Graphlit, by Unstruk Data

?? All month, we are publishing examples of different features of the Graphlit platform as Google Colab Notebooks. ?? We are calling this the '30 Days of Graphlit'. ?? We've already published examples of: - Extracting markdown from PDF - Scraping web site - Publishing summary of web research - Monitoring Reddit mentions - Summarizing a podcast MP3 - Generating a knowledge graph from a web search - Doing research on Slack messages and shared links Sneak peek, tomorrow we will have an example of publishing an audio review of an academic paper, using an ElevenLabs voice. Github: https://lnkd.in/gZHDuGcY All examples are free to try out, just require signup to get API key. You can follow along on our X/Twitter (@graphlit) for the rest of the examples this month.

Day 5 of the '30 Days of Graphlit' is here! In this example, we show how to use Graphlit for competitive intelligence and analyzing mentions on Reddit. By ingesting posts from r/Anthropic, and enabling entity extraction, we can then filter on any Reddit posts that mentioned Google. Notebook: https://lnkd.in/gce-Af5i Colab: https://lnkd.in/ghKRSrad

?? We're starting the Thirty Days of Graphlit. Each day for the month of September, we'll post a Google Colab notebook which dives into a feature of Graphlit, which you may not know about. Graphlit supports a lot more than just RAG, and we'll show you examples all month long. Follow along on our X/Twitter: @graphlit. 1?? Our first example covers the ingestion of a PDF, and automatically extracting the text as Markdown. Under the covers, and by default, Graphlit uses the Azure AI layout model for high-quality document preparation. Github: https://lnkd.in/g9NEdHk7 2?? Scraping websites is an important step for creating context for RAG. Graphlit supports loading web sitemaps, and listing available web pages. It also supports filtering web pages by URL regex. In this example, we show how easy this can be. Github: https://lnkd.in/g4bihW2S

?? Now available: graphlit-ingest CLI ??Using the Graphlit Platform, you can ingest any document, audio/video, image or web page, and extract Markdown text or structured JSON. Also, supports summarization and auto-generated transcript chapters, bullet points, social media posts and more. Even supports Anthropic Sonnet 3.5 and OpenAI GPT-4o for multimodal PDF extraction. ? Free to use, up to 1GB data. Paid plan starts at just $49/mo+usage. Built with our new cross-platform .NET SDK. Signup: https://lnkd.in/gcnTfS2K Code: https://lnkd.in/gsmEV54p

Exciting news! ?? Check out the new Next.js sample applications for Graphlit, by Unstruk Data. These apps demonstrate seamless integration with Graphlit for RAG conversations, web scraping & crawling, and document text extraction (into structured JSON and Markdown). Forget juggling multiple tools - simplify your workflow with Graphlit: ?? RAG chat <~ OpenAI Assistants API ?? File Extraction <~ LlamaParse, Unstructured.IO ?? Web extraction <~ Firecrawl Explore more on our blog: https://lnkd.in/gS9PhGC4 Access the code here: ?? RAG Chat: https://lnkd.in/ghtiEihp ?? Web Extraction: https://lnkd.in/gktER787 ?? File Extraction: https://lnkd.in/gemS2gDi #unstructureddata #ragasaservice #graphrag #rag

Today we're joined by Kirk Marple, CEO and founder of Graphlit, by Unstruk Data, to explore the emerging paradigm of "GraphRAG". Kirk shares the history of RAG, and the potential for deeper integration of databases and AI as RAG matures. We dive into Graphlit's multi-stage workflow for content generation and finally, explore agent-based applications and the future of Graphlit as a cloud service. ?? / ?? Listen or watch the full episode at: twimlai.com/go/681