# ⏱️ Dayflow for Windows **AI-powered time tracking and productivity analysis for Windows** [![Python](https://img.shields.io/badge/Python-3.10+-blue?logo=python&logoColor=white)](https://python.org) [![PySide6](https://img.shields.io/badge/GUI-PySide6-green?logo=qt&logoColor=white)](https://doc.qt.io/qtforpython/) [![License](https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey)](LICENSE) [![Platform](https://img.shields.io/badge/Platform-Windows%2010%2F11-0078D6?logo=windows&logoColor=white)](https://www.microsoft.com/windows) *Silent background recording → AI analysis → visual timeline* [![Download](https://img.shields.io/badge/⬇️_Download-EXE-brightgreen?style=for-the-badge)](https://github.com/SeiShonagon520/Dayflow/releases) [中文](README.md) | **English**

--- ## 🎯 What is Dayflow? **Dayflow** is an AI-powered time tracking tool for Windows. It quietly captures low-frequency screen activity and window context in the background, uses a vision model to infer what you are doing, and turns the result into a timeline, statistics dashboard, and reports so you can understand where your time actually goes. ### 💡 Who is it for? - People who want to know where their day went - People who want to review focus time, distractions, and work patterns - People who need automatic activity logs, daily reports, or weekly summaries - People who prefer passive tracking over manual timers ### 🏆 Key advantages | Advantage | Description | |-----------|-------------| | **Zero effort** | Start it and let AI handle activity recognition automatically | | **Low overhead** | 1 FPS recording + smart compression to keep background usage low | | **Local first** | Raw recordings stay on your machine and temporary chunks are cleaned up after analysis | | **Smart categories** | Automatically detects work / study / entertainment / social / rest | | **Visual review** | Timeline, statistics page, and HTML dashboard for different review styles | --- ## 🔐 Privacy, upfront Dayflow is designed around **local recording + cloud analysis + local storage**. ### 5 things you should know 1. **Full videos are not uploaded** Raw recording chunks stay on your local machine. 2. **Only a limited number of keyframes are sent for analysis** The current README describes up to 8 extracted frames per chunk being sent to the configured vision model. 3. **Analysis results are stored locally** Activities, settings, and statistics are saved in a local SQLite database. 4. **Temporary chunks are cleaned up automatically** After analysis, temporary recording files are deleted to reduce disk usage. 5. **You can pause recording for sensitive moments** Passwords, banking, private chats, or anything else sensitive can be handled by pausing recording first. ### Local data location ```text %LOCALAPPDATA%\Dayflow\ ├── dayflow.db # activities, settings, stats ├── dayflow.log # runtime logs ├── chunks\ # temporary recording chunks └── updates\ # downloaded updates ``` > 💡 If privacy is your first concern, read this section before enabling continuous recording. --- ## ✨ Main features | Feature | Description | |---------|-------------| | 🎥 **Low-power recording** | 1 FPS low-resource background capture | | 🪟 **Window tracking** | Uses Windows API to capture real app names and window titles | | 🤖 **AI analysis** | Vision LLM classifies screen activity automatically | | 📊 **Timeline view** | Clear daily activity review at a glance | | 📈 **Statistics dashboard** | Time distribution, productivity trends, week comparison | | 📊 **Web dashboard export** | Beautiful self-contained HTML report with charts | | 📧 **Email reports** | Automatic daily summaries and deeper analysis | | 🔄 **Auto update** | Check, download, and install new versions | | 🚀 **Auto start** | Launch on boot and minimize to tray | | 📥 **CSV export** | Export activity data for further analysis | | ⏸️ **Pause recording** | Pause when handling sensitive content | | 🎨 **Theme switching** | Dark / light themes with saved preferences | ### 🆕 Recent highlights #### v1.5.2 (2026-03) - Statistics page redesign with metric cards, donut chart, trend chart, heatmap, and week comparison - Activity cards can now be edited or deleted - Better visual polish across the UI #### v1.5.0 (2025-12) - Windows API window tracking for more accurate recognition - UI refresh: efficiency indicator bar, deep work badge, live recording duration, and more - Improved prompting and data processing logic --- ## 🖥️ Screenshots ### Timeline page ![Dayflow Timeline](assets/Dayflow_index.png) *Daily activity cards with time range, app, summary, and productivity score.* ### Statistics page ![Dayflow Statistics](assets/Dayflow_Statistics.png) *Dashboard-style overview with key metrics, distribution charts, heatmap, and comparisons.* ### Web dashboard #### Date selection ![Dashboard Date Selection](assets/Dayflow_Dashboard_Dialog.png) #### HTML report ![Web Dashboard](assets/Dayflow_Dashboard_Report.png) *Exported HTML dashboard that can be opened in a browser and shared directly.* ### Email reports #### Settings ![Email Settings](assets/Dayflow_Email_Settings.png) #### Examples

#### Deep analysis ![Deep Analysis Report](assets/Dayflow_Email_DeepAnalysis.png) ### Auto update / auto start ![Auto Update](assets/Dayflow_AutoUpdate.png) ![Auto Start](assets/Dayflow_AutoStart.png) --- ## ✅ README checklist covered in this revision - [x] Removed garbled text, typos, and broken directory names - [x] Reframed the opening so the project value is clearer - [x] Moved privacy information near the top - [x] Reduced feature overload and tightened the structure - [x] Added a roadmap section - [x] Added known limitations - [x] Clarified the current license choice - [x] Aligned the English README with the Chinese version - [x] Added a minimal Windows CI workflow --- ## 🚀 Quick start ### Requirements - Windows 10 / 11 (64-bit) - Python 3.10+ - [FFmpeg](https://ffmpeg.org/download.html) added to PATH ### Installation ```bash git clone https://github.com/SeiShonagon520/Dayflow.git cd Dayflow conda create -n dayflow python=3.11 -y conda activate dayflow pip install -r requirements.txt python main.py ``` ### Build as EXE (optional) ```bash pip install pyinstaller python build.py ``` Or simply double-click `build.bat`. ### Download prebuilt releases If you just want to use Dayflow without setting up Python locally: 1. Open [Releases](https://github.com/SeiShonagon520/Dayflow/releases) 2. Download the latest installer or archive 3. Extract it and run `Dayflow.exe` > 💡 For the first run, configure the API first and then start recording. --- ## 📖 Basic usage ### 1. Configure your API Go to **Settings** and fill in: - **API URL**: any OpenAI-compatible endpoint - **API Key** - **Model name**: a vision-capable model Then click **Test Connection** and **Save Config**. ### 2. Start recording - Click **Start Recording** - The app records at 1 FPS in the background - A video chunk is generated every 60 seconds - Keyframes are sent to your configured model service for analysis ### 3. Review your timeline Each card shows a time range, category, app, summary, and productivity score. ### 4. Optional features - **Email reports**: scheduled summaries and deeper analysis - **Auto start**: launch with Windows and minimize to tray - **Auto update**: check and install new versions - **System tray**: control recording without keeping the main window open --- ## 📁 Project structure ```text Dayflow/ ├── main.py ├── config.py ├── requirements.txt ├── build.py ├── build.bat ├── updater.py │ ├── core/ │ ├── types.py │ ├── recorder.py │ ├── window_tracker.py │ ├── llm_provider.py │ ├── analysis.py │ ├── email_service.py │ ├── updater.py │ ├── autostart.py │ ├── config_manager.py │ ├── log_manager.py │ ├── stats_collector.py │ └── dashboard_exporter.py │ ├── database/ │ ├── schema.sql │ ├── storage.py │ └── connection_pool.py │ ├── ui/ │ ├── main_window.py │ ├── timeline_view.py │ ├── stats_view.py │ ├── date_range_dialog.py │ └── themes.py │ ├── templates/ │ └── dashboard.html │ └── assets/ └── icon.ico ``` --- ## ⚙️ Configuration | Variable | Description | Default | |----------|-------------|---------| | `DAYFLOW_API_URL` | API endpoint | `https://apis.iflow.cn/v1` | | `DAYFLOW_API_KEY` | API key | (empty) | | `DAYFLOW_API_MODEL` | AI model | `qwen3-vl-plus` | --- ## 🛠️ Tech stack | Component | Technology | |-----------|------------| | GUI | PySide6 (Qt6) | | Screen capture | dxcam (DirectX) | | Video processing | OpenCV | | HTTP client | httpx (HTTP/2) | | Database | SQLite | | AI analysis | OpenAI-compatible APIs | --- ## 🗺️ Roadmap ### Near term - [ ] More explicit privacy controls and recording safeguards - [ ] Smarter activity merging and cleaner timeline segmentation - [ ] Richer statistics and trend analysis - [ ] More reliable update and installation flow - [ ] Better automated testing and CI coverage ### Mid term - [ ] Multi-monitor support - [ ] Better website / app recognition - [ ] Local-model or hybrid analysis mode - [ ] Smarter daily / weekly behavioral insights - [ ] More complete export and reporting options --- ## Known limitations - Windows 10 / 11 only - Recognition quality depends on the vision model you configure - Some apps may not expose stable window titles - Full-screen games, special rendering windows, and remote desktop scenarios may behave differently - Multi-monitor support still has room for improvement - Analysis latency depends on your network and model provider stability --- ## 🧰 Troubleshooting ### 1. No analysis results appear Check the following first: - API URL, key, and model name are correct - The configured model supports vision input - Your network can reach the model provider - The log contains no timeout or request errors ### 2. Screen capture or window tracking looks wrong Check the following first: - You are running on Windows 10 / 11 - FFmpeg is installed and available in PATH - Security software is not blocking capture or window inspection - You are not in a special case such as full-screen games, remote desktop, or unusual rendering modes ### 3. Email reports fail to send Check the following first: - QQ Mail SMTP / authorization code is correct - The built-in test send works - Your local network is not blocking the mail service ### 4. Updates or auto-start do not work Check the following first: - You are running the packaged EXE build - The EXE path has not changed unexpectedly - System permissions or security policy are not blocking startup/update behavior --- ## 💡 Inspiration This project is inspired by [Dayflow (macOS)](https://github.com/JerryZLiu/Dayflow). The original project is macOS-only, so this repository brings a similar idea to Windows users. Thanks to the original author for the creativity and open-source spirit. --- ## 📄 License [CC BY-NC-SA 4.0](LICENSE) © 2024-2025 This project currently uses **Creative Commons Attribution-NonCommercial-ShareAlike 4.0**. - ✅ You can learn from it, modify it, and share it - ✅ Please credit the original author - ❌ Commercial use is not allowed > ℹ️ This is not a typical software license such as MIT or Apache-2.0. If you plan to redistribute or use the project commercially, read `LICENSE` carefully first. --- ## ⭐ Star History

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