Research & summarize
Integrate Screenpipe for AI-powered Data Retrieval
Connect LlamaIndex to your local Screenpipe instance to index and query screen captures and audio transcriptions for AI-driven insights.
Without it
Piece it together by hand, every time.
With it
Leverage your local Screenpipe recordings (screen captures and audio) to build powerful AI applications. This integration allows you to easily index and query your personal data for enhanced research and summarization.
What you get
- Connect to a local Screenpipe instance.
- Load screen capture (OCR) and audio transcription data.
- Filter data by content type, query, and time range.
- Index and query your personal recordings using LlamaIndex.
Add this skill
LlamaIndex Readers Integration: Screenpipe
Reads screen capture (OCR) and audio transcription data from a local
Screenpipe instance.
Screenpipe is a 24/7 local screen & mic recording tool that captures screen
content via OCR and audio transcriptions via Whisper, storing everything in a
local SQLite database and exposing a REST API.
Installation
pip install llama-index-readers-screenpipe
Usage
Make sure Screenpipe is running locally (default: http://localhost:3030).
from llama_index.readers.screenpipe import ScreenpipeReader
from llama_index.core import VectorStoreIndex
reader = ScreenpipeReader()
### Load recent screen and audio data
documents = reader.load_data(content_type="all", limit=50)
### Load only audio transcriptions with a query filter
from datetime import datetime, timedelta
documents = reader.load_data(
content_type="audio",
query="meeting notes",
start_time=datetime.now() - timedelta(hours=24),
)
### Build an index and query
index = VectorStoreIndex.from_documents(documents)
engine = index.as_query_engine()
response = engine.query("What did I discuss in my last meeting?")