🚀 Building Recallr: How I Turned PDFs into Anki Flashcards with AI

This page summarizes the projects mentioned and recommended in the original post on dev.to

InfluxDB – Built for High-Performance Time Series Workloads
InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
www.influxdata.com
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Stream - Scalable APIs for Chat, Feeds, Moderation, & Video.
Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.
getstream.io
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  1. genanki

    A Python 3 library for generating Anki decks

    Using genanki, the process was straight forward, instead of my initial .txt output, now its a full on functional .apkg that can be imported directly to the Anki App as a studying deck. which i faced a problem with my old parsing and cleaning logic.. which in the output looked something like this

  2. InfluxDB

    InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

    InfluxDB logo
  3. hugo-quick-start

    Hugo Quick Start on Render

    hosting was a problem for me at first, since i didn't really want to pay at the start since its a hobby MVP with no revenue, i used Render's free tier for the backend hosting and used https://vercel.com/

  4. fastapi

    FastAPI framework, high performance, easy to learn, fast to code, ready for production

    until i realized Anki has their own API Interface, which made me realize that i can automate this task, efficiently, while also getting hand on experience using FastAPI and LLMs (but am i going to change the stack later?.. lets see)

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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