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    <title>DEV Community: Gyan Arpit</title>
    <description>The latest articles on DEV Community by Gyan Arpit (@gyan_arpit_6245ada6c55ee8).</description>
    <link>https://dev.to/gyan_arpit_6245ada6c55ee8</link>
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      <title>DEV Community: Gyan Arpit</title>
      <link>https://dev.to/gyan_arpit_6245ada6c55ee8</link>
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    <item>
      <title>Study Sprint AI</title>
      <dc:creator>Gyan Arpit</dc:creator>
      <pubDate>Mon, 26 Oct 2026 11:53:27 +0000</pubDate>
      <link>https://dev.to/gyan_arpit_6245ada6c55ee8/study-sprint-ai-55pj</link>
      <guid>https://dev.to/gyan_arpit_6245ada6c55ee8/study-sprint-ai-55pj</guid>
      <description>&lt;p&gt;StudySprint AI is an AI-powered study assistant designed to help students learn smarter, stay organized, and maintain consistent study habits. It aims to simplify the learning process by transforming lengthy study materials into concise summaries, generating practice questions, organizing revision tasks, and helping students break complex topics into manageable learning sessions. By integrating open-source AI models, StudySprint AI seeks to make personalized learning more accessible, flexible, and affordable while reducing the time students spend organizing their studies. The project follows the philosophy of “slow and steady,” encouraging students to make consistent progress through small, focused learning sessions rather than relying on last-minute preparation.&lt;/p&gt;

</description>
      <category>devchallenge</category>
      <category>hf26challenge</category>
    </item>
    <item>
      <title>Local ledger AI</title>
      <dc:creator>Gyan Arpit</dc:creator>
      <pubDate>Fri, 16 Oct 2026 09:19:46 +0000</pubDate>
      <link>https://dev.to/gyan_arpit_6245ada6c55ee8/local-ledger-ai-43hk</link>
      <guid>https://dev.to/gyan_arpit_6245ada6c55ee8/local-ledger-ai-43hk</guid>
      <description>&lt;p&gt;Our solution: LocalLedger AI aims to simplify this workflow by combining document processing with open-weight AI models.&lt;/p&gt;

&lt;p&gt;Key features:&lt;/p&gt;

&lt;p&gt;Extract essential information from invoices and receipts.&lt;/p&gt;

&lt;p&gt;Automatically categorize expenses and identify potential duplicate receipts.&lt;/p&gt;

&lt;p&gt;Generate easy-to-understand monthly spending summaries.&lt;/p&gt;

&lt;p&gt;Process sensitive financial documents locally, helping keep customer data private.&lt;/p&gt;

&lt;p&gt;Reduce recurring AI inference costs by running suitable models on local hardware.&lt;/p&gt;

&lt;p&gt;Why open innovation matters&lt;/p&gt;

&lt;p&gt;Open-weight models make it possible to build specialized AI tools without depending entirely on proprietary AI APIs. Local inference can improve privacy and reduce per-request costs, while customization can make the product more useful for a specific customer group.&lt;/p&gt;

&lt;p&gt;The goal isn't to add AI just for the sake of it. It's to solve a tedious problem, deliver measurable value, and build a product that small businesses can realistically afford.&lt;/p&gt;

&lt;p&gt;The business opportunity: A simple subscription-based tool that saves freelancers time and helps them understand their finances, without requiring an expensive accounting setup.&lt;/p&gt;

&lt;p&gt;This is the kind of AI I want to build: practical, accessible, privacy-conscious, and commercially viable.&lt;/p&gt;

&lt;h1&gt;
  
  
  OpenSourceAI #OpenWeightModels #ArtificialIntelligence #BuildInPublic #AIStartup #LocalAI #IndieHackers
&lt;/h1&gt;

</description>
      <category>devchallenge</category>
      <category>hf26challenge</category>
    </item>
    <item>
      <title>Campus Copilot – An AI Study Assistant I Built for a Friend</title>
      <dc:creator>Gyan Arpit</dc:creator>
      <pubDate>Mon, 05 Oct 2026 15:05:16 +0000</pubDate>
      <link>https://dev.to/gyan_arpit_6245ada6c55ee8/campus-copilot-an-ai-study-assistant-i-built-for-a-friend-45no</link>
      <guid>https://dev.to/gyan_arpit_6245ada6c55ee8/campus-copilot-an-ai-study-assistant-i-built-for-a-friend-45no</guid>
      <description>&lt;p&gt;What I Built&lt;/p&gt;

&lt;p&gt;I built Campus Copilot, a small AI study assistant for a friend who was struggling to keep track of lecture notes, PDFs, assignments, and exam preparation.&lt;/p&gt;

&lt;p&gt;The problem was pretty simple. They had all the study material they needed, but whenever they wanted to find something specific, they had to go through multiple PDFs and notes. And during exams, it became even harder to figure out what to study next.&lt;/p&gt;

&lt;p&gt;So I wanted to build something that could make that process a little easier.&lt;/p&gt;

&lt;p&gt;With Campus Copilot, you can upload your study material and then ask questions directly from it.&lt;/p&gt;

&lt;p&gt;Some of the things it can do are:&lt;/p&gt;

&lt;p&gt;Upload and read lecture notes and PDFs&lt;br&gt;
Ask questions about the uploaded material&lt;br&gt;
Give answers based on the uploaded documents&lt;br&gt;
Show the source/page where the answer came from&lt;br&gt;
Generate quizzes from the notes&lt;br&gt;
Identify topics where the student is making mistakes&lt;br&gt;
Suggest topics to revise&lt;br&gt;
Create a simple revision plan&lt;/p&gt;

&lt;p&gt;The main idea is that it isn't supposed to be another generic chatbot. It is meant to work with your own study material.&lt;/p&gt;

&lt;p&gt;Demo&lt;/p&gt;

&lt;p&gt;The basic workflow looks like this:&lt;/p&gt;

&lt;p&gt;Upload notes → Ask a question → Get an answer with the source → Take a quiz → Find weak topics → Revise → Try again&lt;/p&gt;

&lt;p&gt;How I Built It&lt;/p&gt;

&lt;p&gt;I wanted to use open-source AI for this project instead of just connecting a normal chatbot API.&lt;/p&gt;

&lt;p&gt;The main technologies I used are:&lt;/p&gt;

&lt;p&gt;React + Vite for the frontend&lt;br&gt;
Python + FastAPI for the backend&lt;br&gt;
PyMuPDF for reading PDFs&lt;br&gt;
ChromaDB for storing embeddings and finding relevant information&lt;br&gt;
An open-weight LLM for generating the responses&lt;br&gt;
An open-source embedding model for semantic search&lt;br&gt;
SQLite for storing application data&lt;/p&gt;

&lt;p&gt;The basic process is:&lt;/p&gt;

&lt;p&gt;Upload PDF&lt;br&gt;
   ↓&lt;br&gt;
Extract text&lt;br&gt;
   ↓&lt;br&gt;
Split into smaller sections&lt;br&gt;
   ↓&lt;br&gt;
Create embeddings&lt;br&gt;
   ↓&lt;br&gt;
Store in ChromaDB&lt;br&gt;
   ↓&lt;br&gt;
User asks a question&lt;br&gt;
   ↓&lt;br&gt;
Find the relevant sections&lt;br&gt;
   ↓&lt;br&gt;
Send them to the local LLM&lt;br&gt;
   ↓&lt;br&gt;
Generate the answer with the source&lt;/p&gt;

&lt;p&gt;I also wanted to keep the architecture flexible so I could experiment with different models and retrieval methods instead of being locked into one provider.&lt;/p&gt;

&lt;p&gt;Why Does Open Innovation Matter?&lt;/p&gt;

&lt;p&gt;For me, this was one of the most interesting parts of the project.&lt;/p&gt;

&lt;p&gt;A study assistant will potentially have access to personal notes, assignments and other academic material. I didn't want the entire project to depend on a closed API where I had very little control over what was happening behind the scenes.&lt;/p&gt;

&lt;p&gt;Using open-weight models gives me more control over the system.&lt;/p&gt;

&lt;p&gt;I can decide which model to use, how the documents are processed, how the information is retrieved and, where possible, run the AI locally.&lt;/p&gt;

&lt;p&gt;It also makes experimenting much easier. If I find a better model or a better retrieval technique, I can replace that part without rebuilding the whole application from scratch.&lt;/p&gt;

&lt;p&gt;That's what I like about open innovation — it gives developers the freedom to actually understand, modify and improve the technology they are building with.&lt;/p&gt;

&lt;p&gt;My Agent Session&lt;/p&gt;

&lt;p&gt;I used an AI coding agent while building parts of the project and experimented with it during development.&lt;/p&gt;

&lt;p&gt;Prize Categories&lt;br&gt;
Build for a Friend&lt;br&gt;
Open-source AI / AI-powered application&lt;/p&gt;

&lt;p&gt;Why I Built It&lt;/p&gt;

&lt;p&gt;I didn't want to build something just because AI is popular right now.&lt;/p&gt;

&lt;p&gt;I wanted to build something that would actually be useful to someone I know.&lt;/p&gt;

&lt;p&gt;Students already have a lot of information scattered across PDFs, WhatsApp messages, classroom notes and different platforms. I thought it would be interesting to bring some of that together and make studying a little less frustrating.&lt;/p&gt;

&lt;p&gt;There is still a lot I want to improve in Campus Copilot, but this challenge gave me a good reason to finally turn the idea into a working project.&lt;/p&gt;

&lt;p&gt;The goal is simple: make studying from your own notes a little easier.&lt;/p&gt;

</description>
      <category>devchallenge</category>
      <category>weekendchallenge</category>
      <category>hf26challenge</category>
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