InformationP5
    Meeting RecordsMeeting InformationP2
    RSSConsultation InformationP3
    Deep ResearchHigh-Quality Research AnalysisP3
    Application MCP/APIPayment RecordsP4
    Application MCP/APIResearch PapersP3
    Application MCP/APINewsP4
    Application MCP/APIEmailsP4
    Application MCP/APINotionP2
    Application MCP/APIObsidianP2
    Application MCP/APISlackP4
    Application MCP/APIJiraP4
    Application MCP/APIFigmaP2
    Application MCP/APILinearP4
    Application MCP/APITodoistP4
    Memory Bank Migration ImportUser MemoryP4
    WeChat Data CaptureWeChat Chat HistoryP4
    QQ Data CaptureQQ Chat HistoryP4
    Mobile Screenshot MonitorUser Mobile End InformationP4
    Smart Glasses Data SyncPhysical World Interaction RecordsP5
    Smart Bracelet Data SyncPhysiological DataP5

    🆚 Comparison with Familiar Application

    MineContext vs ChatGPT Pulse

    • 🖥️ Comprehensive Digital Context: MineContext captures your entire digital workflow by reading from screen screenshots, providing a rich, visual context of your daily activities and applications. ChatGPT Pulse, in contrast, is limited to the context of a single text-based conversation.
    • 🔒 Local-First Data & Privacy: Your data is processed and stored entirely on your local device, ensuring complete privacy and security without relying on cloud servers. ChatGPT Pulse requires data to be sent to and stored on OpenAI's servers.
    • 🚀 Proactive & Diverse Insights: MineContext delivers a wider variety of intelligent, auto-generated content—including daily summaries, actionable todos, and activity reports—not just simple tips. ChatGPT Pulse primarily offers reactive assistance within the chat interface.
    • 🔧 Open Source & Customizable: As an open-source project, MineContext allows developers to freely inspect, modify, and build upon the codebase for complete customization. ChatGPT Pulse is a closed, proprietary product with no option for modification.
    • 💰 Cost-Effective API Usage: MineContext avoids the need for a costly $200/month Pro subscription by allowing you to use your own API key, giving you full control over your spending. ChatGPT Pulse's advanced features are locked behind its expensive premium tier.

    MineContext vs Dayflow

    • 💡 Richer, Proactive Insights: MineContext delivers a more diverse range of automated, intelligent content—including concise summaries, actionable todos, and contextual tips—going beyond basic activity tracking. DayFlow primarily focuses on logging user activity.
    • 🧠 Context-Aware Q&A & Creation: MineContext enables you to ask questions and generate new content based on your captured context, unlocking wider application scenarios like content drafting and project planning. DayFlow is limited to passive activity recording and review.
    • ✨ Superior Activity Generation & Experience: MineContext produces activity records with greater clarity and detail, featuring a more intuitive and interactive dashboard for a seamless user experience. DayFlow's activity logs are more basic with limited interactivity.

    👥 Community

    Community and Support

    • GitHub Issues: Errors and issues encountered while using MineContext.
    • Email Support: Feedback and questions about using MineContext.
    • WeChat Group: Discuss SwanLab usage and share the latest AI technologies.

    Star History

    Star History Chart

    📃 License

    This repository is licensed under the Apache 2.0 License.