___  ___ _ __ ___  ___ _ __  _ __ (_)_ __   ___ 
  / __|/ __| '__/ _ \/ _ \ '_ \| '_ \| | '_ \ / _ \
  \__ \ (__| | |  __/  __/ | | | |_) | | |_) |  __/
  |___/\___|_|  \___|\___|_| |_| .__/|_| .__/ \___|
                               |_|     |_|         

Latest News 🔥

• [2024/08] Anyone can now create, share, install pipes (plugins) from the app interface based on a github repo/dir
• [2024/08] We're running bounties! Contribute to screenpipe & make money, check issues
• [2024/08] Audio input & output now works perfect on Windows, Linux, MacOS (<15.0). We also support multi monitor capture and defaulting STT to Whisper Distil large v3
• [2024/08] We released video embedding. AI gives you links to your video recording in the chat!
• [2024/08] We released the pipe store! Create, share, use plugins that get you the most out of your data in less than 30s, even if you are not technical.
• [2024/08] We released Apple & Windows Native OCR.
• [2024/08] The Linux desktop app is here!.
• [2024/07] The Windows desktop app is here! Get it now!.
• [2024/07] 🎁 Screenpipe won Friends (the AI necklace) hackathon at AGI House (integrations soon)
• [2024/07] We just launched the desktop app! Download now!

Library to build personalized AI powered by what you've seen, said, or heard. Works with Ollama. Alternative to Rewind.ai. Open. Secure. You own your data. Rust.
We are shipping daily, make suggestions, post bugs, give feedback.

Building a reliable stream of audio and screenshot data, where a user simply clicks a button and the script runs in the background 24/7, collecting and extracting data from screen and audio input/output, can be frustrating.

There are numerous use cases that can be built on top of this layer. To simplify life for other developers, we decided to solve this non-trivial problem. It's still in its early stages, but it works end-to-end. We're working on this full-time and would love to hear your feedback and suggestions.

There are multiple ways to install screenpipe:

• as a CLI (continue reading), for rather technical users
• as a paid desktop app with 1 year updates, priority support, and priority features
• as a free forever desktop app (but you need to build it yourself). We're 100% OSS.
• as a free forever desktop app - by sending a PR (example) (or offer free app to a friend)
• as a Rust or WASM library (documentation WIP)
• as a business - check use cases and DM louis

PS: we invest 80% of the paid app revenue in bounties, send PR, make money!

This is the instructions to install the command line interface.

Struggle to get it running? I'll install it with you in a 15 min call.

brew tap mediar-ai/screenpipe https://github.com/mediar-ai/screenpipe.git
brew install screenpipe

screenpipe 

screenpipe --ocr-engine apple-native

screenpipe --disable-audio

screenpipe --save-text-files

screenpipe --debug

screenpipe --vad-engine webrtc

screenpipe --audio-transcription-engine deepgram

screenpipe --ocr-engine unstructured

screenpipe --friend-wearable-uid AC...........................F3

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh # takes 5 minutes
brew install pkg-config ffmpeg jq tesseract

git clone https://github.com/mediar-ai/screenpipe

cd screenpipe # enter cloned repo

# necessary to use apple native OCR
export RUSTFLAGS="-C link-arg=-Wl,-rpath,@executable_path/../../screenpipe-vision/bin -C link-arg=-Wl,-rpath,@loader_path/../../screenpipe-vision/lib"
cargo build --release --features metal # takes 3 minuttes

./target/release/screenpipe # add --ocr-engine apple-native to use apple native OCR
# add "--disable-audio" if you don't want audio to be recorded
# "--save-text-files" if you want to save OCR data to text file in text_json folder in the root of your project (good for testing)
# "--debug" if you want to run screenpipe in debug mode to show more logs in terminal

choco install pkgconfiglite rust
cd V:\projects
git clone https://github.com/mediar-ai/screenpipe
cd V:\packages
git clone https://github.com/microsoft/vcpkg.git
cd vcpkg
bootstrap-vcpkg.bat -disableMetrics
vcpkg.exe integrate install --disable-metrics
vcpkg.exe install ffmpeg

SET PKG_CONFIG_PATH=V:\packages\vcpkg\packages\ffmpeg_x64-windows\lib\pkgconfig
SET VCPKG_ROOT=V:\packages\vcpkg
SET LIBCLANG_PATH=C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\Llvm\x64\bin
cd V:\projects\screen-pipe

cargo build --release --features cuda

sudo apt-get update
sudo apt-get install -y libavformat-dev libavfilter-dev libavdevice-dev ffmpeg libasound2-dev tesseract-ocr libtesseract-dev

# Install Rust programming language
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

git clone https://github.com/mediar-ai/screenpipe
cd screenpipe

cargo build --release --features cuda # remove "--features cuda" if you do not have a NVIDIA GPU

# then run it
./target/release/screenpipe

nix-env -iA nixpkgs.screen-pipe

environment.systemPackages = with pkgs; [
  screen-pipe
];

nix-shell -p screen-pipe

nix run nixpkgs#screen-pipe

By default the data is stored in $HOME/.screenpipe (C:\AppData\Users\<user>\.screenpipe on Windows) you can change using --data-dir <mydir>

git clone https://github.com/mediar-ai/screenpipe

cd screenpipe/examples/typescript/vercel-ai-chatbot 

echo "OPENAI_API_KEY=XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX" > .env

npm install 

npm run dev

You can use terminal commands to query and view your data as shown below. Also, we recommend Tableplus.com to view the database, it has a free tier.

Here's a pseudo code to illustrate how to use screenpipe, to summarize meetings:

// 1h ago
const startDate = "<some time 1h ago..>"
// 10m ago
const endDate = "<some time 10m ago..>"

// get all the screen & mic data from roughly last hour 
const results = fetchScreenpipe(startDate, endDate)

// send it to an LLM and ask for a summary
const summary = fetchOllama("{results} create a summary from these transcriptions")
// or const summary = fetchOpenai(results)

// add the meeting summary to your notes
addToNotion(summary)
// or your favourite note taking app

Or thousands of other usages of all your screen & mic data! Check examples, screenpipes makes it easy to write plugins in JS for example that runs directly in the Rust code through Deno engine.

sqlite3 ~/.screenpipe/db.sqlite ".tables" 

sqlite3 ~/.screenpipe/db.sqlite ".mode json" ".once /dev/stdout" "SELECT * FROM audio_transcriptions ORDER BY id DESC LIMIT 1;" | jq .

sqlite3 ~/.screenpipe/db.sqlite ".mode json" ".once /dev/stdout" "SELECT * FROM ocr_text ORDER BY frame_id DESC LIMIT 1;" | jq -r '.[0].text'

ffplay "data/2024-07-12_01-14-14.mp4"

ffplay "data/Display 1 (output)_2024-07-12_01-14-11.mp4"

curl "http://localhost:3030/search?q=Neuralink&limit=5&offset=0&content_type=ocr" | jq

# 2. Search with content type filter (OCR)
curl "http://localhost:3030/search?q=QUERY_HERE&limit=5&offset=0&content_type=ocr"

# 3. Search with content type filter (Audio)
curl "http://localhost:3030/search?q=QUERY_HERE&limit=5&offset=0&content_type=audio"

# 4. Search with pagination
curl "http://localhost:3030/search?q=QUERY_HERE&limit=10&offset=20"

# 6. Search with no query (should return all results)
curl "http://localhost:3030/search?limit=5&offset=0"

# Display first frame from 30m to 25m ago (macos, translate to your OS with AI)
curl "http://localhost:3030/search?limit=1&offset=0&content_type=ocr&include_frames=true&start_time=$(date -u -v-220M +%Y-%m-%dT%H:%M:%SZ)&end_time=$(date -u -v-120M +%Y-%m-%dT%H:%M:%SZ)" | jq -r '.data[0].content.frame' | base64 --decode > /tmp/frame.png && open /tmp/frame.png

# filter by app (wll only return OCR results)
curl "http://localhost:3030/search?app_name=cursor"

• Search
  • Semantic and keyword search. Find information you've forgotten or misplaced
  • Playback history of your desktop when searching for a specific info
• Automation:
  • Automatically generate documentation
  • Populate CRM systems with relevant data
  • Synchronize company knowledge across platforms
  • Automate repetitive tasks based on screen content
• Analytics:
  • Track personal productivity metrics
  • Organize and analyze educational materials
  • Gain insights into areas for personal improvement
  • Analyze work patterns and optimize workflows
• Personal assistant:
  • Summarize lengthy documents or videos
  • Provide context-aware reminders and suggestions
  • Assist with research by aggregating relevant information
  • Live captions, translation support
• Collaboration:
  • Share and annotate screen captures with team members
  • Create searchable archives of meetings and presentations
• Compliance and security:
  • Track what your employees are really up to
  • Monitor and log system activities for audit purposes
  • Detect potential security threats based on screen content

Check other examples

Alpha: runs on my computer Macbook pro m3 32 GB ram and a $400 Windows laptop, 24/7.

Uses 600 MB, 10% CPU.

• Integrations
  • ollama
  • openai
  • Friend wearable
  • Fileorganizer2000
  • mem0
  • Brilliant Frames
  • Vercel AI SDK
  • supermemory
  • deepgram
  • unstructured
  • excalidraw
  • Obsidian
  • Apple shortcut
  • multion
  • iPhone
  • Android
  • Camera
  • Keyboard
  • Browser
  • Pipe Store (a list of "pipes" you can build, share & easily install to get more value out of your screen & mic data without effort). It runs in Deno Typescript engine within screenpipe on your computer
• screenshots + OCR with different engines to optimise privacy, quality, or energy consumption
  • tesseract
  • Windows native OCR
  • Apple native OCR
  • unstructured.io
  • screenpipe screen/audio specialised LLM
• audio + STT (works with multi input devices, like your iPhone + mac mic, many STT engines)
  • Linux, MacOS, Windows input & output devices
  • iPhone microphone
• remote capture (run screenpipe on your cloud and it capture your local machine, only tested on Linux) for example when you have low compute laptop
• optimised screen & audio recording (mp4 encoding, estimating 30 gb/m with default settings)
• sqlite local db
• local api
• Cross platform CLI, desktop app (MacOS, Windows, Linux)
• Metal, CUDA
• TS SDK
• multimodal embeddings
• cloud storage options (s3, pgsql, etc.)
• cloud computing options (deepgram for audio, unstructured for OCR)
• custom storage settings: customizable capture settings (fps, resolution)
• security
  • window specific capture (e.g. can decide to only capture specific tab of cursor, chrome, obsidian, or only specific app)
  • encryption
  • PII removal
• fast, optimised, energy-efficient modes
• webhooks/events (for automations)
• abstractions for multiplayer usage (e.g. aggregate sales team data, company team data, partner, etc.)

Recent breakthroughs in AI have shown that context is the final frontier. AI will soon be able to incorporate the context of an entire human life into its 'prompt', and the technologies that enable this kind of personalisation should be available to all developers to accelerate access to the next stage of our evolution.

Contributions are welcome! If you'd like to contribute, please read CONTRIBUTING.md.

- RAG & question answering
- Automation (write code somewhere else while watching you coding, write docs, fill your CRM, sync company's knowledge, etc.)
- Analytics (track human performance, education, become aware of how you can improve, etc.)
- etc.
- We're constantly exploring new use cases and welcome community input!